id
string | steps_number
int64 | system_prompt
string | user_prompt
list | ground_truth
string |
|---|---|---|---|---|
shape(step:8)_234
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_104
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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PEBe3LGwNs0/geQHzWyqKcVxAAAAABJRU5ErkJggg=="
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Cut the right side of the shape\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_458
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
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{
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"text": "This is the original shape, with its image:.",
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 5th action is Colorize the top layer of the original shape with the color cyan.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_201
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAIAUlEQVR4nO3a220bVxhGUdtIA6khNSlFRjWlhpTgIIANGI4l8TIz57LXKoD4X0js+YafX15evn4C+Ob19fXz6BuA833xZQeAni+jDwAABgWAFQAAWiwAAFAOACsAAHRYAACgHgBWAABosAAAQND/AsAKAAD7++3ZD/jjr9+PuQQ41d9//jP6BGD2VwD3rAB+VABgPf4DAABBbwaAFQAA9mUBAICgdwPACgAAe7IAAEDQhwFgBQCA/VgAACDopgCwAgDAXiwAABB0cwBYAQBgHxYAAAi6KwCsAACwBwsAAATdHQBWAABYnwUAAIIeCgArAACszQIAAEEPB4AVAADWZQEAgKCnAsAKAABrsgAAQNDTAWAFAID1WAAAIOiQALACAMBaLAAAEHRYAFgBAGAdFgAACDo0AKwAALAGCwAABB0eAFYAAJifBQAAgk4JACsAAMzNAgAAQacFgBUAAOZlAQCAoFMDwAoAAHOyAABA0OkBYAUAgPlYAAAg6JIAsAIAwFwsAAAQdFkAWAEAYB4WAAAIujQArAAAMAcLAAAEXR4AVgAAGM8CAABBQwLACgAAY1kAACBoWABYAQBgHAsAAAQNDQArAACMYQEAgKDhAWAFAIBgAAAA0QCwAgBAMAAAgGgAWAEAIBgAAEA0AKwAABAMAAAgGgBWAAAIBgAAEA0AKwAABAMAAIgGgBUAAIIBAABEA8AKAADBAAAAogFgBQCAYAAAANEAsAIAQDAAAIBoAFgBACAYAABANACsAAAQDAAAIBoAVgAACAYAABANACsAAAQDAACIBoAVAACCAQAARAPACgAAwQAAAKIBYAUAgGAAAADRALACAEAwAACAaABYAQAgGAAAQDQArAAAEAwAACAaAFYAAAgGAAAQDQArAAAEAwAAiAaAFQAAggEAAEQDwAoAAMEAAACiAWAFAIBgAAAA0QCwAgBAMAAAgGgAWAEAIBgAAEA0AKwAABAMAAAgGgBWAAAIBgAAEA0AKwAAdckAAIC6bABYAQAoywYAAJSlA8AKAEBVOgAAoCofAFYAAIryAQAARQLACgBAkAAAgCAB8I0VAIASAQAAQQLgB1YAACoEAAAECYCfWAEAKBAAABAkAH7BCgDA7gQAAAQJgDdYAQDYmQAAgCAB8A4rAAC7EgAAECQAPmAFAGBHAgAAggTADawAAOxGAABAkAC4kRUAgJ0IAAAIEgB3sAIAsAsBAABBAuBOVgAAdiAAACBIADzACgDA6gQAAAQJgAdZAQBYmQAAgCAB8AQrAACrEgAAECQAnmQFAGBFAgAAggTAAawAAKxGAABAkAA4iBUAgJUIAAAIEgAHsgIAsAoBAABBAuBgVgAAViAAACBIAJzACgDA7AQAAAQJgJNYAQCYmQAAgCABcCIrAACzEgAAECQATmYFAGBGAgAAggTABawAAMxGAABAkAC4iBUAgJkIAAAIEgAXsgIAMAsBAABBAuBiVgAAZiAAACBIAAxgBQBgNAEAAEECYBArAAAjCQAACBIAA1kBABhFAABAkAAYzAoAwAgCAACCBMAErAAAXE0AAECQAJiEFQCAKwkAAAgSABOxAgBwFQEAAEECYDJWAACuIAAAIEgATMgKAMDZBAAABAmASVkBADiTAACAIAEwMSsAAGcRAAAQJAAmZwUA4AwCAACCBMACrAAAHE0AAECQAFiEFQCAIwkAAAgSAAuxAgBwFAEAAEECYDFWAACOIAAAIEgALMgKAMCzBAAABAmARVkBAHiGAACAIAGwMCsAAI8SAAAQJAAWZwUA4BECAACCBMAGrAAA3EsAAECQANiEFQCAewgAAAgSABuxAgBwKwEAAEECYDNWAABuIQAAIEgAbMgKAMBHBAAABAmATVkBAHiPAACAIAGwMSsAAG8RAAAQJAA2ZwUA4FcEAAAECYAAKwAAPxMAABAkACKsAAD8SAAAQJAACLECAPCdAACAIAEQYwUA4D8CAACCbn4aZC8vLy9fR9/A+isRsC4LAAAECYAoT3kAbQIAAIIEQJgVAKBLAABAkACIswIANAkAAAgSAFgBAIIEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADAp9P8C+ZOEBuXckSIAAAAAElFTkSuQmCC"
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color white.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color yellow.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_328
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_358
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 2th action is Colorize the top layer of the original shape with the color green.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 4th action is Colorize the top layer of the original shape with the color green.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_326
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Colorize the top layer of the original shape with the color green.\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_236
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color blue.\nthe 7th action is Colorize the top layer of the original shape with the color cyan.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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q3w17wMABRG/QeIU8NXVr4PLwMA0aj/AAV8peNszVvxMgBQBvUfIEjRXtnIfXsZAIhG/QfIaOu/VAJQ50a9DABkTf0HiFCl6yYAW7INAohJ/QdIeeW/fALQyN14GQDIkfoPUFjrP16Wm0wAtmQbBBCT+g+Q4NZ/+QRgiXudn5+fm5ub6j68DABkZGv1f+38mvVzG6a6KfUfoO3Wf+nivGgdnnoAWJgBZmZmph0DvBIAZGGJ+r92fs3MzMy0Y4D6D9BS679sTZ5uAFg6BBj+38YAgFAhwPD/NgYA9Nv6L5h2/V9xABiZAYwBANFCgCFjAEBfrX+19f8yA8CEIcCQMQAgVAgwZAwA6Lj1r7z+rz4AbG0GMAYARAsBhowBAJ21/pXX/8sPANOGAEPGAIBQIcCQMQCg7da/zvq/1gCw7AxgDACIFgIMGQMA2mv966z/JxoAKocAQ8YAgFAhwJAxAGDQdOtfc/1fdwCYfAYwBgBECwGGjAFATIN2Wv+a6/9JB4D6IcCQMQAgVAgwZAwA4hi01vrXX/83MABUmAGMAQDRQoAhYwBQtkHLrX/99f8UA0CDIcCQMQAgVAgwZAwAyjNov/VvZP3fzABQZwYwBgBECwGGjAFAGQZdtf6NrP+nGwDaCAGGjAEAoUKAIWMAkK9Bh61/U+v/xgaARmYAYwBAtBBgyBgA5GXQeevf1Pp/6gGg1RBgyBgAECoEGDIGAOkb9NH6N7j+b3IAaHYGMAYARAsBhowBQJoG/bX+Da7/qwwA3YQAQ8YAgFAhwJAxAEjHoNfWv9n1f8MDQEszgDEAIFoIMGQMAPo1SKD1b3b9X3EA6DgEGDIGAIQKAYaMAUDY1r/x9X/zA0DbM4AxACBaCDBkDAACtv4zTa//qw8AfYUAQ8YAgFAhwJAxAIjT+rex/m9lAOhsBjAGAEQLAYaMAUCPff9MMuWu6wGg9xBgyBgAECoEGDIGAAW3/i2t/9saALqfAYwBANFCgCFjAFBk6z/Tzvq/7gCQTggwZAwACBUCDBkDgJJa//bW/y0OAD3OAMYAgGghwJAxACij9Z9pbf3fwACQYAgwZAwACBUCDBkDgKxb/1bX/+0OACnMAMYAgGghwJAxAMi09Z9pc/3fzACQcghQeQbwMgCQdQhQeQZQ/yFy6z+TQ/mqX6PaHQDSmQGMAQABQ4AFxgCIJuvWf6bl9X9jA0D6IcCQMQAgVAgwZAyACHJv/TtY/3cxACQ4A1QeA7wSAGQaAtQcA9R/SF8Zrf9M++v/JgeAjEKAIWMAQKgQYMgYACUppvXvZv3f0QCQ8gxgDACIFgIMGQMgd4W1/jOdrP8bHgByDAGGjAEAoUKAIWMA5Ki81r+z9X93A0AWM4AxACBaCDBkDIBclNr6z3S1/m9+AMg6BBgyBgCECgGGjAGQsoJb/y7X/50OAHnNAMYAgGghwJAxAFJTfOs/0+H6v5UBoIwQYMgYABAqBBgyBkAKIrT+Ha//ux4AMp0BjAEA0UKAIWMA9CVO6z/T7fq/rQGgsBBgyBgAECoEGDIGQJdCtf7dr/97GABynwGMAQDRQoAhYwC0LWDrP9P5+r/FAaDUEGDIGAAQKgQYMgZAG2K2/r2s//sZAIqZAYwBANFCgCFjADQlcus/08f6v90BoPgQYMgYABAqBBgyBkAdwVv/vtb/vQ0A5c0AxgCAaCHAkDEApqX173H93/oA0EEIULnthnFejCGjEKBy2w3j1P/OlNH6r5/b0Mgp9bL+n5mZWTHTk6Ya9/KSBICyNdW4p9YQAEsY/Itp/+La+TVJPdnXz21oqoj1uMVY2dcdAwBQvGor/wSH/PUFpY6tJwBL5BdCAICCLVH/hQAQQbWVf9lb/96v/l8gAQAAoEm2/onr4j0AQgCAmIQAEI2tf/rrfwkAAAANsPXPSEefAiQEAIhJCADFs/XPa/0vAQAAoCJb/0x19z0AQgCAmIQAUB5b/3zX/xETAENCcL46GsJS/4NT/5ti61+ATr8JOIUQwPMfIGYIoP5DTbb+Zaz/IyYAAABMxda/MJ0mAEIAgLCEAJAjW//y1v8SAAAAFmHrX7CuEwAhAEBYQgDIgq1/2et/CQAAAP/M1n9ofn6+4H1BDwmAEAAgLCEApMnWf2j+B2bKXf9LAAAAQrP1D/htIf0kAEIAgLCEAJAIW//2tv4pr/8lAAAA4dj6B9z6J5EACAEAwhICQF9s/TvY+ie+/pcAAACEYOsffOufSgIgBAAISwgAnbH173Lrn/76XwIAAFAsW/8hW/+EEgAhAEBYQgBoj61/L1v/LNb/EgAAgHJUXvnb+ofSfwIgBAAISwgAva/8bf2jrf8lAAAAebP135KtfzYJgBAAICwhAFRm65/O1j+j9b8EAAAgP7b+W0qh789LKgmAEAAgLCEATM7WP8Gtf17rfwkAAEAebP23lFTfn52EEgAhAEBYQgBYgq1/ylv/7Nb/EgAAgHTZ+m8pzb4/R2klAEIAgLCEALAlW/8stv45rv8lAAAAabH131LifX+mkksAhAAAYQkBCM7WP6+tf6brfwkAAED/bP23lEvfn68UEwAhAEBYQgCisfXPdOuf7/pfAgAA0A9b/y1l1/dnLdEEQAgAEJYQgOLV2fqn1v3H3Ppnvf6XAAAAdKdO359g61/zFvLt+3OXbgIgBAAISwhAeepv/dPp/oNv/XNf/0sAAADaZeu/pQL6/gIknQAIAQDCEgJQAFv/8rb+Baz/JQAAAM2z9d9SSX1/GVJPAIQAAGEJAciRrX/BW/8JJb7+lwAAADTD1n9LAfv+jGSQAAgBAMISApAFW/8txdz6Z7T+lwAAAFRXzNa/kYk6ct+flzwSACEAQFhCANJUzNa//srf1j+v9b8EAACgu5W/rT8pyCYBEAIAhCUEoICVv61/8dZlsv6XAAAALMPWf4S+P3c5JQBCAICwhAD0wtZ/hK1/Aet/CQAAwCJs/Ufo+0uSWQIgBAAISwhAN2z9R9j6F7b+lwAAAPwzW/8R+v5Szc4U9xRt6sG67JrHsyJHS/9nzW6Ch4CWqP9N9V7Ldk7qf47aTm+0/mEfM+sybB4kAAAA1Wn9yU5+7wFY4J0AADF5JwDpKOla/4UL/XX/08px/S8BAACYWiJ9fyNzr6Y/oFwTACEAQFhCAHpU3ta/uTMKZ12e638JQP+8hABAFhLp+239CZ0AlBECeAYCVCAEoEu2/pS0/pcAAABsVSJ9v60/zco7AViaEAAgJiEA9dn6U7DsE4B169bV/94+ALKj/tOSRPp+W3/aU3ICIAQACEsIQAW2/gSxovg3YSjNAKVauv43NQMQgdafUEoYALohBACISQhAN7T+dKaQAUAIABCTEIACaP3pWCEDQDeEAAAxCQFoidafXmT/KUATfhzE3NxcGU+P+TV79X0KeZvbcE/fpwB0Wv/Xz21I5Npu2JJP+KFHEoDMQgD9K0AvhAA0xdaf3hU1AHgnAEBM3glAFrT+JKKoAaAbQgCAmIQAVKb1JymlDQBCAICYhACkSetPgkobALohBACISQjA5LT+JKvAAUAIABCTEIBEaP1JXIEDQDeEAAAxCQFYgtafLJQ5AAgBAGISAtAXrT8ZKXMA6IYQACAmIQBb0vqTnWIHACEAQExCADqj9SdTxQ4A3RACAMQkBAhO60/WSh4AhAAAMQkBaI/WnwKUPAB0QwgAEJMQIBqtP8UofAAQAgDEJASgQVp/ClP4ANANIQBATEKA4mn9KVL5A4AQACAmIQB1aP0pWPkDQDeEAAAxCQHKo/WneCEGACEAQExCAKai9SeIEANAN4QAADEJAQqg9SeUKAOAEAAgJiEAbdP6k50oA0A3hAAAMQkBYtL6k6lAA4AQACAmIQCN0/qTtUADQDeEAAAxCQGC0PpTgFgDgBAAICYhAPVp/SlGrAGgG0IAgJiEAKXS+lOYcAOAEAAgJiEAFWj9KVK4AaAbQgCAmIQAxdD6U7CIA4AQACAmIQCT0PpTvIgDQDeEAAAxCQHypfUniKADgBAAICYhAIvS+hNK0AGgG0IAgJiEAEDK4g4AQgCAmIQAQHBxB4BuCAEAYhICAMkKPQAIAQBiEgIAkYUeALohBACISQgApCn6ACAEAIhJCACEFX0A6IYQACAmIQCQIAOAEAAgKCEAEJMBoCNCAICYhABAagwA/0QIABCTEAAIyADQHSEAQExCACApBoB/JgQAiEkIAERjAOiUEAAgJiEAkA4DwA8JAQBiEgIAoRgAuiYEAIhJCAAkwgDwI4QAADEJAYA4DAA9EAIAxCQEAFJgABglBACISQgABGEA6IcQACAmIQDQOwPAIoQAADEJAYAIDAC9EQIAxCQEAPplAFicEAAgJiEAUDwDQJ+EAAAxCQGAHhkAtkoIUJi5DfcsO/AM/kVXJwWkSAgAlG1l3ycQ3fz8/NKzxNzc3LKL/Fq3v+Ge+TV7zRSnZrgxPgMs3RAATGvt/JqlZ4ma9R9gayQASxEC5Ljjn2TTX8EwHJAPQARCAKBgBoD+eSdATe01/VtjEgAa4Z0AQC9cAlSLfLZHKcwtwxnABUIQzfq5Dcu27wBpkgAso5vGTggwlY73/ZMQCEB5uqn/QgCgexKAuoQAnUmt6R8nEIBQhABApiQAyxMC9C7Blf/SBAJQBiEAUCQDQAOU5lbl1fpvyQwAxfNxQECODAATEQL0IrvF/zhRAOROCACUxwDQDKU5/dZ/zWnza06bn+TPLPvHpmUMgIIJAYDsGAAmJQToTFPnMOzmK/T0df7u1pgBIFNCAKAwPgWoMT4OKIXuv/Hl/fjNbrik+mvwYDDwAUFQHh8HBORFAjAFIUCyl/20dOlOG/flciDIkRAAKIkBoElKc2U1W/+mT6f1uzYDQGG8EwDIiAFgOkKANlS7ux5b/0ZOwwwAeRECAMUwADRMae6g+0+k9a9/SmYAKIkQAMiFAWBqQoAGTXsvCbb+NU/PDAAZEQIAZTAANE9pbuMtv4m3/nVO1duCoRhCACALBoAqhADdL/5nciMKgCIJAYACGABaoTQ3JaPFf2EnD1QjBADSZwCoSAhQ2eS3WUb3PPm/QggAWRACALkzALRFaV5UtO5/gRkAQhECAIkzAFQnBJjWhDdV5JUzk/+jzACQPiEAkDUDQIuU5mrd/0y5zAAQhBAASJkBoBYhwIR0/0NmACiDEADIlwGgXUrz5CJ0/9H+pRCZEABIlgGgLiHAsib5u9F64kn+vUIASJwQAMiUAaB1wUuz7n9rzABQPCEAkCYDQAOEAA3+FUaYASBlQgAgRwaALijNS4i5/l8Q+d8OQQgBgAQZAJohBKj2h3XALgSC3AkBgOwYADqiNI/T/S/we4CyCQGA1BgAGiMEqPDHmJAQAFImBADyYgDoTpzS7OKfabkQCMomBACSYgBokhBgQrr/cX4nkDUhAJARA0CnIpRmF/+0RwgA+RICAOkwADRMCLAsq+6t8ZuBrAkBgFwYALqmNAPEJAQAEmEAaF7kEGDZZMCSu+bvx1VAkDIhAJAFA0APlGaAmIQAQAoMAK2IGQJY/zdCCABZEwIA6TMA9ENpBohJCAD0zgDQlpghwBKs/yfndwVZEwIAiTMA9Kaw0uzj/7vkKiDImhAA6JcBoEVCgCEr7Wn5jUHWhABAygwAfVKaAWISAgA9MgC0SwhAS1wFBIkTAgDJMgD0LEJpdjVLNX5vUDYhANAXA0DrgoQAAIwQAgBpMgD0T2kGiEkIAPTCANAFIQBt8DYASJ8QAEiQASAJBZdmF7LX4bcHxRMCAN0zAHRECAAQkxAASI0BIBVKM0BMQgCgYwaA7ggBAGISAgBJMQAkRGkGiEkIAHTJANCpaCGA97DWt/Tv0AcBQS6EAEA6DABpUZoBYhICAJ2ZncmcDSgNSjOy2HDJXO9rRUiQ+g/0aF3Or78r+z4ByKbVBgAogEuAAAAgEAMAAAAEYgAAAIBADAAAABCIAQAAAAIxAAAAQCAGAAAACMQAAAAAgRT+RWDz8yl+sWtJ5ubmCvtiXaAM6df/pevnuvNTP//sDF42l/UDppfH4czMzNr5NfXvZf3chrK/WDc7hQ8AMK0EhxYTCwB9WT+3of4MsHZ+zSQzAJ1xCRAAQFDpRB+DwaDvUwjEAECLhcPqur6lf4cCUwDa1sjyvpFLiWiKAQAAIC4hQEAGAAAAliIEKIwBAAAgNCFANAYAAACWIQQoiQGAdnkfcB1+ewB0QwgQigGAckpGND4CCIAuCQGKYQAAACChjZ4QoG0GAAAAJiIEKIMBgNa5kL0avzcAOiYECMIAQFH1Ig5vAACgF0KAAhgAAABIbqknBGiPAYAuuJplWn5jACRLCJA7AwClLQwicP0PABFe04UALTEA0BEr7cn5XQGQOCFA1gwAAAD8CCFA2QwAdFcsLLYnsexvyfU/AKRACJAvAwAAAKOEAAUzANAkIUBN1v8AZEQIkCkDAAAAixAClMoAQNeEAFvjNwNAdoQAOTIAUOy2oDyu/wEg7Mu6EKBBBgB6YNU9zu8EgEwJAbJjAKCfbYF+d9rfhvU/AL0QApTHAEDhxaIMun8AUiYEyIsBgN4IARb4PQCQuHT2ekKARhgAaIsLgSbh4h8AyiAEyIgBgJ5FngEi/9sByIsQoCQGAEIUi3xZ/wOQCyFALgwAtMuFQFvj4h8A8pLOXk8IUJMBgNaZAcbp/gEokhAgCwYAUhFnBojzLwWgMEKAMhgASKheROiMJ/w3Wv8DkCkhQPoMAHTEDKD7B6AAQoACGABIcQYobwyY/B+l+wcgd0KAxBkASHRtUNIMMPm/RfcPQPqEALkzANC1aDOA7h+AgIQAKTMAkLSsLwfK+uQBYAlCgKwZAMigauTYRk97ztb/ABRGCJAsAwD9mP+BIrfp057quh9o84wAoHlCgHwZAMgsCkh5DKhwelp/AAomBEiTAYD89gcJjgHVTkn3D0DW0gkBmIoBgFzLRyJjQOXT0P0DEEE3IYCrgKZiACDvFUKPY0Cdu9b9A1AGIUCOVvZ9AvAjFWRurkpLPWzE15zWehmqOW9o/QGIZv3chvrX8a+dX7N0mDAYDLzITsgAQFrm5+erzQDj3XmDw0BTIYPCBEB5ar520z0DAMXWkZGufap5oI3LinT/AIQlBEiKAYDSLgeq2dNr/QFgWkKAvHgTMOV8WViCfMkXQO8GL5sbvExv2j8fB5QOAwCpy3cG0PoD9Evr36V8X68DMgCQgeyiAIt/gH5p/dMkBEiE9wCQjeEMkOxVhpp+gN7p+3vknQC5kACQnwQDASt/gN7Z+mdBCJACCQC5SiEQ0PQDpEDfnw4hQBYMAGSv+0lA3w+QCK1/jnwnQO8MAJRjy+uCGh8GFBGApGj9kyUESJ8BgDKNv0lgqmKk3QdIlta/AEKAfhkAiGKSbxdWJgBSpvXPhRAgcT4FCABInU/4KY+PA+qRBAAASFf9vn+SBJjGCQFSJgEAAMrc+if4vTFsSQjQFwkAAFDm1p9+CQGSJQEAAFJh6x+NEKAXEgAAoH+2/kUSAqRJAgAA9MnWPzghQPckAABAP2z9IxACJEgCAAB0zdafLQkBOiYBAAC6Y+sfkBAgNRIAAKALtv4sQQjQJQkAANAuW3+EAEmRAAAA6W79df9xCAE6IwEAAJpXv+/X+hdGCJAOCQAAkOLWX/cfkBCgGxIAAKAZtv4sTQiQCAkAAFCXrT9NEQJ0QAIAAFRn689UhAApkAAAAFXY+tMSIUDbJAAAwHRs/alDCNA7CQAAMClbf7ohBGiVBAAAWJ6tPw0SAvTLAEAUCg1AzNZf/c/U+rkNy67wl7V2fs3SYcJgMFi3bt1MMAYAyqf0A1Sj9ac9QoAeGQAomcoCUI3WnxQIAVpiAKBMSj9ANVp/OiME6IsBgNIoJQDVaP1JkBCgDQYAyqH0A1Sj9acvQoBeGAAogdoBUI3Wn/QJARpnACBvSj9ANVp/EiEE6J4BgFwpFgDVaP3JjhCgWQYA8qP0A1Sj9SdNQoCOGQDIieoAUI3Wn9wJARpkACAP9Uv/wuuWlxAgGq3/Qte4dNtH74QAXTIAEKX1B4hG619/YUzAECACAwDp0voDVKP11/rnKJEQYBDgKiADACnS+gNUo/XX+pdNCNAIAwBp0foDVKP11/oXQAjQDQMAqdD6A1Sj9df6hyIEqM8AQP+0/gDVaP21/uURAnTAAECftP4A1Wj9tf6RCQFqMgDQD60/QDVaf61/8YQAbTMA0DWtP0A1Wn+tP0NCgDoMAHRH6w9QjdZf6x+NEKBVBgC6oPUHqEbrr/Vna4QAlRkAaJfWH6Aarb/WPzghQHsMALRF6w8Qs/vX+tMZIUA1BgCap/UH6JfWnzIIAVpiAKBJWn+Afmn9iUYIUIEBgGZo/QH6pfWnSEKANhgAqEvrD9AvrT/BCQGmZQCgOq0/QL+0/kQgBGicAYAqGnke6v4BArb+un/aIASYigGA6Wj9Afql9ScgIUCzDABMSusP0C+tPyxBCDA5AwDL0/oD9EvrD0KABhkAiNL6p1A1AKal9a8vwkKXBUKACRkAWJzWH6BfWv/6im/jouksBFi75AxQQAhgAGCU1h+gX1r/+rT+YTUSAhTPAMAPaf0B+qX1r0/rXzYhQCMMAPwTrT9Av7T+9Wn9WSAEKHwAGAwGfZ9C9rT+QI5Kqv9a//q0/qEIAaIPANSh9Qfol9a/Pq0/ixICFDsAlLT+6ZjWf1y+QzwEVEb976WKav0pgxAg7gBABVr/cZk+dQGmovUnGiFAgQNAGeufLmn9x2n9IUfq/7S0/hRJCBBxAGByWv9xOT5XAaal9Sc4IUBRA4D1z4S0/uO0/pA19X9CWn8iEALEGgBYltZ/XHZPToAKtP5bq/+mx5iEAIUMAJ7AS9P6j9P6QxnU/6Vp/cep/8UTAkQZANgarf+4vJ6NANVo/cep/wwJAbIfAKx/FqX1H6f0Q2HU/0Vp/cep/9EIAcofABih9R+X0dMPoDKt/zj1n60RAmQ8AFj/bEnrP07ph1Kp/1vS+o9T/4MTApQ8ALBA6z8ul+cbQB1a/3HqPxMSAmQ5AFj/aP0XpfRD8dR/rf+i1H+2JAQocwAITus/LosnGEBNWv9x6j/VCAEyGwAir3+0/uOUfohD/a8pkXZH608HhAClDQAxaf1HpP90AmiE1n+E+k9ThADZDABLrH86G/U6pvUfofRDTEvU/6U3cPnS+o9Q/5mKEKCcASAUrf+IxJ8/AE3R+o9Q/2nJeiFA+gPA0uv/mYJo/Uco/RDc0uv/mYJo/Ueo/9QhBChhAIhA6z8i5ScMQIO0/iPUf7qxPnwIkPQAUPz6X+s/QukHgqz/tf4j1H8aJATIewAomNZ/RLLPEIBmaf1HqP/0Yn3sECDdAaDU9X9JrX8j/xylHwiy/i+p9W+k+1f/aY8QINcBoDxa/xFpPiUAGqf1H6H+k4L1gUOA/AaAdDrgyWn9Ryj9QAU5vlRr/Ueo/0QLAdKU6ABQzHe/a/1HKP3A0tT/LWn9IfcQYJDkVUCJDgDpt8LL0vqPSPDRD2QknVZ4WVr/Eeo/fREC5DQA5L7+0fqPUPqBCan/Wn/o2PqQIUCKA0D6PfHWaP1HpPZwBzKVTk+8NVr/Eeo/iRAC5DEAZLr+0fqPUPqBaUWu/1p/6NH6eCFAcgNA+s3xCK3/iKQe30AB0mmOR2j9R6j/pEkIkPoAkNf6R+s/QukHKgtY/7X+kI71wUKAtAaA9LvkBVr/Eek8oIHCpNMlL9D6j1D/yYIQIN0BIIv1j9Z/hNIP1Ben/mv9IVnrI4UACQ0AibfLWv8RiTyCgYIl0i5r/Ueo/+RICJDiAJDy+kfrP0LpBxpUfP3X+kMu1ocJAVIZANLsm7X+I1J4yAJB9Ns3a/1HqP8UQAiQ1gCQ4PpH6z9C6QfaUGr91/pDptbHCAGSGACSaqC1/iN6f4wCAfXSQGv9R6j/lEcIkMoAkM76p6kHRCLdv9YfSFx59T+R7l/rD3WsDxAC9D8ApNBGa/1HKP1Aj7pso7X+I9R/ijcvBOh9AOh9/aP1H6H0A90opv5r/aE860sPARJNADrop7X+I5R+IAUd9NNa/xHqP9HMhw8BVgZc/2j9Ryj9QMdyr/9afyje+qJDgBQTgPYaa63/CKUfSEp7L7da/xHqP8HNxw4BVgZZ/2j9Ryj9QF8yrf9af4hmfbkhQHIJQOMdttZ/hNIPpKnxF1qt/wj1H7Y0HzgEWFn2+qekb/Wq+W9R94EU5FX/y2j91X+obH2hIUBaCUAirXZq56P1B4qXSKud2vlo/aFV81FDgJUBP/t5Elp/gJj1X+sPFB8CJJQAJNJzJ3IaWn8gjkR67kROQ+sPXZoPGQJ0PQCkvP7R+gPErP9afyBUCJBKAtBv8631B4jZfGv9gfl4IcDK4OsfrT9AzPqv9QfChgArw3bhWn+AmF241p9x3SyAYW0aIcDKgOsfrT9Al9Kp/1p/oLKSQoCVodpxrT9AOrpsx7X+QCLWJhACrAyy/tH6A/Si9/qv9Qeasr6UEGBl8X251h8gQR305Vp/IE1r+w4BVha8/tH6A/Srr/qv9Qdasr6IEKDPBKC9Bl3rD5Cy9l4+tf5AFtb2GgKsLGz9o/UHSETH9V/rD3Rjff4hQG8JQOOdutYfIAuNv3Bq/YEcre0vBFhZwPpH6w+Qmm7qv9Yf6MX6zEOA2Zk+XgASadmbovUHmLD+J9KyN0XrD93vCOKUkXU5DgBL/KctZgDQ+gNMVf+LeeXW+kN9xoCZ5YpJS7Wih/cAlNH9a/0BYr5ga/2hKQtPh2pjwMIzsYCqsraPdwK0lQAUvP7X+gPEXP9r/aE9kdOA9Z2HAF0nAFl3/1p/gJiv0Fp/aFvkNGBt5yFAKwlAeet/rT9AzPW/1h+6FzANWN9tCNBpApBj96/1B6gvx5dkrT/0JWAasLbbEKD5BKCY9b/WHyDm+l/rD+mIkwas7zAE6C4ByKj71/oDNCij12CtP6QmThqwtsMQoOEEIPf1v9YfIOb6X+sP6Ss+DVjfVQjQUQKQfvev9QdoQ/ovulp/yEXxacDarkKAHr4ILDVaf4CYtP6Qo+LHgMwuAdraf4lk1/9af4BW63+yr7JafyhDkRcFrd96gWqq+ARNALT+ADFp/aEk0oCeE4Bc1v9af4CY63+tP5StpDRgfcshQKAEoE7rr+4D5KtO66/+Qy6kAV0nAImv/7X+ADHX/1p/iKmANGB9myFA+QlA5e5f6QfIWuXuX/2H4GnA2jRmgKQTgGTX/1p/gJjrf60/UD8NWJtwKatZrMpMALT+ADFp/YGm0oD15b4xYLaw9b/WHyDm+l/rD5SXBqxvJwQoJwHQ+gPEpPUHJiQNaCABSGT9r/UHiLn+1/oDxacB61sIAfJOALT+ADFp/YGa1gVOA2YzXf9r/QFirv+1/kC0NGB90yFAfgmA1h8gJq0/0JJ1/1Ilpp0EMk0DZjNa/2v9AWKu/7X+QPqBwNqeymCFQpdHAqD1B4hJ6w/k8vaA9fmkAbOJr/+1/gAx1/9afyAFg2TSgAZDgHQTAK0/QExafyAd60pMA2YTXP9r/QFirv+1/kDKBn2nAU2FAGklAFp/gJi0/kD61pWSBswmsv7X+gPEXP9r/YEcDXpKAxoJAfpPALT+ADFp/YF8rcs5DZjtcf2v9QeIuf7X+gMlGXSbBtQPAfpJALT+ADFp/YHyrMstDZjteP2v9QeIuf7X+gMRDDpJA2qGAN0lAFp/gJi0/kAc63JIA2Y7WP9r/QFirv+1/kBkgzbTgDohQLsJgNYfICatP8C6VNOA2ZbW/1p/gJjrf60/QDdpQOUQoPkEQOsPEJPWHyCLNGC2wfW/1h8g5vpf6w/QSxpQLQRoJgHQ+gPEpPUHyC4NmK25/tf6A8Rc/2v9AVJIAyqEANUTAK0/QExaf4Cs04DZCut/rT9AzPW/1h8gwTRg2hBg6gGgAnUfICPqP0AZRXi6AaCpO1b6AfKi/gMUv4tp65uAlX6AmNR/gL7eGzChRRKAmvek9ANkSv0HSFD9MWCkPjeZACj9ADGp/wAd1NimAoHRBKDa7Sr9ALlT/wGClOu6CYDSDxCT+g+Q6dsDfiQBmOqGlH6AYqj/AHGqd5UEQOkHiEn9ByggDfhhAjDJ31T6Acqj/gOEKuaTJgBKP0BM6j9AYWnAPycAS/xRpR+gYOo/QLTavlQCoPQDxKT+AxScBswu+jOlHyAC9R8gYKkfTQCUfoCY1H+AIGnA7PD/UfoBQlH/AWJW/tnNmzf3fSYAAEBHVnR1RwAAQP8MAAAAEIgBAAAAAjEAAABAIAYAAAAIxAAAAACBGAAAACAQAwAAAARiAAAAgEAMAAAAEIgBAAAAAjEAAABAIAYAAAAIxAAAAACBGAAAACAQAwAAAARiAAAAgEAMAAAAEIgBAAAAAjEAAABAIAYAAAAIxAAAAACBGAAAACAQAwAAAARiAAAAgEAMAAAAEIgBAAAAAjEAAABAIAYAAAAIxAAAAACBrOz7BKA7mzZtuv7666+99tovfvGLt9566+233/7ggw9u3LjxiSeeWLVq1erVq/fdd9/999//0EMPPfzww4855piDDjqo71MGAGjY7ObNm5u+TUjLpk2bPvjBD77vfe+76qqrHnnkkcn/4sEHH/zSl770la985cEHH9zmCQIwtQsuuGCqPz87O7tixYptttlm++23X7Vq1S677LLHHnvss88+q1atau0cIVEGAEr20EMPvetd73r7299+zz331LmdU0455c1vfvOznvWs5k4NgFpmZ2cbuZ0DDjjgsMMOe/azn/385z//ec973k477dTIzULKDAAU64ILLviN3/iNu+66q5FbW7Fixete97q3ve1tXhsAShoAtrT99tu/6EUvevnLX/6Sl7xk2223bfz2IREGAAr03e9+91WvetVll13W+C0/7WlPu+yyy572tKc1fssA9D4ADO2///5nnXXWr/3ar7lAiCIZACjNF77whVNOOWX9+vVL/Jkf//EfP/LIIw899NA999xz5513fvjhh7/3ve9t2LDh5ptv/vSnP71hw4Yl/u6uu+760Y9+9Kijjmrh3AFIYgBYcOCBB/7+7//+GWec0fYdQccMABTluuuuO/744++///5Ff3rAAQf8yq/8ystf/vInP/nJW7uFzZs333zzzf/3//7f973vfQ8++OCif2bXXXe9+uqrn/3sZzd34gAkNwAsGAwG7373u3ffffdu7g46YACgHH/3d3937LHHLtr977LLLm9605t+/dd/ffJrOu+7776zzz77He94x6LPkQMOOOCGG27Yd999a581AI0NAEt3Nd///vcff/zxhx566MEHH7znnnu+9rWv/cM//MNnPvOZv/7rv97a5mjBU57ylCuvvPKQQw5p4sShfwYACnHbbbf95E/+5Pe+973xH/3kT/7k/Px8tQ/1v+qqq17xilcs+k7i44477q/+6q8qnSwAPQwAW/Poo49+/OMf/5M/+ZMPfvCDTzzxxKJ/Zs2aNR/+8Idd/0kZDACU4KGHHjr66KM///nPj//o1FNPnZ+f32677Srf+C233PL85z9/0dHiPe95z6tf/erKtwxACgPA0M033/yf/tN/2tpyZ7fddrv66qt9JDQFMABQgle96lV/9md/Nn78lFNOufjii1eurPuN15/5zGf+zb/5N5s2bRo5vs8++9x6662rV6+uefsApDAALPiTP/mTs84669FHHx3/0b777vvZz37W9Z/kbkXfJwB1XXXVVYt2/4cffvh5551Xv/tfuIjoTW960/jxO++8893vfnf92wcgHa997Ws//vGP77rrruM/+va3vz03N/f444/3cV7QGAkAedu0adOhhx761a9+deT4jjvu+LnPfe7ggw9u6o4ee+yxI4888uabbx45/pSnPOUrX/nKihVmaYBCEoAFn/70p3/2Z3/2oYceGv/RH/zBH7z+9a9v6o6ge7oW8vbud797vPufmZl561vf2mD3PzMzs+2225599tnjx2+77bbrrruuwTsCIAXPfe5z3/ve9y76o7PPPvv222/v/IygMQYAMvbwww+fc84548cPOeSQM888s/G7e/GLX3zAAQeMH7/00ksbvy8AenfGGWe87GUvGz/+4IMPLvrqA7kwAJCxv/zLv7zzzjvHj//e7/3eNtts0/jdbbPNNq997WvHj19zzTWN3xcAKfjv//2/r1q1avz4e9/73kVfgCALBgAy9p73vGf84Nq1a1/84he3dI8nnXTS+MGbbrpp48aNLd0jAD068MAD//N//s/jxx955JFzzz23jzOCBhgAyNUtt9zymc98Zvz46173uvbeknv44YfvtddeIwcff/zxL33pSy3dIwD9+g//4T9sv/3248ff//7393E60AADALm67LLLxg/Ozs6eccYZ7d3p7OzsscceO378K1/5Snt3CkCPdt1110Xj33/8gT7OCOpq4CPSoRcf+tCHxg8effTR++23X6v3e8YZZ4x/zNzOO+/c6p0C0KNf+IVfuPjii8ePX3XVVYceemgfZwS1+B4AsvTggw/utttu41/F8qY3vel3fud3ejopAMr5HoAtPfroo2vWrBn/ToCXvOQll1xySRv3CK1yCRBZuvHGGxf9IsbnP//5fZwOACXbbrvtnvGMZ4wf/9znPtfH6UBdBgCy9Pd///eLHj/iiCM6PxcAyrfo68vXvva1Bx54oI/TgVoMAGTpC1/4wvjBffbZZ4899ujjdACIOABs3rx5/fr1fZwO1GIAIEvf/OY3xw8+5SlP6eNcACjfYYcdtujxb33rW52fC9RlAKCcAWDfffft41wAKN9uu+226PFvf/vbnZ8L1GUAIEvf+c53xg+Of0UXADRil112WfT4/fff3/m5QF0GALI0/llsMzMzq1at6uNcACjfrrvuuujxhx9+uPNzgboMAGTpkUceGT+4ww479HEuAJRvawnApk2bOj8XqMsAQJa+//3vjx/0rXYAtGTRL5+ZmZnZdtttOz8XqMsAQJa23377CWMBAKhva5t+4TM5MgCQpUUv91/0jQEAUN/WvvBrxx137PxcoC4DAFnaeeedxw/ec889fZwLAOW76667Fj2+zz77dH4uUJcBgCztt99+4wfvvPPOPs4FgPJt7fP+999//87PBeoyAJClRQvubbfd1se5AFC+L3/5y4sef9KTntT5uUBdBgCy9OQnP3n84F133fW9732vj9MBoHBf/OIXxw/utddeLgEiRwYAsvTMZz5z0eOf//znOz8XAMp3/fXXjx88/PDD+zgXqMsAQJa2VnM/9alPdX4uABTuvvvuu+WWW8aPH3300X2cDtS1svYtQA8OO+ywXXfd9b777hs5fs011/y3//bfWr3rf//v//3I541ut91273//+1u9UwB69OEPf3jRLwI77rjj+jgdqGvWl6eSqdNOO+3SSy8dObjNNtvceeede+65Z0t3un79+qc+9akjBw866KCvfvWrLd0jAIuanZ0dP9hSVzMYDC666KKRg7vtttvdd9/tm4DJkUuAyNWLXvSi8YOPP/74xRdf3N6dfuxjHxs/OD4SAFCMu++++7LLLhs/fvrpp+v+yZQBgFyddtppi1beP/7jP27vTq+66qrxg894xjPau0cA+vXOd77zscceGz/+S7/0S32cDjTAAECu9txzz+OPP378+Oc///lrrrmmjXt8+OGHP/7xj48fP+aYY9q4OwB6993vfveP/uiPxo8fddRRz33uc/s4I2iAAYCMvfa1r130+H/9r/+1jbs777zz7r333pGD22677Qte8II27g6A3r3hDW+4//77x4//l//yX/o4HWiGAYCMnXDCCUccccT48U9/+tMXXnhh43f3rne9a/zgscceu/vuuzd+XwD07sorr/zzP//z8ePHHHPMySef3McZQTMMAOTtt3/7txc9/mu/9mvf+c53Gryjiy666MYbbxw//su//MsN3gsAibj11lt/8Rd/cfz4Ntts8653vWvRzyCCXBgAyNvP//zPL3oFzj333POLv/iLTzzxRCP3cu+995511lnjx9euXXvqqac2chcApOP2228/7rjjNmzYMP6jN77xjb4AmNwZAMjeO9/5zkU/DugjH/nIG97whvq3v3nz5l/91V/99re/Pf6jt73tbdtss039uwAgHTfffPPRRx/9ta99bfxHP/3TP/3mN7+5j5OCJhkAyN5hhx32tre9bdEf/c//+T/f+MY31rz9M88884ILLhg//rM/+7ODwaDmjQOQjs2bN7/73e9+znOe881vfnP8p2vXrp2fn7f3oQC+CZgSbN68+ZRTTrniiisW/ekZZ5zxp3/6p6tXr572Zjdu3Pjrv/7r733ve8d/tGbNmptuuumAAw6odL4AJPdNwFdfffUb3/jGG264YdGf7r333tdee+3atWsr3z6kwwBAIe6///6f+ZmfWfR9ugtrmz/8wz886aSTJr/BT37yk6961atuvfXW8R+tXLnyIx/5yLHHHlvjfAFIYgD40pe+dPnll//FX/zFzTffvLU/c9BBB33sYx/zve8UwwBAOe6+++7nPe95X/nKV7b2B4466qizzjrr5JNP3nnnnbf2Z+6///4rrrjiHe94x9/+7d8u+gdWrFhx7rnnLvrREAD0OwCcf/75S/yVxx9//NFHH924ceOGDRvuvPPOW2+99e///u+X/ci45z73uRdffPG+++5b+5QhFQYAinL33XefcsopW+vdF2y33XbPec5znvGMZzz1qU/dddddt9122w0/8K1vfev666+/+eabl/jsoG233fbcc899+ctf3s7pAzCpDj6Ic8WKFa9//evf+ta3LvpRE5AvAwClefjhh3/lV37l/e9/f+O3vPfee1988cXHHHNM47cMQGoDwE/91E/9n//zf4488shW7wV64VOAKM2qVave9773XXrppfvss0+DN/sLv/ALt9xyi+4foHhHH3305Zdf/rd/+7e6f0olAaBYGzdufOc73/n2t7/9u9/9bp3beeELX/iWt7zlOc95TnOnBkByCcBhhx126qmnvuIVrzjssMOavWVIjQGAwj388MOXXnrp+973vmuuueaxxx6b/C/++I//+Ete8pJXvvKVT3va09o8QQA6GgBWrFixcuXKHXbYYfXq1bvttttee+114IEHHnLIIU9/+tOPPvrovffeu50zheQYAIhi48aN11133bXXXvulL33p1ltv/fa3v/3ggw9u3Lhx8+bNq1atWr169b777nvAAQcccsghRxxxxDHHHHPQQQf1fcoAAM0zAAAAQCDeBAwAAIEYAAAAIBADAAAABGIAAACAQAwAAAAQiAEAAAACMQAAAEAgBgAAAAjEAAAAAIEYAAAAIJDZwWDQ9zlAKtatW9f3KUB31H8YUv8JZYVHPEA0gx9Q/wFi1v+VfZ8GAN2x9QeIacv6/0/vAbAEAgiy9Rk5qP4DBKz/EgCAwtn6A8Q02Er9/+dPAbIEAgiy9R+h/gNEq/8SAIAC2foDxDSYoP7/8HsALIEAgmz9R6j/AKHqvwQAoBC2/gAxDaas/z/yTcCWQABBtv4j1H+AOPV/6gRgfn5+2r8C6Zibm+v7FCDXrb/6T9bUfwozqFH/V0y7BPL8AShj6z9C/QcIUv+9BwAgM671B4hp0FD9H00ALIEA4mz9R6j/ABHqvwQAIAO2/gAxDVqo/4skAJZAAHG2/iPUf4Di6//iAwAABZR+n9sDkKNBy/V/qwOAJRBA1qW/cvev/gOUXf+9BwAgIfXTXlt/gBwNOqz/S10CZAkEEGTrP0L9Byi4/ksAAHpm6w8Q06Cn+r/Mm4AtgQCCbP1HqP8ApdZ/CQBAD2z9AWIaJFD/l/8YUEsggCBb/xHqP0CR9V8CABBo6wNA91Kr/xN9EZglEEAZW59pqf8A5dV/CQBAoK0PAN1Iuf5PlABYAgGUsfWpQP0HKKz+SwAAAm19AGhPLvV/0gTAEgiggK1PNeo/QEn1XwIAEGjrA0Czcqz/UyQAlkAAuW99KlP/AYqp/xIAgEBbHwDqy73+T5cAWAIBZL31qUP9BxgUUf8lAACBtj4AVFNS/Z86AbAEAmIqY+tTk/oPBDQorv5LAAACbX0AmFyp9b9KAmAJBARR3tanPvUfiGBQdP2XAAAE2voAsLQI9b9iAmAJBJSq7K1PI9R/oEiDMPVfAgAQaOsDwLho9b96AmAJBBQjztanKeo/UIZByPovAQBCi7b1AWBB5PpfKwGwBALyFXPr0yD1H8jUIHz9lwAA4UTe+gBEpv43kwBYAgEZsfVplvoP5EL935IEAAjB1gcgJvW/lQTAEghIma1Pq9R/IFnq/9ZIAIBi2foAxKT+d5EAWAIBSbH16ZL6D6RD/Z+EBAAoiq0PQEzqfw8JgCUQ0C9bnx6p/0CP1P9pSQCA7Nn6AMSk/vefAFgCAR2z9UmH+g90Sf2vQwIAZMnWByAm9T+5BMASCGibrU+y1H+gVep/UyQAQDZsfQBiUv9TTwAsgYDG2frkQv0HmqX+t0ECACTN1gcgJvU/swTAEgioz9YnU+o/UJP63zYJAJAcWx+AmNT/vBMASyCgAlufMqj/wLTU/y5JAIAk2PoAxKT+F5UAWAIBk7D1KZL6DyxL/e9L9gnA3Nyc//CQKVsf6jBCQL7U/5ITgG6WQHM/UPNGgC7Z+kTQdv33AIAcqf8pyD4BmJ+fX3gJWfjfHhCQsvorH09zgByp/7ESgI6vBJUGQKkrH1ufHAkBAPU/QdknAFuGAEPSAEiHrQ9ATOp/6ASgr4+DkAZAv2x9EAJATOp/4kpIABYNAYakAdA9Wx+AmNT/LKwI8pnQ0gDohq0P44QAEIH6n5FCEoClQ4AhaQC0x9YHICb1PzvdJQC9hwBb3os0ABpk68OyhABQJPU/U+UkABOGAEPSAKjP1oeMrDnNIy20DZfY/TVJ/c9apwlAOiHAlncnDYAKbH3ILgTQ/0Ej1P8CFJUATBsCDEkDYHK2PgAxqf/F6GEAWLdu3dIPoLm5uV4eHMPJwUMTFtXIyqehcyFLbdf/ZXdAGy6ZcyEQVKD+F6a0BKByCLAlgQCMUPoBYlL/i9T1ewDSfCfA1s4hhdOA3K/1dKEnW/JOAMiF+l+wAhOApUOAdefPD142RfWXBhCWrQ9ATOp/8fpJAHoMAQYvm1t3/vy686d7XEoDCMXWh1YJASBZ6n8QZSYAk7wTYGEGkAbAlmx9AGJS/0PpLQHoNwT44TlIA+AHbH3okhAA0qH+B1RsAjDVxwFJA4jM1gcgJvU/rD4TgERCgB+ejDSAYGx96JEQAHqk/gdXcgJQ7TsBpAFEYOsDEJP6T/8JQGohwJA0gFLZ+pAOIQB0Sf0nSgJQ84uBpQGUxNYHICb1n+QSgGRDgCFpALmz9SFZQgBolfpP0ASgZggwJA0gR7Y+ADGp/6SeAKQfAgxJA8iFrQ+5EAJAs9R/lhUiAWgqBBiSBpAyWx+AmNR/MksAMgoBhqQBpMbWh0wJAaAm9Z+pREkAGg8BhqQBpMDWByAm9Z+8E4AcQ4AhaQB9sfWhDEIAmJb6T2WBEoD2QoAhaQBdsvUBiEn9p6gEIOsQYEgaQNtsfSiSEACWpf7TiFgJQAchwJA0gDbY+gDEpP5TcgJQRggwJA2gKbY+RCAEgHHqP40LlwB0GQIMSQOow9YHICb1n0AJQGEhQP00QCAQlq0PAQkBQP2nbRETgF5CgKF1589XGDMEAtHY+gDEpP4TNwEoNQSoHAUskAZEYOsDQgBiUv/pTNAEoN8QoPIbAxZIA0pl6wMQk/pPx9JNAMoOAYakAdj6wDghAEGo//QibgKQQggwJA0Iy9YHICb1nx4lnQAECQGGpAGh2PrA0oQAlEr9p3ehE4CkQoAhaUDxbH0AYlL/SUTqCUC0EGBIGlAkWx+YihCAYqj/JCV6ApBmCDAkDSiGrQ9ATOo/CcogAQgbAgxJA7Jm6wN1CAHIl/pPsiQAqYcAQ9KA7Nj6AMSk/pO4PBIAIcCQNCALtj7QICEAGVH/yYIEIEvSgGTZ+gDEpP6TkWwSgLaXQEs861ILAYakAUmx9YH2CAFImfpPdiQA2ZMG9M7WByAm9Z9M5ZQACAGWIA3oha0PdEYIQFLUf7ImASiKNKAztj4AMan/FCCzBEAIMAlpQKtsfaAvQgD6pf5TDAlAsaQBjbP1AYhJ/acw+SUAQoCpSAMaYesDiRAC0DH1nyJJAEKQBlRm6wMQk/pPwbJMAIQA1UgDpmLrA2kSAtA29Z/iSQDCkQYsy9YHICb1nyBmZ4p+otZ5Hi6xQ6q2R09QnUAj0xrXdpSR6a+Fgi1VypZbpYet/5PUijWnebJnpu3oRv0nNUvUMQlAaJXTgFCBwIT8KgBiUv/JTq7vAVjgnQD9vjcg7NsDRrjWE7rnnQCkQP0nUxIASk4DXPADJMsIkTX1v6a5uTm/wx7l/R6ABd4J0Ljs3hvQSwqhcpGFUt8DUMY7AcwAOVL8axo+rfwm2+Y9ABSVBiRy0dH4aahlAAVT5Mt4+aaQBEAIECENyK5qeJ0gEWUnAEIAuqGk17To88hvtW0SALJMA7Jr+rd28mocQKYU8JqyfikvWCEJgBCgmDSg+ErhtYSOFZ8ACAFoiXJd07JPHL/htkkASD0NKL7vH/LmJ4DEqc81xXlNz1c5CYAQIMc0QI3wSkPbIiQAQgCaoiDXNNXLut922yQApJgGkPi3KADEoQjX5JU9L3l/E/AIXwyc17cIM/6dygooxPxi4JoBAvTIi1eOJAD0nAa0beRldekX6fHX4O5zeYEAsCjblprSfJHKmr4/X0W9B2CBdwLErLAT7s+mHQCq3U6DTALUFOQ9AEHeCeCFpr2XJ8W2+9bf77xt3gNAaWlA73F5Z1mBQACAdNj6l6Go9wAs8E6A3rX0q1hz2vzwf2bS0+rpucISJlH8OwG80NAjr0QlkQDQpMZfnNLs9ac67QaTAWkAAN3T95enwARACNCLwcvmGvznp7zp7/3fYgcDSxACQIO84pRKAkADmnpBKqPjX/Zf10gmMDc3JwoAoCX1+/5158+bV5NVZgIgBMhr8V/Svr/Lf6/FDCxKCAD9vrj4jqD0SQCoqJG+fya2RjIBbwwAIJ2tf0PnQruKTQCEAK2q+W8Mte/v5hciCoAtCQFgKrb+0UgA6Lr1b+5cSrPwy6ncN4gCAJiWrX9MJScAQoB0LvePdpV/HTV/V94YAAuEALA0W//IJABMpE7r3/S5RFEnEPAZQQBsja0/hScAQoBGVPu3WPk3ovKvUQ4AQgAYYevPAgkAS7H4T8Sa0+YrdBLeFQDAAlt/YiUAQoDKLP6TIgqACoQAYOvPOAkAjb2o6PuTfWOAtwQABGTrT+gEQAjQ9qf92Pp3rMIv3KcDEZYQgIBs/VmaBIAfYfFf9hsDRAEAZbP1ZxJREgAhwCQs/oNEAa2dDiRKCEAEtv5MTgJA9e6/tXOh3ShADgBQElt/phUoARACNHXRv8V/gqb9j+ItAUQjBKBItv5UIwGIzuK/JKIAgCBs/akjVgIgBBih+y+PtwTA1ggBKIOtP/VJAOKa9rKfNs+FJk37XQFyAID0NbKv0fcTNAHoYAmUxW5G91+8ad8S0Oa5QCqEAOSokXdt2foTfQBoVRabVN1/EGYAgKxp/WlJ0AEgcggw+Tn4tJ8CTPUf0QxABEIAsqD1p1VBB4BWLV39+y3NU3X/LZ8L3TEDAORC608H4g4AfYUAPdL9R2YGgCEhAGnS+tOZuANAtBBA948ZACBNWn86FnoAiBMC6P5ZYAaABUIAEqH1pxehB4AgIYDuny2ZAQBSoPWnR9EHgOJDAN0/48wAIASgR1p/ehd9ACg7BND9szVmAIDuaf1JhAGg/BBgWbr/mPx3ByEAGbX+C32/1p9GGACKDQEmvHFdYGQT/tcvfgYGSL/1b+6MwABQaAig+2dCZgCCEwLQHq0/yTIAFBgC6P6ZihkAoFlafxJnACgtBND9U4EZgMiEADRI608WDAAhPg5ohO6fcR4VAHVo/cmIAaCoEGCSWUKfR53HRvrPAqhACEAdWn+yYwAoJwTQ/VOfGQBgclp/MmUAKCQEsN2hS8k+EaAyIQBT0fqTNQNAoHcCWP8zCY8TgCVo/SmAAaCEEMDFPzTLhUDEJARgaVp/imEAyD4E0P3TBjMAwJDWn8IYAPIOAaxz6Fc6zwVohBCAEVp/imQAKP+dANb/VOORA0Sm9adgBoCMQwAX/9A2FwIRkBAArT/FMwCUHALo/qnPowiIQ+tPEAaAXEMAKxzSIQSgMEKAgLT+hGIAyDIEcPEPXXIhEMAStP5kxwCQcQiwBN0/zfKIIhohAJPQ+pMpA0B+IYCqTZqSnYcBGqf1J2sGgAJDAMta2uBxRTRCABal9acABoDMQoBl67UujfYs++hKcB4GaIrWn2IYAHIKAWxrSJ8ZgJIIAVig9acwBoCivhPA+p+2eYwBoWj9KZIBIJsQwJ6GXAgBKIkQICytPwUzAJQTAljN0g2PNKBsWn+KZwDIIwSwoSEvQgBKIgSIQ+tPEAaAQkIAS1m65PEGFEbrTygGgMzeCbAo3Rjd85GghCIEAEpiAEjFstUfAADqMwBkHwJY/9MXIQChCAGAYhgAEiIEAACgbQaAvEMA63/65RFIKEIAoAwGgLQIASiMq4AAIDUGgOxDAAA6IwQACmAAyDgEcPUFKfBWYADIiwGgIiEAQExCACB3BoBcQwDrf9Lh0QgAGTEAVCcEgAl5LlAYIQCQNQNAlixcSY3HJADkwgCQ4hLIupTyeFRTGCEAkC8DAAAABGIAyO+dAK61IE0emUQjBAAyZQBIjislKJXHNgCkwADQAB8HBBCTEADIkQEgM66yIGUenwCQPgNAWksgWQFl8winPEIAIDsGAAAACMQAkNM7AVxfQfo8SglICADkxQAAAACBGAASWgK5PJoIPM4pkhAAyIgBIBuurCAXHqsAkDIDQMN8JwBATEIAIBcGAAAACMQAkMoSSDJAHB7tlEoIAGTBAJAHF1WTF49YAEiWAaAV3gkAEJMQAEifAQAAAAIxACSxBBIIEI3HPAUTAgCJMwBkwOXU5MjjFgDSZABokXcCAMQkBABSZgAAAIBADADtEgIAxCQEAJJlAAAAgEAMAK0TAsCiPPIpnhAASJMBIHU+SoV8efQCQIIMAEksgQAokhAASJABAAAAAjEAdEQIABCTEABIjQEAAAACMQB0RwgAEJMQAEiKAQAAAAIxAHRKCABb8lUAxCEEANJhAEiaj1Endx7DAJAaA0DXhAAAMQkBgEQYAAAAIBADQA+EAAAxCQGAFBgAAAAgkNnBYND3OUAqvGO1DTU3jgBAs1Y2fHuQM60qAFA8lwABAEAgBgAAAAjEAAAAAIEYAAAAIBADAAAABGIAAACAQAwAAAAQiAEAAAACWeaLwObnfTFqu+bmlvrmKV9M2wbf9pWgdevW9X0KES39TfDqf7/1f935fv8NG7wsy1/40qc9MzNzzpoGzvy3Niz/ylitJiz9OFf/++KbgOFHGLp6mbgGg4HXAIAKfmvDXP0Z4Jw185PMAG1Q/3vhEiAAgESlE00su8tflCwxTQYAIIPLUQDYmkaW941cSlSN+t89AwAAQLqEADTOAACkwhIIoBohAFMxACTN59WQO49hgPqEADTLANAzTwnYkiUQQDVCACZnAAAASJ0QgAYZAIC0WAIBVCMEYEIGAACADAgBaIoBAEiOJRBANUIAJmEAAADIgxCARhgAgBRZAgFUIwRgWQaA1PkYdfLl0QvQOCEA9RkA+ueZAIuyBAKoRgjA0gwAQD+MvgDVCAGoyQAApMsSCKAaIQBLMAAAvbEEAqhGCEAdBgAgaZZAANUIAdgaA0AGfJQKBT9uLYEAqhECUJkBIAmeA0Qz1WPeEgigGiEAizIAAD0zAANUIwSgGgMAkAFLIIBqhACMMwDkwdsAKPsRawkEUI0QgAoMAKnwBCCOao92SyCAaoQAjDAAAEkwAwNUIwRgWgYAIBuWQADVCAHYkgEgG94GQPGPVUsggGqEAEzFAJAQj34iqPk4twQCqEYIwJABAEiIMRgg9xCgGvW/SwaAnLgKiPR18Ci1BAJIOQSodhXQJNT/phgAgLRYAgFUIwRgQgaAtHjoU7amHuGWQADVCAEwAOTHVUBEeHyahAGqEQIwCQMAkCVLIIBqhAAYAJJj9qVUUz22PREAqhECsCwDQH5cBUSaun9kWgIBVCMECM4AACTKEgigGiEASzMApMjjnvK09Ki2BAKoRggQmQEgS64CIshj0jAMUI0QgCUYABLlcU9JWn08WwIBVCMECMsAkCshAEEejYZhgGqEAGyNAQBoXXvrnwWWQADVCAFiMgBkPPgKAUhBB49DSyCAaoQALMoAAHRBCACQJiFAQAaApBl8YYHnAkA1QgDGGQDy5iogMnoECgEA0iQEiMYAAOTBEgigGiEAIwwAqfNWYJJV4bEnBABIkxAgFAMAkA1LIIBqhABsyQCQASEACar8qBMCAB0bvGxu8DIvlMsTAsRhACiEGYAgjzdLIGByWv8tCQEYMgDkwYOekggBgLZp/asRAgRhACiHEIAgjzTzMLAErf8ShAAsMABkw4Oekl5ghABA47T+jRACRGAAKErvq1mKN+FjrO0lk3kY2JLWf3JCAAwAmfGgp6SXFiEAUJ/Wvw1CgOIZADLjI0Hp0bKPri27fyEA0Cqtf2VCAAwABTIDkMvjSggAVKD174AQoGwGgPwYfMllpSQEAJql9W+KECA4A0CZhADk8ogSAgCT0Pp3TwhQMANAsYOvGYCmTPJY2toySQgA9N76z/9Ac2dUCCFAZAaAXHncU8yriBAAWJTWv3dCgFIZAEomBCCFR5EQAJiW1r8bQoCwDAAZcyEQKV/8MxUhALBA658aIUCRDADlMwPQ+yNHCAAsS+vfCyFATAaAvHncU8wrhxAAwtL6J04IUB4DQPZcCEQWF/8IAYBxWv8UCAECMgCUwAxAppf+jxACQBxa/7x0EwK0R/0fYQAIxAxAv48TIQCg9U9TIiFA5TWQx8O0DACF8NCnjJcKIQAUTOufNSFASQwA5XAhEOlf/CMEgJi0/ukTAoRiACiKGYAcL/0fIQSAktRv/fV26RACFMMAEJEZgB4fFUIACKKp1t+TujNCgDgMAKWZ8NFvBqDC46Gz1wYhAGRN618wIUAZDAAFMgOQePcvBIBSaf1zJwQIwgBQJjMAme7+h4QAkBetfxxCgAIYAIplBiDl7l8IAMXQ+hdGCBCBAQAzQFDp/3cXAkDitP5hCQFyZwAo2eQlNf1ekGZN/l+8vVWQEADypfUvmxCgeAaAwpkBSLP7n5AQAFKj9WeBECBrBoDymQFItvsXAkBGtP6h9L4AWiAEaIkBIAQzAAl2/xMSAkDvtP4sSgiQLwNAFGYA0uz+hQCQMq1/ZIlsgoQAbTAABGIGiCzN7n9CQgDontafSQgBMmUAiMUMEFPi3b8QAJKi9af7F4WlZwAhQOMMAOFMNQMYA3I31X/EBHf/Q0IA6IDWn75CgB4NQtZ/A0BEU5VmM0C+pvpv12/3LwSAfmn92RohQJEMAEGZAYqXUfc/ISEAtEHrT31CgOwYAOKadgYwBuRi2v9YiXT/QgDomNafCQkBymMACG3ap4QZIH3T/jdKpPufkBAAGqH1p3FCgLwYAKIzA5Qk9+5fCABt0/pTjRCgMAYApi7lLgcq47Kf1Lr/CQkBoBqtP20TAmTEAMA/EwXkK/fF/5aEANA4rT+NEAKUxABArRnAGNCvCv8JUu7+JyQEgAlp/emYECAXBgB+RIUqbwboS4XffBbdvxAA6tP60wYhQDEMADRQ8UUBWSz+s+j+JyQEgK3R+tMvIUAWDAA0GQUYA9pW7ZecXesvBIAKtP50QAhQBgMADT9JjAEtqfyLza77n5AQAIa0/iRFCJA+AwCtvB6YAZpVufXPt/sXAsAktP50TwhQAAMAyxMF9MjifwlCACLT+pMyIUDiDABMpPIrhDGgsjq/ujK6fyEALErrT++EALlb2fcJkI2FZ0u1J9uwkV1zWvSn3LJqzktltP6Tm5uba7WODwaDdevWtXf7MJX6fb/Wh8781oa5pdv3xJVd/yUAdLo0Egi098vJ+or/rRECwAJbf1IjBMiaAYAenjbGgMZ/IeW1/pPzTgDKpvUnX94JkCwDAL29nCx0vZEngUZ+A0Uu/rckBCAsrT+JEwLkywBA/y8t0SaBpv69xbf+kxMCUB6X+1MGIUCaDADMpPMaU/Yk0Oy/LlTrLwSAaVn80w0hQKZ8ChD9f0ZQ2Z8a1Pg8E6r1n5yPA4LgDQ3J8nFACTIAkO4YMNI9ZzQMtBRiRG79150/38gVEVszPz/f9nVE0DatP0XW56Fz1sy3cUHRfMj6bwAggzEgi2Gg1SuXIrf+kxMCEJbWn8R1EAK0+hIwKK7+GwDIbAzYWrfd8UjQ2RsVtP5DQgAYp/UnBUKA7BgA6OjFqe2n1tY68pqDQV/vSNb3VyMEIA6tP3kRAiTFAEAJgUCDHXzvn0Gk9V+CEAC0/i3pZoFNfUKARhgAKDMQyI6+vylCAAqm9a/GK04ihADp8D0A9MNnVA/5Pq+p+E4AYlIzq5n7gb7Pgoa1NEXMR3qKSQDoU+RAQNPfHiEAJQnVlDQo4MtKFoQAiTAAkIQ4k4C+vz7vBCAIrX81nr8ReCdATQYA0n3BK+ZJqOnvnhCArGn9qynmVaNsQoAUGABIV9bDgKa/VUIASqX1r8YTNiAhQB0GAPKQxTCg6U+KEIC8aP2rSfYVgSUIAXpnACA/iQwD2v1+CQEohta/Gs9QhACVGQDIVWdPTo1+voQAJE7rX03xzVkEQoB+GQDIT3ulX6+fFyEAWdP9V9DeUzKv/xw1fw9td95dEgJU44vAyImvdGFabVfwwWDQ6u0DC9T/Br8Y7rc2zLXRNCeo1cfMIOf6bwAgSulf9wPNnRFJ8MXAUDz1f2uMAQt8MXAFBgBSp/RTkxAAMqX+T8IYsDQhwKK8B4CSn7TF1328EwCKpP5Pa2EGqPx7W5gB8n1vgHcCTEsCQIpsfWiWEAByof7XIQ1YlBBgnASAtNj6UIEQAAqg/jclZhogBJiKBIBU2PrQKiEAJEv9b4M0YEtCgBESAPpn60N9QgDIkfrftlBpgBBgchIA+mTrQ5eEAJAO9b9L0gAhwAgJAP2w9aFxQgDIgvrflwhpgBBgQhIAumbrQ4+EANAj9T8FkdMAIcCQBIDu2PrQNiEApEn9T03BaYAQYBISALpg60M6hADQJfU/ZQHTACHAAgkA7bL1oWNCAEiE+p+L8tIAIcCyDAC0ReknWXNzc3WWXssaDAYevUSm/udoWBWr/edLcAzo5SVgkEn9NwDQPKWffgkBoC/qf/BAIJ0xQAiwNO8BoEmu9SQX3gkAzVL/C1Pn7QHpvzdgLvw7ASQANMPWh6QIAaAz6n/Bsk4DhABLkABQl60PmRICQE3qfxBFpgFzsUMACQDV2fqQMiEAtEf9DyjHNEAIsDUSAKqw9aEMQgCYlvofXElpwFzgEEACwHRsfciIEAAapP6TYxogBFiUBIBJ2fpQJCEALEv9p9Q0YC5qCCABYHm2PuRLCAB1qP8UkAYIAcYZAFiK0k8EvhgYxqn/dDkGpPDdYaHqv0uAWJzAl2KsO7/d15VWhwfonvpP9xcFtX1F0BIDxlyNR3u+9V8CwChbHwISAoD6T+9pQO/fHRan/ksA+CFbH0olBIClqf8UnwYIAbZkAKCZ0m/xQ+58HBAxqf+EGgN6MUiv/hsAomuq9Kv+JE4IACPUf6KNAUKAIe8BiKuRfae6T0m8E4Ag1H96Efm9AYPE6r8EICJbH2ISAoD6T/A0QAiwQAIQi60PLE0IQKnUf5ISMA0YpFT/JQBR2PqAEICY1H+S1UsacI4QQAIQga0PTEUIQDHUf7IwLLnTPmKzSwMGydR/CUDJbH1gnBCACNR/4gQCFdKAc8KHABKAMtn6QB1CAPKl/hPz7QG5pAGDNOq/BKA0tj6wLCEARVL/KUnbacA5sUMACUA5bH2gQUIAMqL+U6oi04BBAvVfAlACWx+YlhCAMqj/RNBSGnBO4BBAApA3Wx9ojxCAlKn/RFNSGjDou/5LAHJl6wM1CQHIlPpPZM2mAedEDQEkAPmx9YHOCAFIivoPxaQBg17rvwQgJ7Y+0CwhALlQ/6GlNOCckCGABCAPtj7QFyEA/VL/odQ0YNBf/ZcApM7WB1olBCBZ6j90kwacEy8EkACky9YHEiEEoGPqP3SfBvSir/ovAUiRrQ90SQhAOtR/6CsNCBUCSADSYusDaRIC0Db1H1JIA7rXS/2XAKTC1gd6JASgR+o/JJ4GzBUXAkgA+mfrA1kQAtA49R+6kXgaMOi8/ksA+mTrA+kQAtAl9R/ySgPmygoBJAD9sPWBHAkBqE/9h37NJ5kGdFz/DQBdU/pTNnhZWuWAwszPz6f2kkOX1H9Ix/y/bHMmf2LW2QGlVv8NAN1R+qEAQgAqUP8hWfPJBAJd1n8DQBeUfiDNJRBtU/+hpDFgrpQQwADQLqUfyiMEYBLqP2Rnvu80oLP6bwBoi9IPpL8Eog3qPxQ8BswVEQIYAJqn9EPxhAAsSv2HYsz3lAZ0U/8NAE1S+oG8lkA0Rf2HOGPAXP4hgAGgGUo/RCMEYIH6D8Wb7zYN6KD+GwDqUvqBfJdA1KH+Q9gxYC7zEMAAUJ3SD8EJAcJS/yGs+U7SgLbrvwGgCqW/VK02c5DgEohpqf/ATO2Goff6bwCYjtIPdEkIkA71Hyim/hsAJqX0A43rfQnEJNR/oLD6bwBYntIP9EgI0CP1Hyiy/hsAlqL0A20TAqRJ/QcKrv8GgMUp/UA6hABdUv+B4uu/AWCU0g90TAiQCPUfCFL/DQA/pPQDyRICtEr9B0LVfwPAP1H6gX4JAfqi/gMB63/0AUDpB3IhBGiW+g+Erf9xBwClH0iKEKAz6j8QvP5HHACUfiBTQoCa1H8gU83W/1gDgNIPpEwI0B71H0jZfLf1P8oAoPQDZRACTEv9B8owaK7+lz8AKP1ARoQADVL/gYzMd1j/Sx4AlH6gSEKAZan/QJEGDdX/MgcApR/IlxCgDvUfyNd8V/W/tAFA6QciEAKMU/+BCAZN1P9yBgClHyiGEGAq6j9QjPlO6n8JA4DSDwQkBFD/gZgGtet/3gOA0g+USgiwNPUfKNV8+/U/1wFA6QeIGQKo/wCDevU/vwFA6QeCEAKMUP+BIOZbrv85DQBKP0DMEED9B2iw/ucxACj9QExCAPUfiGm+zfqf+gCg9APEDAHUf4CW6n+6A4DSDxAzBFD/AWbarP8pDgBKP0DMEED9B+ig/qc1ACj9ADFDAPUfoLP6n8oAoPQDxAwB1H+Ajut//wOA0g8QMwRQ/wF6qf99DgBN/WNUf4C8QgD1H6DH+t/PAKD0A8QMAdR/gN7rf9cDgNIPEDMEUP8BEqn/3Q0ASj9AzBBA/QdIqv53MQAo/QAxQwD1HyDB+t/uAKD0A8QMAdR/gGTrf1sDgNIPEDMEUP8BEq//zQ8ASj9AzBBA/QfIov43OQAo/QAxQwD1HyCj+t/MAKD0A8QMAdR/gOzqf90BQOkHiBkCqP8Amdb/6gOA0g8QMwRQ/wGyrv9VBgClHyBmCKD+AxRQ/6cbAJR+gJghgPoPUEz9n3QAUPoBYoYA6j9AYfV/+QFA6QeIGQKo/wBF1v8VHVT/dT9Q/3YAqGAwGFT4W+o/QKn1f5kBoCalH6Bt8/PzM+lR/wGSrf9tDQBKP0DuIUA16j9A4vW/+QFA6QeIGQKo/wBZ1P8mBwClHyBmCKD+A2RU/5sZAJR+gJghgPoPkF39rzsAKP0AMUMA9R8g0/o/3TcBb0ndpzydfakqZE39pzzqP6FUSQBsfQBihgDqP0AB9X+6BEDdB4hJ/QcIlwDY+gDEDAHUf4DC6v/yCYC6D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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_94
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 7th action is Colorize the top layer of the original shape with the color purple.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_139
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color blue.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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/cBABojANBC6a/iBwBoiwAQV5N1v4ofACARAkA4zdT9Kn4AgDQJAFE0UPcr+gEA0icAlK/W0l/RDwCQFwGgZPWV/up+AIBMCQAFqqnuV/QDABRAAChKHaW/uh8AoCQCQCEqL/3V/QAARRIA8qbuBwBgIAJArqot/dX9AABBCAChS391PwBANAJATpT+AACMSACIVfqr+wEAghMAUqf0BwCgQgJA4aW/uh8AgI0JAClS+gMAUBMBIC1KfwAAaiUAFFX9K/0BAOhNACih9Ff3AwDQJwGgZUp/AACaJAC0RukPAEDzBID8qn+lPwAAQxMAmqb0BwCgRQJAc5T+AAC0TgBIvfpX+gMAUCEBoHYa/wAApEMAqJfGPwAASREA6qL0BwAgQQJAQtW/0h8AgLoJABXT+AcAIGUCQJU0/gEASJwAUA2lPwAAWZjX9g6UQPUPAEAuTABaqP6V/gAAtEUAGJ7GPwAA2REAhqTxDwBAjgSAJqp/pT8AAIkQAAaj8Q8AQNY8BWgAqn8AAHJnAtAvy34AACiAADA7jX8AAIohAMxC4x8AgJK4B6AX1T8AAIURAGak+gcAoDyWAE1D6Q8AQKlMAKZS/QMAUDAB4P9Q/QMAUDZLgIas/pX+AADkyATg/1P9AwAQgQnA/1D9A0Bka5aPz/SjPVeONbsvULvoAUDpDwAMlw3EAzIVOgCo/gGAyuOBVEDi4gYA1T8A0EwqEAlIStAAoPoHANqKBPIA7YoYAFT/AEAieUAYoHnhAoDqHwBIhzBA82IFgP6rf6U/ANAwYYBmBAoAqn8AILswIAlQuSgBQPUPAORIEqByIQKA6h8A6GFs2cqZfjS+evmcNEgCVKX8AKD6BwDqyAZtxQNJgBEVHgBU/wBAw/GgsVQgCTCckgOA6h8AaD0VNJAHJpOAGED0AKD6BwBC5QEDAUIHANU/AJB+HqgpDBgIEC4AqP4BgCzUGgbEAKIEANU/AJB1GKg2CVgXROEBQPUPAOSuprGAgQAFBgDVPwBQmMrHAmIA5QQA1T8AULBqk4AYENy8OflT/QMAQYwtW9n7y4n7t2b5+IY7BAilkAlAP1T/AEAZKhwImAYENC9I+1/1DwCUp6qBgGlAKHlPAFT/AABVDQTWLB83Cogg4wmA6h8AoNqBgFFABLkGANU/AMC0xAAKXAKk+gcAqHtdkPuDS5XfBED1DwDQ2EDAKKA8+QWAfqj+AQCqigFWBBVmXqnf+QUAQLUxoOrdoR05BQCLfwAAWowBRgFlyCYAqP4BACpkFBBWHgFA9Q8AUDmjgJjyCAD9UP0DADQcA2rYHWo3r4z2v+ofAKD5GGAUkKPUA4DqHwCgMUYBESQdADz0EwAgl1FAPbtDsADQD+1/AIAUYoDlQLlINwBY/AMA0C6jgCIlGgBU/wAA+Y4CatsdCg0Alv4DACTFcqCSpBgA+qH9DwDQJKOAYiQXACz+AQBIlgxQgLQCgOofACBxMkDuEgoAlv4DABS5HMgtAUlJKAD0Q/sfACARRgGZSiUAWPwDAJAdGSBHSQQA1T8AQJzlQHXuDpkEAAAAsiYDZKT9AKD9DwBQABkgFy0HANU/AEDM5UAyQNwJAAAAJZEBEtdmAND+BwAokgyQstYCgOofAKBgA2UAMaBJ6S4BUv0DAGTNbcFpmpds+x8AgNzJAAlqIQBY/AMAEIcMkJp0lwABAFAGjwcNHQC0/wEAYhpoFECgCYDqHwAgeAYwBCgnALj3FwAgOBkgUACw+AcAABmgdQktAVL9AwAEIQO0aH4zb2PxDwDQmEGrxvHVy7s3umO1bmPLVk77m59izfLxPVeONbJHUTQUAGal/Q8ADKrW9vBMtalgUCEZoNgAoP0PAIwukdUg3QWrSDAKGSDoBED7HwBIuejvbeP6VRgYggxQWgCYtf2v+gcAsiv6ZyIMDEcGKCcAWPwDABRf9M9EGCBNLS8B0v4HgMiKrPt7hwFJYCaGACUEAO1/ACB43d9NEuhBBij/i8C0/wEgmjXLxyNX/xsbX728n2I3Gl8QlvEEQPsfANhAuTYTA4Fu5gDF3gOg/Q8AEbRV+k+pp3sXlN3Fd/O9+cl3FAMGygAkFAA8+hMAgmus7q+pYp7pZeuuSg0EBsoAhgAZfxEYAFCMWkv/1svixmYFBgIyQE4BQPsfAGKqqfRPvAjeePcqDwNiQD9kgEGZAAAAyZX+mZa8NYWByDHAzQAZBADtfwAIpdrSv6Qad8N/S1X1a9gYYCFQ5UwAAICWq/+yi9pqk8D46uVl/7qmJQOkGwC0/wEgiEpK/2iFbFVJIOwoYFYyQJ9MAACARkt/lWslSSBaDHAzQIXmVfVC2v8AULwRq/+xZSvjFKzN/EJC1cT9/K5853SjAQAAKNia5eOjlFZK//p+OeOrl8eJATJAQkuAtP8BoFQj1v2V7kvJRlwXFG1FEKMwAQAAqq/+tfyHNsqvLsIowBAgjwCg/Q8AORquilL6V2LoX6MMMEkGqDcAzLr+BwAIsuJf6V+toTNA8THAkTYKS4AAgP9D4z8pRgFDMwSoKwC4/RcAgtdMSv8GDPdLLjsDWAg0NF8EBgAMX/rXsy/0+oUPVNaX/XQg3w7WwgRA+x8AyqD6z4hRwEAMAbq5BwAAohu0QrLmp3VD/BOUmgEsBEorAGj/A0CR1X9t+8JgZIBJjsnm7gHw9E8AyJrSP+BdAWXfEtDDmuXje64ca3svSp8AaP8DQMpU/yUxCnB8NhEAtP8BIF+q//LIALNyJ8AGbgIGgFgGKoPc75uRQf+xCssADtR6A4CnfwJAkOq/zn2hFjJAD4YAk0wAACAK1X8QkTPArNbIAHUEAO1/AMi67rHspwAD/SOWlAEcurUEALf/AkDZ1X/N+0JzYmaAWa0JPwSwBAgACqf6jyxgBnAYNx0ArP8BgKSo/gmYAWa1JvYQYLAAYP0PAGRE9U/MDOB4bm4CoP0PAOlQ/bMxGWCKNYGHAO4BAIACqf7pFi0DUEEAsP4HALKg+mcmoTKAIUDtEwDrfwAgL6r/mPy7028A0P4HgCz02dRUBUbW57++IUCp3AMAAOVQ/dOnOBmAugKA9T8A0DrVPwMJkgEMAYYMANb/AEDiVP8MIUgGYApLgAAgCtU/MY+KCP+NTQcA638AIP32vxqIUY6NsocAa4KtAjIBAIC8qf4ZnQwQyuwBwA0AAJCsaJ1L2pVvBnArcJUTAOt/ACBx2v/0w3EShyVAAJAri3+oVtkLgQwB+g0A1v8AQJpU/9Sh7AxABRMA638AoBVxWpWkKdMMIBJPsgQIAMqk1mE4kY+cNTGida8AYP0PACTI4h/qZiFQ2UwAAKA0qn9GV+pRNOZW4FECgBsAAKB5EaoTcmEIkCkTAADIhsU/NKnUhUBj4T8jMwYANwAAQHZUNlQr5hG1pvQ525ATAOt/AKBhxRclZCrHIUBwlgABQCFiNmupW5HH1ViJ/1H9EwAAoIT2f/CChlrNenSVNwRYU/TAbfoA4AYAAEhH2bUIZcguA4wFzszDTADcAAAASYlcytAMx1hJLAECgKRp/5OL7IYAYT96AgAA5E1rlmaUd6SNFfdfNHwAcAMAACSi4B4kRSpsCFCqgScAbgAAgHSEbWHSimjH25pCE7glQACQKI/+JEGFPRJ0LOSHSAAAAIBABAAASJH2P8kqbAgQcBXQ1ADgDmAAACjYYBMAdwADQAq0/2lXSUfgWEH/LX2yBAgAklPkqgNCKWkVUHkEAAAACBTIBQAASIvbf8lCSbcCjwX7TP2fAOAOYAAAKNsAEwB3AANA66K1KkmZozFTlgABQELKW21MZBmtAgr1wRQAACAbGq6kpphjcqyU/5B+CAAAkIrCuoxQ0hCgzADgDmAAAChevxMAdwADQLtCLVEgI0GOzDUFDegsAQKAJJRUXkCOq4DGYiQZAQAAAGIRAAAgA3F6k+TI8ZkXAQAA2mf9D2XLZRVQEAIAAAAECurz+nkGqEcAAUCLrK8gfWUcpWNF/FfMygQAAAACEQAAoGXFrCuAHtwGkA4BAACSFmRNAgVwrOZCAAAAgEAEAAAA6GuOUcaCPQEAANpURj0B/XAbQCIEAABIl0XV5MURm00A8CUAAAAQhAkAAAAEIgAAQGvcAEA0bgNIgQAAAImynJocOW7TJwAAAECgJ4EKAAAAEIgAAAAAgQgAAAAQiAAAAO0oYCUxDMGDgFonAABAijxKhXw5ehMnAAAAQCACAAAABDKv0+n0+PGKk69pcGcAAIB6mQAAAEAgAgAAAAT6MmABAAAAAhEAAKAFuXcQYRS+CqBdAgAAJMdj1MmdYzhlAgAAAAQiAAAAQCACAAAABCIAAABAIPN7//jZL9y3qT0BICGeUdMuz0iheLkf5GtyPknOEgAAAIqXezEKA7EECAAAAhEAAAAgEAEAAAACEQAAACAQNwET3apVq9reBQCA5pgAAABAIAIAAAAEIgAAAEAgc9veAQDa0el0evx0z5VjDe5LRL2/RnRs2coG9yUK3/aVlPQP8vGeB0z6J8keJxk3AQMAZFCPZkfiSpYlQAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAkBx3T5I7x3DKBAAAaEH6zxCE+njmUrsEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAABIkceoky9Hb+IEAABoh68CICZfAtA6AQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAABLlUSrkyHGbPgEAAFrjQUBE4xFAKRAAAAAgEAEAAAACEQAAIF2WU5MXR2wWBAAAaJPbAIjDDQCJEAAAACAQAQAAAAIRAAAgaRZVkwvHai4EAABomdsAiMANAOkQAAAAIBABAABSZ2UF6XOUZkQAAACAQAQAAGif2wAomxsAkiIAAEAGrK8gZY7PvAgAAAAQiAAAAEmwCohSWf+TGgEAAPJglQVpcmRmRwAAAIBABAAASIVVQJTH+p8ECQAAkA1rLUiNYzJHAgAAJMQQgJJo/6dJAACAnGi4kg5HY6YEAAAACEQAAIDMVgFpu5KCWY9D63+SJQAAAEAgAgAAJMetwORO+z9lAgAA5McqINrlCMyaAAAAAIEIAACQIrcCkyy3/+ZOAAAAgEAEAABIlCEACdL+L4AAAAAZkwFokuOtDAIAAKTL80DJi/Z/FgQAAMibpizNcKQVQwAAgKQZApAL7f9cCAAAkD2tWermGCuJAAAAqTMEIH3a/xkRAAAgAx4JSos8+rMwAgAAFEIGoA6Oq/IIAACQBwuBSJP2f3YEAAAoh2Yt1XJEFUkAAICihgAqNqrSz7Gk/Z8jAQAAcmIhEOlQ/WdKAACA0hgCMDpHUcEEAADIjIVA1M3in7IJAABQJhmA4ThyiicAAEB+3AlAu7T/syYAAECWLASiDhb/RCAAAECuZACqpfoPQgAAgMLJAPTDcRKHAAAAGXMzAE3S/i+DAAAAebMQiNFZ/BOKAAAA2ZMBGIXqPxoBAACikAHo5qgISAAAgEA3A6j2GOJ40P4vjAAAAIWQARiI6j8sAQAAyiED0CfVf2QCAAAURQZgVqr/4AQAAAhKBojJvzsCAADE/XYwtWA0/f+La/8XTAAAgALJAHRT/TNJAACAMskAbEz1zwYCAAAUSwZgkuqfjQkAAFAyGQDVP1MIAABQOBkgMtU/3QQAACifDBCT6p9pzZ9+MwBQlj1Xjq1ZPt5/1agizNpAQc6/dTQmAAAQRf9zAKOArKn+6U0AAIBAZIDiqf6ZlSVAABBL/2uBLAfKy6CBzT9rWCYAABDOQHMAo4AsqP7pnwAAABHJACVR/TMQS4AAIHQGsBwoa0p/hmACAAChGQXkS/XPcEwAACC6gW4LNgpIwRAxzL8XG5gAAAADzwGMAlqk+mdEJgAAwDC3BBgFNE/pTyUEAABg+OVAYkAzhpu3+EdhWgIAADBqBhAD6jP0Uiv/FszEPQAAwFR7rhwb4q4ANwak0/hX/dODCQAAMD2jgBZp/FMfAQAAqDgDiAGjGGWK4hdOPwQAAKDipwN117IK07pXT/kN0z8BAACoNwYYCPSm9KdhAgAAUPuKoEliQOX3TPtlMgQBAABobhRgXVBVz0oK+9tjdAIAANBCDAiYBKp6RmqQXxf1EQAAgHZWBAVJAtV+N0KRvyIaJgAAAC2PAopMApV/J1oBvxMSIQAAAGnFgCnVc0aFb01fhJzRb4AsCAAAQKIxIIswUFPRn+x/LwUQAACADGLATNV2wyVyreX+xpT+1EcAAADqigH1JYFZK/IRC+jGCv0p1P00QAAAAHIdCFRYwbdV8W+g9KcxAgAAUM5AIDvqfponAAAA5Q8EEqT0py0CAADQtMgDAXU/rRMAAIDWxEkC6n7SIQAAAAklgZLCgKKfNAkAAEBasg4Din7SJwAAAOnKIgwo+smLAAAA5BcGWowEyn1yJwAAAOVEggqDgUKfUgkAAED0WYFan1Dmtb0DAABAcwQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEDmt70DAAAtG1+9vO1dgOaYAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIL4JGACIbs+VY23vAjTHBAAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACmdv2DgDQjk6n0/YuANACEwAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEDmTkxMtL0PAABAQ0wAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAApnf9g5Ac9atW3fZZZddcsklP/7xj6+99trrr7/+zjvvXLt27f33379w4cJFixbtvPPOu+666z777LPffvsddNBBe+yxR9u7DABQsbkTExNVvyakZd26dZ/73Oc+9alPXXjhhffcc0//f3GvvfZ61rOe9aIXvWivvfaqcwcBGNhpp5020J+fO3fuvHnzNtlkkwULFixcuHDrrbfefvvtFy9evHDhwtr2ERIlAFCyu+6664Mf/OB73vOeW265ZZTXOeqoo97ylrc88pGPrG7XABjJ3LlzK3md3XbbbcmSJY961KOe+MQnPuEJT9hyyy0reVlImQBAsU477bTXvva1N910UyWvNm/evFe96lXvfOc7XRsASgoAG1uwYMHTn/705zznOcccc8ymm25a+etDIgQACvT73//+xS9+8dlnn135Kz/sYQ87++yzH/awh1X+ygC0HgA22HXXXU844YRXv/rVFghRJAGA0vzwhz886qij1qxZ0+PPPPShDz3ggAP22WefHXbYYauttrr77rv/8Ic/jI+PX3XVVd/85jfHx8d7/N1tttnmC1/4woEHHljDvgOQRACYtPvuu7/73e8+7rjj6n4jaJgAQFEuvfTSQw899Pbbb5/2p7vtttsrXvGK5zznOQ960INmeoWJiYmrrrrqv/7rvz71qU/deeed0/6ZbbbZ5qKLLnrUox5V3Y4DkFwAmNTpdD784Q9vt912zbwdNEAAoBzf+c53Dj744Gmr/6233vrNb37za17zmv7XdN52220nnnjiSSedNO1nZLfddrv88st33nnnkfcagMoCQO+q5o9//ON9991311133XnnnbfccssvfvGLa6655tvf/vZXv/rVmTpHkx784Aefd955e++9dxU7Du0TACjEdddd95jHPOYPf/hD948e85jHrFy5criH+l944YXPe97zpr2T+JBDDvniF7841M4C0EIAmMn69eu//OUvf+QjH/nc5z53//33T/tnxsbGLrjgAus/KYMAQAnuuuuupUuX/uAHP+j+0dFHH71y5crNNtts6Be/+uqrn/jEJ04bLT760Y++5CUvGfqVAUghAGxw1VVX/d3f/d1MzZ1tt932oosu8khoCiAAUIIXv/jFn/jEJ7q3H3XUUWeeeeb8+aN+4/W3v/3tv/iLv1i3bt2U7YsXL7722msXLVo04usDkEIAmPSRj3zkhBNOWL9+ffePdt555+9+97vWf5K7eW3vAIzqwgsvnLb632+//U499dTRq//JRURvfvObu7ffeOONH/7wh0d/fQDS8fKXv/zLX/7yNtts0/2j3/72t8uXL7/vvvva2C+ojAkAeVu3bt0+++zz85//fMr2LbbY4vvf//5ee+1V1Rvde++9BxxwwFVXXTVl+4Mf/OCf/exn8+bJ0gCFTAAmffOb33zKU55y1113df/ove997+te97qq3giap2ohbx/+8Ie7q/85c+a84x3vqLD6nzNnzqabbnriiSd2b7/uuusuvfTSCt8IgBQ8/vGP//jHPz7tj0488cTrr7++8T2CyggAZOzuu+9+17ve1b197733Pv744yt/u2c84xm77bZb9/azzjqr8vcCoHXHHXfcs5/97O7td95557RXH8iFAEDGPvvZz954443d2//5n/95k002qfztNtlkk5e//OXd2y+++OLK3wuAFPzLv/zLwoULu7d//OMfn/YCBFkQAMjYRz/60e6Ne+655zOe8Yya3vGII47o3njllVeuXbu2pncEoEW777773//933dvv+eee04++eQ29ggqIACQq6uvvvrb3/529/ZXvepV9d2Su99+++24445TNt53330/+clPanpHANr1N3/zNwsWLOje/ulPf7qN3YEKCADk6uyzz+7eOHfu3OOOO66+N507d+7BBx/cvf1nP/tZfW8KQIu22Wabace/P/qTNvYIRlXBI9KhFeeff373xqVLl+6yyy61vu9xxx3X/Zi5rbbaqtY3BaBFz33uc88888zu7RdeeOE+++zTxh7BSHwPAFm68847t9122+6vYnnzm9/8tre9raWdAqCc7wHY2Pr168fGxrq/E+CYY45ZvXp1He8ItbIEiCxdccUV034R4xOf+MQ2dgeAkm222WYPf/jDu7d///vfb2N3YFQCAFn63ve+N+32/fffv/F9AaB8015ffvGLX9xxxx1t7A6MRAAgSz/84Q+7Ny5evHj77bdvY3cAiBgAJiYm1qxZ08buwEgEALL061//unvjgx/84Db2BYDyLVmyZNrtv/nNbxrfFxiVAEA5AWDnnXduY18AKN+222477fbf/va3je8LjEoAIEu/+93vujd2f0UXAFRi6623nnb77bff3vi+wKgEALLU/Sy2OXPmLFy4sI19AaB822yzzbTb77777sb3BUYlAJCle+65p3vj5ptv3sa+AFC+mSYA69ata3xfYFQCAFn64x//2L3Rt9oBUJNpv3xmzpw5m266aeP7AqMSAMjSggUL+hwLAMDoZur0Gz6TIwGALE273H/aGwMAYHQzfeHXFlts0fi+wKgEALK01VZbdW+85ZZb2tgXAMp30003Tbt98eLFje8LjEoAIEu77LJL98Ybb7yxjX0BoHwzPe9/1113bXxfYFQCAFma9oR73XXXtbEvAJTvpz/96bTbH/jABza+LzAqAYAsPehBD+reeNNNN/3hD39oY3cAKNyPf/zj7o077rijJUDkSAAgS494xCOm3f6DH/yg8X0BoHyXXXZZ98b99tuvjX2BUQkAZGmmc+7Xv/71xvcFgMLddtttV199dff2pUuXtrE7MKr5I78CtGDJkiXbbLPNbbfdNmX7xRdf/E//9E+1vvVf//VfT3ne6GabbfbpT3+61jcFoEUXXHDBtF8Edsghh7SxOzCqub48lUwtW7bsrLPOmrJxk002ufHGG3fYYYea3nTNmjUPechDpmzcY489fv7zn9f0jgBMa+7cud0ba6pqOp3OGWecMWXjtttue/PNN/smYHJkCRC5evrTn9698b777jvzzDPre9MvfelL3Ru7IwEAxbj55pvPPvvs7u3HHnus6p9MCQDkatmyZdOeeT/0oQ/V96YXXnhh98aHP/zh9b0jAO36wAc+cO+993Zvf8ELXtDG7kAFBABytcMOOxx66KHd23/wgx9cfPHFdbzj3Xff/eUvf7l7+0EHHVTH2wHQut///vfvf//7u7cfeOCBj3/849vYI6iAAEDGXv7yl0+7/R//8R/reLtTTz311ltvnbJx0003ffKTn1zH2wHQute//vW333579/Z/+Id/aGN3oBoCABk77LDD9t9//+7t3/zmN08//fTK3+6DH/xg98aDDz54u+22q/y9AGjdeeed98lPfrJ7+0EHHXTkkUe2sUdQDQGAvL3pTW+advurX/3q3/3udxW+0RlnnHHFFVd0b3/pS19a4bsAkIhrr732+c9/fvf2TTbZ5IMf/OC0zyCCXAgA5O2Zz3zmtCtwbrnlluc///n3339/Je9y6623nnDCCd3b99xzz6OPPrqStwAgHddff/0hhxwyPj7e/aM3vvGNvgCY3AkAZO8DH/jAtI8D+vznP//6179+9NefmJh45Stf+dvf/rb7R+985zs32WST0d8CgHRcddVVS5cu/cUvftH9o7/8y798y1ve0sZOQZUEALK3ZMmSd77zndP+6N/+7d/e+MY3jvj6xx9//Gmnnda9/SlPeUqn0xnxxQFIx8TExIc//OHHPe5xv/71r7t/uueee65cuVLfhwL4JmBKMDExcdRRR5177rnT/vS444772Mc+tmjRokFfdu3ata95zWs+/vGPd/9obGzsyiuv3G233YbaXwCS+ybgiy666I1vfOPll18+7U932mmnSy65ZM899xz69SEdAgCFuP3225/0pCdNe5/uZNvmfe973xFHHNH/C37ta1978YtffO2113b/aP78+Z///OcPPvjgEfYXgCQCwE9+8pNzzjnnM5/5zFVXXTXTn9ljjz2+9KUv+d53iiEAUI6bb775CU94ws9+9rOZ/sCBBx54wgknHHnkkVtttdVMf+b2228/99xzTzrppG9961vT/oF58+adfPLJ0z4aAoB2A8CKFSt6/JX77rtv/fr1a9euHR8fv/HGG6+99trvfe97sz4y7vGPf/yZZ5658847j7zLkAoBgKLcfPPNRx111Ey1+6TNNtvscY973MMf/vCHPOQh22yzzaabbjr+J7/5zW8uu+yyq666qsezgzbddNOTTz75Oc95Tj27D0C/GngQ57x58173ute94x3vmPZRE5AvAYDS3H333a94xSs+/elPV/7KO+2005lnnnnQQQdV/soApBYAHvvYx/7nf/7nAQccUOu7QCs8BYjSLFy48FOf+tRZZ521ePHiCl/2uc997tVXX636Byje0qVLzznnnG9961uqf0plAkCx1q5d+4EPfOA973nP73//+1Fe56lPfepb3/rWxz3ucdXtGgDJTQCWLFly9NFHP+95z1uyZEm1rwypEQAo3N13333WWWd96lOfuvjii++9997+/+JDH/rQY4455kUvetHDHvawOncQgIYCwLx58+bPn7/55psvWrRo22233XHHHXffffe999573333Xbp06U477VTPnkJyBACiWLt27aWXXnrJJZf85Cc/ufbaa3/729/eeeeda9eunZiYWLhw4aJFi3beeefddttt77333n///Q866KA99tij7V0GAKieAAAAAIG4CRgAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgkLlt7wBUrNPp1Pfiq1atqu/FoaQPC+TF6Z1QBABykkW94ipCRrL4TEEDnLoJddqf3/ZuQGlFyUw77+oCAKRQn5gA0LKsa/3RSQW0LvhnECY5GxPqPG8CQNNUGz1+G65AAEDdRZcJALVT8Q9NHqAZPqTgfEuoE7sJANVTTFTFfAAAqLwMMwGgGor+hgkDVMtHmOCcVAl1JjcBYHgqhkR++a5bABBZZ8CSzASAwSj6EycMMDSfbiJz8iTUqdsEgNIqgxUnX9Pjp89+4b5D/91Z/3pS/1IuZlRubNnKtncBhje+ennbuwCp1GYmAORU989aoM9qxAAw+ls0TxKgwo+8DECpAcCpklDlmQkAKRb9lRTiqe18W8HA3QIAUIZORUWaCQDt1/1NlvsNTACymBVIAszEEIBSmQCQtU6ldZoJAC2U/lk3+Ov7PTSZByb/0V3wACBgnWYCEFeTdX86FX9SE4DemswDkgAbMwSgSCYAZKdTW6lmAhBOM3V/UpV0ppqcD3h2EACUVK2NLVvZI/QKAFE0UPcr+hv79dYXBiQBJv/1e58xxlcvNwQASLb0n/XPCADlq7X0V/SXGgbcJAAA5ZX+kwSAktVX+qv707Hh36KOJCAGhGUIAFBk6T9JAChQTXW/oj/sWMC6IAAoo/SfJAAUpY7SX92fo5rGAgYCoRgCAJRX+k8SAApReemv7i9DHUlADACATEv/SQJA3tT9tJUErAuKwBAAoLDSf5IAkKtqS391fxw1JQExAADSL/0nCQChS391f2TVJgExoFSGAAAllf6TBICcKP2pw+TBIAYAQPGl/yQBIFbpr+6ngYGAGFAYQwCAYkr/SQJA6pT+ZDoQEAMAiKaTfOk/SQAovPRX99PuQEAMKIMhAEAZpf8kASBFSn8KGwiIAQCUqpNV6T9JAEiL0p80iQEYAgAUUPpPEgCKOoyU/mQRA2QAALLWybb0nyQAlHAYqfvJ6/YAo4BMGQIAdDIv/ScJAC1T+pOvEQcCYgAAGekUUfpPEgBao/SnDGJAKIYAQECdgkr/SQJAfkeS0p8iY4AMAEBqOsWV/pMEgKYp/SnYKDHAKCAXhgBABJ1CS/9JAkBzlP4EIQYAkK9O0aX/pHlt70AUQx9MK06+RvVPjkY5dCv5QgzqM2tCG1+9vKl9AahM509GeYWxZSvTr/5NAJqg8U9kK06+xigAgMR1AnT9N2YCUC+NfzAKKJIhAFCGTpiu/8ZMAFIs/aveF8j4xgCjAADq0AnW9d+YCUBCh5SuP8Ub+iA3CkiQIQCQqU7Irv/GTAAqpvEPNd0YYBQAwIgid/03ZgJQJY1/6JNRQBkMAYBc6PpvzASg5dK/hn2Bwm8MMAoAoH+6/t1MACqg+odRGAVkzRAASJau/0xMAEY1xIGl9IeqRgHmAAB00/XvTQAYnsY/tH5zsOVAKVi1alXv8+H46uVlX0qBdCj9+yEADEnjH+pgFADAcJT+/XMPQBNHmOf8QN0fGbcEtMudAECLrPUflAnAYDT+IdkVQZYDAUSj6z8cE4ABqP6hYUN8gowC2mIIADRJ138UJgA1LvupbV8gkCHuCnBLAEDBdP1HJwDMTuMfWmc5UBY8DgioldK/KgLALDT+IRFGAQBhKf2r5R6AXlT/kBpPB0qcOwGAalnrXwcBYEaqf0iTDAAQgdK/PpYATUPpD4UtB3JLQJPcCQCMyIKfupkATKX6h1wYBQAURte/GQLA/6H6h7zIAGlyJwAwKKV/kywB+l8DHXZKf8h3OZC1QADpsOCneSYA/5/qH7I20KfSHKABhgDArHT925J9AKjkQq76hwI0nwEECYDhKP3bVcISoFGe76H0h7DLgRo7dYTlcUBANwt+UjC/mAvMENdy1T8UacXJ19R3S8DG5w33EgA02TdR+lcl+yVAQ0+UVP9QsDqWA40+sA7InQBAJSdPC36qNa/IC8ysh5rqH4pXYQaY9pSi/Q/Qm9I/WSUEgEEPO9U/BDF6BtD1H50hAASk9E/cvOIvMFMOQdU/hDJ0Buh99dL+B5iW0j8L2d8E3Cdf8QthDfFoIKrlcUAQgdt8M1LIBKDahpzqH8pT4eda+x9gY7r+2SknAFRF9Q+l8ulukTsBoEhK/0wVFQBGb8upD6Bso3/Gtf8BlP65KyoAjEj1DxH4pLfFEADKoPQvwPxot5oBwfX/JcHdtP+ByNzmW4zSAkAlZYEGIRRplNKfSngcEGSqkpZ/RftCBQoMAKMPASarBDEAilFJ6a/9DwSk9C9SgQGgKmIAFEDXPzWGAJALpX/B5kc7XseWrRzoPjMxAIKU/rOeHDqdjiEAEIHSv3hz58Q7ZCcPyiEeNyEGFF8U+icOW/r3f06QAZo5V6seqFzvz7iP9iSlf5Bjfn7Yo3aIGGAaAEWW/gMxBwCKpPQPZW7k6n8D04A4TABKNWLpP+hJQAYYnSEADTMBmInSv1TlTwBGPHZNAyBfDXT9u5kDAAVQ+oc1N+zhO9MhaxpQNhOAklRV+g/9BbQywIgMAWiSCcDGlP4RlD8BqJBpAKSvla4/QAGU/pQwARjlOJ71CDYNKI8JQO4qL/2Hbv/H7BpWzhCAxpgAKP2jGS91AjD6odybaQCkI82uv5sBgPQp/Zli3pzSj+YetXiflf3YspWDHvfPfuG+vn8UqjLoB6r/z2zvk0CfSb7uTkTZZo1PI45oILjOn4zyCkNUQaRvfoTqf8XJ14xejpsGQKiu/0BnD3MAIDW6/pQ2ARi99z90b8k0AHLv+g/68TcHqJshAFRL158CJwDDVf+VDAE2MA2Astf6D3cCMQcA2qXrT7EBoB8D1dnjq5cPd7iLAVChISL6KBeqQZvK1TYRmGLVqlW9C5ehT9QQhNKfkgPAKMd3TddvMQDyKv1nNcpn0xAAaJjSn8LvAahw6X/lC0zdGwBDGOJTUMnK1OE+8m4GqJU7AWBQ1vpT/gSgkuq/7iG+aQBk2vWv9hxiDgDUStefEBOA+nr/dfSWTAMgwa5/VR92c4D6GALArHT9iTUBqOqq3NidfKYBkEvXP9nTCMAGuv7EmgD0c8RXUjTX0VsyDYAUuv6Vf8z7OecYAgzBEAC66foTbgJQR/XffPfONICw0u/613omcTMAMApdfyIGgOb7Z7U+anroGCAJkKMES/9WmscywKB8JwAo/QkdAPoxXGXc4hLesWUrh6hCDATIyHAfrnavVdmdSYBSKf0JfQ9AY0v/m+8RDr0Uz+0BJG64Q7SZxak1fbTdDFAHdwIQk7X+RJ8ANFD9t966G2JF0CTTABKUY9e/yZOJhUBAD7r+NCzFCUDr3bIme0umAeQu5a5/Ug3j1s9seTEEIAhdf1qR6ARgVpX0v1sfAmxgGkCOsu76l3oyAXKh60+LkpsAtLX0P4XekmkAucii69/wx9nNAJUzBKBUuv60bn7w6j/Bvp1pACkro+vf4vnEzQAQma4/iUhoApBab6zd3pJpAKnJq+ufcpM4tXNdygwBKIauP0lJawIwqzra2wkOATYwDSAFhXX9w55PgFbo+pOgVCYAiSz9T7O3ZBpAWzLt+rf7EXYzQLUMAciXrj/JSmIC0Hr1n0XTzjSAJpXa9U/nlOJmACiYrj+JSyIApGx89fKkPoRiALUaOgkn9TGZpDFcjFWrVvUup1I7UROZ0p8stB8AWm//50gMoHIllf4pMASAaJT+ZGRuu2+fVPXf42qd8mdy6DZnzBjQuybzOxlIvp+LFM4qG8gAVV0vUj4gSf+0MMonUelPdsd8+xMARmQawNCKLP0BGqP0J1NtTgCSav9nPQTYwDRgViYAEUr/RNr/kwwBKmQIQDoTAKU/6UtxApBg9V8A0wCCl/4JcjMAFEbpTwFS+R6Abq0Uoz3eNKMnivjeAKr9983rQdRJtf9bfNMi+U4A2uW5/hSjnQmAL8FpgGkAG+j6p88QAFKm609hWrgHIP3FP7nfCdDNvQFh7wGIVvon2P7fwM0AVXEnAE3eA6D0J18p3gNAk0wDAopW+gNUS+lPwZqeAKTf/i91CLBB8GlAhAlA2NI/5fb/JEOAqhgCUOsEQOlPGXKaAKRwkS6baUDBwpb+JT0RCGiR0p8gGp0A5NL+L34IUMkTM9L5lxpIqRMApX/67f9JhgBVMQRgUHU/JMohR2qSmADkVf0HMfQ0wEAgHUr/vPhaACiP0ynZSeh7AFIrJcv4ToC6H0vsqwNaFOS5/iW1/9Pcn0z5TgBSUN7plCAamgB48H/6TAMyoutfPEMASJzTKVlLZQKQZu0YZwiwgWlA4nT9c2//p7xX2TEEoBUFn06Jo4kJgPZ/dkwDEqTrH40hAKTG6ZRiJDEBSLlYDDgE2MA0IBG6/oW1/9Pft4wYAtCMCKdTQpnfevvfVTBxpgFtGSVBuVCV8UQgQwBondMpRap3AlDG4p/IQ4ANTAOaNMpvLFSbKt/2f7SzaK0MAahJqNMp0bT8TcBlXKHjMA2om65/NL4bGBLkdErxapwAlNS4MgTYmGlAHXT9BxWh/V/eubQmhgBUJebplIDanACUdIUOyDSgKrr+wRkCQAqcTgmlrglAeS0rQ4BpmQaMQtd/aHHa/6WeUStnCACQwQSgvCt0ZKYBg9L1Z2OGAABkPwEo9dGfhgC9mQb0Q9d/dEW2/2fdbUOAWRkCAOTxFCDKYxowE11/ACAF1U8ASm3/TzIE6JNpwMZ0/StUZPt/kiHA6AwBAPphAkCNTAN0/QGAwicAZbf/JxkCDCrmNEDXvw4Ft/8nGQKMzhAAYFYmADQkzjRA1x8AiDIBiND+n2QI0EqBm/40YMQ9VP0Hb/9PMgQYnSEAQG8mAOQ0Ckh2GjBiMlH6AwD5TQDitP8nGQKMaMRl7ulMA0bv+qv++xGk/T/JEGB0hgAAPZgA0KaspwG6/gBAjuZW8irR2v/9lIDKu0GN3pDr5zDrXbX3eaAq/RsWqv3f/2E2a5ObWa9NPoyh9D6TOBgIdcybAFDINKCZgYDSHwDIXfXfBBynP+dOgDqMvia+jtsDJl/TWv9WxGz/l/2f1hh3AgDUNQFwOxoFTwNGzxLqfmrS6XSsAgIg0QlA2QwBSp0GjD5J0PUfXdj2P1UxBACoPgCEvf2XgmOA0p9EeB4oAHUwAaiAIUAxMUDpnxTtfyphCABQZQDQ/qdhKZfXKe8b+TIEAKByJgDVMASIXGqntj9l0P6nQoYAAA0FAFdoii+7U9gHiudcCkAqAcDceQpDgFAluNK/Vtr/A3E27ochAEDtEwBXaEotx5X+NM8ZFYD2A4CG07QMAdpVd2mu9G+G9v8QnJP7YQgAUNk3AUNh3yI802sCAASdAHj653D0lppUVbde179hPiYz8TzQShgCAHgMaPWEn6SMUr4r/RPk8wUAKQYAV+ge9JZaMWgpr/Rviw9Ib86ulTAEABg4AJgyj3iRdmlpSz9lvdK/RbN+NJS/s3J+BqAflgABEIshABBcxQFAi26SIQAMRPu/T34PADQdAMyXAVLmLN0nQwAgsionAFpTGzMEgD5p/w/EbwOAEbkHAICIDAGAsAYIACbLgzIEgFlp/1fOuRqAhiYALtIAzXC+rYohABBTvwFAS2k4hgDQg/Z/TZyxAejBPQAAxGUIAARUTQDQpevBEACmpf0/Cr8cAOoNAKbJAHlx3u6fIQAQjSVATTAEgCm0/wEg4wDgOg3QPOfeChkCAKGYADTEEAA20P4HgKQDgIWkADly9h6IIQAQx6gTAI26/hkCgPZ/tfyuABiCJUAA8D8MAYAgZgkAJsjVMgQgOO3/hjmHA1DxBMClGqBdzsPVMgQAIrAEqGmGAISl/Q8AqQcAs2OA3DmTD8oQACieCUALDAEISPsfALIPAK7WAClwNq6cIQBQNhOAdhgCEIr2PwBkEAAsGwUog/P5EAwBgIINOQHQrhudIQBBaP83wO8QgP5ZAgQA0zAEAEolALTJEIDiaf8DQB4BwIJRgJI4qw/HEAAo0jATAB27ChkCUDDt/yb5ZQLQJ0uAAGBGhgBAeQSA9hkCUCTtfwDIJgBYKgpQHuf2oRkCANEnAJp2dTAEoDDa/63wWwWgH5YAAcAsDAGAkggAqTAEoBja/wCQMgEAAGZnCAAUGwDcJdYiQwAKoP2fMmd4AAaeALhyA6TMWbpWhgBAGSwBSoshAFnT/geA9AkAANAvQwCgAAJAcgwByJT2PwDkFwDcHwZQNuf50RkCAIEmALp3jTEEIDva/+nwqwagN0uAAGAwhgBA1gSALLm0kBQHJABkRABIlCE+JXE8Ux5DAKCEAODOsLy4tJAIh2J2nO0Bgut3AqCB1zy/c8rgSG6e33kzDAGATFkClDGXFlrnIASA7AgASdPGI3eOYcpmCADkSADIm0sLLXL4AUCOBIDUaaCSL0cvERgCANkRALLn0kIrHHgAkHcA6P1UOG28dvn9kyPHbcq/f08CrZYhAJAXE4ASuLTQMIccAORLAMiDZip5ccQSjSEAkBEBoBAuLTTGwQYAWRMAsqGlSi4cq8RkCADkQgAoh0sLDXCYAUDuBICcaKySPkcpkRkCAFkQAIri0kKtHGAAUEgA8CUAGfHPQcocn0nxVQCtMAQA0mcCUBqXFmri0AKAMggA+dFkJU2OTJhkCAAkTgAokEsLlXNQAUAxBIAsabWSGsckbMwQAEiZAFAmlxYq5HACgJIIALnScCUdjkboZggAJEsAKJZLC5VwIAFAYQSAjGm7kgLHIczEEABIkwBQMpcWRuQQAoDyCAB503ylXY5A6M0QAEiQAFA4lxaG5uABgCLN63Q6PX6svZc+/0a0xbGXPv9GKTAEAFJjAlA+lxaG4LABgFIJACXQ5KN5jjronyEAkBQBIASXFgbigAGAggkAhdCOpUmONxiUIQCQDgEgCpcW+uRQAYCyCQDl0JSlGY40GI4hAJAIASAQlxZm5SABgOIJAEXRmqVujjEYhSEAkAIBIBaXFnpweABABHN7fxMwwAba/zl69gv3bXsXAEjL/LZ3AMiGUhIACmAJEAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIHPb3gEqNutXO48tWzknsPHVy3v81C+n7V0gIcE/DpTH+T/NK8uqVaua2hf+l28CjsUJjh7Glq10pg5l1n4BQN06nY4rS/MsASqKyzl1c4wB0D+dxzQJAIH4EDIrBwkADdNaap4AUA6fH5rhSAOgf1pLCRIAovDxo08OFQAaprXUMAGgED45NMnxBkD/tJZSIwCE4IPHQBwwADRMa6lJAkAJfGZonqMOgP5pLSVFACifjxxDcNgA0DCtpcYIANnzaaEtjj0A+qe1lA4BoHA+bAzNwQNAw7SWmiEA5M3nhHY5AgHon9ZSIgSAkvmYMSKHEAAN01pqgACQMZ8QUuA4BKB/WkspEACK5QNGJRxIADRMa6luAkCufDZIh6MRgP5pLbVOACiTjxYVcjgB0DCtpVoJAFnyqSA1jkkA+qe11C4BoEA+VFTOQQVAw7SW6iMA5MfngTQ5MgHon9ZSiwSA0vg4UROHFgAN01qqiQCQGZ8EUub4BKB/WkttEQCK4oNErRxgADRMa6kOAkBOfAZIn6MUgP5pLbVCACiHjxANcJgB0DCtpcoJANlw9JMLxyoA/dNaap4AUAgfHhrjYAOgYVpL1RIA8uC4Jy+OWAD6p7XUMAGgBD42NMwhB0DDtJYqJAAAANAyraUmCQDZR14fGFox64GnVQNAtVxZqiIAAADQPj3NxggAqdP+J1mGAAA0zJWlEgIAAABJ0NlshgCQNO1/EmcIAEDDXFlGJwAAAJAK/c0GCADp0v4nC4YAADTMlWVEAgAAAAnR5aybAJAo7X8yYggAQMNcWUYhAAAAkBa9zloJACnS/ic7hgAANMyVZWgCAAAAydHxrI8AkBztfzJlCABAw1xZhiMAAACQIn3PmggAadH+J2uGAAA0zJVlCAIAAACJ0v2sgwCQEO1/CmAIAEDDXFkGJQAAAJAuPdDKCQCp0P6nGIYAADTMlWUgAgAAAEnTCa2WAJAE7X8KYwgAQMNcWfonAAAAkDr90AoJAO3T/qdIhgAANMyVpU8CAAAAGdAVrYoA0DLtfwpmCABAw1xZ+iEAAACQB73RSggAbdL+p3iGAAA0zJVlVgIAAADZ0CEdnQDQGu1/gjAEAKBhriy9CQAAAOREn3REAkA7tP8JxRAAgIa5svQgAAAAkBnd0lEIAC3Q/icgQwAAGubKMhMBAACA/OiZDk0AaJr2P2EZAgDQMFeWaQkAAABkSed0OAJAo7T/Cc4QAICGubJ0EwAAAMiV/ukQBIBUOHwJwqEOQMMMAaYQAJrj4IN++KQAMBCtpUEJAElw4BKKAx6AhukubUwAaIjDDvrn8wLAQLSWBiIAtM8hS0AOewAapru0gQDQBAccDMqnBoCBaC31TwBomYOVsBz8ADRMd2mSAFA7hxoMx2cHgIFoLfVJAGiTw5TgfAQAaFhHd0kAqJuDDEbhEwTAQLSW+iEAtMYBCj4IADSvE767JADUyOEFo/M5AmAgWkuzEgDa4dCEDXwcAGhYJ3Z3SQCoS/ADCyrk0wTAQLSWehMAWuCghCl8KABoWCdwd0kAqEXkQwrq4DMFwEC0lnoQAJrmcGzL+Orl46uXj/5nqImPBgAN60TtLgkAjR5MSpxWDFrWiwFt6f0BCXuaBmA46q6ZCACUbJRSXgwAgOJ1QnaXBICKaf8noqryXQxomCEAABVSfU1LAKA0dZTsYgAAlKoTr7skAFRJ+79ddZfpYkAzDAEAqJAarJsAQAmaLM3FAAAoTCdYd0kAqIz2fyvaKsfFgFoZAgBQIZXYFAIAuUqhBE9hHwCA0XUidZcEgGpo/+dYdq/6k3T2h40ZAgBQIfXYxub/n/8Haauqzt647p/836MXlJP75vwCAJnqdDqVdAbTZwJQAe3/Arr+pgEJMgQAoEKqsg1MAIjY9e/9Z0wDACCmTowhgAnAqLT/y1vrbxqQDkMAACqkNptkAkD0rn/vv2saAAChdAIMAUwARqL9X/wTfkwDWmcIAECFxlRoJgCkI4Wu/6yvOWK5aRoAAOnrlD4EMAEYnvZ/qV3/ut/CNGBQhgAAVGgsfJ1mAkCbqqr7q9iXgd/RNAAASlX2EMAEYEja/yl0wRto+df97qYBfTIEAKBCY7GrNRMAmpZp138mpgEAUKROuUMAE4BhaP8PLfeuf93TgIp2p0yGAABUaCxwzWYCQE6l/5y0jT4NMAoAgHR0Ch0CmAAMTPu/+WXuaXb969tbNwbMxBAAgAqNRa3cTACoUYSu/0xMAwCgAJ0ShwACQGUUahuLXPpvTAyo3NiylcYjAFRlLORlxRKgwVhjMKtoC376YVFQY3xCAahcp7iLiwlANTRodf1nZRpQlZjdGgBqMhbvsmICEDr/VUXXv3+mAXXzOQWgcp2yLi4mABWI3JHV9R+OacCIAnZrAKjPWLDLigAQNPmNTuk/OjGgJkU+sQEYWqjCjvp0Crq4CACjClh7Kf2rJQYMJ1q3BhiCswT9G4t0WREA+qL9P0npXx8xoFol9WmAIcSp5GhSp5SLiwAwkjjFltK/GWLAQEJ1a4A+OS0wtLEwlxUBYHbB2/9K/+aJAZUopk8D9ClI6Ua7OkVcXASA4RVfXSn927Xhtzd0EogQA+J0a4AenAeoyliMy4oAMIuY7X+lf0kDgQgxoOw+DdBDhFqN1HTyv7gIAEMqtZxS+idLDAjerQGm8MGnJmMBLisCQC+h2v9K/yyIAQH7NMAUxRdnpK+T+cVFABhGYfWT0j87YkDAbg2g9KcxY6VfVgSA0O1/pX/WxIAgfRpA6U+COjlfXASAgZVRMCn9iyEGBOnWQFhVXbAi9PWo0FjRlxUBYHoFnyZGPJrV/WkSAwru00BYelUkrpPtxUUAGEzWFZLSv3jBY0DZ3RoIRelPCsbKvawIACHa/0r/UILHgPL6NBCK0p+8dPK8uAgAA8ixJFL6hxUzBhTcrYHiKf1J0FihlxUBoNj2v9KfsDGgsD4NFE/pT9Y6GV5cBIB+ZVQDKf2JHANK7dZAkZT+pG+sxMuKAFBU+1/pTw+hYkBJfRooktKfknRyu7gIAH1Jv+hR+tOnCDGgyG4NFEPpT3bGirusCADZt/+V/gwhQgwopk8DxVD6U7C8Li4CwOySrXKU/oyo4BhQXrcGsqb0J3djZV1WBIAs2/9KfypUcAwoo08DWVP6E0cnn4uLADCL1MoapT81KS8GFNatgewo/SnMWEGXFQEgm/a/0p8GbDhOhvtQJBgDCujTQHaU/oTVyeTiIgD0kkgdo/Qnr4FAOjGgpG4NZEHpT9nGSrmsCABJt/+V/rSrjBiQe58GsqD0h4wuLgLAjNotXJT+pCPrGFBMtwaSpfQnlLEiLivRA0CC7X+lP2nKOgZk3aeBZCn9IdOLS/QAMJNWKhWlP+nLMQaU0a2BpCj9iWws/8tK6ACQTvtf6U9ecowB+fZpIClKfyjg4hI6AMykydJE6U++MooBBXRroHVKfyjmshI3ALTe/lf6U4aMYkCmfRpondIfCru4xA0AM2mgFlH6U570Y0Du3RpohdIfirysCABNG+VYcRql7BjQ+igA2EDpDwUPAYIGgJkKlFrrD6U/QQwdA+oeBfTo1iR7jobmKf2h+CFA0ADQsKEPDudQ8pVsDABmovSHyqXZYIoYAJps/yv9CS61GGAIANNS+kOoIUDEANAMpT8kGwOADSqpXVy5oIcEG0zhAkAD7X+lP6QcAwwBYJLSH8IOAcIFgFop/SGXGACRKf2hYak1mGIFgPra/0p/yCgGGAIQltIf6pDdECBWAKiD0h+GZhoAjVH6Q7s6KTWYAgWAytv/Sn/INwYYAhCH0h8aMJbVECBQAKiQ0h8qt+HTMWgSMA2AmSj9ISmdZBpMUQJAVe1/pT+kORAYIgYYAlAwpT80byyfIUCUADA6pT8UGQOgMEp/SFknjQZTiAAwYvtf6Q+lxgBDAEqi9IfWjWUyBAgRAIam9IcUmAZAb0p/yEgngQZT+QFguPa/0h+CxABDALKm9IfUjOUwBCg/AAxK6Q8pMw2ASUp/yFen7QZT4QFgoPa/0h9ixgBDAPKi9IfEjSU/BCg8APRJ6Q85Mg0gGqU/FKPTaoNpfvD2v9IfcldJDDAEIHFKf8jLWNpDgJIDQG9KfyiJaQClUvpDqTrtNZjmB2z/K/2hVCPGAEMAkqL0h6yNJTwEKDYAzGS4fwknUAgSAyAFSn8IotNSg6nMADDohb8HJ1AIFQNmYghAM5T+UJKxVIcAZQaASjiBQgGqjQFQH6U/xNRpo8FUYAAY/UrvBAqFqSQGGAJQE6U/FGwsySFAgQFgaM6eUDbTAFKj9AfmtNFgKi0ADHdpd/aEOEaJAYYAVEXpD3GMpTcEKC0ADMrZE2IyDaAtSn+g9QZTUQFgoGu5syew4TzQ/9nDEIChKf0hrLHEhgBFBYA+OXsCUxgIUCulP5BUg6mcANDPldvZExg9BhgC0D+lP5DgEKCcANCbsyfQJ9MAKqH0BwbVWIOpkADQ41Lt7AlUHgMMAehB6Q8kPgQoJABMy9kTGJFpAANR+gMjaqbBVEIA6L42O3sCdccAQwA2pvQHMhoClBAANubsCdTENIBpKf2BajXQYMo+AGy4GDt7Ag3HAEOA4JT+QKZDgOwDgLMn0DzTgOCU/kCt6m4wZR8AnECBtjj/BKT0BwoYAmQfAACgAUp/oJghgAAAAL0o/YHChgACAABMT+kPFDkEEAAAYCqlP1DwEEAAAID/pfQHih8CCAAA8D+U/kCQIYAAAEB0Sn8g1BBAAAAgLqU/EHAIIAAAEJHSHwg7BBAAAIhF6Q8EHwIIAABEofQHMlXtEEAAAKB8Sn8gZWPNDgEEAABKpvQHytCpbgggAABQJqU/kJGxBocAAgAApVH6A0XqVDQEEAAAKIfSH8jXWFNDAAEAgBIo/YEIOlUMAQQAAPKm9AeKMdbIEEAAACBXSn8goM7IQwABAID8KP2BUo3VPwQQAADIidIfoDPaEEAAACAPSn8giLGahwACAACpU/oDVDgEEAAASJfSH4hprM4hgAAAQIqU/gA1DQEEAADSovQHmFPnEEAAACAVSn+ABoYAAgAA7VP6AzQ2BBAAAGiT0h+g4SGAAABAO5T+AK0MAeZV+3IAMKvx1ctV/wBV6XQ6A/15EwAAmlNVH0vpD8QxVvUQQAAAoAlKf4BE7gQQAACol9IfIKkhgAAAQF2U/gAJDgEEAACqp/QHSHYIIAAAUCWlP0DiQwABAIBqKP0BshgCCAAAjErpD5DREEAAAGB4Sn+A7IYAAgAAw1D6A2Q6BBAAABiM0h8g6yGAAABAv5T+AAUMAQQAAGan9AcoZgggAADQi9IfoLAhgAAAwPSU/gBFDgHmVb0zAJSgkup/1Z9UsTsADKzT6Uy73QQAgOqp+wGSHQKYAABQJV1/gMSHACYAAFRD3Q+QxRDABACAUen6A2Q0BDABAGB46n6A7IYAJgAADEPXHyDTIYAJAACDUfdTnqq+9QKyYAIAQL90/QEKGAKYAAAwO3U/QDFMAADoRdcfoLAhgAkAANNT9wMUyQQAgKl0/QEKHgKYAADwv9T9AMUTAAD4H0p/gAg6nY4AABCd0h9gTiT/DzqfaBwJ3pFwAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_325
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color yellow.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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ADIiwaA3JTXAIS2/W/0B9JrA+aUUwJoAACIm9EfGCZtwAANAHnRAJCbkhqAQLb/jf5A8m3AnBJKAA0AAPEx+gNdmp9xG6ABIC8aAHJTRgNQ7/a/0R/IrQ2YU3QJoAEAIA5Gf6Ak8///WWKkSSDSNkADQF40AOSm8Aaglu1/oz8QfiHQV9NpsIMTnQYAgHAZ/YFY3h4wJ542QANAXjQA5KbYBqDK7X+jPxCC3mDagAJLAA0AAGEx+gPhmJ9iG6ABIC8aAHJTYANQwfa/0R8IWW/dbUBRJYAGAID6Gf2B8M1PpQ3QAJAXDQC5KaoBKG/73+gPxKi3pjagkBJAAwBAPYz+QLzmx9wGaADIiwaA3BTSABS+/W/0B1LSW20b0H0JoAEAoDpGfyA982NrAzQA5EUDQG66bwCK2v43+gM56K2kDeiyBNAAAFAuoz+Qj/kxtAEaAPKiASA3XTYAXW7/G/2BnPWW2QZ0UwJoAAAontEfYH6obYAGgLxoAMhNNw1AZ9v/Rn+AatqAjksADQAAxTD6A0TRBmgAyIsGgNx03ACMaPvf6A9QSxvQWQmgAQCgc0Z/gOjaAA0AedEAkJvOGoDhbP8b/QFCaAM6KAE0AACMjNEfIOo2QAAAYLjb/0Z/gABjwFAn597e3panXwEAgGHpYPo39wNUEwNGZPRI/wMAEtbZ1ajN5v9RITcFkJX5hZ4/W57VNQAAFMncD1BXGzBMGgAA/leXrzR2/QGKVch5tfncrgEAoFvmfoAKzrFFFQIaAAA6f12x6w9QmY5PuQ1neA0AAJ0w9wNE+vYA3wRMXkp6Mw3EPsGP6Klh9AcIRGdnbw0AAMNl9AdIoA3wHgCA3A3nlcO1/gDBGuYpevBsrwEAoB1zP0BibYAGACBrbV4q7PoDRKf9qXvgnK8BAKCRuR8g4TbApwCRF58CBIPmz5/f/Iww+gMkxjcBA9Ca0R8gkzZAA0BeNADQzOgP0JOHgUHo/wFnvoP43cg1tgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_22
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color white.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color yellow.\nthe 7th action is Colorize the top layer of the original shape with the color purple.\nthe 8th action is Colorize the top layer of the original shape with the color red.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_292
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 4th action is Colorize the top layer of the original shape with the color red.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_322
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 4th action is Colorize the top layer of the original shape with the color yellow.\nthe 5th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_456
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
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},
"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_306
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
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{
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"text": "This is the original shape, with its image:.",
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color green.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_335
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_298
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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{
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"text": "This is the original shape, with its image:.",
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 4th action is Colorize the top layer of the original shape with the color blue.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
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CIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABDKqreL+sadW9BZIh6cTQ/WFjq6itxBXreYXFmA4NAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEEjlvwl4YF1dvqSTIXx1qCcM9XzdbEV1dnYWvQXKpbu7u+gtQFloAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACCQUUVvAIirVqt1dXUVvQsoRnd3d9Fb4E9qtVrRWwjH63+BBACgAP7WAkBRBAAgV0Z/ACiWAADkxOgPAGUgAAAtZ/QHgPIQAIAWMvoDQNkIAEBLGP0BoJwEACBjRn8AKDMBAMiM0R8Ayk8AADJg9AeAqhAAgKYY/aEVOub5ktSM9SwY6MXKf/D8/5tTIAEAGCajPwBUkQAADJnRHwCqSwAAhsDoDwBVJwAAg2L0B4A0CADANhj9ASAlI4reAFBetT9q5h66unywBgCUiwYAaMmpv9EfAMpJAAD+jNEfANImAAD/x+gPABEIAIDRHwACEQAgNKM/AEQjAEBQRn8AiEkAgHCM/gAQmQAAgRj9AQABAEIw+gMAmwkAkDijPwCwNQEAkmX0BwDqCQCQIKM/ANAfAQCSYvQHAAYmAEAijP4AwGAIAFB5Rn8AYPAEAKgwoz8AMFQCAFSS0R8AGB4BAGLN/UZ/AAhOAIBqMPoDAJkQAKDsjP4AQIYEACgvoz8AkDkBAMrI6A8AtIgAAOVi9AcAWkoAgLIw+gMAORAAoHhGfwAgNwIAFMnoDwDkTACAYhj9AYBCCACQN6M/AFAgAQCqNPqb+wGAJgkAkAejPwBQEgIAtJbRHwAoFQEAWsXoDwCUkAAA2TP6AwClJQBAloz+AEDJCQCQDaM/AFAJAgA0y+gPAFSIAADDZ/QHACpHAIDhMPoDABUlAMDQGP0BgEoTAGCwjP4AQAIEANg2oz8AkAwBAAZi9AcAEiMAQGNGfwAgSQIA9GX0BwASJgDAnxj9AYDkCQCQDaM/AFAJAgA0y+gPAFSIAEDB18wkoNj/COIHUIieBV7/i9SzoNYxz+s/wzRiuP8QAIjL9FmUngU16YsmaQAAACrA3E9WNAAAwHAoAXLj1J9saQAAAErK3E8raAAAgGFSArSOU39aRwMAAFAi5n5aTQMAAAyfEiBDTv3JhwYAAKBg5n7ypAEAAJqiBGiGU3/ypwEg1p+EgV9kS7hhx0JAGro6phS7gVrP8raS8fJOUTQAAECztnmAUsL5u0BO/SmWBgAAICfmfspAAwAAZEAJMDCn/pSHBgAAoIXM/ZSNBgAAyIYSoA+n/pSTBgAAIGPNz/1dHVOi5SVyowEAADKjBGj+1L+rY0rhn5pK2jQAAADNyuRSH3M/+dAAAABZilYCZHKhv1N/8qQBAAAYDqf+VJQGAADIWPIlgFN/Kk0DAAAwWE79SYAGAADIXnolgFN/kqEBAAAYiFN/EqMBAABaIoESwKk/SdIAAAD05dSfhGkAAIBWqWIJ4NSf5GkAAAD+wKk/QQgAAEALdczrGniwrvUsL3xozuTIP6O9QMsJAAAAw2f0p3K8BwAAaK0qvhNgMFzoT0VpAAAAhsbcT6VpAACAlkumBHDqTwI0AAAA22buJxkaAAAgD9UtAZz6kxgNAABAY+Z+kqQBAAByUqESwKk/CdMAAAD8ibmf5GkAAID8lLkEcOpPEBoAACA6cz+haAAAgFyVuQSACAQAAAAIRAAAAPKmBIACCQAAABCIAAAAFEAJAEURAAAAIBABAAAohhIACiEAAABAIAIAAFAYJQDkTwAAAIBABAAAoEhKAMiZAAAAAIEIAABAwZQAkCcBAAAAAhEAAIDiKQEgNwIAAAAEIgAAAKWgBIB8CAAAABBIe2dnZ9F7AAAAcqIBAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBARg188xc6utrK7R97agPc2tVV9v3XagPtv/zf09zd3T3ArR3zSvffv2dBrVob3uaeK/ecr5yBf0mr/iI5AM+lYp9a5Xw5GvxLU1fHlLaSqfUsb8WGB77bSvxPWdiTxItMcS8yGgAAgFIc4kA+BAAIdKYIQLZK2HXANgkAAAAtpASgbAQASI0SACBPSgAqRwAAAGgtJQClIgBAgpQAAHlSAlAtAgAAQMspASgPAQDSpAQAyJMSgAoRAAAA8qAEoCQEAEiWEgAgT0oAqkIAAADIiRKAMhAAIGVKAIA8KQGoBAEAACA/SgAKJwBA4pQAAHlSAlB+AgBUW/f8rqK3AMDQKAEolgAA6VMCAORJCUDJCQBQeUoAgMpRAlAgAQAAIGNKAMpMAIAQJYCrgICwaj3Laz3L28pHCUBRBAAAIE3Fjv5KAEpLAIBEKAEAyn/q34cSgEIIAABAOko1+isBKCcBANKhBAAiK9XoP3hKAPInAAAA1Vbm0V8JQAkJAJAUJQAQSplH/8FTApAzAQAAqJ4Kjf5KAMpGAIDUKAGAtFVo9B88JQB5EgAAgGqo7uivBKBUBABIkBIASEx1R//BUwKQGwEAAEh59O+Y19UxbxvHIjlQAlAeAgCkSQkAVF0yo//gKQHIx6icHgcAYHCav9qnnHN/V8eU5C9kohI0AJAsJQAQ81r/ck7/g6QEIAcaAACgeJkcjZd/9FcCUAYaAEiZEgCIc+pf/ul/kJQAtJoGAAAoRpBT/z6UABROAwCJUwIAJeTUf2BKAFpKAwAA5CfmqX8fSgCKpQGA9CkBgDJw6j8kSgBaRwMAALSWU/96SgAKpAGAEJQAQCGc+jdDCUCLaAAAgOw59d8mJQBF0QBAFEoAIDdO/bOiBKAVNAAAQImEmvuVABRCAwCBbLMEACiQU/+GlABkTgAA/sRVQEAhIo/+XR1Tit4C4QgAEIsSACiVyKP/4CkByJYAAPwZJQCQD6P/FkoAciYAQDhKAKBYRv9hUAKQIZ8CRAtV7tWqchtukVqt1tXlbzOQvdLO/T6Kh1A0ABCREgDIX2mn/6pwSkVWBACgAe8EADLkmh8oFQEAglICADkw+mdLCUAmBACIa+AMoAQAmmH0h9ISAACALBn9W0oJQPMEAAhNCQBkyOgPlSAAAEDe0kvXRv88KQFokgAA0SkBgGYY/aFyBAAAyFUyudroXyAlAM3wTcA0pbOzs61Suru7s7y3VD5Js3t+V+fb+v1b4ouBgXqJjf6J/b8DA9MAwPB1vq02wNwMkPDxPzTJ70KBBABoVhoxwDsBACAIAQCykUYMAFpKloat+Y0oigAAWap0DFACAEAEAgD8SdcfBY8BQItI0VDP70UhBABoHAOaTwJVzABKAABIngAA/Wo+BqgCgM3kZ+iP3478CQCwDdFigBIAANImAMCgRIsBAJAbp0s5EwBgCILEgGS+4RhKwnADlIoAAEMWJAb0xygDQOb8ccmTAADDlHYMUAJAVow1QNkIANCUtGNAfww0AGTOH5fcCACQgSRjgBIAmmegAUpIAIDMJBkD+mOsASBz/rjkQwCAjKUUA5QA0AyjDFBOAgC0REoxoD+GGxg26Rr6449LDgQAaKEEYoAxBYbHEAOUlgAAOcWAZpJA4TGgP0YcGAa5Ggbmj0urCQCQn4rGAMMKDJXxBSgzAQDyVtEY0B+DDgyJRA2D4Y9LSwkAUIxqxQAjCwyewQUoOQEAilStGNAf4w4MkiwNg+ePS+sIAFC8SsQAgwsMhpEFBqnJT8mjGQIAlEUlYkB/DD2wTVI0DJU/Li0iAEC5lDkGGF9g2MOKXx+opwQoigAAZVTmGNAf5zQAZM4fl1YQAKC8ShgDnGJCfxz/wzAoAQohAEDZlTAG9Mc5DQCZ88clcwIAVEN5YoCzTKjn+B+GTQmQPwEAqhcDhv1amUMb4JwGgMz545ItAQAqqdgY4EQTtub4H5qkBMiZAABxY0BbazinASBz/rhkSACAuDGgmSrAuSZs5vgfMqEEyJMAAIkoJAb0xzkNAJnzxyUrAgAkJc8Y4HQTHP9DhpQAuREAIEGlagMAICtKgEwIAJCsHGLAAGecXqNJnuN/yJwSIB8CACROGwBAShwwNU8AgBBaFwOUAMTk+B9aRAmQAwEAAtEGAJAAB0xNEgAgnMxjgBKAaBz/Q0spAVpNAICgtAEAVJcDpmYIABDa5hgwjCTQJwYoAYjD8T/kQAnQUgIA8AeZxAAAyI0DpmETAIBsYoASgAgc/0NulACtIwAAmcWA1mwHABpzwDQ8AgCQ8buEG/IaTQIc/0POlAAtIgAA+cUAAMiWA6ZhEACAnGKA12hS5fgfWschVCsIAMBgaQOITIKF0vLrOVQCAJBfDPAaTXoc/0OrOXvKnAAADIc2gFBkVyg5v6RDMmpoP06+uru7i94CDGRzBhjSy26tVpMcSEbrjv97FphmcuU/eMl1dXUZ8TOkAQCapQ0gbcYOqAS/qoMnAAB5xwCv0aTB1f+QJydNGRIAgOxjgJdpkiGvQoX4hR0kAQBoiYFjgNdoqs7xP+TP6VJWBACghbQBVJqkCpXj13YwBACgmBjgNZrqcvwPRXGolAkBAMiJNoBqkVGhovzybpMAABQWA7xGU0WO/6FYzpKaJwAABdAGUHLSKVSaX+GB+SbggpmBcuYVoVQ8/4l8/F+GJqHzbbU4v8UDv/5X6P8RfDFw8wQAAPgzEQaLUKM/MdVqNc/S/ggAAFCZM/vmGf1JgxKgGQIAAPxJwiNFk6O/uZ/KUQL0RwAAgMSP/43+JEkJMGwCAAD8n/SGCaM/wSkBGhIAACDB43+jPxEoAYZHAACAP0hmjDD6w9aUAPUEAABI5Pjf6E9ASoBhEAAAoPLH/0Z/GIASoA8BAAAqfPxv9AclwFAJAABEV9HRwegPg6cE2JoAAAAVO/43+kMfSoAhEQAACK1aQ4PRH4ZNCbCFAAAAFTj+N/rDwJQAgycAABBXJcYFoz9kRQmwmQAAACU9/jf6w5AoAQZJAAAgqDIPCkZ/aJGaEkAAAIBSHf8b/aEZSoDBEAAAiKiEI4LRH/JRC18CCAAAUPDxv9EfMqQE2CYBAIBwyjMcGP2hELXYJYAAAAAFHP8b/aF1lAADEwAAiKXwscDoD2VQC1wCCAAAkNPxv9EfcqMEGMCIgW4EAEow/Xf9UabbAdrCJgQNAACB9Pf3vqXH/02O/pnuBQJRAvRHAACA0o3+5n7IRy3kOwEEAACiyPP43+gPZaAEaEgAAIAsGf2hWmrxSgABAIAQcjj+N/pDCSkB6gkAANAsoz9UWi1YCSAAAJC+1h3/G/2h/JQAfQgAADAcRn9ISS1SCSAAAJC4zI//jf5QOUqArQkAADBYRn9IWC1MCSAAAJCyrI7/jf5QdUqALQQAABiI0R/iqMUoAQQAAJLV5PG/0R8SowTYTAAAgL6M/hBWLUAJIAAAkKbhHf8b/SFtXUoAAQAANjP6A0FKAAEAgOjH/0Z/CKUrfAkgAAAQl9EfCFgCCAAARDz+N/pDZF2xSwABAIBYjP5A8BJAAAAgyvG/0R/YInIJMKLoDQBAHoY3/Xf9UQu2A1RALdGEIAAAkI4M/1ob/SF5XVF/xwUAAPgzRn8g7RJAAAAgEc3/nTb6QzRdIX/lvQkYgOhiTgBA2I8D0gAAEPf435E/0BXvRUAAACAioz8Q9p0AiV8ClNj/WrSaJwxE+OU191PP6z+haAAAiMKpPzBsKaXExBsAAJI3mL/K5n6ALTQAAKTMqT+QlVoqJYAGAIA0/x6b+wEa0gAAkBqn/kCL1JIoATQAAKTzl9jcD7BNGgAAUuDUH8hHrfolgAYAgGr/DTb3AwyJBgCAqnLqDxSiVvESoPINwBc6vPQzBP/YM9BvrKcTVIjRnwx5OhGKBgAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACae/s7Cx6DwAAQE40AAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgbT39vYWvQcAACAnGgAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBARhW9AcjP+vXrFy9efNNNN/36179eunTpI488smrVqtWrV2/atGns2LHjx4/fZZdddt1115kzZ+67774HHnjgHnvsUfSWAQAy1t7b25v1fUK5rF+//vLLLz/nnHOuu+66devWDf4f7rXXXscdd9y73/3uvfbaq5UbBGDILrjggiH9fHt7+4gRI0aOHDlmzJixY8dOnDhxp512mjZt2tixY1u2RygpAYCUrVmz5utf//qXvvSl5cuXN3M/c+fOPf3001/xildktzUAmtLe3p7J/cyYMWPWrFn77bffwQcffNBBB02YMCGTu4UyEwBI1gUXXPDRj3708ccfz+TeRowY8aEPfejzn/+8vw0AKQWArY0ZM+awww57+9vffuyxx44ePTrz+4eSEABI0FNPPXXSSSddeumlmd/zS1/60ksvvfSlL31p5vcMQOEBYItdd931lFNO+fCHP+wCIZIkAJCaX/7yl3Pnzr3//vsH+JmXvOQl+++//8yZM3feeecddthh7dq1Tz/9dE9Pz5IlS2655Zaenp4B/u2kSZN+8IMfHHDAAS3YOwClCACb7bbbbl/84hdPOOGEVj8Q5EwAICk333zz4YcfvnLlyoa3zpgx4wMf+MDb3/72F77whf3dQ29v75IlS/7nf/7nnHPOWbVqVcOfmTRp0sKFC/fbb7/sNg5A6QLAZp2dnWeeeeaOO+6Yz8NBDgQA0vGzn/3skEMOaTj9T5w48VOf+tRHPvKRwV/TuWLFitNOO+2MM85o+DsyY8aMW2+9dZdddml61wBkFgAGnmqef/75jRs3rlmzZtWqVcuXL3/wwQd/8Ytf3HbbbT/60Y/6Ozna7EUvetGVV1659957Z7FxKJ4AQCIeeOCBV73qVU8//XT9Ta961au6urqG96H+11133YknntjwncSHHnroD3/4w2FtFoACAkB/NmzYcP3113/zm9+8/PLLN23a1PBnOjo6rr76atd/kgYBgBSsWbNmzpw5d911V/1NxxxzTFdX13bbbTfsO7/nnnsOPvjghtHirLPOes973jPsewagDAFgiyVLlvz93/99f4c7kydPXrhwoY+EJgECACk46aSTvvOd79Svz5079+KLLx41qtlvvL7tttv+8i//cv369X3Wp02btnTp0vHjxzd5/wCUIQBs9s1vfvOUU07ZsGFD/U277LLL7bff7vpPqm5E0RuAZl133XUNp/999933/PPPb37633wR0ac+9an69WXLlp155pnN3z8A5fH+97//+uuvnzRpUv1Njz32WK1W27hxYxH7gsxoAKi29evXz5w587e//W2f9XHjxt1555177bVXVg/03HPP7b///kuWLOmz/qIXvei+++4bMUKWBkikAdjslltueeMb37hmzZr6m7785S9/7GMfy+qBIH+mFqrtzDPPrJ/+29raPve5z2U4/be1tY0ePfq0006rX3/ggQduvvnmDB8IgDJ47Wtf++1vf7vhTaeddtojjzyS+44gMwIAFbZ27dovfOEL9et77733ySefnPnDveUtb5kxY0b9+iWXXJL5YwFQuBNOOOFtb3tb/fqqVasa/vWBqhAAqLDvf//7y5Ytq1//13/915EjR2b+cCNHjnz/+99fv75o0aLMHwuAMvi3f/u3sWPH1q9/+9vfbvgHCCpBAKDCzjrrrPrFPffc8y1veUuLHvGoo46qX7z77rtXr17dokcEoEC77bbbP/zDP9Svr1u37uyzzy5iR5ABAYCquueee2677bb69Q996EOte0vuvvvuO2XKlD6LGzduvPfee1v0iAAU62//9m/HjBlTv37uuecWsR3IgABAVV166aX1i+3t7SeccELrHrS9vf2QQw6pX7/vvvta96AAFGjSpEkN699f/VERO4JmZfAR6VCIq666qn5xzpw506dPb+njnnDCCfUfM7fDDju09EEBKNA73vGOiy++uH79uuuumzlzZhE7gqb4HgAqadWqVZMnT67/KpZPfepTn/nMZwraFADpfA/A1jZs2NDR0VH/nQDHHnvsggULWvGI0FIuAaKS7rjjjoZfxHjwwQcXsR0AUrbddtvts88+9et33nlnEduBZgkAVNLPf/7zhuuzZ8/OfS8ApK/h35cHH3zw2WefLWI70BQBgEr65S9/Wb84bdq0nXbaqYjtABAxAPT29t5///1FbAeaIgBQSQ8//HD94ote9KIi9gJA+mbNmtVw/fe//33ue4FmCQCkEwB22WWXIvYCQPomT57ccP2xxx7LfS/QLAGASnryySfrF+u/ogsAMjFx4sSG6ytXrsx9L9AsAYBKqv8stra2trFjxxaxFwDSN2nSpIbra9euzX0v0CwBgEpat25d/eL2229fxF4ASF9/DcD69etz3ws0SwCgkp5//vn6Rd9qB0CLNPzymba2ttGjR+e+F2iWAEAljRkzZpC1AAA0r7+TfuUzVSQAUEkNL/dv+MYAAGhef1/4NW7cuNz3As0SAKikHXbYoX5x+fLlRewFgPQ9/vjjDdenTZuW+16gWQIAlTR9+vT6xWXLlhWxFwDS19/n/e+666657wWaJQBQSQ1fcB944IEi9gJA+n7zm980XN99991z3ws0SwCgkl74whfWLz7++ONPP/10EdsBIHG//vWv6xenTJniEiCqSACgkl7+8pc3XL/rrrty3wsA6Vu8eHH94r777lvEXqBZAgCV1N9r7o9//OPc9wJA4lasWHHPPffUr8+ZM6eI7UCzRjV9D1CAWbNmTZo0acWKFX3WFy1a9C//8i8tfei/+Zu/6fN5o9ttt925557b0gcFoEBXX311wy8CO/TQQ4vYDjSr3ZenUlHz5s275JJL+iyOHDly2bJlO++8c4se9P7773/xi1/cZ3GPPfb47W9/26JHBKCh9vb2+sUWTTWdnZ0XXXRRn8XJkyc/8cQTvgmYKnIJEFV12GGH1S9u3Ljx4osvbt2DXnvttfWL9ZEAgGQ88cQTl156af368ccfb/qnogQAqmrevHkNX3m/8Y1vtO5Br7vuuvrFffbZp3WPCECxvva1rz333HP16+9617uK2A5kQACgqnbeeefDDz+8fv2uu+5atGhRKx5x7dq1119/ff36gQce2IqHA6BwTz311Fe/+tX69QMOOOC1r31tETuCDAgAVNj73//+huv//M//3IqHO//885955pk+i6NHj37DG97QiocDoHAf//jHV65cWb/+T//0T0VsB7IhAFBhRxxxxOzZs+vXb7nllgsvvDDzh/v6179ev3jIIYfsuOOOmT8WAIW78sorv/vd79avH3jggUcffXQRO4JsCABU2yc/+cmG6x/+8IeffPLJDB/ooosuuuOOO+rX3/ve92b4KACUxNKlS9/5znfWr48cOfLrX/96w88ggqoQAKi2t771rQ2vwFm+fPk73/nOTZs2ZfIozzzzzCmnnFK/vueeex5zzDGZPAQA5fHII48ceuihPT099TedeuqpvgCYqhMAqLyvfe1rDT8O6Jprrvn4xz/e/P339vZ+8IMffOyxx+pv+vznPz9y5MjmHwKA8liyZMmcOXMefPDB+pte97rXnX766UVsCrIkAFB5s2bN+vznP9/wpv/4j/849dRTm7z/k08++YILLqhff+Mb39jZ2dnknQNQHr29vWeeeeZrXvOahx9+uP7WPffcs6ury7kPCfBNwKSgt7d37ty5V1xxRcNbTzjhhG9961vjx48f6t2uXr36Ix/5yLe//e36mzo6Ou6+++4ZM2YMa78AlO6bgBcuXHjqqafeeuutDW+dOnXqTTfdtOeeew77/qE8BAASsXLlyte//vUN36e7+djmK1/5ylFHHTX4O7zxxhtPOumkpUuX1t80atSoa6655pBDDmlivwCUIgDce++9l1122fe+970lS5b09zN77LHHtdde63vfSYYAQDqeeOKJgw466L777uvvBw444IBTTjnl6KOP3mGHHfr7mZUrV15xxRVnnHHGT3/604Y/MGLEiLPPPrvhR0MAUGwAmD9//gD/ZOPGjRs2bFi9enVPT8+yZcuWLl3685//fJsfGffa17724osv3mWXXZreMpSFAEBSnnjiiblz5/Y3u2+23XbbveY1r9lnn31e/OIXT5o0afTo0T1/9Pvf/37x4sVLliwZ4LODRo8effbZZ7/97W9vzfYBGKwcPohzxIgRH/vYxz73uc81/KgJqC4BgNSsXbv2Ax/4wLnnnpv5PU+dOvXiiy8+8MADM79nAMoWAF796lf/93//9/7779/SR4FC+BQgUjN27NhzzjnnkksumTZtWoZ3+453vOOee+4x/QMkb86cOZdddtlPf/pT0z+p0gCQrNWrV3/ta1/70pe+9NRTTzVzP29605s+/elPv+Y1r8luawCUrgGYNWvWMcccc+KJJ86aNSvbe4ayEQBI3Nq1ay+55JJzzjln0aJFzz333OD/4Ute8pJjjz323e9+90tf+tJWbhCAnALAiBEjRo0atf32248fP37y5MlTpkzZbbfd9t5775e97GVz5syZOnVqa3YKpSMAEMXq1atvvvnmm2666d577126dOljjz22atWq1atX9/b2jh07dvz48bvsssuMGTP23nvv2bNnH3jggXvssUfRWwYAyJ4AAAAAgXgTMAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAg7Z2dnUXvAQCgSN3d3UVvAfKjAQAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQEYNfPOeXR157QTycH+tZ4BbPeGJ9pwfgO+JJzG+6xe20AAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIKPaKu7+Wk/RWyAdnk4M1Z5dHUVvIa7u7u6it0A6Ojs7i94CFdNd5ZcgDQAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABFL5bwIeWFdXV9FboFxqtdoAt3rCMNTnDKXVMc+vM3+mZ8FAv8ueMAz1OVNpGgAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIZFTRG4iuVqsVvQUACtCzwOs/cfUsqHXM6yp6F3FpAACgAKYfYupZUJN+C6cBAACg5cz95aEBAIBiKAEIwql/2WgAAABoCXN/OWkAAKAwSgBS5dS/zDQAAABkxtxffhoAACiSEoBkOPWvCg0AAABNMfdXiwYAAAqmBKC6nPpXkQag1Do7O4veQmq6u7uL3gLAcHR1TCl6C9VW61le9BZSY+6vLg0AAFSgBDC/Uh5O/atOAwAAwKCY+9OgAQCAUlACUGZO/VOiAQAAoF/m/vRoAACgLJQAlIpT/1RpAAAA+DPNz/1dHVPk1dLSAABAiSgBqPqpf1fHFJ9aW3IaAAAAsjn1z2gvtJYGAADKRQlAzpz6R6MBAAAIyql/TBoAACgdJQCt5tQ/Mg0AAEAgTv3RAABAGSkByJxTfzbTAAAAJM6pP1vTAABASSkBaJ5Tf+ppAAAAEuTUn/5oAACgvJQADINTfwamAQAASIRTfwZDAwAApaYEYDCc+jN4GgAAgApz6s9QaQAAoOyUADTk1J/h0QAAAFSMU3+aoQEAgApQArCZU3+apwEAAEj/yN+pP1toAACgGpQAMTV/5O/Unz40AAAAZeTUnxbRAABAZSgBgnDqT0tpAAAAysKpPznQAABAlSgBUuXUn9xoAAAAiuTUn5xpAACgYpQAyXDqTyE0AAAAeXPqT4E0AABQPUqA6nLqT+E0AAAAeXDqT0kIAABQSR3zugYeKGs9yw2LJZHJkX9GewEBAACgZYz+lJD3AABAVXknQNrX+rvQnxbRAAAAZMmpPyWnAQCAClMClIpTfypBAwAA0Cyn/lSIBgAAqk0JUCyn/lSOBgAAYDic+lNRGgAAqDwlQM6c+lNpGgAAgMFy6k8CNAAAkAIlQKs59ScZGgAAgIE49ScxGgAASIQSIHNO/UmSBgAAoC+n/iRMAwAA6VACNM+pP8nTAAAA/IFTf4LQAABAUpQAw+DUn1A0AAAAw2fup3I0AACQGiVAPpz6U1EaAJrS3d3dlpBardmrP/PX1bWNP/MAZM7cT6VpAAAgQUqAFnHqTwI0AAAA22buJxkaAABIkxIgK079SYwGAACgMXM/SdIAAECylADD5tSfhGkAAAD+xNxP8jQAAJAyJcDgOfUnCA0AABCduZ9QNAAAkDglALA1DQAt1D2/dF9S2/m2WrU2vM09AwAMiQYAANKnBAC2EAAAACAQAQAAQlACAJsJAAAAEIgAAABRKAEAAQAAAGIRAAAgECUAIAAAAEAgAgAAxKIEgOAEAAAACEQAAIBwlAAQmQAAAACBCAAAEJESAMISAAAAIBABAACCUgJATAIAAAAEIgAAQFxKAAhIAAAAgEAEAAAITQkA0QgAAAAQiAAAANEpASAUAQAAAAIRAAAAJQAEIgAAAEAgAgAA8AdKAAhCAAAAgEAEAADg/ygBIAIBAAAAAhEAAIA/UQJA8gQAAAAIRAAAAP6MEgDSJgAAAEAgAgAA0JcSABImAAAAQCACAADQgBIAUiUAAABAIAIAANCYEgCSJAAAAEAgAgAA0C8lAKRHAAAAgEAEAABgIEoASIwAAAAAgQgAAMA2KAEgJQIAAAAEIgAAANumBIBkCAAAABCIAAAADIoSANIgAAAAQCDtnZ2dRe8BAACqpLu7u62yNAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEMiogW/es6ujrdzur/UMcGtXV1eOewmhVqsN/oe755fuv3/n22rV2vA297yZp3pRz/lKv0hW+mss//CrMeA32XfMK/svRc+CgZ5aXR1TctxLCLWe5VX8Dz7wtivxVK+ungF/SStNAwDhghkAyUh4SKV1BACGwJQJAHkqbTVBpQkAkAjxDCAmJQBDJQAwWOZLAMifEoDMCQCQDiENICYlAEMiADAoJksAKIoSgGwJAJAUUQ0gJiUAgycAsG1mSgAolhKADAkAkBqBDSAmJQCDJACwDaZJACgDJQBZEQAgQWIbQExKAAZDAGAg5kgAKA8lAJkQABi+7vldRW+BfglvADEpAdgmAYB+mSABoGyUADRPAGCYHP+XnwgHEJMSgIEJADRmdgSAclIC0CQBgOFw/F8VghxATEoABiAAAABUjBKAZggADPnY2PF/tSgBAGJSAtAfAQCqratLHgOISAnAsAkA9OX4Pz1KAICYlAA0JABA5SkBAGJSAjA8AgB/xvF/qpQAADEpAagnAEAKlAAAMSkBGAYBgD9x/J82JQBATEoA+hAAIBFKAICYlAAMlQDA/3H8H4ESACAmJQBbEwAgHUoAgJiUAAyJAMAfOP6PQwkAEJMSgC0EAEiKEgAgJiUAgycA4Pg/HCUAQExKADYTACA1SgCAmJQADJIAEJ3j/5iUAAAxKQEQACBNSgCAmJQADIYAEJrj/8iUAAAxKQEQACBNSgCAmJQAbJMAEJfjf5QAADEpAYITACBZSgCAmJQADEwACMrxP5spAQBiUgJEJgBAypQAADEpARiAABCR43+2pgQAiEkJEJYAAIlTAgDEpASgPwJAOI7/qacEAIhJCRCTAADpUwIAxKQEoCEBgD9x/B+ZEgAgJiVAQAJALIa8sJQAADEpAagnAPB/HP8jHwLEpASIRgAIxHgXnBIAICYlAH0IAPyB4382kxIBYlIChDKq6A2Q8mDX+baKvZpUbsND1dXVZcQHCKirY0qtZ3nRu6AsNAA4/ufPSAhAYmo9y82+g6EEiEMACMFIxxbeCQDEYfTfmncCsIUAEJ3jf+pJjEDVGf2HRwkQhAAQepgz/cekBAASZvQfgBKAzQQAoAElAFA5Rv9MKAEiEAAS5/ifhpQAQEqM/oOnBEAAAPqlBADKz+jfCkqA5AkAKXP8zwCUAEClGf2HTQmAAAD0SwkAlJDRPwdKgLT5JuBk5XP8X3iTkO1390Y7FPfFwEC1mPuz4ouBg9MAUFWdb6tlO/3TkIQAlIFT//wpARKmAUhT2lf/m/szpAQASq75ub9j3h/+8Bln+1ACRCYAUCVG/0LUarVoF0cBKY3+DFvPgpr/hkkSABKU5PG/0b91lABA2Rj986EECEsAIMrov/kM26Q7PEoAIB9G/7JRAiRJAEhNYsf/mUz/JtdtUgIAhTP6F0IJEJMAQLKjv7k/W0oAoEWM/iWnBEiPAJCUNI7/jf6FUAIA+TP6l4ESICABgBIx+pecEgDIitG/WpQAiREAQij/8b/RvwyUAEAOjP4lpASIRgBIR0VHN6N/tSgBgGEz+leaEiAlAkD6Snv8b/QvISUA0ApG//JTAoQiACSiWkOb0b/SlADA4GUyU5r+S0IJkAwBIHFlO/43+pefEgDIhNG/cpQAcQgAKajEuGb0T4kSABiA0T9hSoA0CAApK8nxv9G/cpQAwPAY/atOCRCEAFB5ZR7UjP4JUwIAWzP6x6EESIAAkKxij/+N/lWnBAAGyeifGCVABAJAtZVwRDP6x6EEgOCM/mEpAapOAEhTIcf/Rv/EKAGA/hj906YESJ4AUGHlGc6M/mEpASAaoz+bKQEqTQBIUJ7H/0b/tCkBgC2M/qEoAdImAFRV4WNZk6O/uT8ZSgBIntGfhpQA1SUApCaH43+jfyhKAIjM6B+ZEiBhAkAlFTWQGf1pSAkA6TH6MxhKgIoSAJLSuuN/o39kSgAIxejPFkqAVAkA1ZPzKGb0ZzCUAJAAoz/DoASoIgEgHZkf/xv92UIJAGkz+tMfJUCSBICKyWcIM/ozDEoAqCKjP81TAlSOAJCIrI7/jf70RwkAiTH6M0hKgPQIAFXS0vHL6E/zlABQCUZ/MqcEqBYBIAVNHv8b/RkkJQBUndGf4VECJEYAqIwWDV7NTP9Gf+opAaCcjP60mhKgQgSAuMf/Rn+GQQkAlWP0JxNKgJQIANWQ7chl9KellABQEkZ/cqYEqAoBINbxv9Gf5ikBoPyM/rSCEiAZAkAURn/ypASAohj9KZYSoBIEgAro77R1kMf/Rn8ypwSAEjL6kwMlQBoEgJQNe/Q399M8JQDkxuhPqSgByk8ASPP43+hPqykBoAyM/uRPCZAAASA1Rn/KQwkArWP0p8yUACUnAKRz/G/0J2dKACiE0Z/CKQGqTgBIgdGf0lICQIaM/lSIEqDMBIBqH/8b/SmWEgDyYfSnbJQAlSYAVJXRn6pQAkAzjP5UlxKgtASA6h3/G/0pFSUAtIjRn5JTAlTXiKI3wNAMb/rv+qMWbAcGRUKAoTL9k4aeBV7/y0gDkPi0ZO4nB0oAKBujP/lQAlSUBiBZTv0pFQkB8tExr8v0T6koAUpIA5DgnGTuJ39KACicuZ9CKAGqSAOQFKf+lJmEAC3i1J+SUwKUjQYgkQnJ3E/hlACQP3M/ZaAEqBwNQOU59adCJATIilN/qkUJUCoagArPRub+zBlPgfIz97eCA2xCEQCqx9xPpfliYBg2oz+V5ouBy0MAqNLZs7EJICZjE5Ah7wGoBhf6kxKXWsHgudaflHgnQEloAMo+D5n7AWIy9wMtogEoL6f+JEwJAANw6k/ClABloAEo4yRk7geIydwP5EADUC5O/YlDCQBbc+pPHEqAwmkAyjIDmfsBYjL3AznTABTPqT9hKQEIzqk/YSkBiqUBKJjRv1T8zwHkxuhfKv7nIBQNAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQyqi1ptVqt6C1QJZ4wkIyeBX6dGQJPGELRAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIJX/JuA9uzqK3gJVcn+tZ4BbPZ2gQrq7u4veAkAlaQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgkFED33x/rSevnUDxPOEBgORpAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAA2uL4/1V82T0CNgBTAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_197
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 2th action is Colorize the top layer of the original shape with the color white.\nthe 3th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 4th action is Colorize the top layer of the original shape with the color yellow.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_34
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_54
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAIAElEQVR4nO3ay40bVxRFUUlwAh44tHaQ7tA8cAgyDEiAIKu7+amq99lrBUDcCYldp/j55eXl6yeAb15fXz+PvgE43xdfdgDo+TL6AABgUABYAQCgxQIAAOUAsAIAQIcFAADqAWAFAIAGCwAABP0vAKwAALC/3579gL9+/+OYS4BT/fnP36NPAGZ/BXDPCuBHBQDW4z8AABD0ZgBYAQBgXxYAAAh6NwCsAACwJwsAAAR9GABWAADYjwUAAIJuCgArAADsxQIAAEE3B4AVAAD2YQEAgKC7AsAKAAB7sAAAQNDdAWAFAID1WQAAIOihALACAMDaLAAAEPRwAFgBAGBdFgAACHoqAKwAALAmCwAABD0dAFYAAFiPBQAAgg4JACsAAKzFAgAAQYcFgBUAANZhAQCAoEMDwAoAAGuwAABA0OEBYAUAgPlZAAAg6JQAsAIAwNwsAAAQdFoAWAEAYF4WAAAIOjUArAAAMCcLAAAEnR4AVgAAmI8FAACCLgkAKwAAzMUCAABBlwWAFQAA5mEBAICgSwPACgAAc7AAAEDQ5QFgBQCA8SwAABA0JACsAAAwlgUAAIKGBYAVAADGsQAAQNDQALACAMAYFgAACBoeAFYAAAgGAAAQDQArAAAEAwAAiAaAFQAAggEAAEQDwAoAAMEAAACiAWAFAIBgAAAA0QCwAgBAMAAAgGgAWAEAIBgAAEA0AKwAABAMAAAgGgBWAAAIBgAAEA0AKwAABAMAAIgGgBUAAIIBAABEA8AKAADBAAAAogFgBQCAYAAAANEAsAIAQDAAAIBoAFgBACAYAABANACsAAAQDAAAIBoAVgAACAYAABANACsAAAQDAACIBoAVAACCAQAARAPACgAAwQAAAKIBYAUAgGAAAADRALACAEAwAACAaABYAQAgGAAAQDQArAAAEAwAACAaAFYAAAgGAAAQDQArAAAEAwAAiAaAFQAAggEAAEQDwAoAAMEAAACiAWAFAIBgAAAA0QCwAgBQlwwAAKjLBoAVAICybAAAQFk6AKwAAFSlAwAAqvIBYAUAoCgfAABQJACsAAAECQAACBIA31gBACgRAAAQJAB+YAUAoEIAAECQAPiJFQCAAgEAAEEC4BesAADsTgAAQJAAeIMVAICdCQAACBIA77ACALArAQAAQQLgA1YAAHYkAAAgSADcwAoAwG4EAAAECYAbWQEA2IkAAIAgAXAHKwAAuxAAABAkAO5kBQBgBwIAAIIEwAOsAACsTgAAQJAAeJAVAICVCQAACBIAT7ACALAqAQAAQQLgSVYAAFYkAAAgSAAcwAoAwGoEAAAECYCDWAEAWIkAAIAgAXAgKwAAqxAAABAkAA5mBQBgBQIAAIIEwAmsAADMTgAAQJAAOIkVAICZCQAACBIAJ7ICADArAQAAQQLgZFYAAGYkAAAgSABcwAoAwGwEAAAECYCLWAEAmIkAAIAgAXAhKwAAsxAAABAkAC5mBQBgBgIAAIIEwABWAABGEwAAECQABrECADCSAACAIAEwkBUAgFEEAAAECYDBrAAAjCAAACBIAEzACgDA1QQAAAQJgElYAQC4kgAAgCABMBErAABXEQAAECQAJmMFAOAKAgAAggTAhKwAAJxNAABAkACYlBUAgDMJAAAIEgATswIAcBYBAABBAmByVgAAziAAACBIACzACgDA0QQAAAQJgEVYAQA4kgAAgCABsBArAABHEQAAECQAFmMFAOAIAgAAggTAgqwAADxLAABAkABYlBUAgGcIAAAIEgALswIA8CgBAABBAmBxVgAAHiEAACBIAGzACgDAvQQAAAQJgE1YAQC4hwAAgCABsBErAAC3EgAAECQANmMFAOAWAgAAggTAhqwAAHxEAABAkADYlBUAgPcIAAAIEgAbswIA8BYBAABBAmBzVgAAfkUAAECQAAiwAgDwMwEAAEECIMIKAMCPBAAABAmAECsAAN8JAAAIEgAxVgAA/iMAACDo5qdB9vLy8vJ19A2svxIB67IAAECQAIjylAfQJgAAIEgAhFkBALoEAAAECYA4KwBAkwAAgCABgBUAIEgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB8Os2/DOAWqzCF+jQAAAAASUVORK5CYII="
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is Colorize the top layer of the original shape with the color blue.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_142
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_172
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 5th action is Colorize the top layer of the original shape with the color white.\nthe 6th action is Colorize the top layer of the original shape with the color red.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_262
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is Colorize the top layer of the original shape with the color blue.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_115
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color red.\nthe 7th action is Colorize the top layer of the original shape with the color green.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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mUDAAAAU9ELgCUAAAAUyQYAAAACWbIAWAIAAEB5bAAAACCQYQXAEgAAAApjAwAAAIEsUwAsAQAAoCQ2AAAAEMjyBcASAAAAimEDAAAAgYxUACwBAACgDDYAAAAQyKgFwBIAAAAKYAMAAACBjFEALAEAACB3NgAAABDIeAXAEgAAALJmAwAAAIGMXQAsAQAAIF82AAAAEMgkBcASAAAAMmUDAAAAgUxYACwBAAAgRzYAAAAQyOQFwBIAAACyYwMAAACBVCoAlgAAAJAXGwAAAAikagGwBAAAgIzYAAAAQCA1FABLAAAAyIUNAAAABFJPAbAEAACALNgAAABAILUVAEsAAABInw0AAAAEUmcBsAQAAIDE2QAAAEAgNRcASwAAAEiZDQAAAARSfwGwBAAAgGTZAAAAQCCNFABLAAAASJMNAAAABNJUAbAEAACABNkAAABAIA0WAEsAAABIjQ0AAAAE0mwBsAQAAICkrOr6AgAAarNp06YmRpZQksYLwOzs7PB/inObp9dtnGn6MgCAyBEf6LEBAAASJetDrgXAEgAAWJa4D+2wAQAAuiHxQ8kFwBIAABD6IQU2AABAs4R+CFoALAEAIA6hH5JlAwAA1Ebuh/S1WgAsAQCgSHI/ZMQGAAAoJ/fPzAyeJE5PT7d+LZCotguAJQAA5K7b3L9UxAdGZAMAACSa+2V9KKQAWAIAQF5ai/4SP7TABgAA6Cz3S/wQpQBYAgBA2Ogv9EO3bAAAgMajv9AP6eisAFgCAEA65H6IwwYAAEKrPfoL/ZC4LguAJQAAFBP95X7IhQ0AAIRTY/SX+yE7HRcASwAAaJPoD9gAAEAIdUV/uR9y130BsAQAgEaJ/kBaBQAASDn9y/1QmCQKgCUAANRO9AfSLQAAQI1EfyCDAmAJAACdR3+5HyJIpQAAAB2mf9Ef4kioAFgCAMBkRH8gywIAALSZ/kV/iCmtAmAJAACjE/2BCayc5D8CALom/QMlbAAsAQBgWaI/UFQBAABqT/+iP5B0AbAEAIB+oj9QC/cAAEAGpH+g8AIwOzs7/C/MbZ5u61oAIL/0P/OEZi4HyFuKR4AAgCrRv5lrAQqR6AbAEgAApH+gCTYAAFBC+hf9gew3AJYAAMS06Qlj/SfSPzA6GwAASIjoD4TeAFgCABCK9A+0IPUCAABBSP9AOzI4AuSNgQEom+gPtMkGAAC6JP0DLcujALgTAIAiSf9A+zI4AgQARRor/Yv+QKwNgCUAAIWR/oGuZFMAAKAY0j/QoZwKgCUAAKHS/8wTGr4cIJycCgAAhEr/DV8LEFRmBcASAIB8Sf9ACrwKEAA0zqF/IB2ZbQAsAQDIjvQPJCW/AgAAGZH+gdRkWQAsAQDIgvQPJMg9AADQCLf8AmnKcgNgCQBAMaR/oGW5FgAAKGD8L/0D7cu4AFgCAJAm6R9IWcYFAAASJP0Dicu7AFgCAJAU6R9In1cBomQaIJBs+p+enlYDCGvTpk3LjnFpTvYFYHZ2dvgT7tzm6XUbPcMWTtAHcpz9T0//+LlLDSCUsd4cg4ZkXwAISNwHCkj/MzMz8wVADSDgPxPj/26VUAAsASIQ+oGyz/2rARTM1D81JRQASiX0A2Wn/94SoEcNIMI/EOP/zhVSACwBiiH0A6gBFMDUP2WFFAByJ/cDMQ//9C8BetQAivx3YfyfgnIKgCVAjuR+IF/tvOS/GkAujPwzUk4BIC+iP5C1GtP/kCVAjxpAGdHf+D8RRRUAS4D0yf1AAbp6u99eT9AESISpf6aKKgCkrKvov6jyaSBAO8bK6KMsARayECDH6G/8n47SCoAlQGpaC9y+rUA6uaedaK4G0AlT/wKUVgAIEv3FfaCw9D/uEqBHDSCL6G/8n5QCC4AlQKnR33cN6FbKg081gLA//EygwAJASdFf6AfyUiWCT7wE6FEDSDP6G/+npswCYAmQe/T33QFSk87R/2WpAdTC1L9gK7u+AEpQV/pft3Fm/v/V8tEAskv/Qz7IO9aN9/Gnn1D9kgho0xNG//vDfziN/xNU5gbAEqA1tUR/3wggZYnMQd84Nz0fs9445wVDSeWnfYKfSVJQbAEg/egv9wPFqDFhL3sngBpAOtF/Wcb/aSr5CNCyP3PeE2piFb90zvkAuUjq6P/C0P+OdTMOBdHVgZ+FP3vG/zmyAaDt6F/ftQCUmf5Hfzkg2wDaPNs2buc0/k9W4QXAnQCJRH9fZIB67wRYSA2gq+hv/J+pwgsAnad/0R/IVLeHfyZ4TwA1gBSm/j3G/ykr+R6Aee4EqG6yL5GD/kC+kjr6v8jwiO/eAGo56D/Kz5Lxf75sABjG4B+gq/Rf5Y2BbQPoZOrfY/yfuBAFwJ0ALQ/+G7gWgHAv/D/unQA11gBNoAyNRn/j/6yFKAC0k/5Ff6AASR3+qbIEqPhWTRYCWetk6t9j/J++KAXAEmB0oj/AEIlk4hGXAD1qQBDtRH/j/9xFKQCMSPoHIkvw8E8tS4AeNaBg3U79e4z/s1D+qwD1eDmgZY37FfA6P0BJkjr80+gUdoJXCvJiQdFe4WcI4/8CBCoA1J7+G7sWgBR1lf4b+ryT5T81IPfo39Dgf57xfy5iHQFyJ8BAoj9Agod/mrgToJYTQQ4F5fsTWz36G/+XIVYBoJ/0DzCKbsNuvXcCLKIG5KWr6L8s4/+MhCsAlgALSf8A+Y7/a1kC9KgBpf6U1hj9jf+LEa4AMFn6F/2ByOKkWzUgQSlEfwqzYiqkZf8tFZ93w6b/4f/DrS8hoGV/I6QTaoecAmoi6k087k3nK7bQ8DNUaT7/JxX9h/88pPkFZCk2ABGFTf8AJR3+aZptQIeSiv6UJ+jLgEZ+T4DR/6d5mX+ApFLskItp7nD2xC8Y7wVD23xlz4ov7b8s4//C2ADEMlb6b/haADpm/D8624AWmPrTmqAbgJhLAOkfYCwJxtZOlgA9tgGhpv49xv/lsQGIQvoHWMj4f2K2ATUy9acTQV8FKNrLAUn/PV4FCMjuxX86fzmgIaqsHVr+Cqf2KkC5RH/j/yLZAJRP+gcoKf2XsQ2IvBDIJfpTsLj3AAS5E0D6ByhPt3cC1HsSPdTtAYmf9e9n/F8qG4CSSf8A/Yz/G2IbMISpP0mJvgGIsARYlvQPkJ3UlgA9tgH9I/+8pv49xv8FswEo1oi9RfoHQjH+b4dtQJWXmTL1p2k2AGUuAaR/gOIluwQIvg2YeOSfwtS/x/i/bDYABZL+AQYy/u9EnG2AqT+5sAEobQkg/QPEkf4SIMg2oIypf4/xf/FsACKS/gH65TJmzlp52wBTf3JkA1DUEmCUK5T+gZiqBLWUZbQEKGwbUNjUv8f4PwIbgHJI/wBkJN9tgKk/ubMBKGQJkOyFAaSg7Nt/c1wCZLoNKHXq32P8H4QNQCDG/wCkKf1tgKk/JVnR9QWkaNl/5KklaYd/6vpamW1Akcoe//cMmYXnFUCrbC2GfCuH7wqGPP/Hif7G/3HYAGRP+gegJOlsA+JEf6JxD0DedwKkcyUAmSpj/J/7nQD1Buj5ewOq3B5Q5ax/punf+D8UG4DyGf8DkZX66p8RVFkFTLYQqP7TkmP0JyD3AGR8J4DDPxNwDwBEE+QGgPLuBMhuiVHwl9cvx/LYAJRM+geCi5b+C1Z9G9CcrKM/MbkHINc7AZz+B6D4OwESfyn91K5nMsb/AdkAZMnhH4DqjP8zlcI2oIDcT2Q2ABkvAYaQ/gHC3v5b9hKg8+l7GVP/HuP/mGwA8pNU60jqYgCIps1tQEm5n+BsAApcArQ5/rdqADJV9vmfIEuA1qbyhU39e4z/w7IByMyyfUMiB4h8/ieyJrYBReZ+sAHIaQmQ4LZB5QByVPb4f1lFLgFqn9aXOvUP8mPAcApAUWRxAOYFLzlV4nvx0X8Uzv+UTQHIZgmQ5vh/nuIBJMX5n2UFmf6OG+XjRP8gPwAsRQEohxQOMIo4o/Hh/0vjRMBRYn2c6D/Kt974v3gKQB5LgJTH//PUDwCALCgAhZC/AeY5/7OQJQCLGP+jAOSxBMjlpT8TuQyAIeKc/wFYivcBoFWHzqzr9gJunZ7r9gIAWjYzMzM9veQg6Y1z03HOvmP8zzwbgNSXALmM/0e8GPkbaJTzPwDLUgAAoHDuBMD4n4UUgCzfEyDN8f88SwAgWW4AAFAAUpf+q38CkAVLgOCM/1lIAch+CZAgSwCgE24AABiFApCuvG7/BUic8z+WAGEZ/7OIAjAhS4DhLAEAANKkAOTK+B+AcVkCBGT8Tz8FINElQAELBEsAoE1uAAAYkQKQJeN/gLG4AaDHEiAU438GUgBSXAIUMP6fZwkAAJAaBQAAYrEECML4n6UoAPm9HFBe538sAYAWuAEAYHQKQHKKOf8DkAg3APSzBCie8T9DKAA18J4Aw1kCAACkQwHITF7nfwBIliVAwYz/GU4BSGsJUOquwBIAACARCgAAeXMH8MQsAYpk/M+yFICc7gTI+vyPJQDQCXcAAyyiAABAXJYAhTH+ZxQKQEJLgFJvAOixBAAA6JwCkI2sz/8AkCxLgGIY/zMiBaBm3hNgOEsAAIBuKQAAFPsSQO4AHpElQAGM/xmdApDKEiDOZsASAACgQwpAHtwAAECHLAES5xvEWBSARrgTYDhLAIDUOC5VNud/WEgBAACWZ8acLN8axqUAJLEECLgQsAQASI0lQKmM/1lEAciAGwAASIFJc4J8U5iAAtAgdwIMZwkAVOQ1QGvni1Ye43/6KQAAwKjMm5Pi28FkFIBmWQIMZwkAkBpLgJIY/zOQAgAAjMHUORG+EUxMAWicJcBwlgAAqbEEKIPxP0tRAFLnJYAASI3Zc+d8C6hCAWiDCj6cJQBAaiwBcid7MIQCAACMzQS6Q774VKQAtEQRH84SACA1lgD5kjoYTgEAACZhDt0JX3aqUwDao44PZwkAjMXbALfAlzFH8gbLUgAAgAmZRrfMF5xaKACtUsqHswQASI0lQF4kDUahACTNmwAAkDgz6db4UlMXBaBtqvlwlgAAqbEEyIWMwYgUAACgEpPpFvgiUyMFoAMK+nCWAACpsQRIn3TB6BQAAKAq8+lG+fJSrxXDX0cZQjE+IRTP/1AMv78Yiw0AAAAEogAAAGTM+J9xKQAAABCIAgAAkCvjfyagAMBPuCcSACieAgAAkCujKyagAAAAQCAKAABAxiwBGJcCAAAAgawa/sfrNs5MpW1u87A3x56ZSf36p6enC/76Hzqzbioxt07PdX0JkIfcn3/Sf/7PzvBfWFNTU+9Yl/TX/I1z06Ve/PwSwMsBMTobAACgqsQDdO58eamXAgAAVB3/0zl3AjA6BQAAqMR8ugW+yNRIAQAAhjH+z4UlACNSAACAyZlMt8aXmrooABm/xgUANM34Py+WAIxCAeiYF6oDIF9m0i3zBacWCgAAMJjxf44sAViWAgBAgW9VJrm2wDS6E77sVKcAAAADKFH5sgRgOAUAIKjZ2dkhf+pFCBjOHLpDvvhUpAAAAIsZ/+fOEoAhFAAAYDwm0J3zLaAKBSB1tvAAtMz4vwyWACxFAeietwIAICNmz4nwjWBiCgAA8BPG/yWxBGAgBQAAGJWpc1J8O5iMAgAAAIEoAERx6/TcrdNzXV8FUCdvBly74V808+YELftNcQqIfgpABrwQUEWiPwBAjwKQBC8E1BDRH2B0xv+ZsgRgXKvG/i8gB3I/AMBANgCUxtQfRjc7OzvkT50/DMX4P2uWAIxFAciDX8OjEP0BAJalAKTCbQBViP4AVRj/F8ASgNEpAORN9IfgvBIowLgUAHIl+gPUwvi/GJYAjEgByIbbAHpEfwCAiSkACXEbQAvRf/hpAYBojP8LYwnAKLwPAHmoPvIX/QEAbAAyE/MUUC1Tf+kfwr4VgPuAhzD+L5IlAMuyASBdpv7AKNZtnCmgqAC0xgYgLW4DqPE2X+kfYAjj/4JZAjCcDUBm5jZPl51ra3l5n7K/RAAAVdgAUNrUX/oHWJbxf/EsARhCAUhOwFNAoj/QKPcBAyykAOSnpHvdRH9IXxbPOZ4ExmL8H4QlAEtxDwDdcNYf0jE7OysHAMRhA5Cisk8BmfoDdMj4PxRLAAZSALKUxUa+n+gPdMVtAAA9CkCiClsCiP5A0zw/jML4PyBLAPopALnKZQkg+kMBcnnCAWAUCgANEv0hF7Ozs11fAo0z/g/LEoBFFIB0LXsKqOyZnOgP1MttAADzFACSI/oDk/HUMTHj/+L5FrOQApC0wm4FXpboD9AQCxCGcwooFAUgb8WcAhL9IXFlPNsIwQOZDQfhG02PAkDHRH9IhPuAC6b5MApLgDgUgNQVfCuw6A/UzrPKuEyFQ/HtZp4CQAdEf4DWGP8zOkuAIBSADBS2BBD9gQ5JwwuZBwfkm44CUI4sOoDBP2Qti+cZU4ZFFB7GZQkQgQKQh9xfD1T0hyy4DziUOJPgN85Nv3FuuvrfKUacbz1LUQDKkeZwTvQHUhNnKD7kf2mQCDhurI9TA4b/AFgCFE8ByEZ2SwDRH+iKJx+qRPk4NYCwFICiJLIEEP2hVIk8yTCKsOP/uuJ78TXAEiAyBSAn6S8BRH/IXZDbAOKcAgqlichefA0gJgUgM8m+JKjoDyQl+DNStPF/0zG91BpgCRCWAlCgljuA6A/kyBKgDG1G81JrAAEpAPlJ6iCQ6A/RuA0gfUHG/13F8cJqgCVATApAmfyGBiZWzG0AJhSlSiGCp3ANMDEFoNglgA4AEPAUUNnj/9Rid2rXMxlLgIAUgFwldRAICMV8gfalHLVTvjYYSAEomV/SQHDLngIqbAlQ5Pi/rnjd9OAs6xpgCRCNApAxB4GAhhRzGwBZqzH6j/Ibs5Yf+6xrAHEoAOXTAYDI4twKXNj4v83o3zP7/6v4eXPsAJYAoazq+gKoZGZmprD9NZCFuc3TxQTr6elpd1UlpXp6rv4Nne8AVVLv/P+KHKsXEdgAZM9BIKAJTgHlpYzxf/XzM+OO/Iervg3I60SQJUAcCkAJdACAIaLdCpyj1KJ/5BpABApAIDoAUCNPKVlIf/yfcvQPWAPS/4GhFgpAIRxgBWpX0imgspcAmV58LtE/YA1YilNAxVAAyuEgEABZTHNzjP5xakCyPzbUSAEoig4AtCmv55NiXrYo6/F/7tE/Tg1YiiVAGRSAiPL6nQ3QjrySdHZz3JKif/E1ILUfHmqnAJRmxCdHHQCIdhtAkbIoLaVG/+JrwFIsAQqgABRIBwBak9czSdm3Aic4wY0Q/UutAYn8CNEQBaBMOgBA8VKuK9Gif6k1YCmWALlTAIqlAwC1KOwUUIQlQLez28jRv7AaYAlQsFVdXwDdm9s8XeqLYwAt8BzSiQSLSvW0WkDuX6TXASYemc9/VRPM4ps2bSpsOhCKDUDJRn8mtQcAhijs13zZS4BOkqKpf9MLga62AQkWD2qhABROBwAoTzoVRfSPUAOW4k6AfCkA5dMBgKZl9+xR6hKgzXmt6B+kBlgCFEkBCEEHACoq7BTQKJLtAJ1fWMUAOp/7Y0b/fGvAUiwBMqUARKEDAI3K7qmjvBuXW5jU1hL9a72i7GVRAywByqMABKIDAOQ1a0/nkkT/RmVRA5ZiCZAjBSAWHQCYWHmngEpaAjQ3oxX9W5NyDbAEKIwCEM5YHUANAEZX5DNGUkuAli9G9O9EyjVgKZYA2VEAIhrrGbnI3+gAJS0Bap/Oiv6dS7AGWAKURAEISgcAJrBsIsnx6SKXlwRt5zJE/6QkWAOWYgmQFwUgrnE7QI6/1wFqkUgHaHQuK/onK50aYAlQDAUgtHGfrHUAoLxbgbM4CNRoAxH9M6oBE/8DbGEbYAmQEQUgOh0AqFepzxJpLgEqTmRF/xx1WwMsAcqgADD2M7jjQBCcJUAZ3UP0j1wDppphCZALBYD/xyoAqEupzw+pLQEmnsVWGQOL/mXUgCo/A5YABVAAqNQBSv01DwQ0yhKg/Q5Q72cU/YvUSQ1YiiVAFhQA/pkJntx1AAioyNcDTfwgUMUprOhfvDZrgCVA7lZ1fQEkZ/5ZfqyZ0/xv+ox+cQJMbHp6Oq80XPGsf63XQuPmO8AEY/j5nxPJPggbAOpcBWQ68wMmEHkJ0NpBoKU+0YgpzdQ/rBa2AUN+CJ0CSp8NAEuamZmZ4JecbQCQu3UbZzJtLz1Vcn/d10JnbANYig0AjUyAcv/dCYR9PdARtbAEmGz8P/HU38i/VM1tAywB8qUAsLyJO4AaAMHl+ySQ1EGgEYn+5PJKQXROAWAkE/9uUAOATHXbAcYa/4v+dFUDLAEy5R4AGnx1oJ5eB3BvABRmdnZ2+K/5uc3T/uE3x1l/JuDeAGwAaHVcZCEAZKSrJcAo439Tf2rZBkywEFj0s2cJkCMFgElU/OWhBkBJSn090GRvBhD9qVctNYC8OAJEByeC5jkXBBSjxncHGzL+d+CH1M4F9Q4FLfXDuWnTpsgvF5YsGwAqqWWeNL8QyHpGCMFZArTA1J+UtwHNXA5NUQCoQV2/XTQBIPhBoBpPE4n+tP9iQQO5EyBBCgAp/qbRBCA7ZS8B0rwZYCmiPwnWAJLiHgDq0dCvvYWJIZEtPEBDNwNUfyKV+0nnNUMXcidAahQAqmpt4qUMQOKKf0+AdRtnkt1jiP6kXwNIhwLA5Dpcdvf/Ds46VQAldYDJlgATP6OK/mRRAywBkqIAMIlEzrkutNSvZMUA2lT8EqDRDjAu0Z9O2AYUQAEg++g/XLL7egirgA4wirE6wLhPraI/OdYAS4B0KAC0Gv17v/Xlcgi7BCjAiDcD1L4HkPtJjW1AprwMKMubfkLFD7Ju48zCmd+i/xMIpYARwIjPYKM8eY7yd7yyJ2W8YKiqkAgbANqb+g/5owLSABBqCdDaHkDuJxe9DhDhn3/uFAC6if5L/U1NAIIo406A6h1gyJOt6E+R54LcCZACBYCOo/+Q/1AZgHwFWQI0RPSnAG4PSJl7AGj2rH/1D+VuAcjUskO+Mkp+lZsB+h901p8ItwdoBZ2zAaD7qf+4H7yM0AA4CLSQ3E/BbANSowBEl370H/7plAFIWZyDQBN0gN7Tr+hPwBrgToBuKQBx5Rj9FxL9oQxlLAEm6wCiPwHZBqRAAYhI9Dd1gNbEWQKM2wGkfyLzi7hbCkAsor9nHEhQMUuADt8kGGB0XgUoitRe4Wdcc5unK6b/0d+nEKjXKP/0SjrUV+ObBAM0wQagfKb+cj90LtRBIHsAIHEKQMlEf9EfMlLSQSAdAEiZAlAm0V/0hxyXAIV1gBHpAEDLFIDSiP6iP5DXEqD31K0GAO1wE3A53ObrNl9IXLS7gcedp7gtGGiHDUAJTP3lfshFtLuBx9oDOA4EtEMByJvoL/pDecq7E0AHAJKiAORK9Bf9IVMx7wae/58z+i0BOgDQHPcA5MdZf2f9IXcBbwaYN/oTr/sBgObYAOTE1F/uB0K9NJA9ANAEBSAPor/oD4WJeRBonpcHBbrlCFDqHPhx4AdKFfYgkJcHBbplA5AuU3+5HyiYlwYCuqIApEj0F/0hiMgHgSboAI4DAbVwBCgtDvw48APRRD4INMGwxnEgoDobgFSY+sv9wBD2AD2OAwEVKQDdE/1FfwhulINAZRvrbcIcBwIqcgSoSw78OPADzAt+EGie40BAOxSAboj+oj+wiA6gAwDtcASobQ78yP1AFQXfDDDxLQGOAwFjUQDaI/qL/sBwbgaY7JYAdwYDY1EA2iD6i/7AiIK/M8BCVgFAQ9wD0Cxn/Z31B8blZoCeCZ783RUALMsGoCmm/nI/0Kg4e4AJjgNZBQBDKAD1E/1Ff6AiNwNUPA6kBgBDOAJUJwd+HPgB6uIg0CKT/WpwIgjoZwNQD1N/g3+gdm4Irn4cyCoA6KcAVCX6i/5At0J1gMmOA6kBwEIKwOREf9EfSORmgIAdYLKncTUAcA/AhJz1d9wfaM2ITzWh7geYN/EvETcGQHA2AOMx9Tf1B9pnD7AUqwBgAgrAqER/0R/okBcGrf2uADUAwlIAlif6i/5ALgIuASquAtQACEgBGEb0F/2BdDgI1NwqQA2AUBSAwUR/0R9IkA7Q6Cpg4a8/TQAKpgAsJvqL/kDKdIAWaoCFAJRNAaj/ZdE6fHHP6h9E9AfSpwOMSA0ABlIAfkz0F/2BvOgA7dwYMM+5IChM9AIg+ov+QKZ0gDZXAfMsBKAMcQuA6C/6A0HoAE3UAE0A8hWxAIj+oj8Q7d3BdIDaa4CFAOQrVgEQ/UV/oDA6QCI1QBOAjEQpAKK/6A+USgdIoQZoApCR8guA6C/6A8XTAdKpAYt+8yoDkKAVw58x03+WrPEJaymiP0AWRuwAWfx2K+8XawpNYPhM0G9M4ih/A1CF6A+QEXuANBcC86wFIB0KwGCiP0COdIDEa8A8ZQC6pQAsJvoDZE0HqFHv69PcgdtFx3L0AWiBAvAToj9AGXSAvBYCC+kD0AIF4MdEf4DC6ACZLgRGuW1XK4CKohcA0R+gVDpASU1g9BfzUQ9gWXFfBlT0B4jAa4O2o5MmUC+/W4kj4gZA9AeIwx4gwk4AGEusAiD6AwSkA7RJE4D0RSkAoj9AZGN1AMeBarHwa6gMQFLKLwCiPwBjdQCrgNopA5CUkguA6A/AQjpACpQB6FyZBUD0B2AgHSApi768+gC0o7QCIPoDMJwOkKz+L7VKAE0opwCI/gCMSAfIxcCvvFYAFZVQAER/ACZ7+vXSQDka/o1QD6D8dwLuhOgPUIzRVwF+LZb969vvZeJY2fUFZGZu83T19D/7hJquCIBKxnpCNl0GClDCEaB2mPoDlGrcWwKsAoCs2QAsz9QfoHjjPkVbBQD5UgCGEf0B4tABgCAcARrMgR+AgMZ6aSDHgYBM2QAsZuoPEJxVAFA2BeAnRH8A5ukAQMEcAfoxB34AqPLSQI4DARmJXgBEfwDquiVg/teKDgAkLm4BEP0BGIVVAFCYiPcAOOsPwFgmeMJ3VwCQrFgbAFN/ACbjOBBQjCgFQPQHoDrHgYAClF8ARH8AOuwAagCQmpILgOgPQCLHgZwIAtJRZgEQ/QFomlUAkKnSXgXIK/wA0JrJfll4gSCgW+VsAEz9AcjoOJBVANCVEgqA6A9AdseB1ACgK3kXANEfgKxXAW4OBtqXawEQ/QFIkFUAkL78CoDoD0CpqwA1AGhBTgVA9Aeg7FWAGgC0II8CIPoDEGcV4MYAIHQBEP0ByJpVAJCadAuA6A9AGSquAtQAoPwCIPoDUB41AEhEWgVA9AegbBOfCFIDgNIKgOgPQBBVVgFqAFBCARD9AQhIDQAiFoBaor/0D0DwGqAJABkUANEfAGq5MWCehQCQbgEQ/QGg9lXAPDUASKsAiP4AMJwaABRSAER/AOikBmgCQNsFQPQHgA5rgIUA0F4BEP0BILUaoAkAjRQA0R8A0qwBFgJAzQVA9AeAjGqAJgAx1VMARH8AyK4GaAIQU9UCIPoDQPt6vzc1AaC9AiD6A0BhCwFNACKYpACI/gBQdg3QBKBg4xUA0R8A4pwL6v/trwxAoAIg+gNA5IXAPGsBCFEARH8AyFFzNcBaAEouALWkf9EfAAo7F7SQMgDR3wl4IdEfAOI0gf7RoT4AgQqA6A8AkZvAPH0AQhQA0R8AstDoTQID6QNQWgEQ/QEgO20uBJa91VAlgGwKgOgPALlb+Nu8/TIw/NVHFANIqACI/gBQng7XAhO/LKGSAI0XANEfAIqXWhNo4Z2LoHiTFADRHwCiSeGAENBBARD9AQBlAEIUANEfAOinDECBBUD0BwBGsSgz6AOQXwEQ/QGAiekDkFMBEP0BgHrpA5BoARD9AYAWDIwcWgG0WgBEfwCgW0ulEcUAarRi+/btdX48AAAgYSu7vgAAAKA9CgAAAASiAAAAQCAKAAAABKIAAABAIAoAAAAEogAAAEAgCgAAAASiAAAAQCAKAAAABKIAAABAIAoAAAAEogAAAEAgCgAAAASiAAAAQCAKAAAABKIAAABAIAoAAAAEogAAAEAgCgAAAASiAAAAQCAKAAAABKIAAABAIAoAAAAEogAAAEAgCgAAAASiAAAAQCAKAAAABKIAAABAIAoAAAAEsqrrC4D2bN269brrrrvmmmu+8pWv3HLLLbfffvuDDz64ZcuWxx9/fM2aNWvXrt1///0PPPDAI4444sgjjzzuuOMOOeSQri8ZAKBmK7Zv3173x4S0bN269cMf/vAHPvCBK6+88pFHHhn9PzzssMNe+tKXvvKVrzzssMOavEAAxnbBBReM9fdXrFixcuXKHXbYYfXq1WvWrNl999333nvv9evXr1mzprFrhEQpAJTsoYcees973vPOd77znnvuqfJxTjvttLe85S3Petaz6rs0ACpZsWJFLR/noIMO2rBhw7Of/eznP//5z3ve83bddddaPiykTAGgWBdccMHv/M7v3HXXXbV8tJUrV77uda97+9vf7ncDQEkFYKHVq1e/6EUvevnLX/6Sl7xkxx13rP3jQyIUAAr0gx/84FWvetWll15a+0d+2tOedumllz7taU+r/SMD0HkB6DnwwAPPPvvs3/qt33JAiCIpAJTmS1/60mmnnXbrrbcO+Ts//dM/ffTRRx9xxBH77LPPbrvt9vDDD//whz+cm5u76aabPvvZz87NzQ35b/fYY4+Pf/zjxxxzTAPXDkASBWDewQcf/Id/+Idnnnlm058IWqYAUJRrr732xBNPvP/++wf+6UEHHfQbv/EbL3/5y5/85Ccv9RG2b99+0003/Z//838+8IEPPPjggwP/zh577HHVVVc9+9nPru/CAUiuAMzbtGnTe9/73r322qudTwctUAAoxz/8wz8cf/zxA9P/7rvv/uY3v/m3f/u3Rz/Ted99951zzjnvete7Bv4bOeigg66//vr999+/8lUDUFsBGJ5qfvSjHz322GMPPfTQgw8+eM8993zzm9/8p3/6p8997nN/+7d/u9TkaN5TnvKUK6644vDDD6/jwqF7CgCFuO222372Z3/2hz/8Yf8f/ezP/uzMzMxkL+p/5ZVXvuIVrxh4J/EJJ5zwN3/zNxNdLAAdFIClbNu27ZOf/OSf/dmfffjDH3788ccH/p1169Z99KMfdf6TMigAlOChhx469thjv/jFL/b/0emnnz4zM7PTTjtN/MFvvvnm5z//+QOrxfve975Xv/rVE39kAFIoAD033XTTf/gP/2Gp4c6ee+551VVXeUloCqAAUIJXvepVf/EXf9H/+GmnnXbxxRevWlX1Ha8/97nP/at/9a+2bt266PH169ffcssta9eurfjxAUihAMz7sz/7s7PPPnvbtm39f7T//vt//vOfd/6T3K3s+gKgqiuvvHJg+j/yyCPPO++86ul//hDRm9/85v7H77zzzve+973VPz4A6Xjta1/7yU9+co899uj/o+9973vT09OPPfZYF9cFtbEBIG9bt2494ogjvvGNbyx6fJdddvnCF75w2GGH1fWJHn300aOPPvqmm25a9PhTnvKUr3/96ytX6tIAhWwA5n32s5/9xV/8xYceeqj/j/7oj/7o9a9/fV2fCNontZC39773vf3pf2pq6m1ve1uN6X9qamrHHXc855xz+h+/7bbbrr322ho/EQApeO5zn/v+979/4B+dc845t99+e+tXBLVRAMjYww8//I53vKP/8cMPP/yss86q/dO9+MUvPuigg/ofv+SSS2r/XAB07swzz3zZy17W//iDDz448LcP5EIBIGN//dd/feedd/Y//l//63/dYYcdav90O+yww2tf+9r+x6+++uraPxcAKfhv/+2/rVmzpv/x97///QN/AUEWFAAy9r73va//wUMPPfTFL35xQ5/xlFNO6X/wxhtv3LJlS0OfEYAOHXzwwf/xP/7H/scfeeSRc889t4srghooAOTq5ptv/tznPtf/+Ote97rmbsk98sgj991330UPPvbYY1/96lcb+owAdOvf/bt/t3r16v7HP/jBD3ZxOVADBYBcXXrppf0Prlix4swzz2zuk65YseL444/vf/zrX/96c58UgA7tscceA9e/X35CF1cEVdXwEunQiY985CP9Dx577LEHHHBAo5/3zDPP7H+Zud12263RTwpAh37lV37l4osv7n/8yiuvPOKII7q4IqjE+wCQpQcffHDPPffsfyuWN7/5zb//+7/f0UUBUM77ACy0bdu2devW9b8nwEte8pLNmzc38RmhUY4AkaUbbrhh4BsxPv/5z+/icgAo2U477fSMZzyj//EvfOELXVwOVKUAkKV//Md/HPj4UUcd1fq1AFC+gb9fvvnNbz7wwANdXA5UogCQpS996Uv9D65fv37vvffu4nIAiFgAtm/ffuutt3ZxOVCJAkCWvvOd7/Q/+JSnPKWLawGgfBs2bBj4+He/+93WrwWqUgAopwDsv//+XVwLAOXbc889Bz7+ve99r/VrgaoUALL0/e9/v//B/rfoAoBa7L777gMfv//++1u/FqhKASBL/a/FNjU1tWbNmi6uBYDy7bHHHgMff/jhh1u/FqhKASBLjzzySP+DO++8cxfXAkD5ltoAbN26tfVrgaoUALL0ox/9qP9B72oHQEMGvvnM1NTUjjvu2Pq1QFUKAFlavXr1iGsBAKhuqUm/5TM5UgDI0sDj/gNvDACA6pZ6w69ddtml9WuBqhQAsrTbbrv1P3jPPfd0cS0AlO+uu+4a+Pj69etbvxaoSgEgSwcccED/g3feeWcX1wJA+ZZ6vf8DDzyw9WuBqhQAsjTwCfe2227r4loAKN/Xvva1gY8/6UlPav1aoCoFgCw9+clP7n/wrrvu+uEPf9jF5QBQuK985Sv9D+67776OAJEjBYAsPfOZzxz4+Be/+MXWrwWA8l133XX9Dx555JFdXAtUpQCQpaWecz/zmc+0fi0AFO6+++67+eab+x8/9thju7gcqGpV5Y8AHdiwYcMee+xx3333LXr86quv/i//5b80+qn/7b/9t4teb3SnnXb64Ac/2OgnBaBDH/3oRwe+EdgJJ5zQxeVAVSu8eSqZ2rhx4yWXXLLowR122OHOO+/cZ599Gvqkt95661Of+tRFDx5yyCHf+MY3GvqMAAy0YsWK/gcbSjWbNm266KKLFj2455573n333d4JmBw5AkSuXvSiF/U/+Nhjj1188cXNfdJPfOIT/Q/2VwIAinH33Xdfeuml/Y+fccYZ0j+ZUgDI1caNGwc+8/7pn/5pc5/0yiuv7H/wGc94RnOfEYBuvfvd73700Uf7H/+1X/u1Li4HaqAAkKt99tnnxBNP7H/8i1/84tVXX93EZ3z44Yc/+clP9j9+3HHHNfHpAOjcD37wgz/5kz/pf/yYY4557nOf28UVQQ0UADL22te+duDj//k//+cmPt1555137733Lnpwxx13fMELXtDEpwOgc294wxvuv//+/sf/03/6T11cDtRDASBjJ5100lFHHdX/+Gc/+9kLL7yw9k/3nve8p//B448/fq+99qr9cwHQuSuuuOIv//Iv+x8/7rjjTj311C6uCOqhAJC33/u93xv4+G/91m99//vfr/ETXXTRRTfccEP/47/+679e42cBIBG33HLLr/7qr/Y/vsMOO7znPe8Z+BpEkAsFgLz98i//8sATOPfcc8+v/uqvPv7447V8lnvvvffss8/uf/zQQw89/fTTa/kUAKTj9ttvP+GEE+bm5vr/6E1vepM3ACZ3CgDZe/e73z3w5YA+9rGPveENb6j+8bdv3/6bv/mb3/ve9/r/6O1vf/sOO+xQ/VMAkI6bbrrp2GOP/eY3v9n/Rz//8z//lre8pYuLgjopAGRvw4YNb3/72wf+0f/4H//jTW96U8WPf9ZZZ11wwQX9j//iL/7ipk2bKn5wANKxffv29773vc95znO+853v9P/poYceOjMzY+5DAbwTMCXYvn37aaeddvnllw/80zPPPPPP//zP165dO+6H3bJly2//9m+///3v7/+jdevW3XjjjQcddNBE1wtAcu8EfNVVV73pTW+6/vrrB/7pfvvtd8011xx66KETf3xIhwJAIe6///5f+IVfGHif7vzY5o//+I9POeWU0T/gpz/96Ve96lW33HJL/x+tWrXqYx/72PHHH1/hegFIogB89atfveyyy/7qr/7qpptuWurvHHLIIZ/4xCe87zvFUAAox9133/285z3v61//+lJ/4Zhjjjn77LNPPfXU3Xbbbam/c//9919++eXvete7/v7v/37gX1i5cuW555478KUhAOi2AJx//vlD/pPHHnts27ZtW7ZsmZubu/POO2+55ZZ//Md/XPYl45773OdefPHF+++/f+VLhlQoABTl7rvvPu2005bK7vN22mmn5zznOc94xjOe+tSn7rHHHjvuuOPcE7773e9ed911N91005DXDtpxxx3PPffcl7/85c1cPgCjauGFOFeuXPn617/+bW9728CXmoB8KQCU5uGHH/6N3/iND37wg7V/5P322+/iiy8+7rjjav/IAKRWAH7u537uf//v/3300Uc3+lmgE14FiNKsWbPmAx/4wCWXXLJ+/foaP+yv/Mqv3HzzzdI/QPGOPfbYyy677O///u+lf0plA0CxtmzZ8u53v/ud73znD37wgyof54UvfOFb3/rW5zznOfVdGgDJbQA2bNhw+umnv+IVr9iwYUO9HxlSowBQuIcffviSSy75wAc+cPXVVz/66KOj/4c//dM//ZKXvOSVr3zl0572tCYvEICWCsDKlStXrVq18847r127ds8999x3330PPvjgww8//OlPf/qxxx673377NXOlkBwFgCi2bNly7bXXXnPNNV/96ldvueWW733vew8++OCWLVu2b9++Zs2atWvX7r///gcddNDhhx9+1FFHHXfccYccckjXlwwAUD8FAAAAAnETMAAABKIAAABAIAoAAAAEogAAAEAgCgAAAASiAAAAQCAKAAAABKIAAABAIAoAAAAEogAAAEAgK7q+AAC6sWnTpq4vAVIxOzvb9SVAe2wAAIKSeABiUgAAACAQBQAgLksAgIAUAAAACEQBAAjNEgAgGgUAAAACUQAAorMEAAhFAQAAgEAUAAAsAQACWdX1BQCQh3UbZ7q+BJjc3Obpri8BUmEDAMBISwD5CaAMCgAAAASiAADw/1gCAESgAAAAQCAKAAA/YQkAUDwFAAAAAlEAAPhnLAEAyqYAAABAIAoAAItZAgAUTAEAAIBAFAAABrAEACiVAgAAAIEoAAAMZgkAUCQFAAAAAlEAAFiSJQBAeRQAAAAIRAEAYBhLAIDCKAAAABCIAgDAMiwBAEqiAAAAQCAKAADLswQAKIYCAAAAgSgAAIzEEgCgDAoAAAAEogAAMCpLAIACKAAAABCIAgDAGCwBAHKnAAAAQCAKAADjsQQAyJoCAAAAgSgAAIzNEgAgXwoAAAAEogAAMAlLAIBMKQAAABCIAgDAhCwBAHKkAAAAQCAKAACTswQAyI4CAAAAgSgAAFRiCQCQFwUAAAACUQAAqMoSACAjCgAAAASiAABQA0sAgFwoAAAAEIgCAEA9LAEAsqAAAABAIAoAALWxBABInwIAAACBKAAA1MkSACBxCgAAAASiAABQM0sAgJQpAAAAEIgCAED9LAEAkrWq6wuARmzatKmJyAIAkDsFgFgRH2jN7Ozs8H+nc5un122cafGKAPgxBYAMyPoAAHVRAEiOuA/FsAQASJACQPckfgCA1igAdEPohyAsAQBSowDQHqEfAKBzCgDNEvoBSwCApCgANELuBwBIkwJAneR+YCBLAIB0KACUmfsPnVk38PFbp+davxYAgIQoAOSa+5eK+ECaLAEAEqEAkEHul/UBAOqiAJBi9Jf4oUiWAAApUABIIvdL/AAA7VAA6Cz6C/0QkCUAQOcUAFqN/kI/AEC3FAD+GbkfaJolAEC3FACaiv5CPwBAghQAao7+cj+wLEsAgA4pAKHVGP3lfgCALKzs+gLoxqYn1PKhDp1ZJ/0D45qdnR3+F+Y2T7d1LQCx2ACEU2Pur+XjAADQJhuAQOqa+hv5A7WwBADohA1AFNWjv9APAFAAG4DyVR/8G/kDDbEEAGifDUDJTP0BAFhEAShT9ZF/fdcCMIz3BABomQJQoCrpX/QHACibewCKUuW4v4P+QFfcCQDQJhuAclSJ/nVfCwAAibIBCD34N/UHEmEJANAaBSB7Bv8AAIxOAciYwT9QEksAgHa4ByBXE0f/Bq4FAIBs2ABEGfyb+gPpswQAaIECkBmDfwAAqlAAcmLwDxTPEgCgae4BKDn6N3MtAABkzAYgA9I/EIolAECjbABKS/+iPwAAQ9gAFPVqP9I/UAZLAIDm2AAkSvQHAKAJNgApkv4BLAEAGqIAJEf6BwCgOQpAxof+vcY/UDZLAIAmKACpMPgHAKAFCkASpH+AgSwBAGrnVYC6N+6xnyavBQCAwtkAdEz6BxjOEgCgXgpAl6R/AABapgBkkP692g8QnCUAQI0UgAzSf8PXAgBAIApAB6R/gHFZAgDUxasAtcqhfwAAumUD0B7pH6AKSwCAWigALZH+AQBIgQLQBukfoBaWAADVuQegcW75BQAgHTYAqZD+AUZhCQBQkQKQxPhf+gcAoB0KQIOkf4AmWAIAVKEANEX6BwAgQQpAI6R/gEZZAgBMzKsAdZz+b52eUwMIa9OmTcvGOIAJaIAwhALQ/ez/1uk52wCiGevNMWCg2dnZ4T9Ic5un122cafGK6ICgDxNQADpO/4fOrJsvAGoAQSz8Z2L8D4xF3IdaKABpnftXAyiYqT+1swSIQOiH2ikA3af/3hKgRw0gwj8Q439gKUI/NEoBSJcaQAFM/WmaJUAxhH5ojQKQxOGf/iVAjxpAkf8ujP+BeXI/tE8ByOMl/9UAcmHkT/ssAXIk90OHFIBU0v+QJUCPGkAZ0d/4HyIT/aFzCkB+b/fb6wmaAIkw9adzlgDpk/shHQpAs8bK6KMsARayECDH6G/8D9F0Ff0XVT4NBHoUgAZzTzvRXA2gE6b+pMYSIDWtBW7fVhiXApBW+h93CdCjBpBF9Df+hwgajf7iPlSnABQ1+FQDCPvDD5YABUd/3zWolwLQiCoRfOIlQI8aQJrR3/gfClZ79Bf6oTkKQK5H/5elBlALU3/yYgmQe/T33YEWKAAppv8hS4B3rJt549wYT7VqAK1F/+E/nMb/UKS60r/cD21SADKbg75xbvod6378LKkGkFT0H/dnEppjCZBR9PeNgE4oAHWqMWEveyeAGkA60X9Zxv9QkurRX+6Hbq3s+PNnIqmj/wtD/zvWzYyYwHpunZ6reJMxRdr0hNH//qKfPeN/krJs5/SeUBOr+KVbt3FG+ofO2QCkm/5Hfzkg2wDaPNs2buc0/ocyVI/+9V0LUIkCkKXenQALqQF0Ff2N/0mQOwESif6+yJAgBSDpwz8TvCeAGkAKU/8e438Im/5Ff0iWewCyOfq/yPCI794AajnoP8rPkvE/yXInQHWTfYkc9IfE2QBU0kL6r/LGwLYBdDL17zH+h3wZ/EPBFIDUX/h/3DsBaqwBmkAZGo3+xv8kzp0ALQ/+G7gWoH4KQAaHf6osASq+VZOFQNY6mfr3GP9DnPQv+kNeFIAJJZKJR1wC9KgBQbQT/Y3/yYIlwOhEfwhCAcjj8E8tS4AeNaBg3U79e4z/ITvSP8ThVYCSPvzT6BR2glcK8mJB0V7hZwjjfzLi5YCWNe5XwOv8QNYUgLF1lf4b+ryT5T81IPfo39Dgf57xPxSf/hu7FqANjgClfviniTsBajkR5FBQvj+x1aO/8T/ZcSfAQKI/xKQAjKfbsFvvnQCLqAF56Sr6L8v4H3Ih/UNYCkD24/9algA9akCpP6U1Rn/jfzJlCbCQ9A+RKQBjiJNu1YAEpRD9gYDpX/SH8qzo+gKySVfphNohp4CaiHoTj3vT+YotNPwMVZrHV5KK/sN/HtL8AsJY/6CKz7th0//w/+GevgjFBiD7wz9Nsw3oUFLRHyhA2PQPLORlQEeSVIodcjHNHc6e+AXjvWBom6/sWfGl/Zdl/E8BIr8nwOj/07zMP5TNBsD4fwy2AS0w9Qc6T/8NXwvQMRuA5SUYWztZAvTYBoSa+vcY/1OMgEsA6R9YKPoGwPh/YrYBNTL1B5oj/QOL2AAsI9mc2u0SoK5tgIVA4lP/HuN/ChNnCSD9A/1CbwAyeunPUrcBkRcCpv5A06R/YCAbgIwlsgSoZSYdahuQy9S/x/ifIhW/BJD+gaXE3QAY/zfENmAIU3+gHdI/MIQNQN5SWwL02Ab0j/zzmvr3GP9TsOKXAMuS/iGmoBsA4/922AZUeZkpU39gMiP2FukfwrIByF6yS4Dg24CJR/4pTP17jP8pXnlLAOkfWFbEDYDxfyfibANM/YGuSP/AKGwASpD+EiDINqCMqX+P8T9BFLMEkP6BEUXcAAyXy5g5a+VtA0z9gSxI/0DEDUCVoJayjJYAhW0DCpv69xj/E0oBS4BRrlD6B+bZANCxfLcBpv5AIqR/YCyxNgBl3/6b4xIg021AqVP/HuN/Asp3CZDshQHJsgEgIelvA0z9gRwZ/wMLrZgKo+zxf8+QWXheAbTK1mLIt3L4rmDICDBO9Df+J7Jl/6WnlqQd/qnra+XJjVBsAEhUOtuAONEfyIv0D0wm1j0AxY//c78ToN4APX9vQJXbA6qc9c80/Rv/E1xGdwKkcyVAdqJsAEp99c8IqqwCJlsIVP9pyTH6A+Ux/gdC3wMQ5AaA8u4EyG6JUfCX1/ifONK/E8Dhnwm4BwBibQCipf+CVd8GNCfr6A8URvoHhnAPQJkKuxMg8ZfST+16JmP8D7ncCeD0P1BRiA3AcMb/mUphG1BA7gfy4vAPUF35G4Cwt/+WvQTofPpextS/x/gf8loCDCH9A8uyAaAEbW4DSsr9QF6Sah1JXQwwlvI3AJHP/wRZArQ2lS9s6t9j/A/FLAHaHP9bNUC+Ct8AhD3/E1kT24Aicz+Ql2X7hkQOjCj0BqDs8f+yilwC1D6tL3XqH+THAIpZAiS4bVA5IF+FbwA4dGbdkDcFK16VbUDZuX9Ezv9ALmRxYHQlbwCc/1lWkOnvuFP84qf+0X4AIPclQJrj/3mKB+So5AIwXJzzP8P/l8aJgKPE+jjRf5RvvfE/5EIKB8YStwAAQPpLgJTH//PUD8hOsQXA+Z+FLAFYxPgfiiF/A+MqtgAMF+f8DwD5LgFyeenPRC4DGJFXAYpi+MsBvXFuOs7Zd4z/gfbNnt/xb5lNL7PuhqI3AM7/AJD7EiCX8f+IFyN/QzrKLAAM5E4AjP8BgIgFwA0AAGT6ngBpjv/nWQJALiIWgMgsAYIz/odcpP/qn0C+CiwAbgAAIMISIEGWAJCFAgvAcM7/WAKEZfwPucjr9l8gO+EKAABUYQkwnCUApE8BiMgSICDjfyiG8T9QUWkFwA0AAGS9BChggWAJAIkrrQAM5waAHkuAUIz/oRjG/0B1sQoAAKS8BChg/D/PEgBSpgDEZQkQhPE/AFBsAXADAAAFvxxQXud/LAEgWUUVgOHcANDPEqB4xv+QkWLO/wCJC1QAAKBe3hNgOEsASJMCEJ0lQMGM/6EkeZ3/AVKmAABA90uAUncFlgCQoHIKgDuAJ2YJUCTjfwCg8AIwnDuAAcj3ToCsz/9YAkBqohQAhrMEKIzxPwCwFAUAADpeApR6A0CPJQAkRQHg/7EEKIbxPxQm6/M/QIIUAACogfcEGM4SANKxMsJLALkDeESWAAUw/gcAQhQAAMh0CRBnM2AJAIlQABiDJUDifIOgPG4AAGqnAPDPOC5VNud/oGnuBBjOEgBSoAAwHjPmZPnWAACjUABYzBKgVMb/kOASIOBCwBIAOqcAMDaT5gT5pkCR3AAANKGEAuA1QGvni1Ye439okzsBhrMEgG6VUABon3lzUnw7AIDRKQAMZglQEuN/aJ8lwHCWANAhBYAJmTonwjcCABiLAsCSLAHKYPwPXbEEGM4SALqiADA5s+fO+RZAwbwEENAQBYBhLAFyZ/wP3fJvcDhLAOiEAkAlJtAd8sUHACagALAMS4B8GT1CCvxLHM4SANqnAFCVOXQnfNkBgKAFwNsAt8CXMUeGjpAO/x6HswSAlmVfAEiBaXTLfMEBgIkpAIzEEiAvxo2QGv8qh7MEgDYpANTDTLo1vtQQgTcBAJqjADAqS4BcGDRCmvzbHM4SAFqjAFAbk+kW+CIDABUpAIzBEiB9RoyQMv9Ch7MEgHYoANTJfLpRvrwAQHUrpop+HwAIxXCRsXj+hB7Pn4RiAwAAAIEoAFAI4ysAYBQKAAAABKIAQAmM/wGAESkAAEB07oknFAUASuBXFwAwIgUAAAACUQCgEJYAAMAoFAAAAAhk1VTRDp1Z1/UllObW6bnhf+Ed62amEvbGuelSL35+CeDlgKjLuo1J/3OYmpqa2zzsX8TMTOrXPz09XfDXf/b85K5/08uWeQqFOGwAqFPiATp3vrwAQHUKAHWO/+mcOwEAgOEUAGpjPt0CX2QAoCIFgFEZ/+fCEgAAGEIBoB4m063xpQYAqlAAGInxf14sASB3w19jB6AKBYAamEm3zBccCpD+C5UCpVIAWJ7xf44sAQCAMgvA8Lc9klxbYBrdCV92ACBoAaBpSlS+LAEAgH4KAJWYQ3fIFx8AmIACwDDG/7mzBAAAFlEAmJwJdOd8CwCAcSkALMn4vwyWAJApbwUANEQBYEJmz4nwjYB8eSsAoBMKAIMZ/5fEEgAA6FEAmISpc1J8OwCA0SkAAAAQSAkFwJsB1274F828OUHLflOcAgLC2vSy6U0vc0c1/MSqBf9/ACAhc5un1200c5mc3A/FbgCol/F/piwBIEdeCKghpv4whA0AAFAOuR+WZQPAP2P8nzVLACAyU38YkQ0AAKTLbQCjkPthLDYA/ITxfwEsASA7bgOowtQf4hYArwQKAKGI/hC9AFCd8X8xLAGAson+UJF7AAAgaW4D6JH7oRY2APyY8X9hLAEgL24DaGHqr0RBjw0AAFDy1F/0h6AbAPcBD2H8XyRLACjJ3OaIR19qmfpL/1DyBmB2dlagAYACmPpDo6JsAFiK8X/BLAEgI24DqPEVfqR/iLIBAICCFf9aQLW8wk/ZXyKoiw1AaMb/xbMEAOJM/aV/GFGgDcCt03OHzqzr+ioAYLCZmZnp6Vg3+5r6QyeK2gDMzs52fQk5Mf4PwhIAilHSawGZ+kOHAm0AAIDOmfpD54raADA64/9QLAEgF2W/FpCpPyQi1gbAbQAAZC3T1wIy9YeklLYBcBvAKIz/A7IEgFwUtgQw9YcExdoAAEDuclkCmPpDskrbALAs4/+wLAGA1pj6Q8rCFYDh8RcA0j8FVNLrgfYT/aFpBRYAtwFMzPi/eL7FQMpEf2hHgQWAISxAGM4pIEhEYbcCL0v0hzZFLABC8EBmw0H4RkMZijkFJPpD+yIWgLA0H0ZhCQC0Q/SHrpRZANwGMC5T4VB8uyELBd8KLPpDt8osAPQz/md0lgBAQ0R/SEHQAiANL2QeHJBvOmShsCWA6A+JKLYAOAW0kMLDuCwBIBdZdACDf0hKsQWAEcWZBL9xbvqNc9PV/04x4nzrIWu5vx6o6A8JilsA4gzFh/wvDRIBx431cWrA8B8ASwDIRZpLANEfklVyAXAKiCpRPk4NABKX3RJA9IfElVwAiDz+ryu+F18DLAGgDIksAUR/yMKqqcBunZ47dGZd11dBzZrI6/Mfs+zKBKRsZmZmejqJiL8UuR8yUvgGIPgpoGjj/6an9aVuAywBIAvJviSoqT9kJ/QGwBKgGG3mctsAIFlzm6fbzOJyP2Sq8A1AZEHG/11N5QvbBlgCQBaSuhtY+od8lV8Agp8CKlgKETyFawBI8G5gIGXlF4CYbwhQ9vg/tdid2vVMxhIAilkC6ADAcAoAOUk5aqd8bUBJkjoIBOQoRAFY9hRQYUuAIsf/dcXrpu/5zroGWAJAMSwBgOgFgKzVGP1HSf+13DSSdQ0A0ucgEFBFlAIQ51bgwsb/bUb/ntn/X8XPm2MHsASAkugAwEDR3wegxxsCpKZ6eq7+DZ3vAFVSrzcNAMK+NzCQrCgbgCDKGP9XPz8z7sh/uOrbgLxOBFkCQC4cBAImE6gARLsVOEepRf/INQDIgg4ATCBQAYgs/fF/ytE/YA1I/wcGGIsOAMQtAGUvATK9+Fyif8AasBSngCAp3hYAGFesAhBTstPcHKN/nBqQ7I8N0M9BIGAs4QpAqa8Hmtf4P/foH6cGLMUSAFKjAwCjC1cACkvS2c1xS4r+xdeA1H54gOp0AEABKEQWpaXU6F98DViKJQBkejOADgBELABl3wqc4AQ3QvQvtQYk8iMEjEgHAEYRsQAUJuW6Ei36l1oDlmIJAAnSAYBlBS0AEZYA3c5uI0f/wmqAJQBkRwcAhlu1zJ+TtgSLSvW0WkDuX6TXASYemc9/VRPM4ps2bSr1lbUggrnN0+s2JvfEAjQt6Aag+CVAJ0nR1L/phUBX24AEiwdQ17uD2QNAQHELQAHHl9OpKKJ/hBpQ8D8lKJIOACwlbgHIK2EnO68V/YPUAEsAyJEOAAwUtACMPrNMtgN0fmEVA+h87o8Z/fOtAUuxBIBk6QBAv6AFoGAtTGprif61XlH2sqgBlgCQKR0AWCRiARh3Wtn5rD2dSxL9G5VFDViKJQCkTAcAoheAgjU3oxX9W5NyDbAEgHzpAEDcAjDZnDKpJUDLFyP6dyLlGrAUSwAoqQOoAVCwcAWgYLVPZ0X/ziVYAywBIEgHsAqAgsUqAFUmlIksAdq5DNE/KQnWgKVYAkD6dAAgVgGoKJEO0OhcVvRPVjo1wBIAonUANQAKE6gADJ9Nzp4/M3v+TOQGIvpnVAMmbgItbAMsAaC8DmAVAIUJVAAKXgJUnMiK/jnqtgZYAkABdAAIK0oBWHb8v+j/E6d7iP6Ra8BUMywBIBczTxj97zsOBGWIUgAKXgJMPIutMgYW/cuoAVV+BiwBoBhWARCNArB46j/KEqD9DlDvZxT9i9RJDViKJQAU3wHUAMhXiAIwbhZJ+SBQxSms6F+8NmuAJQBE7gBWAZCvVVOxTZz1b52eyysNVzzrX+u10Lj5DjDBGH7+50Syh8gdYHp6etwOsG6jJw3ISfkbgMmOIiR1EGipTzRiSjP1D6uFbcCQH0KngCDUKsA2ADJSfgGYOOVndBCo9ug/n/tF/zIkdW8AUGoHUAMgI4UXgKZnkC0sASYb/1eM/hP8h4StAZYAUKRxXyG0RweA9BVeACoO+JM6CDQi0Z8hbAOAsVgFQJFKLgC1TB+77QBjjf9Ff7qqAZYAULDJOoAaACkL+ipABZzvX6jKPb51XwvZ8EpBQHOvDtTT6wBeKQjSUewGoMa5Y1dLgFHG/6b+1LINmGAhsOhnzxIAijfxXQHzLAQgHcUWgHrH/wneDCD6U69aagBQvCodQA2ARJR5BKiriWON7w42ZPzvwA+pnQvqHQpa6odz06ZNk911ABR2Imiec0HQrTILQBOn/2fPn9n0su6HFhNP/Ru4FopVpQYAQVSvAZoAdKXAI0DNjf9bOwhU42kiB35o/8WCBnInABSp4omgRUeDnA6CdhRYABp98Z8EbwZYiuhPgjUAKE/Fm4MX0QSgBaUdAUpkyljlZoDq/UHuJ53XDF3InQBQpIqngJaysAM4IAT1Kq0AtPDa/4ncDDCQ6E/6NQAoRkPRv58yAPUqqgC0lktG6QCTLQEmHv+L/mRRAywBoAytRf9+/aeDVAIIXQDafOvf5jrAuER/OmEbADF1GP2XstQNA4oBlF8A0gwiY3WAccf/oj851gBLAMhUgtF/OHcSQ/kFoM3x/1g3A9S+B5D7SY1tAJStlujfm8fL5dC5Ql4GtKvkMWK1GGW0P8rf8cqelPGCoaoC5GL6CRU/yLqNMwtP4yz6P4H2lb8BaGj83/IeQO4nF70OIOVD1uqd+g/5IwsBaF8JBWBIzmg6/dfVAYaM/0V/ijwX5E4ACBv9l/qbmgC0poQCUCrRnwK4PQAy0nL0H/IfKgPQqOwLQOfj/+pLgP7xv+hPhBpgCQDp6Db6D/9QygDULvsCkI5abgYQ/SmYbQAkKLXoP/yDKwNQi7wLQCLj/yodoDf+F/0JWAMsAaBD6Uf/4Z9OGYCgBSBBE3QA0Z+AbAOgQzlG/4VEf4hbAFIb/0/WAaR/IjP+h5aJ/p52IO8CkLKu3iQYAAYS/UV/yL4AJDv+79EBAEiB6C/6QyEFIAs6AAAdEv1FfyinAKQ//u/RAQBon+gv+kNpBaBIOgAA1Yn+oj8UWAAyGv+PtQTovSeAGgDABER/0R+KLQA5Gr0DWAUAMC7RX/SHkgtAduP/Hh0AgNqJ/qI/lF8AsqYDAFAX0V/0hxAFIN/x/6LrHP2WAB0AgEVEf9EfAhWAYox1W7AOAMA80V/0h1gFoIDx/0I6AACjE/1Ff4hYAMrj5UEBWJboL/pD0AJQ2Pi/x23BACxF9Bf9IXQBKJgOAMAior/oD9ELQKnj/4k7gONAAKUS/UV/aEEGBSCCsTqAVQBAeUR/0R9ak3oBKH7836MDAMQk+ov+0LLUC0AoY71NmONAALkT/UV/6ETSBSDO+H8hqwCA4on+oj90KOkCEJYOAFAq0V/0h86lWwBijv+rdADHgQBSJvqL/pCIdAsA494SYBUAkCbRX/SHpORXACKM/xeyCgDIl+gv+kOCVmV3/iegcTuAVQBA50R/0R+SlWgBWEq08X/F40BWAQDtE/1Ff0hcigXA+L/eVYAaANAO0V/0hyykWACWEnb8X7EDOBEE0DTRX/SHjCRXAIz/mzgOZBUA0BDRX/qH7CRXAJZi/F/XKkANAKiF6C/6Q6bSKgDG/y2sAtQAgIpEf9EfspZWAViK8X/tqwA3BgBMQPQX/aEACRUA4/+JWQUANE30F/2hGAkVgKUY/7ewClADAJYi+ov+UJhUCoDxf7erADUAoJ/oL/pDkVIpAEsx/m9zFaAGAMwT/UV/KFgSBcD4P6lVQK8GaAJAQKK/6A/FS6IALMX4v8NVwDwLASAO0V/0hyC6LwDG/w2pGP0XUgOAstUS/TtM/6I/kFkBWIrxfwrRfyHngoDyiP6iPwTUcQEw/s8i+i9iIQAUQPQX/SGsRDcAxv9pRv+FLASATIn+oj8E12UBMP7PNPovYiEA5EL0F/2BRDcAxv+tRf/5XwO1NDELASBlor/oD3RfAIz/U4j+C///dX1HNAEgKaK/6A+kvgEw/m8z+vc/XmMx6zUBZQDohOgv+gMJFQDj//aj/4i/A3p/rd7vkbUA0LKs39VL9AcCbQCM/zuM/gP/q9qrmrUAkAXRHyhYBwXA+D/x6N//ERr6likDQIJEf6B4CW0AjP+Tiv4DP1pz5W1hGdAHgE6I/kAQbRcA4/+8ov/AD97CN1EfANok+gOhpLIBMP5PPPoP/ESt1blFfWCeVgBUJ/oDAbVaAIz/c4/+S33eTr6zA1tBj3oADCf6A2ElsQGIPP7PNPon1QQmqAdAZKI/EFx7BSCdaJiIMqJ/+k0AoEf0B0hiAxBw/F9k9F9EEwCSIvoDtF0ApMA40X/INfsxANon+gOktQGIM/4PGP37KQNAm0R/gM4KQPCoJ/oPpAwAzRH9ARLdABQ//hf9J/tfqg8AExP9AbovADHDnOhf7//8mD9FwFhEf4DUNwCljv9F/yYM/LJoBcA80R8goQIQKqKJ/i0b/hUL9bMHYYn+ANlsAAob/4v+CfJVheJ1kv5Ff6AADRaACCNY0R8gCNEfKEYHG4Ayxv+iP0AQoj9QmKYKQMHjf9EfIAjRHyhS2xuArMf/oj9AEKI/ULBGCkB543/RHyAI0R8oXqsbgBzH/6I/QBCiPxBE/QWgmPG/6A8QhOgPhNLeBiCj8b/oDxCE6A8EVHMByH38L/oDBCH6A2G1tAFIf/wv+gMEIfoDwXXwRmCpEf0BghD9AWouAEud/0l2/C/6AwQh+gNE3wCI/gBBiP4ATRWAXMb/oj9AEKI/QPQNQJXo7xcAQEZEf4DGC0Di43/RHyAI0R9gWeVvACZO/34BAGRE9AdorwAkO/4X/QEiEP0BxlLmBkD0B4hA9AfooACkNv4X/QEiEP0BJlbOBkD0B4hA9AfosgAkMv4X/QEiEP0BapH3BkD0B4hA9AdIogB0O/4X/QEiEP0BapffBkD0B4hA9AdIqwB0Mv4X/QEiEP0BGpXHBkD0B4hA9AdItAC0Of4X/QEiEP0BWpPuBkD0B4hA9AdIvQC0MP4X/QEiEP0BOpHWBkD0B4iglujvyR+gjQLQ3Phf9AeIQPQH6Fz3GwDRHyAC0R8gvwJQ+/hf9AeIQPQHSEo3GwDRHyAC0R8g4wJQ1/hf9AeIQPQHSFZ7GwDRHyAC0R+ghAJQcfwv+gNEIPoDZKHZDYDoDxCB6A9QVAGYbPwv+gNEIPoDZKf+DYDoDxCB6A9QZgEYa/wv+gNEIPoDZK2eDYDoDxCB6A9QeAEYZfwv+gNEIPoDFGPyDYDoDxCB6A8QpQAMGf+L/gARiP4ARRp7AzBB+vfUDxAz/Xv+B8imACw1/h+Xp36AmDz/A4R7J2BP/QAxef4HyK8AVBz/e+oHiMnzP0C4DYCnfoCYPP8DZFwAJhv/e+oHiMnzP0C4DYCnfoCYPP8DlFAAxhr/e+oHiMnzP0C4DYCnfoCYPP8DFFUARhn/e+oHiMnzP0C4DYCnfoCYPP8DlFkAhoz/PfUDxOT5HyDcBsBTP0BMnv8BCi8A/eN/T/0AMXn+Bwi3AfDUDxCT53+AIFb1xv+e+gFi8vwPMBXJ/wfo9JHLZVUBfAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_1
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Cut the right side of the shape\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 8th action is Colorize the top layer of the original shape with the color green.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_497
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
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"text": "This is the original shape, with its image:.",
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_205
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 4th action is Colorize the top layer of the original shape with the color white.\nthe 5th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_60
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_166
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_271
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color red.\nthe 5th action is Colorize the top layer of the original shape with the color cyan.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 7th action is Colorize the top layer of the original shape with the color purple.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_463
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_211
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
},
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_329
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_55
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color cyan.\nthe 3th action is Colorize the top layer of the original shape with the color cyan.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color white.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_246
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_430
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 8th action is Colorize the top layer of the original shape with the color green.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_194
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Colorize the top layer of the original shape with the color yellow.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_92
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 2th action is Colorize the top layer of the original shape with the color white.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Cut the right side of the shape\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_44
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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{
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"text": "This is the original shape, with its image:.",
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color blue.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_403
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 8th action is Colorize the top layer of the original shape with the color white.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_407
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGcklEQVR4nO3YsQ3CQBQFQYxogIDS7CJxaQ5cAiQU4OSMpZ2Jv3QvXN00z/PnBvCzruv07w3AePcT3gAALkYAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIOhx9PD9fI1dAgy17Nu/JwAX4gcAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQY+jh8u+jV0CAJzGDwAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAwG2YL2qMCz4RR1G2AAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_312
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_108
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 7th action is Colorize the top layer of the original shape with the color cyan.\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
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{
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_260
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Colorize the top layer of the original shape with the color cyan.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_133
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color cyan.\nthe 6th action is Colorize the top layer of the original shape with the color white.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_74
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_449
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_315
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_300
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 2th action is Colorize the top layer of the original shape with the color blue.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 4th action is Colorize the top layer of the original shape with the color red.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color white.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_270
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color cyan.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_310
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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p/dEPoQoEnt9f0SBZkx5YTBG4BRnh76J4AYmPoDUI33AAAkRt8PQJMbAEsAgGiZ+gNQnw0AQAL0/QC0uAGwBACIh6k/AM2yAQCIVP2+f+PktHkNACNtACwBAJKe+m+cnPapzQAMZAMAkNvUv6FjAaCwDYAlAECXTP0B6IYNAEBgpv4AxLIBsAQAaJWpPwDdswEACMDUH4BINwCWAADNMvUHICwbAICOmPoDkMYGwBIAoCZTfwDiYQMA0CJTfwCS3ABYAgCMy9QfgDjZAAA0zNQfgBw2AJYAAEsy9QcgfjYAAA0w9Qcgww2AJQBAP1N/ANJiAwBQkak/APlvACwBAEz9AUiaDQDAGEz9AShuA2AJAJTJ1B+APNgAACzB1B+A0jcAlgBAIUz9AciPDQDAAKb+AOSq4gbAEgDIlak/AHmzAQD4J6b+AJSg+gbAEgDIhqk/AOWwAQCKZuoPQGlqbQAsAYB0mfoDUCYbAKA4pv4AlKzuBsASAEiIqT8A2AAARTD1B4DGNgCWAEDMTP0BYD4bACBbpv4A0NYGwBIAiIqpPwAsxgYAyIqpPwB0tAGwBADCMvUHgFHYAADJM/UHgDAbAEsAoGOm/gAwLhsAIEmm/gAQxQbAEgBom6k/ANRhAwAkw9QfAGLcAFgCAI0z9QeAptgAAFEz9QeABDYAlgBAfab+ANAGGwAgOqb+AJDeBsASAKjA1B8A2mYDAETB1B8Akt8AWAIAozD1B4AuJb8BECGIaghNaXVA8AhoZmbGcxYgug2AJQAA7Zl5UuijAEhM6wEAANrQG/+LAQDRBQBLAADaJgYAjMgGAIBU9b8HQAwAiCUAWAIA0BkxAGAIGwAAEjbkg4DEAIDAAcASAIDuiQEAC9gAAJC2Ub4NQAwACBMALAEACEgMAMjhm4CH8yWRLDD8td8Dhn76xSRMTU2N/pea+5ee70Cxuj4FyBIAgBjYBgDF8h4AAHJQbaIvBgAFChAALAEAiMpcDJAEgELYAACQifqn9YsBQAnCBABLAACiJQYAebMBAKCIJcDGyemxrkoMAHIVLABYAgDQpfNnN2ycnBYDAGwAACjrnQBiAFC4kAHAEgCALs1/WREDgGLZAABQ7scBiQFAgQIHAEsAALo08GVFDACKYgMAQIYqfCeAGAAUInwAsAQAoEvDX1bEACB74QMAAMT2xcBiAJCxKAKAJQAAXRrxZUUMALIURQAAgNiWAD1iAJCZWAKAJQAAXRr3ZUUMALIRSwAAgGiXAD1iAJCBiAKAJQAAXar8siIGAEmLKAAAQPxLgB4xAEhUXAHAEgCALtV/WREDgOTEFQAAIKElQI8YACQkugBgCQBAlxp8WREDgCREFwAAIMUlQI8YAEQuxgBgCQBAl9p4WREDgGjFGAAAIOklQI8YAEQo0gBgCQBAl1p9WakcAyQBoKAAAAB5LAF6xs0Ac8QAoKAAYAkAQJc6eFmpsAqYIwYARQQAAMhsCTBHDADCijoAWAIA0KUuX1bEACCUqAMAAGS5BOgRA4DuxR4AVDcAuhRktywGAF2KPQAAQN5LgB4xAOhGAgFAUQOgS2HfYCYGAG1LIAAAQCFLgB4xACg9AKhlAHQpkk+ZEwOAcgMAAJS2BOgRA4BCA4ASBkCBS4AeMQAoLgAAAGIAUFYAULkA6PIsoNiWAD1iAFBKAAAAesQAoIgAoGAB0LgUlwA9YgCQeQAAAPqJAUDOAUCdAqBxSS8BesQAIM8AAAAMIQYAGQYA5QmAxuWxBOgRA4CsAgAAMAoxAMgnAKhKADQusyVAjxgA5BAAAICxiAFA8gFAMQKgcbkuAZqKAV58IQMJBwAAoOMYYCEAGUg7AChAADQu+yVAjxgAZVoR+gBKNzMzM+SVBvLm8U/J8sgSMgCkKO0NQB4MUSiQhz2R62AJUHn0DlCTABDLa4x+iELMf6gb/wNA9wSAuIgBZMzDm7RYAgC5EgBifI3RJ5GZgQ9p438ACEIAiJcYQAY8jEmaJQCQJQEg9tcY/ROJGv7QNf4HgFAEgDSIAaTCd4WSGUsAID8CQCxGGYjqq4jZ6I9P438ACEgASI8JK7HxgCRvlgBAZnwTcESmpqbG6qLm/rFhKgFV6Ps9YqGazZtuC30IaTv7nKNCHwLEwgYgeYavBOGBR1FiWALoX4GmCABxqTwc1Y3RmToPNuN/AAhOAMiKGECrPMAomSUAkA0BIDr1R6S6NBrXyIPK+B8AYiAAZEsMoBEeSNBjCQDkQQBI7DVmenLNWFele6OycR88wxsX438AiIQAkJgNs1umJ9eIAcTW+m+cnG5qAgoxswQAMuB7AFL9ToC5DLBhdsvo1+l7A1jSuEFxxG8v8qgDgHjYAKRnftNvG0DYqX/v/xr/Uw5LACB1NgA5fDGwbQCVVUiDI079ezzMACAqNgBJGtjr2wbQ9l9/wdS/x/if0lgCAEmzAchkCdBjG0AMU/8ejysAiI0NQKqGt/i2AbQ99e8x/qdMlgBAumwAMlwC9NgGEGTq3+OBBAARsgFI2IidfeVtgIVAHtqY+vcY/1MySwAgUTYAmS8B6mwDLARSF2Tq3+NhAwBxsgFI27gNfYVtgLcHpKjVqX+P8T9YAgApsgEoaAnQYxuQsbBT/x6PEwCIlg1A8sbt43tsAzLTzdS/x/gf5lgCAMkRAJLR0ki1QgYQA2JT7c/RxuB/jvE/AMRMACh6CVBnFSAGJN361+z+jf9hPksAIC3eA1DuOwEaeWOA9waEUu2R0N7Uv8cjAQAiZwOQiZpLgB7bgMhV/oqG+lP/HuN/6GcJACTEBoABbAMiVDlfdTD1BwASYgOQmCG9dVNLgB7bgEhUvj8bnPqPOMuU/WAgSwAgKjYALME2ICBTf0hIq2/TAmiQDUB6ulwC9NgGlDz17zH+h8osAYB4CACMQQwotvUHRjE8BnsDPRAJASBJQZYAPWJAma2/8T9EwhIAqEkAoCIxoJzWHxidJQAQPwEgVWGXAE3FAEkgldbf+B+iYgkA1CEAEDIGlLwQSKX1B8ZlCQBETgBIWCRLgB4xINfW3/gfImQJAFQmANAwMSCn1h+oxhIAiJkAkLbYlgA9YkBTb3gI3vob/0O0LAGAagQAWiQG1Pktgrf+QB2WAEC0BIDkRbsEKDwG5NH6G/9D5CwBgAoEADpSTgzIo/UH6rMEAOIkAOQg/iVAITEgs9bf+B+SYAkAjEsAIID8YkBmrT/QFEsAIEICQCYSWgJkFgNybf2N/yEhlgDAWAQAAks3BuTa+gPNsgQAYiMA5CPFJUCiMSD71t/4H5JjCQCMTgAgIvHHgOxbf6ANlgBAVASArCS9BIg8BpTT+hv/Q6IsAYARCQBEKp4YUE7rD7THEgCIhwCQmzyWAD2VM0Cvca+TBGr+5ym2/sb/kDRLAGAUK0b6VxA6A9RJL3NN/OjNa/3tQYqtP9C2qampIeXl/NkNSgfQDRuADGW2BKh/RtDo4/z65w4lfc6P8T9kwBIAWJIAQFkxoD1Jt/5AN7wTAIiBAJCnLJcA0caAPFp/43/IhiUAMJwAQKpiiAF5tP5AlywBgOAEgGzlvQQIHgMya/2N/yEzlgDAEAIAtUSSJbqMAVG1/oaFkCJLgI6dfc5RAg/M52NAC/3IuQ2zW5rqmOcyQPCzcRr5wNDh4un7m20RjP8hSxsnp4c/u88+56jNm26byI5eH5YkAFDL9OSauYY77xgQbesf1YEBo/OdAM3S9MNYBIByNbgEmH+dmcWAqF6D2zgxwMkGkLHslwD6fqhGACh6yNTsEiCzGBBP67/Y63cHR+j8H2iPJUBl+n6oSQAoWhtLgPlXPvc/gieBcWNAPC+6bY/njf8he5ktAbT+0AifApS/4UPcRs6VH97ib5jdEsOHBY3ySUHxfMLP+bMbhr9m1z/OJbt/439om48DGutjfHT/0BQBgI5EEgPit2TrD1DOdwLo+6ENAkARgi8B5t+WGFC/9Tf+h2xYAgyh9YeWCAAEIAYsYOoPtCq5JYDBP7RKAChFPEuA+TdaeAyY6/vHbf2N/yEzlgBtt/6HTU8eNj3Z7HVC0nwKEIHF85mhXSrtFR0ILomPA2qq9dfuw3A2AAWJcAlQ4Dag5tk+xv+QJUuA+t3/3JjfsB9GYQNAROL56oA2FPISDkQr2iVAndZfuw8V2ACUJeYlQMYLgabe42v8DxkrdglQufs37IfKBADilUEM8PE+QFRi+zigajen9YeaBIDihF0CVJhhJxoDGv94H+N/yF5pS4AK3b/WHxrhPQB06vzZDXON7LivZKl8WFC1V+hq9wlAuu8EGLf71/dDg2wAStTBEmBJGyenM9sGVDvbp9r9UIHxPyShhCXAuJ/0b+oPjRMAaMWQUf38F7A8YkAjrf/wa+gmJACFCPhOAIN/iIEAUKgYlgAZxIDIp/49xv+QjTyWAKMw+If2CAAEXgI0EgO6TwLNtv7G/0DHgTzIEmD069T6Q6sEgHJFtQSo3+x2FgMqf7JnqD7e+B8yk+gSQPcP8RAAiGgJUP8MmfZiwFzfX7n1H/IbGf8D2S8BRrwqp/1ANwSAosW5BIgtBtT5Mq/uT/dfwPgfspTWEmD07r/9YwF+QgAgxiVAJDGgg9bf+B/Iewmg+4cICQCli3kJEDAGJD317zH+h4yltQQYTvcPHRMAiH0J0HEM6LL1N/4H8l4CjPLf6v6hewIAaSwBmooBw/9BBlP/HuN/yF7kSwDdP0RLACClJUCEDXflIzH+BzJeArT3XcJAfQIA6S0BIokB8YSQfsb/UIjIlwDDGf9DKAIAqS4BAjbi9W/R+B/IeAng5B+InABA2kuAjmNAzFP/HuN/KEqKSwDdP4QlAJDDEqCn1e68qSs3/gcyXgI4+x/iJwCQzxKgvSF9EoP/Ocb/UKB4lgBO/oEkCADk+QLWVMveeOsfz+s0kJC0lgBD6P4hBgIAY6i/BBhyFlAb6rTvQab+rb63GMhYDE9/J/9AKgQAIjo/pKUXsHFb+fZa/+Cv0M7/gXRlsAQw/odICADEtQRor0Uepa1vdeq/5K9m/A/UoQgAIxIAWMiQOFf+spC6mJcAS24GjP8hHgIABS0BAjL+BzqgFACjEAAYwKg4P/6mkIc4lwDG/5AWAYAqLAHGYvwPdEZBAJYkADCYgXFO/DUhJ3EuAYYw/ofYCABUZAkwIuN/oGMdlwUf/w/JEQBYlLFxHvwdIT8JLQGM/yFCAgDVWQIsyfgfCEJxAIYQABjG8Dh1/oKQq4SWAEBsBABqsQQYwvgfCCiGEuH8H4iTAMASjJDT5W8HeYtkCQAkRwCgLkuAgYz/geAUCmAgAYClGSSnyF8NSmAJAFQgABDFEiCzIVbbB5zcHQKEErBceAMAREsAIIoh0/CzgPLT9jjN+B/KYQkAjEsAoBmWAD3G/0BUFA1gAQGAUVkCNMX4H2iWJQAwFgGAxlgCGP8DcVI6gPkEAMZgCVCf8T9QwhLAO4AhZgIATSp8CWD8D0RLAQF6lpkXAgCFm5mZCX0I0B0bAAAAKIgAAAAABREAAACgIAIAAAAURAAAAErnM1EoigAAAAAFEQAAAKAgAgAAABREAAAAgIKsGP7jjZPTEyl/t3n87+kZ/tWD8d//3X9Zfc37ZPj1t3rlc2Y2V7+JqbOXvv74H/PJGf4kTfrbQ4c/WjyW2jb8wbN5020TcTv7nKOG/PSw6cmJ+Hxjw2zoQ4Ao2ACQksgTUduHVyc8AADMEQCIyCgT9NSNMsWvI+mBNADQAQGAZEQ+/p9jCQAUYvhJSk62gZgJAJAbSwAAYAgBgFi0+vbcLi15qDXPArIEAADqEACiVsI58bTBEgAAWIwAEJgP2sts/D/HEgAAiJYAAHmyBADC8j5giJYAQHiZjf/nWAIA2Yv/28qAgQQAyJYlAADQTwAgsCzH/3MsAQCACAkAkDNLACAgbwOAOAkAhJTx+H+OJQCQN28DgBQJALHzVQDUZAkAAMwnAIRX7FcBZD/+n2MJAJTMWUAQIQEA8mcJALTHWUCQHAGAMAoZ/8+xBABKZgkAsREAAACgIAIA0cls/N/NL7XkEsBZQEDAs4AsASAqAkAC8vsgoPx+o/pqngUEADAiASAKxX4QUJeT8vNnNywZPEb5N5VZAgAZswSAhAgAdG1Ih91SizxuW99eDBj+C1oCAAAdEADIWZ1WvtVtQEssAYCYWQJAJASANCTXiQYf/zfVvjceAywBgFz5QgBIhQAQC28DaEobk/uEtgGWAEDMLAEgBgIAWY3/W23Tm7pySwCg5CWADADBCQBkopshfRKrAEsAICAnAkH8BIBkxN93hhr/d9+U179FSwCgZJYAEJYAEBFvA0hrHh/zNsASAAjIiUAQOQGAJMf/8TTflY/EEgAonAwAoQgAKYmk5Q0rntY/8qOyBAAC8k4AiJkAQEhjjf8bOfO+pS8brnaErR4MQFhOBIJoCQBxyfJtAPVH4122/jObp5ecnXezDah/FpAlABCWDABxEgASE9t5JnWM0pGHmvp3FgMsAQBkAOiYAEC7KrfvMZzwE3wbYAkAFPJmABkAuiQARCfLs4D6DWnNY2j9u4wBlgBA3mQAiI0AkJ6EzgKqcKhRtf79MaBOEqj2q1kCAEVlADEAOiAAEMDAHr3m4L/tT/jpqRMDFvsdLQGA7I3+waAyALRNAIhRHmcBjd7N12n95/r+7hvoNmLAYiwBgDzIABAJASBJCZ0F1G9+s16/9Z8IqsEYEPx3AYiK04GgPQJApFJfAizZ1qfe+ne8DbAEAMr8hmAZANqwopVrpX3nz26Iqgke0cbJ6Zon+k/Eaq7Drtapz90nNe8cgIQywNnnHDVWBjhserLl44KC2ADQvCFdbDZT/zY+LGj4nWMJABS+CrANgKYIAPFa8iygQqbFqbT+jX97AEDexs0AYgA0RQCgYQ3GkkRb//ZiQAdLAIDIM4AYAPUJAFFL/a3AJbf+iW4DnAUEJJEBxACow5uA05boW4EXk9Pv0uy7hJs9jODHAFDnbcHz9TKAdwnD6GwAaFL27/ENvg3ooHe3BADSWgXMXwhYC8AoBIDYZf9W4HJa/3hOCkrlfCSgNDUzwMAwIA9AP6cA0Zhxo0iBff9ijfhYc/2psze03cHPzMwU+/4TIN3TgRYjA8ACNgAJyG8JUObUP6qFgCUAELPNm25rahsA9BMAMhE8A4x4AFr/RmKAdwIAJZABoCUCQBoyOB8jldY/+CfkdLYNsAQA4mcVAG0QAPIRcAkw/KZTaf17ps7eEH8MaOQIh9+EJQAQVQyQBKAp3gScjKmpqbQasrSa/sU67LBj8ki+OgAg47cIQ4FsALISZAnQf6PJjfyT2Ab0RxFLAKBMFgJQkwCQkvjfCZBT6x9bDAj+7QFAg6TrRsgAUI0AkJjYPhK0d3O5tv6RxwBLAKBYZ59zlHOBoBrvAcjQ+bMbuuzFs+/7I3xvgLcHQNLk6pr0/VCTDUB6ojoRqLTuP8JtQAfXo1kBsp/6K3QUxQYgTx0vAYoVyTYASIhGsxpTf2iQDUC2S4Dg3w1cjki2ATVZAgC5Tv2nJ9dMT65p7oggeTYAqUruawGyZxsALEnd7njqr++HgWwAcmYJ0L2ktwGWAEAkTP2hVQJAwpwIFO17rJOOAUBLpOhRaP2hAwJA/mSAcU39/+peT4IZwBIACEXrD53xHoC0eSdAq+YyQJ172BsDgDlq9RDO9YeO2QAkz4lAbau/DUjrjCBLAKAzpv4QhACQAxmgA6XFAIBWaf0hIAGgIDJAfYXEAOcsQbOszubT+kNwAkAmGvnsGkZUSAxYjFYGqEbrD5EQAPLhRKCO5R0DLAGgKTKz1h9iIwBkRQboXt4xYDEaGqCz1t+H/EDjBIASyQCNyzIGWAJAfSWn5aZaf90/NE4AyM2IbagM0IYsY8BiSm5rgOG0/hA5ASBDMkBYOcUASwCoo8CcrPWHJAgAeZIBgsspBiymwOYGmpJfg6v1h4QIANmSAWKQQQywBIBqyknIWn9IzorQB0B4589u2DipyWtRLwNUbgjmMkCEvfjMzIzvoIBxZdPp1u/7c7o3ICE2ADkbvTOzB0hiIRBqGxBh8IDIZT/+N/WHpAkAmZMBIpRoDCi20YFmpd7yav0hAwJA/mSAOKUVAywBYHS5pmKtP2RDACiCDBCttGJAae0ONC7R3lfrD5kRAEohA8QsiRhgCQAF5mGtP2RJACiIDBC5JGJAIU0PtCGtJjin1n/D7JYNs1tCHwVERAAoiwwQv5hjgCUAVE7CMfTBI9L6Q/YEgOKMlQHEgFBijgGLsQSA1Gn9oRACQInG6ixlgIAijAGWAJDl+F/rD0URAAolAyQkwhiwGEsASI7WHwokAJRr3AwgBoQVTwywBIA8xv9afyiWAFC0cRtKGSCSGFA5CXSwDbAEgPhp/aFwAkDpZIBEhY0BlgCQ6Phf6w8IAFRpJZ0OlE0MmGiHJQBESOsP9AgA/BOrgAJjQJ1VgCUApDL+1/oDCwgA1MoAYkDhMWAxlgAQA60/MJAAwL9QoYOUAYqNAZYAEO34X+sPDLFi2A8p0lz7ONYEdy4DbJzUDib8R/yn//DJDKCzh3TV7/uDp5eepvr+yiURcmUDQJOrANuA0rYBQ6KC11qyF9v439S/8W9QgVzZALCoqampCj2cbUBsbAMge6b+/fT9MIQNAK3MTqwCytkGWAJQpkjG/6b+/Uz9YUk2ACzNKiAbtgGQDVP/fvp+GJENAO1WVW8MKGEbYAlAacKO/039+5n6w1hsAOjiUxR6GcBCIB62AZAcU/8FNP1QjQBApx+m5ryg2PRePsf9my6IATObpxd7q8DMzIwXaXISZPyv9V9AVYE6BAC6e1dAjxiQTbSzDYC2af0X0PpDfQIAwb5XxXlB+cUASwCy1+X4P6fWv5HuXxmBpggAhP96RUkgpxgANCKn7l/rD7ERAAh/RlCPJJBfuuuxBCADkXz2/ygiOR6tP8RJACDGZlESyPUvC7RN6w8sSQAg6mZx/ncICAOp/2UtAchVJD13JIeh9Yf4CQAkMzMWBoKzDaBkMT/ytf7AWAQAkmwW+79dWCRI4i9rCUB+wjbfWn+gAgGASL9nqn4kmCMYtMQ2gKJE+FDX+gOVCQBk3i8uFgwI9We1BCAnQbpwrT9QkwBAngsBumQbQN7ieWxr/YFGCACEoWUs+W9qCUAeumzHtf5AgwQAQrIQyI+/KZkJ/kjW+gONEwCIgq6xtIWAJQCp66Av1/oDLREAiMv81wlhIAPO9SJpoR66Wn+gVQIA8RIG8o4BlgCkq70GXesPdEAAIA3CQAZsA0hLx49VrT/QGQGA9PS/uugpE40BlgCkqPFOXesPdEwAIAeLveoIBtGyDSBy3Tw4tf5AEAIAORt3V+A1rGPucJLTYMseQ/ev9YcyCQAA1U1NTdlj5KeEv6nWH0omAABAMjP7+rT+gAAAUIslQGYy/mvWbP31/ZANAQAAMh//a/2B+QQAgLosAbKR399R6w/0EwAAIMPxv9YfWIwAANAAS4AMZPMX1PoDwwkAAJDJ+F/rD4xCAABohiVA0lL/22n9gdEJAACQ8Phf6w+MSwAAaIwlQKIS/atp/YFqBAAASGz8r/UH6hAAAJpkCZCctP5eWn+gPgEAABIY/2v9gaYIAAANswRISBJ/Ka0/0CwBAAAiHf9r/YE2CAAAzbMESELMfyOtP9AeAQAAIhr/a/2BtgkAAK2wBIhchH8drT/QDQEAAAKP/7X+QJcEAIC2WAJEK56/i9Yf6J4AAAABxv9afyAUAQCgRZYAEQr+F9H6A2EJAADVbZycPn92Q+ijIJnxv9YfiMHy0AcAkDlNG/W7/6knNXo4QLlsAABqsQTI4/yfVsf/NVv/Ro8FQAAAaJ93AhSrcuuv7wfaIwAA1GUJkIoux/9afyBaAgBAFywByqH1ByInAAA0wBIgfh2M/7X+QBIEAICOWAJkTOsPJEQAAGiGJUCZ43+tP5AcAQCgO5YAOdH6A4kSAAAaYwlQyPhf6w8kTQAA6JQlQNK0/kAGBACAJlkC5Dr+1/oD2RAAALpmCZAWrT+QGQEAoGGWANmM/7X+QJYEAIAALAEip/UHMiYAADTPEiDd8b/WH8ieAAAQhiVAbLT+QCEEAIBWWAIkNP7X+gNFEQAAgrEECE7rDxRIAABoiyVAzON/rT9QLAEAICRLgO5p/YHCCQAALbIEiGr8r/UHmJiYWB76AABKp7nsRrXuf+pJLRwOQDA2AADtsgToUoPnU+n7gVzZAACEp9eMiqk/kDcbAIDWWQKkMv7X9wMlEAAAouDjgALS9wNFEQAAumAJ0LZq8UnrDxTIewAAYqEZ7ZIT/YFiZb4BsE9nLB4wtMoSIJInr74fKJwNAEBE9KatMvUHyH8DABAVS4BQ4399P0CPDQBAXLSqzTL1B1jABgCgU5YAnY3/9f0AA9kAAERH51qTqT/AEDYAAF2zBGhv/K/vB1iSDQBAjDSy4zL1BxiRDQBAAJYADY7/9f0AY7EBAIiUvnZJpv4AJW4ANk5Od3+jjcztfOlsEMN7hSAPJ4plCVCT1h+g0ADQMa0/0KWpqSkVA4BmCQCj0voDjbMEAKB7AsDStP5AQJYAADRLABhG6w+0zRIAgI4JAINp/YF4WAIA0CABYCGtP9AxSwAAuiQA/DOtPxAtSwAAmiIA/ITWHwjLEgCAzpQeALT+QCosAQBoRLkBQOsPRMUSAIBulBgAtP5AoiwBAKivrACg9QdiZgkAQAdKCQBafyAPlgAA1JR/AND6AwmxBACgbTkHAK0/kCVLAADqyDMAaP2BdFkCANCq3AKA1h8ogSUAAJXlEwC0/kA2LAEAaE8OAUDrDxTIEgCAEgOA1h/IlSUAAC1JNQBo/QEsAQAoIgBo/YFCWAIAUHoA0PoDLGAJAECeAUDrD5TJEgCA4gKA1h9gOEsAADIJAFp/AEsAAIoIAFp/gLFYAgCQagDQ+gP0swQAIMMAoPUHqMMSAIBkAoDWH2BJlgAANGX5RDjnz27Q/QM0ZWpqKvQhAJCAMBuApuZYWn+gHJYAACQZALT+AO3xTgAAIgoAWn+AmiwBAEgjAGj9ATpjCQBAyACg9QdoliUAAJEGAK0/QCiWAAB0GgC0/gCtsgQAIJYAoPUHiIQlAADtBgCtP0CXLAEACBYAtP4AcbIEAKDhAKD1BwjIEgCA7gKA1h8gCZYAANQNAFp/gHhYAgDQYgDQ+gOkyBIAgLEDgNYfIFqWAACMa/nwHzfyujLzpPrXA0AFU1NToQ8BgKy/CXg+fT9A2ywBAGhyA1CZqT9APCwBAGhxA6DvB+iYJQAAYTYApv4A0bIEAKDJDYC+HyAsSwAAOtoAmPoDpMISAIBaGwB9P/kxQIUeRR4gV1U2AKb+AImyBABgvA2Avh8AAIrYAJj6A+TBEgCgcEtvAPT9AABQxAbA1B8gS5YAACUbvAHQ9wMAQBEBQOsPUAJLAIBi/XMA0PoDAED2lu3YsSP0MQAAABF/ERgAAJAoAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgICtCHwB0Z9u2bTfccMN11133la985fbbb7/zzjsfeuihrVu3PvHEE6tWrVq9evUBBxxw0EEHHXnkkUcfffTxxx9/6KGHhj5kAICGLduxY0fT1wlx2bZt24c//OH3v//9V1999aOPPjr6f3j44Ye//OUvf9WrXnX44Ye3eYAAjO2iiy4a698vW7Zs+fLlO+2008qVK1etWrXnnnvuu+++a9euXbVqVWvHCJESAMjZww8//O53v/sd73jHli1b6lzP6aef/pa3vOXZz352c4cGQC3Lli1r5HoOPvjgdevWPec5z3nBC17w/Oc/f/fdd2/kaiFmAgDZuuiii37nd37nnnvuaeTali9f/vrXv/7tb3+71waAnALAfCtXrnzxi1/8ile84qUvfenOO+/c+PVDJAQAMvTDH/7w1a9+9eWXX974NT/jGc+4/PLLn/GMZzR+zQAEDwA9Bx100Hnnnfdbv/VbThAiSwIAufnSl750+umnf+Mb3xjyb376p3/62GOPPfLII/fbb7899tjjkUce+dGPfjQ7O3vLLbd89rOfnZ2dHfLf7rXXXh//+MePO+64Fo4dgCgCwJxDDjnkD//wD88666y2bwg6JgCQleuvv/6kk0564IEHBv704IMP/o3f+I1XvOIVT33qUxe7hh07dtxyyy3/9//+3/e///0PPfTQwH+z1157XXPNNc95znOaO3AAogsAc6ampt7znvfss88+3dwcdEAAIB//8A//cMIJJwzs/vfcc883v/nNv/3bvz36OZ3333//BRdc8M53vnPgc+Tggw++8cYbDzjggNpHDUBjAWB4V/PjH//48ccff/jhhx966KEtW7Z861vfuu222z73uc/97d/+7WKTozlPe9rTrrrqqiOOOKKJA4fwBAAycccdd/zsz/7sj370o/4f/ezP/uz09HS1D/W/+uqrX/nKVw58J/GJJ574N3/zN5UOFoAAAWAx27dv/+QnP/lnf/ZnH/7wh5944omB/2ZycvKjH/2o8z/JgwBADh5++OH169d/8Ytf7P/RGWecMT09vcsuu1S+8ltvvfUFL3jBwGjx3ve+9zWveU3lawYghgDQc8stt/zH//gfFxvu7L333tdcc42PhCYDAgA5ePWrX/0Xf/EX/Zeffvrpl1566YoVdb/x+nOf+9y/+Tf/Ztu2bQsuX7t27e2337569eqa1w9ADAFgzp/92Z+dd95527dv7//RAQcc8PnPf975n6RueegDgLquvvrqgd3/0UcffeGFF9bv/udOInrzm9/cf/ndd9/9nve8p/71AxCP173udZ/85Cf32muv/h99//vf37Bhw+OPPx7iuKAxNgCkbdu2bUceeeQ3v/nNBZfvtttuX/jCFw4//PCmbuixxx479thjb7nllgWXP+1pT/v617++fLksDZDJBmDOZz/72V/8xV98+OGH+3/0R3/0R294wxuauiHonq6FtL3nPe/p7/4nJibe9ra3Ndj9T0xM7LzzzhdccEH/5Xfcccf111/f4A0BEIPnPe9573vf+wb+6IILLrjzzjs7PyJojABAwh555JGNGzf2X37EEUece+65jd/cS17ykoMPPrj/8ssuu6zx2wIguLPOOuvss8/uv/yhhx4a+OoDqRAASNhf//Vf33333f2X/7f/9t922mmnxm9up512et3rXtd/+bXXXtv4bQEQg//+3//7qlWr+i9/3/veN/AFCJIgAJCw9773vf0XHnbYYS95yUtausVTTz21/8Kbb75569atLd0iAAEdcsgh/+k//af+yx999NFNmzaFOCJogABAqm699dbPfe5z/Ze//vWvb+8tuUcfffSaNWsWXPj4449/9atfbekWAQjr3//7f79y5cr+yz/wgQ+EOBxogABAqi6//PL+C5ctW3bWWWe1d6PLli074YQT+i//+te/3t6NAhDQXnvtNXD9++UnhTgiqKuBj0iHID7ykY/0X7h+/foDDzyw1ds966yz+j9mbo899mj1RgEI6Fd+5VcuvfTS/suvvvrqI488MsQRQS2+B4AkPfTQQ3vvvXf/V7G8+c1v/v3f//1ABwVAPt8DMN/27dsnJyf7vxPgpS996Yc+9KE2bhFa5RQgknTTTTcN/CLGF7zgBSEOB4Cc7bLLLs985jP7L//CF74Q4nCgLgGAJP3jP/7jwMuPOeaYzo8FgPwNfH351re+9eCDD4Y4HKhFACBJX/rSl/ovXLt27b777hvicAAoMQDs2LHjG9/4RojDgVoEAJL03e9+t//Cpz3taSGOBYD8rVu3buDl3/ve9zo/FqhLACCfAHDAAQeEOBYA8rf33nsPvPz73/9+58cCdQkAJOkHP/hB/4X9X9EFAI3Yc889B17+wAMPdH4sUJcAQJL6P4ttYmJi1apVIY4FgPzttddeAy9/5JFHOj8WqEsAIEmPPvpo/4W77rpriGMBIH+LbQC2bdvW+bFAXQIASfrxj3/cf6FvtQOgJQO/fGZiYmLnnXfu/FigLgGAJK1cuXLEtQAA1LfYpN/ymRQJACRp4On+A98YAAD1LfaFX7vttlvnxwJ1CQAkaY899ui/cMuWLSGOBYD83XPPPQMvX7t2befHAnUJACTpwAMP7L/w7rvvDnEsAORvsc/7P+iggzo/FqhLACBJAwvuHXfcEeJYAMjf1772tYGXP+UpT+n8WKAuAYAkPfWpT+2/8J577vnRj34U4nAAyNxXvvKV/gvXrFnjFCBSJACQpGc961kDL//iF7/Y+bEAkL8bbrih/8Kjjz46xLFAXQIASVqs5n7mM5/p/FgAyNz9999/66239l++fv36EIcDda2ofQ0QwLp16/baa6/7779/weXXXnvtf/2v/7XVm/53/+7fLfi80V122eUDH/hAqzcKQEAf/ehHB34R2IknnhjicKCuZb48lUS97GUvu+yyyxZcuNNOO91999377bdfSzf6jW984+lPf/qCCw899NBvfvObLd0iAAMtW7as/8KWupqpqalLLrlkwYV77733vffe65uASZFTgEjVi1/84v4LH3/88UsvvbS9G/3EJz7Rf2F/JAAgG/fee+/ll1/ef/mZZ56p+ydRAgCpetnLXjaw8v7pn/5pezd69dVX91/4zGc+s71bBCCsd73rXY899lj/5b/2a78W4nCgAQIAqdpvv/1OOumk/su/+MUvXnvttW3c4iOPPPLJT36y//Ljjz++jZsDILgf/vCHf/Inf9J/+XHHHfe85z0vxBFBAwQAEva6171u4OX/5b/8lzZu7sILL7zvvvsWXLjzzju/8IUvbOPmAAjujW984wMPPNB/+X/+z/85xOFAMwQAEnbyyScfc8wx/Zd/9rOfvfjiixu/uXe/+939F55wwgn77LNP47cFQHBXXXXVX/7lX/Zffvzxx5922mkhjgiaIQCQtt/7vd8bePlv/dZv/eAHP2jwhi655JKbbrqp//Jf//Vfb/BWAIjE7bff/qu/+qv9l++0007vfve7B34GEaRCACBtv/zLvzzwDJwtW7b86q/+6hNPPNHIrdx3333nnXde/+WHHXbYGWec0chNABCPO++888QTT5ydne3/0Zve9CZfAEzqBACS9653vWvgxwF97GMfe+Mb31j/+nfs2PGbv/mb3//+9/t/9Pa3v32nnXaqfxMAxOOWW25Zv379t771rf4f/fzP//xb3vKWEAcFTRIASN66deve/va3D/zR//yf//NNb3pTzes/99xzL7roov7Lf/EXf3FqaqrmlQMQjx07drznPe957nOf+93vfrf/p4cddtj09LS5DxnwTcDkYMeOHaeffvqVV1458KdnnXXWn//5n69evXrcq926detv//Zvv+997+v/0eTk5M0333zwwQdXOl4Aovsm4GuuueZNb3rTjTfeOPCn+++//3XXXXfYYYdVvn6IhwBAJh544IFf+IVfGPg+3bmxzR//8R+feuqpo1/hpz/96Ve/+tW33357/49WrFjxsY997IQTTqhxvABEEQC++tWvXnHFFX/1V391yy23LPZvDj300E984hO+951sCADk4957733+85//9a9/fbF/cNxxx5133nmnnXbaHnvssdi/eeCBB6688sp3vvOdf//3fz/wHyxfvnzTpk0DPxoCgLABYPPmzUP+k8cff3z79u1bt26dnZ29++67b7/99n/8x39c8iPjnve851166aUHHHBA7UOGWAgAZOXee+89/fTTF+vd5+yyyy7Pfe5zn/nMZz796U/fa6+9dt5559knfe9737vhhhtuueWWIZ8dtPPOO2/atOkVr3hFO4cPwKg6+CDO5cuXv+ENb3jb29428KMmIF0CALl55JFHfuM3fuMDH/hA49e8//77X3rppccff3zj1wxAbAHg537u5/7P//k/xx57bKu3AkH4FCBys2rVqve///2XXXbZ2rVrG7zaX/mVX7n11lt1/wDZW79+/RVXXPH3f//3un9yZQNAtrZu3fqud73rHe94xw9/+MM61/OiF73orW9963Of+9zmDg2A6DYA69atO+OMM175yleuW7eu2WuG2AgAZO6RRx657LLL3v/+91977bWPPfbY6P/hT//0T7/0pS991ate9YxnPKPNAwSgowCwfPnyFStW7LrrrqtXr957773XrFlzyCGHHHHEEUcdddT69ev333//do4UoiMAUIqtW7def/3111133Ve/+tXbb7/9+9///kMPPbR169YdO3asWrVq9erVBxxwwMEHH3zEEUccc8wxxx9//KGHHhr6kAEAmicAAABAQbwJGAAACiIAAABAQQQAAAAoiAAAAAAFEQAAAKAgAgAAABREAAAAgIIIAAAAUBABAAAACiIAAABAQZZNTU2FPgaIxczMTOhDgO6o/wBlWq7jASjN1JNCHwUAYawIdLsABKDvB+An7wGwBADInqk/AHNsAAAyp+8HYMCnAFkCAOTH1B+AfjYAABnS9wOw9PcAWAIAZMDUH4DhbAAAMqHvB2DsbwK2BABIkak/AC1uALzGkDQpl8y0V5NVe4qq/x7wFPWYXz5ue6R/AoiBqT8A1XgPAEBi9P0A1LFwA2AJABAtU38A6rMBAEiAvh+AFjcAlgAA8TD1B6CLAABABq2/5ADAGAHAEgAg6dZf9w/AQN4DABCR+l27vh+A6qcAWQIAdMbUH4Bu2AAABGbqD0BEbwK2BABoj6k/AN2zAQAIwNQfgHg/BtQSAKBBpv4AhGUDANARU38AkvkiMEsAgDpM/QGIhw0AQItM/QFIcgNgCQAwLlN/AOJkAwDQMFN/AHLYAFgCACzJ1B+A+NkAADTA1B+ADDcAlgAA/Uz9AUiLDQBARab+AOS/AbAEADD1ByBpNgAAYzD1B6C4DYAlAFAmU38A8mADALAEU38ASt8AWAIAhTD1ByA/NgAAA5j6A5CrihsASwAgV6b+AOTNBgDgn5j6A1CC6hsASwAgG6b+AJTDBgAomqk/AKWptQGwBADSZeoPQJlsAIDimPoDULK6GwBLACAhpv4AYAMAFMHUHwAa2wBYAgAxM/UHgPlsAIBsmfoDQFsbAEsAICqm/gCwGBsAICum/gDQ0QbAEgAIy9QfAEZhAwAkz9QfAMJsACwBgI6Z+gPAuGwAgCSZ+gNAFBsASwCgbab+AFCHDQCQDFN/AIhxA2AJADTO1B8AmmIDAETN1B8AEtgAWAIA9Zn6A0AbbACA6Jj6A0B6GwBLAKACU38AaJsNABAFU38ASH4DYAkAjMLUHwC6ZANAnmTLJKQ+9Z+ZmRE8IDbqPx2YSbz+rwh+B6V+DxKKEp+0DFr/gLcOhfMEJKCZLB5+NgAkII8nG0117fG0/oYX0Db1n3jMZFT/uwgAlgCMRbnPUmatP9AGzzLiNJPdI9MGgPDye15RQutvbAH1qf9EbibT+t9RALAEYAFFvwS5tv5AHZ5WJGEm6weqDQDdyfu5RFGtv4EFjEX9JyEzBdT/7gKAJUCZFP3SZN/6AyPyVCI5M8U8aG0AaEU5TyEKbP2NKmAI9Z8UzRRW/zsNAJYA2VP3y1RO6w8sxpOIRM0U+dC1ASDPJ8/GyemBl58/u6HzY8lZ6q1/hYeuIQXMp/6TqJmy63/XAcASICdh6/5iJZ5uFNj6Az3qP+maUf9tAEjimaPWR6Xk1t94gsKp/yRN/Q8ZACwB0tVZ6Vfx41T/ielEf0iU+k/S1P8FbACI4mmj4kdO6x/8V4Ag1H9Sp/5HFAAsAVLRaulX9JOg9Ycyqf+kTv0fwgaATp82in5CSmv9pyfXbJjdsthPjSQoh/pP6tT/eAOAJUCc1H3KbP0nJiaGVH8ogfpPBtT/EdkA0FbpV/RTVGbrvyTDCPKm/pMB9T+ZAGAJkGXpV/cTVXjrX+D4B9R/8qD+V2ADULQGS7+6n67CW/8lGUOQJfWfDKj/qQYAS4BQlH60/oWPfyiW+k8G1P+abACK01TpV/eTpvUfkQEEOVH/yYD6n0kAsATojNKP1r9fseMfiqL+kwH1P6sAQCrVX91PndZ/XEYP5EH9J3Xqf54BwBKgVUo/Wv/FlDz+oQTqP6lT/3MOALRE6UfrX5mhA0lT/0md+l9EALAEiKr0q/sZ0PovqfDxD7lS/0md+l9QACCS6q/0Z0DrX59xA4lS/0ma+l9iALAEqE/pL1zSrX+FR2+d0m/8Q2bUf9Kl/hcdAAhV/ZX+DGj9G2TQQHLUfxKl/ocSVwCwBKhG6S+Z1r8C4x+yof6TKPU/rLgCABWo/sXS+rfBiIGEqP+kSP2PQXQBwBJgdEp/sbT+dRj/kAH1nxSp//GILgDQavVX+lOn9W+V4QJJUP9JjvofmxgDgCXAcEp/mbT+jTD+IWnqP8lR/+MUYwBgCNW/QFr/bpQ8ViAJ6j9pUf9jFmkAsARo6rmk9CdN698s4x/Spf6TEPU/fpEGABZQ+ktTWusfcPAzp8CBAqlQ/0mI+p+KeAOAJUCP6l8UrX9LjH9IkfpPKtT/tMQbAKj2jFL606X1D6WQUQLJUf9JgvqfoqgDQOFLAIOfcmj922b8Q1rUf5Kg/qcr6gBQMoOfQmj9g8t4iECi1H/ip/6nLvYAUOYSQPUvgda/M8Y/JET9J3Lqfx5iDwAFUv2zp/WPR37jA5Km/hMz9T8nCQSAcpYASn/2tP7dM/4hCeo/MVP/85NAACiE6p83rX+E8hgckAH1n2ip/7lKIwBkvwRQ/TOm9Q/I+If4qf/ESf3PWxoBIG9jPceU/oRo/WOW9MiAbKj/REj9L0EyASDXJYDqn6V0W/9qdT/O0m/8Q+TUf6Ki/hclmQCQJdU/P1p/YBTqP/FQ/wuUUgDIbAkw+vNN6U+C1j+h8U9ChYIsqf9EQv0vVkoBICeqf060/sDo1H9ioP4XLrEAkMcSQPXPhtY/TsY/REv9Jzj1n/QCQOqc9JkNrT8wFvWf4NR/Eg4A6S4BVP88aP0jZ/xDhNR/wlL/1f/kA0CiVP8MaP2BCtR/AlL/yScAJLcEUP1Tp/VPhfEPsVH/CUX9n0/9zyEApMVbvpKm9QcqU/8JQv0n2wCQ3BJgSap/bLT+yTH+IVHqP01R/wdS//MJAJk9FVX/qGj9gfrUf7qk/lNKAIh/CaD6J0frny7jH6Ki/tMZ9V/9LysARE71L43WH5ij/tMN9Z9CA0C0SwDVvyha/+CMf4iH+k8H1P8e9b/EAJBB9T9/dkP7R0RbtP41bZjdEtshQR3qP21T/2lE8gEgtiXAuLOfjZPTXgNSpPVvdWbT4FUZ/9AZ9Z9Wqf/jXpX6n3MAiIrNbwm0/vGUfoiH+k971H8al0MAiGQJULn6GwKlQusfYek3/iEG6j8tUf8rX6f6n38AiIHZT95ifit5saUfIqH+0zj1n7ZlEgAiWQJUZggULa1/zKXf+IcMqP/Mp/43cuXqfykBICzjnyxp/Wsy9aEE6j9NUf/pUj4BINQSoKnqbwgUD61/EqXf+Ifg1H8aof43eyvqf1kBIAizn8xo/Wsy9aEc6j/1qf+EklUA6HgJ0Hj1NwQqjdLf0s0Z/9A29Z+a1P+Wbk79LzEARKjx2c/mTbc1e4WlOfucoyYioPRD9hqv/5YJNUUSsdR/YrB8Ii9LPq/qPPHGvZ4KxXrJ/ySS/pXKZp5U7b+dnlwTVfXfMLslSPU3/iGsUPU/kv6VytT/Rm53yE/V/9HZAERU/cmbqQ9kQP2nAvWf2OS2AehgCdDUDmExlgD5MfVp9gCG/NT4h1YFr/+WAMlR/5s9gCE/Vf/HYgPQCuMf5pj6QGnUf+ao/8Qsww1Aq0uAbpa/lgAZMPVpg/EPAUVS/y0B4qf+t0H9b5YNwBic+skoTH3m27zpNnmVDKj/jEL9n8+H28Yszw1AG0uAtk/9XMASoLSpT2zVv/7UZ/Om25r91FrjH0KJrf5rqiKk/s+3cXK62Tys/jfOBqBJxj/FqtkfxFb6a16Db6ugQOp/sdT/+TwRUpFzAGjwi4GDLH+X3J2dfc5ROq3glP752ntAGv8QSpz1//zZDTqt4NT/+dp7QKr/bcg5ADTFqZ8MpPTPJ4uSJfWfgdT/+TwFUpR5AGhwCRCEJUCclP75OngEGv9QIEuAOKn/83XwCFT/W5J5AKjP+If5lP75hE/ypv4zn/o/n0d+6vIPAHWWADFUf0uAPD4DJLPS3+VDzviHIJKo/5YAHVD/F+jyIaf+tyf/ANAqlTd7Sv8C0ibMUf+zp/4v4DGfkyICQLUlQMcf/DyEJUAQSv8CQR5jxj8EkVD9twRog/q/QJDHmPrfqiICQKLLX0JR+hcQLymK+l8y9X8BD/VclRIAGv84oI6fEpYA3VD6Fwj7oDL+IU6x1X9LgEao/wuEfVCp/20rJQAkuvwlIZmVfnmSMqn/VJBZ/ZcnS7B8ohhLlvW5fxDt8nfJGz37nKO6Ohb+henJNfFU/w2zW2pW/82bbouh+zf+oXvp1v/hKwLak1n93zg5HUP3r/53wAZgbDE8N4hEPHXf1B86oP6Ta/332C5NQRuA0ZcA0bIEiEdmU59Ipv49xj90L/X6bwnQmczqfyRT/x71vxs2AOOJ6klCEPHUfVN/6JL6T2b130O6ZGVtAOKf8SzJEiCgzKY+sU39e4x/6F4SLw2WAAFlVv9jm/r3qP+dsQEYQ5zPFjoQVd2vfyVx9v0QM/W/WJnVf49kCt0AVJ70xPOcsQQoc+pTf+QT89S/2Vc4aPZFIaH6bwnQoMzqf7RT/x71v0s2ADBYJHXf1H8++1/KPPmHjmVW/yPv+0ek/jerxA1AhYof25PHEqBVmU194p/69xj/EKHk6r8lQB2Z1f/4p/496n/HbADgn0VS98uc+i/5Kxv/0Djjf3Kt/6n0/XPU/+4VugEYq+7H+SyyBMhVaVN/iFmi9d8SIFGlTf0JyAYAYlHg1L/H+IfuGf8TjwKn/j3qfxDlbgBGrP4xP50sAbJh6g8RSrr+WwKkwtSfIIreACyZKT2daFvJU/8e4x+6l9BHf5Krkqf+Pep/KEVvADJgCZAuU3+gDkuAdJn6E1y5GwDjf0Ix9Z/P+IfuGf8Tiqn/fOp/QOUGgGxsnJwePuY5+5yjsmkWU9fIyL+hYwHyr//nz27IpllMXSMj/4aOBUoNAMb/dEzrX43xD40z/qdjWv9q1P9WeQ9ADrwTIO9zPZ3oDyzGOwHyrv9O9KclJW4AjP/phql/TcY/NM74n26Y+tek/rfNBiATlgBRMfUHOmMJEBVTf5JQ4gZgOM866jD1b4rxD91T/6nD1L8p6n8HitsAZPyosgQIy9QfMvj290RZAoRl6k9ybACgLlP/xmUc1IGcmPo3Tv3vRlkbgOzf/msJ0DFTf0hF9m//tQTomKk/SbMBgCpM/dtj/APEzNS/Pep/ZwraAGQ//p9jCdA2U39ITvbj/zmWAG0z9ScbNgAwKlP/Dhj/ABEy9e+A+t+lgjYA5TwzLQEaZ+oPGSuq/lsCjMvUnyyVsgEQK6nG1L9Lnqe0IeNP/6RVpv5dUv87ZgOQJ0uA+kz9gRRZAtRn6k/2itgAFPL2X5pi6h+E8Q9tKOTtvzTF1D8I9b97NgDZsgSowNQfyIAlQAWm/hSliA3AcJ6uNELfX4fxD0Go/zTCA6kO9T+I/DcAJT+wLAG6YeoPcSr57b+WAN0w9SdRNgDUcvY5R5Xc+wb/3fO4/0tO6UAH2kg7+v5GqP+hlB4Asn8Cb5ycHl746neQc2uEDNrQsQT/fW1voCb1//zZDVneCW0vN7K80yhN5gFAsmzb5k23zXWi5cSA4L/j/NY/+MHU50lKS0o+/6dAnZ3RpPtvkPofUOYBYLhCnsYdLAHmX1UeXelAwX8vU39oivqfxxKg+3cy9G4x6fsNig4ANLsEyDgGhP1dFuv7c7qHAUYXwzuYJQGSlnMAsFoKsgSYf50Z9Klxtv7AcM7/yXUJEEPrP/CQEroPIfMAMJznaqtLgAwWApG3/sndnxAP9T85Efb9C1gIkJb8vweASL4T4Oxzjkplnh32c/0TuqOAJCT9nQDnz26I+fAyOGDKlO0GwPk/US0BUtkGRD7174n2DoQYOP8nG+l20mmdWEWBCt0AlPm0DL4EmH9DhtzzuUOgM+p/Eq12BnP0DH4FMpbtBoBolwCpbAM6UK3pL/keA7LXRtN82PTkxMTENzbMLvlvlvxn4/IWYeKUZwBw/k9UHwc0XJkxwLwfWuL8n6Q/Dqip7r/Xzdf/bxvJAzHct5B/ACCVJUCBMaBm61/CXQSUqWb3X6fpH/Fq64QBGYColBgACn8GRrgEmH/TGbe5pv4QnPof5xKgTuvfUt8//LaqJQGnAxGPQt8ETHsa6d0ze1NsU79OlrkIKFzl7v+w6ckuu/+mbto7g4lBhgHAGwAS+jig7GNABr8CJMQbAJL7OKBqNxew9W/kMGQAgsswAAxn9daBIYPqCrUy0R66wmEPv3OM/6Em9T82FfrgSFr/+ockAxBWcQGAsEuAb2yYrVYrU4kBc8dZofU/bHqy2c+eA4h5CTDurUTY+tc8PBmAgEp8EzAxGOVTmdP6sKBq+STm1zOASFr/iUxf2rwtmFBy2wB4A0AkS4AhPfr8ypjHNqDa8Sz43Ye/YMSZeSAq3gCQxBIg4+6/xyqA+JW1ARCy45TuNsDUH1Kh/icn6VJZ7XUNOpPbBoDklgCNbAO6Xwg0MvXvMf4HSlgCjH6dSXf/FX4LSwA6JgAQl8pFv7MYUPmG8ng9A6imtO5/jgxAnLIKAN4AkPoSoP5HPbQXA+qsGob/Rsb/UJ83AES+BBjxqiL/qJ9qRv+lZAA6U9B7AJwAWs4JlM2+PaBOosjvlQxSpP6HNXr3P5GvET/r+fzZDR6udCCrDQDZLAEi2QbUuYYRj9z4H8h7CaD777EHIB4FbQBIV/fbAFN/gM6UUzZ95yORsAEg9iVAx9uADqb+Pcb/QN5LgFH+23K6/9F/X0sA2pZPAPAO4ELUjAE1/0FRb1yDVHgHcJx0/4uRAQgunwAwnLfU5LEEiLDhrnwkxv/QDfU/yBJA/1qf+5D2lBIAyFLYGBBPCAFIUckltOTfnRgIAKS6BAjYiNe/ReN/IOMlgJN/RuFEIAISAMhENzHA1B+gPoV0jvuBUAQAclgCdFNMm7py438g4yWAoXWz3J+0YXkJHwHkHWBFaWNIb/APiX4EkPrfMSf/jMuJQASRSQAglSXAEM1+N0pTLXvjrb+vgAFK/mJg3X8/9wndEwDoVMfnt9Rp34NM/Z3/A6TLoLo97luaJQCQ7RKgcivfXutv/A+UvAQw6l6Me4aOCQBMRDXkbq9FHqWtb3Xqv+SvZvwPAHRAACCuJQAAKS4BltwMGHLXvH+cBUSDBAAKWgIEZPwPAEQihwDgM0BbYgkARM5ngEayBDD+b4QlAJ3JIQCQoqKWAMb/AEA8BACGsQQAKFODHwdk/D869xXdEAAIppAlgPE/kDfnpXTJvU0jBACWYAkAUKZGlgBG2uNyj9EBAYCQsl8CGP8DALERAFiaJQBAmVr9YmCqcZ9TnwBAYBkvAYz/gcI5m6Ua9xttEwAYiSUAQJl8nQLkRwAgvCyXAMb/AECckg8Avga4M5YAQFR8DXBn3Jmx8TYASg8AlCC5JUByBwzQOCey1+Heo1UCAFEsAUo7H6a03xdInSUA5EQAIA0JzdQTOlQAoEACAOOxBKivnN8UyIklAGRDACAZSUzWkzhIAKBkAgBjswSoo4TfEcjV6EsA72Gtb/h96IOAqEMAICWRz9cjPzwAgImJiWXDP0cfACB7ca4szJVoyYq2rhgAIBFabYriFCAAACiIAAAAAAURAAAAoCACAAAAFEQAAACAgggAAABQEAEAAAAKIgAAAEBBlvgiMN8T3LaZmZkhP9286baJwpx9zlGtflnj8K96afXK6/xNl7xbNk5OT9R2/uyGJf9NtZow/HE+yj+gDcP/mup/24Y/7Bt5UrdqeMXwxbqdibz+E2eR8U3ApCTOV5Sew6YnQ726nD+7of5rwMbJ6VFeA9owNTUlAwBhRfgSM8prSur1nyCcAkRElpxzF/s7xrMLqtammxsBpM6YJicCAMmIcDYT1UE2MrwJeNaBkABpGV4usjzZpmOj34ep13+6JwBAGiwBAAjLEiAbAgBpnBuTxPh/xENt70yn1IdAQgJAmfWfjgkAkAxLAADCsgTIgwBAFLIZ/8+xBKhMSAAos/7TJQEAUmIJAKTC+4BzvfcsATIgABBeZuP/OZYAlQkJkArT4tikXv/pjAAAibEEACAsS4DUCQAEluX4f44lQGVCAkCZ9Z9uCACQHksAIAkxn8gesyTuN0uApAkAhJTx+H+OJUBlQgIkwag4QqnXfzogAECSLAEAyhRPa24JkC4BgGCyH//PsQSoTEiADCRxNkt+91jq9Z+2CQCQKksAIAbaxO7v7Xjuc0uARAkAhFHI+H+OJUBlQgJkwBIgyH2Vev2nVQIAJMwSAKBM8bTmlgApEgCITmbj/+C/VOpDICEB4rdkibAEGMWS99K4pTj1+k97BAACaO+MlwLvE0sAgDLF05pbAiRHAKCUSfk3NswuOVwZ5d9UZglQmZAA8bMEiG38n0f9pyUCABGNultqkcdt69uLAcN/QUsAABJtzS0B0iIAkLM6rXyr24DupT4EEhIgAzkV1YTumdTrP20QAMhz/N9U+954DLAEGEh/DxnQIwa5b+O52y0BEiIAkJs2Jvd5bANSHwIJCZCBDGppivdJ6vWfxgkAZDX+b7WMNnXllgAD6e8hA6P0iDLAuPfGkvdqPK25JUAqBAAy0c2QPvVVQOpDICEB4hdPM5qHpu7P1Os/zRIASH78331TXv8WLQEG0t9DIZKepMR5P8TTmlsCJEEAIGFh5/GJbgNSHwIJCRA/JwJ1dvJPUfWfBgkAJDn+j6f5rnwk2S8BqtHfQzkiKePZ/O5ac0YnAJCYeFr/+I8q7BCovS2wkADx04zGeR+mXv9pigBASGON/+s32UtOx2uOz8c9wpa++dgSAIiBE4G6P/lH7mJEAgCtq3w2S7Ot/4ht8ej/su1tQP37LeMhkJAASZABYjj1P7P6TyMEAIIZZf7dZetf/7+qcOSWAAPp76Eo5WSADn5TSwBGIQDQrspj7FCtf7PXUPO3sAQYQkiAJIzYj5aQAUb8HTvo4FOv/9QnABDGkMl3DK1/s9c2/DeyBBhIfw/ZkAE67v4tAViSAECLKgywo2r9+6+5zpVX+9UsAYYQEiC/DJBfDBj9l+qycU+9/lOTAEAAA2feNet+e61/gze02O9oCTCQ/h5yMnp3m1MGGP13abb7twRgOAGAtow+uq7T+tcfzNe53Wr/7bi/ryXAEEICJKS0DBCq+y+k/lOHAEDX5k+767f+zR1X18ew4He3BBhIfw/FSvp0oBgO3hKAIQQAWrHk0Dr11r/jbYAlwBBCAiRk3K40eBtdwbjHHLBTT73+U9mK6v8pjO+w6cmaJ/pPxGru2Kp16nP3Sc07Z8iBtZof2jY1NeXFA3Iy1y+O3nr2KuRE9GJr/TdOTjfS4pMfGwCaN6TdzGbq38Z7EobfOZYAQ1gCQAmrgJi3ARUOL5JTdFKv/1QjABC7VFr/mA87niOpRn8PWarQAUcYA6odUmfdfyQxg9gIADSswUF1VD10DL+CJcAQQgKkqFp7GkkMqHwYsTXlqdd/KhAAiFEGrX9sv07wA6hJfw+5qtwNB4wBdW66++4/trxBDAQAIhLqQ/27Ef+vlvoQSEiARG2cnK4ZA7pJAjVvq86v2bbU6z/jEgBoUuVzVOJvjptS8zetcxZQ6vew/h7yVrM57nXnzYaBpq42bOsfbfAgFAGAwMpp/ZP4rVMfAgkJkLSm+tT5Xfu4jXud/zbp/jv1+s9YfA8AjRl3OB1nB9yl3j0w1l139jlHVb7rfCcAkNm3BIxixD6+jfOI4mn9fScA89kAUMr8++xzjoq2941qIZD6EMgSADIQ8+nyGf8Kqdd/RicA0IwRe2utfyN3jncCACVIroGO/MjjPCqCEADoiNY/oW1A6kMgIQGykdwcPbkDzqz+MyLvAaABw5vsIO1scn3/wDttyG/hnQChjwLoTq+hjPYs9lSafu8EYI4NALl9qH+KU/8ItwGpD4EsASBLEc7XIzykwus/o7ABoK7+bjtUz5pN3z/ihwVZAoQ+CqDchUC6Tb8lADYAgeXXwYSaWOc09Y/n7k19CGQJQMzyq/+FdOFz8/50u/9C6j9LsgGgll7bbeof5O0BlgChjwIIprMxdn7tviUAAkAw2fQuWv843yXciPNnN9R/5VvylWZmZqalab2QQJw8LGtqtXnNr90vs/4znABALT7hJ+n73xIASEt7rX9pfb8lQOG8ByAMXUs1hZzrH5XUzwQ1WyI26n81589u0LB2LPX6zxACAKW0/jObp2c2lzXgGUXwLx2rSX8P2avf+qv/A5W29GA+ASAAYXcsWv/gUh8CCQnEQ/0fi9Y/uNTrP4vxHgDiVf9sH3V/FN4JAOTXd6r/o/BOgGLZAHRNpzIKU//YpD4EsgQgBur/KEz9Y5N6/WcgGwDiYuofhCUAEJypfxCWAGWyAeiUHmUIU//IpT4EsgQgLPV/CFP/yKVe/+lnA0B4pv4xsAQAumfqHwNLgALZABCSqX9auhkCtccSAOJh6p+W1Os/CwgA3TGenE/rH6FIvhOg8jNFf0+01P/5tP4RiqQ190zpjABA17T+SUt9CCQkQEBa/6SlXv+ZTwDoiFCr9U+CJQA0Tv3X+ichktbc86UbAgBptP7e6RWP1IdAQgKk1fqr//FIvf7TIwB0oeQ421Trr/p3xhIAGlRy/W+q9Vf/OxNJa17ys6YzAgBt0fpnLPUhkJAArdL6Zyz1+s8cAaB1BQZZrX/qLAGgEQXWf61/6iJpzQt87nRMAAgpvwKn9S9H6kMgIYGw8qtyWv9ypF7/EQBaV06E1fpnxhIAaiqn/mv9MxNJa17OMygIASCYbCqd1r9YqQ+BhARCyabcaf2LlXr9RwBoUfbhVeufN0sAqCz7+q/1z1skrXn2z6OABIAwUi95Wn/yGAIJCXQv9bqn9SeP+l84AaAtucZWrX9RLAGgglzrv9a/KJG05rk+m4ITAAJItPZp/clyCCQk0KVEC6DWnyzrf8kEgFZkFli1/iWzBICS67/Wv2SRtOaZPacisSL0ARQnrSJYv++P51eeOruBQQUDnT+7of7rxMbJ6UaGSRVMTU15gaEDkRTDETXyfIzkV1b/25N6/S+WDUDzhnQSkZTC0qb+U2dvUP2TWAIMfxWxBCB+edT/nKb+6n8qS4CW6j+LsQFgIVN/Qg2BArIEAFN/yqz/ZbIBaFjS4x9TfxZjCQB5139TfxZjCZAlGwB+wtSf+lIfAlkCUCZTf+pLvf4XyAag9PGPqT8jsgSAzOq/qT8jsgTIjw1AuUz9aVzqQyBLAAph6k/jUq//pbEBKHH8Y+pPNZYAkHr9N/WnGkuAzNgAlMXUn7alPgSyBCBXpv60LfX6XxQbgFLGP6b+NMISAJKr/6b+NMISICc2APkz9adjqQ+BLAHIhqk/HUu9/pfDBiDn8Y+pP22wBID467+pP22wBMiGDUCeTP0Xa/tUjW6kPgSyBCBdpv4Drkf971Dq9b8QAkBu4x+t/4DrMfFt2uZNtzXySFvSxsnpId3MzMxMtT+u/p4s67/Wf8D1qP/dluX46z9zBIB8aP0HXI/qEE7qQyAhgYRo/Qdcj/ofTur1vwQCQA7jH63/gOtR+ltmCUDhIqn/Wv8B16P+t8wSIAMCQNq0/gOuRzmIRupDICGBmGn9B1yP+h+N1Ot/9gSAVMc/Wv8B16P0d8sSgGKFrf9a/wHXo/53yxIgdQJAerT+C6/Ekz9iqQ+BhASiovVfeCXqf8RSr/95EwBSGv9o/RdeidIfmiUABQpS/7X+C69E/Q/NEiBpAkAatP4Lr8SzPR2pD4GEBMLS+i+8EvU/HanX/4z5JuDYxz85fZtvI9V/6kkNHQ4N8MXAFKXL+p/Tt/mq/1nyxcDpsgGImsH/v7gGdT9ZqQ+BLAHonsH/v7gG9T9Zqdf/XNkApPrZzwkNfqbO3lCz+pv6RM4SgEKo/+NS/7NnCZAoG4A8xVD3TX3IaQhkCUAq1H9ik3r9z5IAkFvNjeQwlP7SRPJxQJXp78mg8EZyGOp/aSL5OCDGIgCMJ+YWQeknch0MgVr9PDghoXAx//XVfyKXev3PjwCQQ/FV+omBJQBlUv/VfywBkiMAjCHC5kDpJy2pD4GEhGJF+HdX/0lL6vU/MwJAqlVY6W9DNwNs6rMEIBLqfzb131w5FZYAjRAARhVPW6D0p/4XLFzqQyAhoUDx/MXVf5KWev3PiQCQUjlW+lN/8aZBlgAEp/5XuQbNGbVZAtQnAIwkeEOg9Cf6hyPLIZCQUJTgf2v1n5ykXv+zIQDEXpeV/kRfs+mAJQABqf9jXINujKZZAtQkACwtVCug9FejdUtC6kMgIaEQ6n/da9D6k139z4MAEGOBVvqr0ZAVyBKAINT/pa9B+0XLLAHqEACW0HEToPRXo1dLUepDICEhe+p/xWvQ+pN7/c+AABBLpVb6q9GBYQlAx9T/Ra9Bv0W3LAEqEwCG6eblX+mvRnOWgdSHQEJCxtT/8a5B609h9T91AkDgkh1D9U+u9Lf3wpxWpah5P7RdebtkCUBn1P+ky2Y2v4j632MJUI0AsKgSXviTK/0l/FHGvfMr3ydzFTOnl4HFWAIwrhL+psnVf+ZT/0dkCbAYASDJmU2Bpb/+6/HcNeRXCLwMzLEEoAPq/z9dQ3aFNFHq/xxLgAoEgMEyfsmvWfq7r/tNtf558zIwnCUAo8v4r5lc/WcU6v9wlgADCQAFjX+SK/1a/3EV/jJgCUCr1H9ipv5bAoxFABggvxf75Eq/1r+Owl8GFmMJwCjy+zsmV/+pQ/0fyBKgnwCQ+fgnudKv9W9KmS8DlgC0RP0nIeo/SxIAFsrmZT650q/1b0OZLwOLsQRguGz+gsnVf9qg/s9nCbCAAJDh+Ce50q/1b1tRLwOWADRO/Sdd6j8DCQD/Quov8MmVfq1/l4p6GViMJQCLSf1vl1z9p0vqvyXAAgJAJuOf5Eq/1j+UEl4GLAFokPpPNtR/egSAf5boS3typV/rH4MSXgYWYwlAv0T/asnVf2Kg/oc+iigIAAmPf5Ir/Vr/2GT8MmAJQCPUf3Kl/hdOAPgnab2oJ1f6tf4xy/hlYDGWAMyX1t8rufpPzNT/YgkAiY1/kiv9Wv9U5PcyYAlATeo/hVD/CyQA/EQSL+fJlX6tf4p6j5Nqd36ELwOLsQRgThJ/qeTqPylS/4siACQw/kmu9Gv9Cx8IxfMyYAlAZeo/xVL/SyAARN1rJlf6tf6ZyeNlYDGWAMT8N0qu/pMZ9T9vAkCk45/kSr/WP2NJvwxYAlCB+g9z1P9clR4AInwJT670a/0LkfTLwGIsAUoW4V8nufpPIdT//JQeAKIa/yRX+rX+BUrxZcASgLGo/zCQ+p+TogNAPC/eyZV+rX/hUnwZWIwlQJni+bskV/8pnPqfh6IDQAzjn+RKv9afFF8GLAEYkfoPo1D/U1duAAj+sp1c6df6k/rLwGIsAUoT/C+SXP2HgdT/dJUbAAKOf5Ir/Vp/MngZsARgSeo/VFBs/U+aANC1OtVf60/eLwPBR0EtERJIsf7DWNT/tBQaABZ7gLY6/kmr9Gv96f5loO1R0JAhUJ0tsP4+Leo/tKe0+p+uQgNAxyqX/iCPSK0/eb8MBCEkFCut+g+NUP/jV2IA6HL8k1bp1/qT/cuAJUDh1H/oTCH1P1ElBoBupFX6G+ldNECk8jIQhJBQjrTqP7RK/Y9TcQGgg/FPWqVf609pLwOWAMVS/yGUvOt/iooLAK1Kq/Rr/Sn5ZSAIISFjadV/CKLk+h+bsgJAe+OftEq/1p/CXwYsAQqk/kMksqz/ySkrALQhrdKv9ScqBU6DhIScpFX/ISoF1v+oFBQAGh//pFX6tf5EK8jLgCVAUQqv/xCtnOp/WgoKAA1Kq/Rr/UlC79kx7oMtuWmQkJC0tOo/JKGc+h+PUgJAU+OftEq/1p9yBkIVXgYsAQpRZv2HFKVe/xNSSgCoL63Sr/UndZ29DAQhJKQlrfoPqcu7/keiiABQc/yTVunX+pOTtl8GLAGyV1T9h5wkWv9TUUQAqCyt0q/1J1dZToOEhMilVf8hV1nW/xjkHwCqjX/SKv1af0rQ0suAJUDGSqj/UIK06n8S8g8A40qr9Gv9KU1O0yAhITZp1X8oTU71P7jMA8BY45+0Sr/Wn5I1+zJgCZCljOs/lCyJ+h+/zAPAiNIq/Vp/yGYaJCQEl1b9B7Kp/2GtKHz8k1bp1/pDSy8DlgCZya/+A2nV/8jlHACGS6v0a/0h12mQkNC9tOo/kGv9D2hFgeOftEq/1h86exmwBMhDNvUfSLr+xyzbALCYatVf6w+FvAwEISR0I6H6DxRS/0PJMwA0+FKq9YeiXgYWYwmQitTrP5BT/Y9WngGgEVp/yECzLwPtERKikt+LPRQolfofRIYBoP5fWusPmWnkZcASIH6J1n8g4/ofpwwDQGWh/rRaf+hG5NMgISGgzF7agbTqf/dyCwDV/rRafyhHnZcBS4CYpVX/gXLqf4RyCwDj0vpDmeKcBgkJXcrptRxIvf53LKsAMNbfUusP9OrA6M8pS4A4JVH/gWLrf2yyCgAj0voD0Q6EhIRWZfPiDeRX/7uUTwAY5S+n9QfqvwxYAsQm5voPJGGq/foflXwCwHBafyCVaZCQ0Kw8Xq2BEup/ZzIJAEP+VFp/oPGXAUuAeERY/4GkTbVW/+ORSQAYSOsPJDoNEhJqyuDlGQhrKuttQA4BoP9vo/UH2n4ZsASIQTz1H8jSVNP1PxI5BID5tP5AHtMgIWFcqb8eA9Gaym4bkHwA6P0xtP5Axy8DlgCF13+gKFMN1f8YJB8AtP5ArtMgIWFJSb8AAymaymIbkHwACFL9tf5A/fqjv69J9w+EMpV4/Uk+AHRM6w90SUgAoHECwKi0/kDj9PcAdE8AWJrWHwhISACgWQLAMFp/oG36ewA6JgAMpvUH4iEkANAgAWAhrT/QMf09AF0SAP6Z1h+IlpAAQFMEgJ/Q+gNh6e8B6EzpAUDrD6RCSACgEeUGAK0/EBX9PQDdKDEAaP2BRAkJANRXVgDQ+gMx098D0IFSAoDWH8iDkABATfkHAK0/kBD9PQBtyzkAaP2BLAkJANSRZwDQ+gPp0t8D0KrcAoDWHyiBkABAZfkEAK0/kA39PQDtySEAaP2BAgkJAJQYALT+QK709wC0JNUAoPUHEBIAKCIAaP2BQujvASg9AGj9ARYQEgDIMwBo/YEy6e8BKC4AaP0BhhMSAMgkAGj9AfT3ABQRALT+AGMREgBINQBo/QH66e8ByDAAaP0B6hASAEgmAGj9AZakvwegKcsnwpl5UiPX08ThAKRtamoq9CEAkIAwG4CmWnatP1AOSwAAkgwAWn+A9ggJAEQUALT+ADXp7wFIIwBo/QE6IyQAEDIAaP0BmqW/ByDSAKD1BwhFSACg0wCg9Qdolf4egFgCgNYfIBJCAgDtBgCtP0CX9PcABAsAWn+AOAkJADQcALT+AAHp7wHoLgBo/QGSICQAUDcAaP0B4qG/B6DFAKD1B0iRkADA2AFA6w8QLf09AONaPvzHjbyuzDyp/vUAUMHU1FToQwAgnQBQk9YfoG36ewCiCABaf4B4CAkAtBgAtP4AHdPfAxAmAGj9AaIlJADQZADQ+gOEpb8HoKMAoPUHSIWQAMDY3wQ8n76f/HhUQ4+nA0XxgKcoVTYApv4AibIEAGC8DYC+HwAAitgAmPoD5MESAKBwS28A9P0AAFDEBsDUHyBLlgAAJRu8AdD3AwBAEQFA6w9QAksAgGL9cwDQ+gMAwETu/j9Wx6of1XaCLAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_80
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_50
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color yellow.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_481
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 2th action is Colorize the top layer of the original shape with the color green.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Cut the right side of the shape\nthe 8th action is Colorize the top layer of the original shape with the color white.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_140
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 2th action is Colorize the top layer of the original shape with the color cyan.\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
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AAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCBLut4BSMjU1NR8f5qenm53XwCoeSQHZgkAUMMZRTwAaI0SHyoSAKCps5FUAFCRWh+aIABAe+ctkQBgAOU+tEMAgM7ObfIAEJyKHzohAEASZz5hAAhC0Q+dEwAgCcIAUDBFPyRFAIDkCANAART9kCwBAPI4g0oCQBbU/ZA+AQDyIAkAKVP3Q0YEAHjAgNo6nXObJACkI52xcbP5xsYEdxW6IgDAUAZX252cVyQBoCvdFtMGPahIAICmzkatnSAlAaDUut+wBk0QAKCl81YLJ87Zp3C+BPIt/Y1g0AIBAErLAxoCQEZ1v5EK2icAQDe2POc1dIrVEADSLP2NS9AtAQAKDwNiAJBC6W8UgnQIAJCWzefIes/B1gUBg6n7IQ4BAGK1BTQEgKZLfyMMJE4AgIhtATEAqL30N6RALgQAiJsExAAIq8bS3xgC2REAIEuzZ1wxABiV0h8QACBjNTYExAAoXl2lv4ECcicAQAnqagiIAVAkpT+wJQEAylFXQ2BqasppHopRvfo3IEBhBAAoUPWGgFYAFEDpD/QlAECxxAAIS+kPDCAAQOGqrwsSAyBO6e+bDhEs7noHgJZM/0I6vxUK1K7K97TiEAFkRAcAYqmyLkgrAEot/WvdFyB1OgAQUZWpPq0ASM3Y30qz/hCTDgDENXY3QCsACij9694XIBs6ABCdVgBkSvUPjEcHANAKgMwo/YEqdACAqquBtQKgTeN94yz3BzbTAQBq6AZoBUDKpX8D+wJkTAcA6EMrAFKj+gfqIgAAdS4YkAGgCWN8s6z5AeZjCRBQ84ogy4Gg89K/mX0BCqEDACxMKwA6ofoHmiAAAE0tJ5ABoIpRv0HW/ABDEgCAEYyRAcQAGNUYXxylPzA8AQAYjVYANMrEP9A0AQAYhwwATTDxD7RAAADGJANAvVT/QDvcBhRo7yah7hAKfSn9gTbpAABVaQVAFap/oGUCAFADGQDGo/oH2icAAPUY9VYkMgCM9C1wtx+gLgIAUCcZABqq/pvcFyAWAQComQwAC1L9Ax0SAID6jbRWQQYgmuGPect+gCYIAEBTZACoWP03vC9AUAIA0CAZALak+gdSIAAACWUAMYBSjXR4q/6BRgkAQONcFkxwLvkFkiIAAG2QAQhL9Q+kRgAAWiIDEJDqH0iQAAC0x+1BCcXtPoE0CQBA2xQ6sCXfCKBlAgCQbsWjCUC+hjx6Vf9A+wQAoBsyAAVT/QMpEwCAzsgAFEn1DyROAAC6JANQGNU/kL4lXe8ApH7mdp5u2vT09DA109TUlM+CxKn+0zHqrIHxn1AEABjzLOLEUCMZgAKo/jvRaHvQ+E+pBACo7cTglFCFDEDWVP/tSGQ1oPGf3AkA0MgpwclgDDIAmVL9Ryj6BzP+kxcBABrhZDAeGYDsqP7DFv3zMf6TPgEAGudkAFB20T8f4z9pEgCgm5OBM8F8NAHIiOn/6oqs+/sy/pMOAQC64UwwgAxAFlT/VcSp+3sZ/+mcHwKDjk39Qtd7kRw/EEbiVP9jM+ht5q2gKzoAkAQTQr30AUiW6n8MKt35GP9pnwAADzh77dzBd/LkqU7OBE4DI2UASJBv8WZdfYunV6z8P7uxft3w/3jBf98E4z+tEQBgtEjQTjAwITRSBtAEILVy1gHZZt3fW7s3+rBNBwPjPy0QACDpXoEJIRmApKj+Oy/9Gyr3q+xAQ5HA+E9zBACoPxLUHgacBoYhA9A0C9K6eos6L/qH373aw4DxnyYIAJBNGIh8GnAxALmI+Q1tovRPvOhvOQxEHv9pggAALYWBupJA2NOAhUB0y+Kfdkr/TOv+wa+lriQQdvyndn4HAFpy9trp2f/V8mgxp8OHOe3FfGdomuq/6W/c9IqVs/+bKFG9r84oR3U6AJBrT8BU0Hz0AaiXequ5t6XUir/pnoDxn4oEAMg7CUQ7DbgYgDTF+Q7WUvpHq/sbSgLRxn9qZAkQdK/60qBQNbGFQLTJ4p96v1wFr/Pp6g0x3DEGAQAKiQFTvzARgwxAO1T/NQ4ySv/m3pxQ4z+1sAQIiloXpCMM1K5i3V/rvpSs4rog4z/D0wGAAhsCEaaCNAFomun/it8jU/5jq/LWGfcYhgAAZcaACOcAGYDmqP6rfIOU/rUY+2007rEgAQAyMHYGKP40EKECI03FH3tjDyBK/3qNnQGKH/+pQgCAPGgFjM07wKgcMyb+k6IVQO0EACg/BpR9DrAQiHpZ/DPG90Xp34Lx3mSjH325CxDkZzYDjHSboLLvDuHXwWhTqd+jsUv/ZvaFQW/4SLcJKnv8Zzw6AJArrYCRRH7tDC/ycaL6z4hWABUJABBrRVCp5wALgagu8uKfUb8d1vx0boyPwBjIZgIAZE8GKLsyIx2lHmNjVP+N7QujkQEYj2sAIOJVAWGXhE5NTQV81QwjZmGk9A94VUDY8Z8t6QBAObQCnNJoTnlHl+q/JFoBjEQAgKLIAAsK+JJZUMCjQvVfHhmA4QkAEP3K4MLOAeVN05KCwo6rkb71rvfNyKgfVmHjP8MTAKBMMkCc10tFCx4Pwav/JveFRsgALEgAgGJFzgALivZ6mU+0I0H1H4QMwGACAJRspOVAJZ0DCpuypUMlHUvDf8ct+ynASB9iSeM/wxAAoHwxM8CCQr1Y+gp1DIxU/Te8L7RHBqAvAQBCCJgBSpq4pSvFHEWq/8hkAHoJABBFwAywoDivlMifvuofGYA5BAAIJFoGKGb6lk6Ucfyo/pklA7AlAQBikQGKfJmMKsitP1X/bEkGYDMBAMKJlgEgJtU/vWQAZgkAEFGoDKAJQMDpf9U/85EBEAAgrpF+Jgwokuo/Jp87AgDENWQGKGASSBOAzUz/b6YKjGzIT9/YWCoBAEKLkwEgCNU/Q5IBIhMAILogGUATgAjT/6p/RiIDhCUAAFEyAJRN9c8YZICYBAAgyjXBuU/u0rQIR4jqn16OioAEAGCEDFD2JFDZr46yP99hXp06jyrHRtnfoGgEAOABMgDkSPVPdTJAKAIAMLJ8zwEuBQ6r4Mt/HbS0yfFWBgEACHcxAERj+p9hOE7iEACAWAuBNAECCj79r6pjeBYCBSEAAOEyAJRB9U8TZIAIBABgfJmeA/Kd7qUJmR4PmX77KIYjMGsCANBf5IsBnNhKEvnTNP3PeBw5xRMAgHlZCARpsviHplkIVDYBAIjYB3ApcBAFX/47mOqf6hxFBRMAgKrUytAm3zjS4WjMlAAABF0IVOrUL2UfAxb/0CYLgUolAABxFwIN5qyWu5ifoOqfejmiiiQAAPWIWWxB2G/Z1Pp1Xe9CaEm9/0kdmQxDAADiNgFyXAFCXYr89FuerJ1avy6pMjSI9t92TYDyCABAbRmgvEmg8l5RHOV9dgvf0ajdKm3z04kBrdnyre7q447zjSubAADUKbtzQJHTwJT3uaf/zRIDGpXF25v+UcpmAgAQfSEQFKCTRRq9T5pFnZqR2fez9y1N5OMmXwIAULPCJoEKezlBFPapZfdy5itbGV6mb2B2x2pYAgAQvQmQ3WoQKirvE+9wanbwU2daxXZrwTct2Y+bjAgAQP1MAkFdCvg2iQGh3qgCjtgIBABgZOU1AQZzPstLtM+r80nZIXegjOq2IcO/Obl83CROAADGUdgtQctbE0IZn3Vqt/6sTgwo4A1xS9ACLOl6BwCAvE2vWDlSFTv7j7NLLzUar+iP/I5RLx0AYEyFNQHivJaylfRJlTf9X8Dkd3VlvGpNgNwJAABAVWOnkTIK4hZeae55j6QIAMD4SroaOK+l4YynpE+5sHKw7J8OKPKlFXYERiMAAA3SBYY4351aKsLCauW6Xk6O1XaOx3AcAgDAUJzM0uczKkYBMaCAl0DBBACgkpIuBS5pfQhZf775Xv47YMfG2OdMa+gxdnvwm5Pjx53d+B+N24ACAI2bWr9utl4ctTjO5Z6hVe7smWPOIWs6AEBVJV0KDOlLvxQebHrFysK6AePt23jvQ2oKeAkxCQBA44rpAhfzQopUzKeT+wsZUBFuWSWXEQNqKf0HP0LuFXbux3OpBACgBsU0ATJaJk7MTzb3cnCOfGNA5Fn/Ocp7RREIAEAbTAJBnG/KkE2AWmJA+0mg3tK/7On/ko7qwggAAED30v8t4bGfqIw6npIIAEA9ilkFNJiprDQF+VwyqiNHbQJs/q8SjAFVWg2DX1Ex0/8Z7SqzBACgJbmUaMUsFie7zzSX70jT0okBVR6tyOX+Y3Nsp0YAAADqN/bMdwoxoIXSv5jpf3IkAAC1CbIKCDoRsyJsPwaY9R9P2BeeKQEAaI8uMIT6dlRsArQcA9os/QNO/xd5hOdLAAAYjdNYanwiQVSMARX/wXwiz/qTLwEAqFMZq4ByuWaUOJ9mviVmXU2ALR8wkXdj7D0pdfo/3z0PaEnXOwAAME6t2dXvAat0yZ0OANAqqzUg2vei9ibAlo/cci1e/RlLnf4fRtnHeV4EAKBmZawCgnSUXRRW104MSGfpUcq8RbkQAACAXJsAwzxFOg8eefqfpAgAACNfOaqRnY7Bn0UZVwDT4SS9iX+KJAAAbVM9w5Z8I+q9lreukr320r+rS5aT4mhPhAAA1M9lAFCXYqafM7pat5NZfx80bRIAAICONTQ7Pmop31zpb/qfpAgAAEAbBtfWzZXIw5T1jc76L/jSzJrTMgEA6IBloDDLd4FoHPMpEACARrgMAKorb2K4qyZAhwJO/5f3isojAAD0506g6XMPUIAxCAAAQHtCNQECTv+TBQEAAAACEQAAgFYFaQKY/idZAgDQDWvowbeAmBz5nRMAgKa4ERBUUfb0cPFNgODT/2W/ugIIAAAAEIgAAAB0oOAmQPDpf9InAAAAQCACAADQjSKbAKb/SZ8AADAvPwacMj8DDDAeAQAASFR2TYDsdpiYBACgM2bQiczxH3M9TLTXOx/Hf7cEAKBBfgoAxqNMzHFOPaNdbYFjOGUCAADQpTiVYpxXSuIEAAAgaVnMrGexkzBLAAAAOhZhajzCayQXAgAAkLrE59cT3z2YY9Hk5OTcbRCVK1abMHly3jdrd6sKoLqY0/9yUbIEAAAACMQSIAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQJYM/nP6P9IJI/GrrtQr/UFy7GM+95e29vSvTKTt5OceNOCvAX84dsFfja34ngx+/EYfnEwHmdwNGCQXCAAQzdlrjUc1mzx5UJXmBAAMI/FENL1iZdMBJkdyUbIsAQIAOhahUozwGsmFAAAAJC2LufMsdhJmCQAAABCIAAAAdKnRy3PbtOCuWgVEIgQAoLMrgIH5qBTJnWM4ZQIA0Bm3ACKy9G9U2o5ipv9naQIMyfjfLQEAAAACEQAAgG4UNv0/SxOA9AkAAAAQiAAAAHSgyOn/WZoAJE4AAACAQAQAAKBtBU//z9IEIGUCANAUPwIAVSgQyZejN3ECANANN4GGsD8FUPz0/yxNgPkY/zsnAAAAQCACAADQniDT/7M0AUiTAAAAAIEIAABAEgqb/i/4RZE7AQBohFsAQXXlrQ8p7xVVV957Ut4rKo8AAHTALSAg+I2A2pwpn1q/bsGSdJh/MzZNgC0Z/1MgAAAAbRhQYTdUIo9a1jcXAwa/QFPmtGxJ208IANCwKiX17H9r2p6C6QAA9XMBANSlmLnh1qb/65rFr70bEKQJUMwLKZsAALTNAlDYkssA6tLEAp5Grw0IyPifCAEAAMh++r/RMr2uBw/SBCB9rgEAADLWTt3swgBKogMA1MwFAFCv3CeGm5v+b399TvVnLLsJkPv+xyEAAK2yABR6uQwgr6X5LgwYj/E/HQIAAJDN9H86xffYe1J2E4AsCABAnaz/gSYoCpMq/dPfq054HzIiAAAAbRtp+r+WlfeNXr876h66mJhuCQBAeywAhVCXAVSfEm6z9K8eEmr8DbKJ4hj/kyIAALWx/geaU1JROEyd3dWsf2sxoLAmQEnHZwR+BwAASKgirF5KVq+tZx+hyp5U/N2AqfXrCksIJEUHAGiJ/i8EXAXUa0Bdm9pa/6a7AXFKfON/agQAoB7W/0DTMlplMcauJlX69z5ylQcf76WV/XHTLUuAAICW9C2jG/1t3RpVWRc034qg6RUrVc+0TwAA2qD/C8NYe/pXTn7uQROZG76irVL7drV+pokYMODfF7BMyPifIEuAgBpY/wPtyHq2eMtatspy/6Zv6t/0Psx57Z2/lsjHZFgCANA40z8Q51LgBcvB3Ev/hmLAgH82kTPjf5osAQKqMv0Pbcp0WUjFxe4pv+RaFgVlWuhnutvoAAAAjZeDxcz6N3GzoMFvTtZF9tSUGaIUCQBAs9P/+r9Q+yqgrCvC8kr/MnZ7DEGOwyIJAABAWuVgATV0vS8h61JbEyBBAgDQINP/EPNS4Milf8Evh2IIAMD4XP4LXcl6SriJX9tNWZEvbaQjUBMgNQIAAFBV8df4VlfxlRYW+eiWAACMyeW/0KjiLwWOU/qX96rHOPY0AZLidwAAgFbLwQIq4Io2vwOjLaTJ8ycgSJAOADAO0//QgvKaAGXMfwd/Q8Y+6jQB0iEAACNz7S+ko/MMMOQO5Fjptmb4NyeXj5vECQBA/Uz/Q10KuB+o0n9IEd4oTYBECADAaEz/Q2o6nJQd/NQRKtraLfimJftxkxEBAKiZ6X8I3gQo+6b+7cj0DZycnFzw32gCpEAAAEZg+h/S1MnUbO+TZlq2ZhelEvm4x84AdE4AAOpk+h9iNgGU/o3K4u0dvvTXBOicAAAMy60/oUOp3RJ089NlUZuWYcu3uquPe5jqXxMgfQIAMBSLfyB9LReFSv9OtP+2N3FcaQJ0SwAA6mH6H0ItBFL6dyup9793yl8TIHECALAw0/+QCzdqJJcjShOgQwIAUEP1b/of0mkCyADUZZhjab7Jfk2AlAkAQFWqfwi7EIjgKlb5mgBdEQCAQSz+gRxpApDCUaQJkCwBAJiXxT+QJguBSHnxz2hPpAnQBQEA6M/cP+ROBqDzI0cTIE0CADA+0//QFVcC0K0aK3tNgPYJAEAfFv9A+iwEIovFP5oACRIAgLlU/5ALGYBMl/7PfV5NgHYJAMD/Yek/lEcGoNvjRBMgNQIAMDLT/5AOFwPQpuZKeU2ANgkAwAMs/oEcWQhE+ot/NAGSIgAA/0v1D/mSAchx6f/c3dAEaIsAAPycpf8QgQxAh0eFJkA6BABg2Orf9D8UcDGADMAYx0NrtbsmQDsEAIhO9Q/FkAFIvPrXBEiEAAChqf6hMDIAmc79b6YJ0AIBAOJS/UORZABSrv41AVIgAEBQrvoFZICY0v/cNQGaJgBARMNX/6b/oexfB0u/FqRew3/izU3VawJ0TgCAcFT/EIEMQJrV/5A0ARolAEAsqn+IQwYg2eq/84ARnAAAgaj+IRoZgASr/yFpAjRHAIAoVP8QkwxAmtV/OkkjIAEAQlD9Q2QyQGRpVv9D0gRoiAAA5VP9AzJATIlX/wlGjiAEACjZ5MlTqn9gjAwgBuRupA8x5UJcE6AJAgAUa6Sf+lL9QwTDZwCtgKyN9Nl1W/2nnD0KJgBAmVT/QF8yQPEyqv6HpAlQOwEAQi/7Uf1DQKNmADEgF6N+WIlU/4nsRigCABRlpNJf9Q9hjZQBtAKyMOpnlFfZrQlQLwEAyqH6B4YnA5Qk9+o/tf0p3pKudwCogdIfGDsDnPzcg0aqMqdXrGx4vwhU+g9vamrKyasuOgCQPdU/UIVWQL5Kqv5T3rfyCAAQ6Hpf1T9QVwYQA7o1xkdQQIXtSoC6CACQq1FLf9U/UGMG0Aro0BjvfBbVfxY7WQbXAEB+lP5ACpcEuCqgfaWW/sNzJUAtdACg8DU/qn+ghVaAbkDTxnuTs6v+s9vhTAkAUHLpr/oH2skAYkBzxn5jSy2mXQlQnSVAkAGlP5D+cqBZU+vXWRFUo4Cl/+Tk5Nlnn931XhROBwCSZuIf6JBWQIdM/A+gCVCRAACllf6qf6DzDCAGVFHlrSuj+i/jVaTMEiBIy9hF/yylP5DOcqAtV7BYF7SginkpWtHsdkBVCACQCqU/UGoMcMPQwZT+vVwJ0ChLgCDv1T6zVP9A4iuCZlkXVPsbUmT1PyRXAoxNBwA6U7Hon6X0B/JqBVgXVNePKBdf+msCNEcAgCzrfqU/kHsMCJgE6up+FF/6D8+VAOMRACCzun+W8Q5IwdrTv1IxA0RIAvWuegpV/WsCNEQAgJzqfqU/UGQroMgkUPvVDqFK/+FpAoxBAIAMiv5ZBjggQXWV/gOq54zCQEOXOEcu/TUBmiAAQNJF/yylPxCn9M8uDDR6X6PIpf/wNAFGJQBAcuX+loxoQOTSf5hqu+VI0NptTJX+m2kC1E4AgCQK/TnU/UCaOiz9R63IKwaDrn6vQN0/Hk2AkQgAkETFv5nxC0hTgqV/vRV8579QpvQfQBOgXgIAJEHdD5Rd+m8e5fx66xzq/rpoAgxPAICOGa2AIKX/lv+vGKD0H5UmQI0EAOiGuh+IVvr3/VPAJKDub44mwJAEAGiVgQkIXvqHTQLq/uo0AeoiAEDjFP1AFlou/Qf8h8WEAUV/+zQBhiEAQCOMPkBGui39CwsDiv5GaQLUQgCA2ij6geykVvpnGgYU/UnRBFiQAABjMrgAWUu/9B/m6TqJBMr9bmkCVCcAwAIU+kBhciz9R92NWoKBQj9fmgCDCQDwAIMFULaSSv96ewVq/bxoAlQkAABA+eKU/jBLE2AAAQAASqb0p0iaAFUIAABQJqU/wWkCzEcAAIDSKP2JQBNgbAIAAJRD6Q9b0gToSwAAgBIo/QlIE2A8AgAA5E3pDwNoAvQSAAAgV0p/0AQYgwAAAPlR+sPwNAHmEAAAICdKf5hDE2BUAgAA5EHpD2PTBNiSAAAAqVP6w2CaACMRAAAgXUp/qIsmwGYCAACkSOkPI9EEGJ4AAABpUfpDQzQBZgkAAJAKpT9UoQkwJAEAALqn9Id2TGkCCAAA0C2lP9RIE2AYAgAAdEPpD52YCt8EEAAAoG1Kf2iOJsCCBAAAaI/SH1IwFbsJIAAAQBuU/tAaTYDBBAAAaJbSHxI0FbgJIAAAQFOU/tAVTYABBAAAqJ/SH9I3FbUJIAAAQJ2U/pAITYD5CAAAUA+lP2RnKmQTQAAAgKqU/pAmTYC+BAAAGJ/SH3I3Fa8JIAAAwDiU/pAFTYBeAgAAjEbpD4WZCtYEEAAAYFhKf8iRJsAcAgAALEzpD2WbitQEEAAAYBClPxRAE2BLAgAA9Kf0h1CmwjQBBAAAmEvpD+XRBNhMAACAByj9IbKpGE0AAQAAfk7pD8XTBJi1+H//LwBEdfJzD1L9A7OmpqYmSqcDAEBctdT9Sn/IyKQmgAAAQExKfyDslQACAACxKP0huMnwTQABAIAolP7AkMpuAggAAJRP6Q9saTJ2E0AAAKBkSn9gPFPlNgEEAADKpPQHBpgM3ATwOwAAFKiu+/qr/iGyqUJ/E0AHAADmUvdDBJNRmwA6AADwALP+QPFNAB0AAPg5dT8ENBmyCaADAEB0Zv2BUE0AHQAA4lL3A5PxmgA6AABEZNYfCNsE0AEAIBZ1P72iTQATnA4AAFGY9QfGVlITQAcAgPKp+wE20wEAoGRm/YG6TJXSBNABAKBM6n6AvnQAACiNWX+gIVNFNAF0AAAoh7ofYEE6AACUwKw/0I6p/JsAOgAA5E3dDzASHQAAcmXWH+jEVOZNAB0AALKk9KdGDidC0QEAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQBZNTk52vQ8AAEBLdAAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAJZNDMz0/U+AAAALdEBAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACGRJ1zsA7dm4ceMVV1xx2WWXff3rX7/uuutuuOGGO++8c8OGDffff/+yZcuWL1++xx577LXXXgceeODBBx98+OGH77vvvl3vMgBAzRbNzMzU/ZiQlo0bN37kIx953/ved/HFF99zzz3D/4f777//M5/5zOc973n7779/kzsIwMjOPPPMkf79okWLFi9evNVWWy1dunTZsmU77rjjrrvuumrVqmXLljW2j5AoAYCS3XXXXW9961tf//rXr1u3rsrjHH/88a94xSse9ahH1bdrAFSyaNGiWh5n7733Xr169aMf/ejHP/7xj3vc47bffvtaHhZSJgBQrDPPPPNP/uRPbr755loebfHixS9+8Ytf85rXODcAlBQAtrR06dKnPOUpz3rWs572tKdtvfXWtT8+JEIAoEA/+clPnv/8559//vm1P/LDH/7w888//+EPf3jtjwxA5wFgs7322uvUU0/9oz/6IwuEKJIAQGm++tWvHn/88d/+9rcH/JuHPexhhx566IEHHrjbbrvtsMMOd999909/+tP169dfc801n//859evXz/gv91pp50+8YlPHHbYYQ3sOwBJBIBZ++yzz+te97qTTjqp6SeClgkAFOXyyy8/6qijbr/99r5/3Xvvvf/gD/7gWc961oMf/OD5HmFmZuaaa675t3/7t/e973133nln33+z0047XXLJJY9+9KPr23EAkgsAsyYnJ9/+9rfvsssu7TwdtEAAoBz//d//fcQRR/St/nfccceXv/zlf/zHfzz8ms7bbrvttNNOe/Ob39z3O7L33ntfeeWVe+yxR+W9BqC2ADC4qvnZz35233333XXXXXfeeee6deu++93vfuUrX/nCF77wmc98Zr6Zo1kPechDLrroogMOOKCOHYfuCQAU4vrrr/+1X/u1n/70p71/+rVf+7Xp6enxbup/8cUXP/vZz+57JfGRRx75H//xH2PtLAAdBID5bNq06VOf+tQ73vGOj3zkI/fff3/ff7NixYqPfexj1n9SBgGAEtx1111r1qz58pe/3PunE044YXp6epttthn7wa+99trHP/7xfaPFO9/5zhe84AVjPzIAKQSAza655po///M/n29yZ+edd77kkkvcEpoCCACU4PnPf/573vOe3u3HH3/8ueeeu2RJ1V+8/sIXvvAbv/EbGzdunLN91apV11133fLlyys+PgApBIBZ73jHO0499dRNmzb1/mmPPfb44he/aP0nuVvc9Q5AVRdffHHf6v/ggw8+44wzqlf/s4uIXv7yl/duv+mmm97+9rdXf3wA0vGiF73oU5/61E477dT7px/96EdTU1P33XdfF/sFtdEBIG8bN2488MADv/Od78zZvt12233pS1/af//963qie++999BDD73mmmvmbH/IQx7yrW99a/FiWRqgkA7ArM9//vNPfOIT77rrrt4/veENb3jJS15S1xNB+1Qt5O3tb397b/U/MTHx6le/usbqf2JiYuuttz7ttNN6t19//fWXX355jU8EQAoe+9jHvvvd7+77p9NOO+2GG25ofY+gNgIAGbv77rtf+9rX9m4/4IADTjnllNqf7qlPferee+/du/28886r/bkA6NxJJ5108skn926/8847+559IBcCABn74Ac/eNNNN/Vu//u///utttqq9qfbaqutXvSiF/Vuv/TSS2t/LgBS8A//8A/Lli3r3f7ud7+77wkIsiAAkLF3vvOdvRv322+/pz71qQ0947HHHtu78eqrr96wYUNDzwhAh/bZZ5+/+Iu/6N1+zz33nH766V3sEdRAACBX11577Re+8IXe7S9+8YubuyT34IMPXrly5ZyN99133ze+8Y2GnhGAbv3pn/7p0qVLe7e///3v72J3oAYCALk6//zzezcuWrTopJNOau5JFy1adMQRR/Ru/9a3vtXckwLQoZ122qlv+/drv9DFHkFVNdwiHTrx0Y9+tHfjmjVr9txzz0af96STTuq9zdwOO+zQ6JMC0KHf/u3fPvfcc3u3X3zxxQceeGAXewSV+B0AsnTnnXfuvPPOvT/F8vKXv/xVr3pVRzsFQDm/A7ClTZs2rVixovc3AZ72tKd9+MMfbuIZoVGWAJGlq666qu8PMT7+8Y/vYncAKNk222zziEc8onf7l770pS52B6oSAMjS//zP//Tdfsghh7S+LwCUr+/55bvf/e4dd9zRxe5AJQIAWfrqV7/au3HVqlW77rprF7sDQMQAMDMz8+1vf7uL3YFKBACy9IMf/KB340Me8pAu9gWA8q1evbrv9h/+8Iet7wtUJQBQTgDYY489utgXAMq38847993+ox/9qPV9gaoEALL04x//uHdj7090AUAtdtxxx77bb7/99tb3BaoSAMhS773YJiYmli1b1sW+AFC+nXbaqe/2u+++u/V9gaoEALJ0zz339G7cdtttu9gXAMo3Xwdg48aNre8LVCUAkKWf/exnvRv9qh0ADen74zMTExNbb7116/sCVQkAZGnp0qVDtgUAoLr5Zvo1n8mRAECW+i7373thAABUN98Pfm233Xat7wtUJQCQpR122KF347p167rYFwDKd/PNN/fdvmrVqtb3BaoSAMjSnnvu2bvxpptu6mJfACjffPf732uvvVrfF6hKACBLfQfc66+/vot9AaB83/zmN/tuf9CDHtT6vkBVAgBZevCDH9y78eabb/7pT3/axe4AULivf/3rvRtXrlxpCRA5EgDI0iMf+ci+27/85S+3vi8AlO+KK67o3XjwwQd3sS9QlQBAluYbcz/3uc+1vi8AFO6222679tpre7evWbOmi92BqpZUfgTowOrVq3faaafbbrttzvZLL730b//2bxt96t/7vd+bc7/RbbbZ5v3vf3+jTwpAhz72sY/1/SGwI488sovdgaoW+fFUMvX0pz/9vPPOm7Nxq622uummm3bbbbeGnvTb3/72Qx/60Dkb99133+985zsNPSMAfS1atKh3Y0NVzeTk5DnnnDNn484773zLLbf4JWByZAkQuXrKU57Su/G+++4799xzm3vST37yk70beyMBAMW45ZZbzj///N7tJ554ouqfTAkA5OrpT39635H3bW97W3NPevHFF/dufMQjHtHcMwLQrbe85S333ntv7/bf/d3f7WJ3oAYCALnabbfdjjrqqN7tX/7yly+99NImnvHuu+/+1Kc+1bv98MMPb+LpAOjcT37ykze96U292w877LDHPvaxXewR1EAAIGMvetGL+m7/67/+6yae7owzzrj11lvnbNx6662f8IQnNPF0AHTupS996e233967/a/+6q+62B2ohwBAxo4++uhDDjmkd/vnP//5s846q/ane+tb39q78Ygjjthll11qfy4AOnfRRRe9973v7d1++OGHH3fccV3sEdRDACBvf/M3f9N3+x/90R/9+Mc/rvGJzjnnnKuuuqp3++///u/X+CwAJOK66657znOe07t9q622eutb39r3HkSQCwGAvD3jGc/ouwJn3bp1z3nOc+6///5anuXWW2899dRTe7fvt99+J5xwQi1PAUA6brjhhiOPPHL9+vW9f3rZy17mB4DJnQBA9t7ylrf0vR3Qxz/+8Ze+9KXVH39mZuYP//APf/SjH/X+6TWvec1WW21V/SkASMc111yzZs2a7373u71/+s3f/M1XvOIVXewU1EkAIHurV69+zWte0/dP//RP//Syl72s4uOfcsopZ555Zu/2Jz7xiZOTkxUfHIB0zMzMvP3tb3/MYx7zgx/8oPev++233/T0tHkfCuCXgCnBzMzM8ccff+GFF/b960knnfSud71r+fLloz7shg0b/viP//jd7353759WrFhx9dVX77333mPtLwDJ/RLwJZdc8rKXvezKK6/s+9fdd9/9sssu22+//cZ+fEiHAEAhbr/99t/6rd/qe53u7LTNG9/4xmOPPXb4B/zsZz/7/Oc//7rrruv905IlSz7+8Y8fccQRFfYXgCQCwDe+8Y0LLrjgAx/4wDXXXDPfv9l3330/+clP+t13iiEAUI5bbrnlcY973Le+9a35/sFhhx126qmnHnfccTvssMN8/+b222+/8MIL3/zmN//Xf/1X33+wePHi008/ve+tIQDoNgCsXbt2wH9y3333bdq0acOGDevXr7/pppuuu+66//mf/1nwlnGPfexjzz333D322KPyLkMqBACKcssttxx//PHz1e6zttlmm8c85jGPeMQjHvrQh+60005bb731+l/44Q9/eMUVV1xzzTUD7h209dZbn3766c961rOa2X0AhtXCjTgXL178kpe85NWvfnXfW01AvgQASnP33Xf/wR/8wfvf//7aH3n33Xc/99xzDz/88NofGYDUAsCv//qv/+u//uuhhx7a6LNAJ9wFiNIsW7bsfe9733nnnbdq1aoaH/a3f/u3r732WtU/QPHWrFlzwQUX/Nd//Zfqn1LpAFCsDRs2vOUtb3n961//k5/8pMrjPOlJT3rlK1/5mMc8pr5dAyC5DsDq1atPOOGEZz/72atXr673kSE1AgCFu/vuu88777z3ve99l1566b333jv8f/iwhz3saU972vOe97yHP/zhTe4gAC0FgMWLFy9ZsmTbbbddvnz5zjvvvHLlyn322eeAAw446KCD1qxZs/vuuzezp5AcAYAoNmzYcPnll1922WXf+MY3rrvuuh/96Ed33nnnhg0bZmZmli1btnz58j322GPvvfc+4IADDjnkkMMPP3zfffftepcBAOonAAAAQCAuAgYAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIZNHk5GTX+wAAALREBwAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAlky+M/T09Nt7Qm0YWpqasBfHfBEO+YH8HWgMMZ/opma/5jXAQAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBAlnS9A5CQqamp+f40PT3d7r4A439hYVTGf0IRAKCGUsPpAdo3PT0tA9AC4z/lEQCgqdODswJA8Yz/5EgAgPbOCk4JUC9NANJk/CdxAgB0dkpwPgAIwvhPUgQASOJ84GQA49EEIEfGf7olAEASnAwAYjL+0z4BAJLjZAAj0QSgGMZ/2iEAQB4nA2cCgFCM/zRHAIA8OBPAAJoAFMz4T+0EAHjAgLE1ndrCmQDGs/b0r3S9C3Tp5OceNOCvxn9CEQBgKINH205OD84EMFIT4OTnHiQDMAbjP+URAKAGfYfg1s4KzgQAXTH+kyMBAJoyZzhu4Xww+xROA4SlCUAijP8kTgCA0s4HJoQAkmL8JzUCAHRjy9G5oZOBCSEC0gQgfcZ/OicAQOEnA6cBgGQZ/+mEAABp2TxS13sm0BcmDk0AMmX8pzUCAMSaFjIhBJA44z9NEwAg4rSQ0wBl0wSgGMZ/miAAQNwzgdMAQC6M/9RocZ0PBrRl+hdqeaipX6jloSAdC35BTn7uQW3tC9TJ+E91OgCQsRonhMwGAWTE+E8VOgBQgromhMwGURJNACIw/jMGAQBKOw1UPxM4BwDkxfjPSAQAKFD104CpIMqgCUA0xn+GIQBAsZwGAGIy/jOYi4ChcNUvFHN9GFnzmwCEZfxnPjoAEEXFCSFTQQCZMv4zhwAAsVQ5DegIkylXAoDxny0JABBRxdNA3bsDQEuM/wgAENrYpwFTQWRHEwC2ZPwPTgCA6EwFAcRk/A9LAABMBRGCJgD0Mv7HJAAANZwGGtgdAFpi/I9GAABqOA2YCiILmgAwgPE/DgEA6MNUEEBMxv8IBACg5qmgZnYH6qEJAAsy/hdPAABqPg1oBwMUwPhfMAEAWJipIEqiCQDDM/4XSQAAGpwKamx3AGiJ8b88AgAwAu1gyqAJAKMy/pdEAABGYyoIICbjfzEEAGAczgHkThMAxmP8L4AAAIzJOQAgJuN/7gQAoL12sCWhJEUTAMZm/M+aAABUZSoIICbjf6YEAKAGzgFkShMAKjL+50gAADprBze5OwC0xPifHQEAqJNzANnRBIBaGP8zIgAANXMOAIjJ+J8LAQDouB3sHEDnNAGgLsb/LAgAQFOcAwBiMv4nTgAAGuQcQC40AaBexv+UCQBAQucApwGAYhj/kyUAAI1zWRhZ0ASA2hn/0yQAAG1wDgCIyfifIAEAaIlzAOnTBIAmGP9TIwAA7XF7OICYjP9JEQCApKeCoGWaANAc438iBAAg3XOASSCAwhj/UyAAAN1wDiBZmgDQKON/5wQAoDPOAQAxGf+7JQAAXXIOIE2aANA043+HlnT55JCYvqOMK5aaNj09Pcz4PjU15bMAhjRqQjP+d8L435VFk5OTA/7s7aYwNU4k+HZ08tF421s75r3Vw7x7a0//Slv7QkKtGN+Oehn/239jdQCgtu+VsakK80DAghJZeWX8r5fxv306AMTS2lJC353xmAeqnQ5ARZoAnUuk6B+e7854jP+10wGALr91RqvhmQcCciz6t2T8H4/xv00CADTOyQAKLkpOfu5BmgC1yLron4/xnzS5DSi0aur/63pH0uXGcBDKyc89aPZ/E6Uz/i/I+N8aAQC64UwwgHMASfGbAE2IU/f3Mv4PYPxvhwAAHXMa6Ms5AEoVtu7vZfzvy/jfAgEAkmBCqJdzAOnQBKgu8pT/YMb/Xsb/prkIGB4wvWLlnC1T69e1vA+zw5lrxUa6KQSQsq6K/jkD6eDBpHfUbX/wMf5vyfjfKL8DQCwLnAB6AsC8j9NWMPAdHPI07I2aj98BqJHfBEiz7q9ltnj4A97vybTJ+F+F3wGAXHsFJoSGnAdyZ2gIUvp3/k1vrVdg/Df+N0cAgPojQe1hwGlgGM4BNM1vAnRV+if+1d5y92oPA8b/YRj/RyUAQDZhIPJpwGJQiFb6ZzrWNRQGjP9d70Vp3AUImjW9YuXs/+p6wLA3ixjmzBfznaFNbgfUq957+0z/fxP5q/21GP8HiPnOjE0AgCyTQMyRzjkAUlNX6V9S3d/0q4s5yhn/62UJELRtcwaouDoockd4MItBaZQrAWos/aN9VTe/3oqlqvF/Psb/IQkAkHcSiHYasBgUCij94wxZjSYB4z9jswQIuld9aVCoMVEjmM5FvhKg4ksreJ1PV29IqOHO+F8XAQAKiQGhLg5zDoDsLvZV+jf35hj/54jzbozNEiAoal1QtI4wdCXUlQAV6/5a96VkFdcFGf8Zng4AFNgQiDD5YRIIEq/+TfmPrcpbF2HcM/5XJwBAmTEgwtjnHEC3IlwJMN5LUPrXYuy3McK4Z/yvSACADIydAYof/hQZkNqKf9/Keo2dAYz/DCAAQB60AsbmHaA5pTYBTPwnRStgbN6B+QgAUH4MKHsE1AiGzqt/pX8LxnuTyx79jP9jEwAgRAwoux2s8qBDJTUBxlj2o/Rv2RhvuPGfXgIA5EorYCSRXzs0N/HfzL6wAK2AkUR+7fMRACBcK2CiRBrBdKiAJoCJ/yCtgIkSGf/HIABA9mSAWcoRaK36b2xfGI0MMMsxOSoBACK2AspeEjpAzFdNCzJtAoy66N/Ef4JG/VCM/wgAUBStAKUJDM/Ef0m0AhyfIxEAoCgywIICvmTakVcTQPVfHhlgQQFf8nwEACjNGMuBJgqiTIEFWfZTqjGWA00UxIE6PAEAyiQDxHm9pCOLJsCo1X+T+0IjZIA4r3dsAgAUK3IGWFC01wuzVP9BRM4AC5oK9nr7EgCgZCMtByppTFS40JWUmwDDP7VlPwUY6UM0/kcjAED5YmaABYV6sTBS9d/wvtCemBlgQVORXmxfAgCEEDADKGLoSoJNANV/ZAEzgMN4QQIARBEwAywozislMtU/ATPAgqbCvNK+BAAIJFoGUM3QlXSaAKp/YmYAx/NgAgDEIgMU+TKhL9U/W5IBinyZ4xEAIJxoGQBiNgFU//SKlgGYjwAAEYXKACaBCEj1z3xCZQDj/3wEAAhqpJ8JA3JsAixI9R+Tzx0BAOIaMgMUMEFiEohQhswVqsDIhvz0Cxgbjf99CQAQWpwMAEGaAKp/hhQnA9BLAIDogmQAk0BEoPpnJEEygPG/lwAARMkAUHYTQPXPGIJkAOYQAIAo1wSre8C3gJhHRYTXOBIBABghA5Q9CVT2q6PsJsAwj6AGosqxUfYIOVX0q+slAAAPkAEgR6p/qpMBQhEAgJHlew5wKRjlNQE6/zEBQsl3kDT+b0kAAMJdDADRmP5nGI6TOAQAINZCIJNAlNQEsPiHepW9EMj4v5kAAITLAFAG1T9NKDsDMEsAAMaX6TlASUQBTQBL/+mW8T9rAgDQX+SLATI9scEcah3GE/nImYox/gsAwLwsBII0mwAW/9A0C4HKJgAAEfsALgWjbKp/qiv1KJo2/gsAQHURxkpIpwlg9T/pMP5nSgAAgi4EKnVyi7JZ/EObSl0INB3+OyIAAHEXApV3ViMXzf0wsMqGesU8oqZKH/8FAKAexQ+X0DmLf0iT8T87AgAQtwkQc2aLgpsADmmaUORxNV3iixqeAADUlgHKmwQq7xWRrwXzQPCChkYFvHPOVHGvaEsCABB6xFQzkUUTwOIf0mf8z4gAAERfCAQFiFzK0A7HWEkEACD6JFCol0OOTQDT/+SisAFzqqyXsyUBAIjeBDCtRe4cw7SjvCNturhXNCQBAKhfwbMmULuwJQhFMv5nQQAARlZeE2Aw5zNSJj/QpmjH21Sh478AAIyjsFuCRjulUcwR6NClfYXdEnQ65JdIAAAAgEAEAGBMhTUB4rwWipmGjDlzSQoKawLEeS2bCQAAABCIAACMr6SrgU2mktdB6IilWyUdgdMFvZYhCQBAg4rsnAKwION/ygQAgKE4mdGCgDORkL6p4sZ/AQCopKRLgdVe5MKxSgpKuhR4Oth3SgAAgIREK0SA9gkAQFUlXQoM6ZMQSIejMVMCANC4jLrAQV4IKXOYUZJijuepUl7ILAEAqEExTQCzWSTOIUpqijkmp0t5IcMQAIA2FDZ3Ag3xTaE8juoECQAAABCIAADUo5hVQIOZyqJDoZYokJEgR+ZUQeO/AAC0JJehM8iZjATl8h2BUo/t6TDjvwAAAACBCABAbYKsAoJOxJmbJEeOz7wIAEB7cukCQ/t8OyibIzwpAgDAaJzGAGKaKmX8FwCAOpWxCkgvm9Q4JklfGUfpdBGvYkECAAAABCIAAK0qpn8KNfK9IALHeToEAKBmZawCgnQEWZNAARyruRAAAAAgEAEAYOR5LI1sgFJNBxj/BQCgbWWMnlAX3wjicLQnQgAA6ucyAKiLRdXkxRGbBQEAAAACEQAAACAQAQDogGWgMMt3gWgc8ykQAIBGuAwAqrOcmhw5btMnAADEvRMcAAHHfwEAAAACEQAAACAQAQAAAAIRAIBuFLCGEiryLSAmR37nBACgKW4EBFW4lQr5cvQmTgAAAIBABAAAAAhEAAAAgEAEAAAACEQAAIj7Y5AABBz/BQAAAAhEAAA6k/sMClTh+Ccyx3+3BACgQX4KAMbjNurkzjGcMgEAAAACEQAAACAQAQAAAAIRAAAAIJAlg//sGm2AmINkwS8tC95/SNxUzl/SRZOTk13vAwAA0BJLgAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAlngl4Cnp6fb2hNoQ9a/20eC0h8kxz7mc39p6f/M5dlnn531+58jpwBqNJ38l3TAAb9AAIBoples7HoXSjO1fl3WAygQhOGo5cTlDe+QJUAAABCIAAAAAIEIAAAAEIgAAAAAgQgAQGdXAAPzcb8acucYTpkAAHTGLSCILP0blUJzjP/dEgAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQCApvgRAKjCbdTJl6M3cQIA0A03gQY/BUBMxv/OCQAAABCIAAAAAIEIAAAAEIgAAAAAgQgAQCPcAgiqcysVcuS4TZ8AAHTALSBglhsBEY3xPwUCAAAABCIAAABAIAIAUD8XAEBdLKcmL47YLAgAQNssAIUtuQyAOIz/iRAAAAAgEAEAAAACEQCAmrkAAOplUTW5cKzmQgAAWmUBKPRyGQARGP/TIQAAAEAgAgBQJ+t/oAlWVpA+R2lGBAAAAAhEAADaYwEozMdlAJTN+J8UAQCojfU/0BzrK0iZ4zMvAgAAAAQiAAAt0f+FwawColTG/9QIAEA9rP+BplllQZocmdkRAAAAIBABAGiD/i8MwyogymP8T5AAANTA+h9oh7UWpMYxmSMBAGic6R8YniYAJTH+p0kAAKoy/Q9tMuFKOhyNmRIAAAAgEAEAaHb6X/8Xal8FZNqVFCx4HBr/kyUAAABAIAIA0CDTPzAelwKTO+N/ygQAYHwu/4WuWAVEtxyBWRMAAAAgEAEAGJPLf6FRLgUmWS7/zZ0AAAAAgQgAwDhM/0MLNAFIkOn/AggAwMhc+wvpkAFok+OtDAIAUD/TP1AX9wMlL8b/LAgAwGhM/0NqTMrSDkdaMQQAoGamf6BemgDkwvifCwEAGIHpf0iTqVma5hgriQAA1Mn0DzRBE4D0Gf8zIgAAw3LrT+iQW4LSIbf+LIwAAAzF4h9InwxAExxX5REAgHqY/oGmWQhEmoz/2REAgIWZ/odcmKylXo6oIgkAQA3Vv+kfSKcJoGKjLsMcS8b/HAkAQFVGf2iThUCkw/ifKQEAGMTiH8iRJgDVOYoKJgAA87L4B9JkIRBNs/inbAIA0J+5f8idDMB4HDnFEwCA8Zn+ga64EoBuGf+zJgAAfVj8A+mzEIgmWPwTgQAAzKX6h1zIANRL9R+EAAD8H5b+Q3lkAIbhOIlDAABGZvoH0uFiANpk/C+DAAA8wOIfyJGFQFRn8U8oAgDwv1T/kC8ZgCpU/9EIAMDPWfoPEcgA9HJUBCQAAMNW/6Z/oICLAVR7jHE8GP8LIwBAdKp/KIYMwEhU/2EJABCa6h8KIwMwJNV/ZAIAxKX6hyLJACxI9R+cAABBueoXkAFi8rkjAEBEw1f/pn+g7F8HUwtGM/wnbvwvmAAA4aj+IQIZgF6qf2YJABCL6h/ikAHYkuqfzQQACET1D9HIAMxS/bMlAQCiUP1DTDIAqn/mEAAgBNU/RCYDRKb6p5cAAOVT/QMyQEyqf/pa0n8zEO9m/0Z/KNvk5OTZZ589fNVoTMjaSEHOZx2NDgAUS/UPjN0H0ArImuqfwQQAKJPqH+hLBiie6p8FWQIEoUt/oz8ENPxaIMuB8jJqYPOxhqUDAEVR/QO19wG0ArKg+md4AgCUQ/UPDE8GKInqn5FYAgQlUPoDY2cAy4GypvRnDDoAkD3VP1CFVkC+VP+MRwcAApX+Rn+g+mXBWgEpGCOG+bzYTAcAcqX6BzrsA2gFdEj1T0U6AJAfpT+QwiUBWgHtU/pTCwEACi/9jf5Ao8uBxIB2jNdv8aHQlwAAJZf+Rn+gnQwgBjRn7KVWPgvmIwBABkz8A+kvB5o1NTVl8KmRiX+aIABA0kz8Ax3SCuiQiX+aIwBAaaW/0R/oPAOIAVVUub2SN5xhCABQTt1v6AeSWg60ZS1rdGr6tqreYYYnAEAqlP5AqTFAQ2AwpT8tEwAg+9Lf6A+kvyJolhhQ+4+peTMZgwAAGdf9hn4gu1aAdUF1/Yhy2HeP6gQAyLLuN/QDuceAgEmglro/zttFcwQAyKzun2X0BwpYERQkCdRV9xf8FtEyAQByqvsN/UCRrYAik0C9dX8Z7wmJEAAgg6J/lqEfSFBdpf+A6jmj0a/2oj+7d4AsCACQdNE/y9APxCn9swsDDRX9yb5eCiAAQHLl/pYM/UDk0n+YarvlcbLRcn9Lxn+aIwBAEoX+HMZ9IE0dlv6jVuQVB9LWCv05jP+0QACAJCr+zQz9QJoSLP3rreC7qvg3M/7TGgEAkmDcB8ou/TePcp3X2akx/tM+AQA6ZugHgpT+W/6/YoDxnw4JANAN4z4QrfTv+6eAScD4T+cEAGiVcR8IXvqHTQLGf9IhAEDjDPpAFlou/Qf8h8WEAeM/aRIAoBEGfSAj3Zb+hYUB4z/pEwCgNgZ9IDuplf6ZhgHjP3kRAGBMhnsga+mX/sM8XSeRwPhP7gQAWICBHihMjqX/qLtRSzBI5DVC7QQAeICxHihbSaV/vb2CLF4U1EUAAIDyxSn9gQUJAABQMqU/MIcAAABlUvoDfQkAAFAapT8wgAAAAOVQ+gMLEgAAoARKf2BIAgAA5E3pD4xEAACAXCn9gTEIAACQH6U/MDYBAAByovQHKhIAACAPSn+gFgIAAKRO6Q/USAAAgHQp/YHaCQAAkCKlP9AQAQAA0qL0BxolAABAKpT+QAsEAADontIfaI0AAABdUvoDLRMAAKAbSn+gEwIAALRN6Q90SAAAgPYo/YHOCQAA0AalP5AIAQAAmqX0B5IiAABAU5T+QIIEAACon9IfSJYAAAB1UvoDiRMAAKAeSn8gCwIAAFSl9AcyIgAAwPiU/kB2BAAAGIfSH8iUAAAAo1H6A1kTAABgWEp/oAACAAAsTOkPFEMAAIBBlP5AYQQAAOhP6Q8USQAAgLmU/kDBBAAAeIDSHyieAAAAP6f0B4IQAACIrpbSX/UP5EIAACAupT8QkAAAQERKfyAsAQCAWJT+QHACAABRKP0BBAAAQlD6A2wmAABQMqU/wBwCAABlUvoD9CUAAFAgv+oFMB8BAADmUvoDBRMAAOABSn+geAIAAPyc0h8IQgAAIDqlPxCKAABAXEp/ICABAICIlP5AWAIAALEo/YHgBAAAolD6AwgAAISg9AfYTAAAoGRKf4A5BAAAyqT0B+hLAACgNEp/gAEEAADKofQHWJAAAEAJlP4AQxIAAMib0h9gJAIAALlS+gOMYfE4/xEAdE31DzAeAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACWTQ5Odn1PgAAAC3RAQAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAAmIjj/wG7p9vKqjJDdAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_242
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color green.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_365
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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ACMZRH4mAUAgBidFoFt5xXAAgBADIvATxYAAGI9FF8E9lwBLAAAxHoOXgQsAABQeBHYawWwAABA4CJgAQCA4ovAHiuABQAAAhcBCwAANFgEVq8AFgAACFwELAAA0GQRWLkCWAAAIHARsAAAQKNFYNUKYAEAgMBFwAIAAM0WgRUrgAUAAAIXAQsAADRcBO5dAQQAADQNga8IAAAIDYHnDyLAOwAA0PwdgVtYAABg+CLwXmQIAAAYHgMCAABCQ+D5lwjwDgAABL4nYAEAgJBF4L8hYQEAgMBFwAIAAEGLwI94sAAAQOAiYAEAgLBF4CUYLAAAELgIWAAAIHAREAAAEBgCAgAAvuX4EQL/Bzx9LDu7jNbQAAAAAElFTkSuQmCC"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is Colorize the top layer of the original shape with the color green.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_356
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color cyan.\nthe 7th action is Colorize the top layer of the original shape with the color red.\nthe 8th action is Colorize the top layer of the original shape with the color red.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_102
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGdUlEQVR4nO3YSw2DABBAQWgwUA3VBCKLJjQgobXAhU/yZs6b7B5fdhgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC4yDjP8++qZcDzres63n0DcL7XBTsAgIcRAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAiajg5+vu9zLwFOtS373ScAD+IDAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABB09HBbdnPvQQAuIwPAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIaeP3YgCzC+NJnZAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 4th action is Colorize the top layer of the original shape with the color green.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_162
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color green.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_51
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color yellow.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_43
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is Colorize the top layer of the original shape with the color white.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_161
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_253
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color white.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_32
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_435
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color purple.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_35
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color green.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color green.\nthe 8th action is Colorize the top layer of the original shape with the color cyan.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_311
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_3
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"type": "image_url"
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{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color white.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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AAEMkIAsAkEEJP6D5ArEwAAAAhk5ABgEwggJvUfIEsmAAAAEEhHAcAmEEBM6j9AfkwAAAAgkE4DgE0ggJjUf4DMmAAAAEAgowgANoEAYlL/AXJiAgAAAIGMLgDYBAKISf0HyIYJAAAABDLqAGATCCAm9R8gDyYAAAAQSDcBwCYQQEzqP0AGTAAAACCQLgOATSCAmNR/gNSZAAAAQCDdBwCbQAAxqf8ASTMBAACAQHoKADaBAGJS/wHSZQIAAACB9BoAbAIBxKT+AyTKBAAAAAIpIADYBAKISf0HSJEJAAAABFJMALAJBBCT+g+QHBMAAAAIpLAAYBMIICb1HyAtJgAAABBIkQHAJhBATOo/QEJMAAAAIJCCA4BNIICY1H+AVJgAAABAIMUHAJtAADGp/wBJMAEAAIBASgkANoEAYlL/AZrPBAAAAAIpKwDYBAKISf0HaDgTAAAACKTEAGATCCAm9R+gyUwAAAAgkHIDgE0ggJjUf4DGGlf3AqAUeguAmNR/GNGYvvLNmTNn+G+YOru/gmWQmTJK/Ih7lsCoqP+UQf2HHpkAkADbOQAxqf+Q6gTAJhCplHs7QFA49Z/Oqf9QDRMA6meDByAm9R9yngDYBCKJom8HCMqg/rM29R9qZwJA9KIPQNnUfwg6AbAJFFNaRd8OEJRE/Q9I/YfGMgGgFGnVfQCKov5D81U6AbAJlL3U674dICiP+p839R8SYgJAnnX/c1PbdxL/b1HjlgqQrgbW/3VFTS0+1BYABgYGht8EWjRvrk2gVNRb99fV4gPNpP7npN76P+I0CRieCQAJ1H29PkDM+q/Xh0wCgE2gdFVW+nX8kCX1P12V1X8dP1TABIBG1H0dP0DM+q/jhygBwCZQKkot/Zp+CEj9T0Wp9V/TD/UyAaDS0q/pB4hZ/zX90By1BQCbQM2k7wfKpv43k74f4jABoKzSr+kHiFn/Nf3QcHUGAJtAWZZ+fT8wIvU/y/qv74dUmACEVmDp1/cDxKz/+n5Izth6337Ez+Vu4GeM52HRvLlF/Ww/N7Vf9w+MlvqfQf2f8weFvBRQJROAcArs+wt5HQCqUWDfX8jrAEEnADaBUtz1seUPFEL9T67+2/KHPJgARNF76df0A8Ss/5p+yEz9EwCbQM3f+LHlD5RE/W94/bflD1kyAciZXX+AmOz6AwkEAM+ELlbvW/7FrQVgOOp/sXrf8i9uLUBDNSUA0JDqr/UHiFn/tf4QRyPuAVjNSdB6j3s66A/URf2vt/476A/RmADko5fWv+i1AFCdXlr/otcCJKBBEwCbQNVv/Nj1BxpC/a+4/tv1h8iaFQDogo1/gJhs/AOZBACbQJ2z8Q/kRP3vnI1/oBfuAUhV161/CWsBoDpdt/4lrAVIUuMmADaBStr4sesPNJ/6X0b9t+sPJBAAGIaNf4CYbPwDmQcAm0Bt2fgHsqf+t2XjHyiQewBybv3LWQsATW/9y1kLkImGTgBsAq1N9w+Eov6vofsHymACkFv11/oDxKz/Wn8g+QmATaAunvag+wfyoP7r/oHymAA0lNYfICatPxB6AhB2E0j3D6D+d0L3D2QYAALS/QPEpPsHqpFAAIizCTTaQ5+e8Q/kTf1fF8/4BzIPAEHY+AeIycY/ULE0AkD2m0C6f4C21P8hdP9A7zwFqH6jPfZT5loAqM5oj/2UuRYgkDQmABlvAun+AYan/uv+gaABIEu6f4CYdP9AjVIKAJltAnW+Wk/7AYILW/897QeIHgByMqruv+S1ANDQ7r/ktQBBJRYA8tgE0v0DjFa0+q/7B8rjKUCVcugfICaH/oHmSGwCkPQmkO4foBdB6r/uHyhbegEgUbp/gJh0/0DTJBkAktsE0v0DFCLv+q/7B6rhHoDSueUXICa3/ALNlOQEIMVNoBHp/gFi1n/dP1CxVANAKjr8PaT7B4hZ/3X/QPUSDgDN3wTS/QOUIZv6r/sHapFwAGg43T9ATLp/oOHSDgCN3QTS/QOUKvX6r/sHauQpQDV3//9vUWI3qwGwLrr/hCIiRDamL30jVtKps/sbu/cvADSKXxiQlhTrv+6/mXVb/ScUE4AiOfkDEJPuvxradChEDhOAhmwCddf9mwA0il8tkJyE6r/uv8mVWf0nFBOAYtj7B4hJ918G7TiUKu2nADX/cRAAlEr9z8bAWupeC2TOBKAAtv8BYrL93zvtPlQvkwlAjZtAun+AejW8/uv+27LZDzUyAeiJ7h8gJt1/1zT9ULt8JgDVbwLp/gEaopn1X/e/Nlv+0BwmAOXqsfvv7xceCjZ3rtsBgSro/teoq+kf8jtU/YdsA8DAwMDwNXfRvLmFPBO6k+0fe/8AMeu/7r/Kvt9mGUQPANXQ/QPEpPuvvfXX7kPvMgwAZW8CeaQ0QDOp/7m2/pp+KFaGAaAJbP8DxBR2+7/w1l/TD+XJ6ilAFTwOwuEfgCart/7H7P6LfbZP//8q6gWBViYAo6D7B4hJ978uRbX+On6oUp4TgDI2gRz9BEiC+p/Qxr/9fqiFCUCRbP8DxBRq+7+Qvr+gtQDdyHYCUOwmkMM/AAmpuP7r/jtnvx+awARgZLp/gJh0/8W2/sWtBehJzhOAUh8HAUCTqf8NOe7vlD80kAnACGz/A8Rk+3+1Xlr/otcCFCPzCUCPm0C6f4B0lV3/df/rYssfGs4EoCe6f4CYsu/+bfxDxvKfAHS9CeR4KEDq1P/u2PiHvJkAtOfwD0BMDv900f3r+yEtISYAZTwOQvcPELP+Z9z9d/G0H7v+kKIoAWBUDH8BYopc/238QxyBAkCHm0AO/wBkpsD6n+v2v41/CCVQACiK7h8gJt3/alp/SF2sm4AHBgaGL9+Rh78AGVP/29L6Q0wmAKNj+x8gpvy2/3X/EFa4AND1J5sAkDT1f226f4gs1hGgHtn+B4gps+3/UXX/Wn/IT7gJQNebQLp/gJj1X/cPZCZiAACAmHT/QNwAMNpNINv/ADHrf07b/53/2T3mH/IWNAAAQCij6v5LXgtQs7gBoPNSaPsfIGb9z2b7X/cPrC1uAACACHT/wBChA0AnNdH2P0DM+p/H9r/uH2gVOgCMWNx1/wAx67/uH8hY6AAAALnS/QPrEjcA2P4HiCnC9r/uHxhG3AAAAMHp/iGmoAHA9j9ATLb/19D9Q1hBAwAAZEn3D4woYgCw/Q8QU/bb/7p/oBMRAwAA5Ef3D3RIABjK9j9ATKlv/3dC9w9EDAAR6jsA0ep/J9v/un8gaAAAgMzo/oFRiRUA3P4LEFPGt/92/plfABEDAAAEZPsfCBoAbP8DxBR8+1/3D8QNAACQE90/0B0B4I9s/wPElOj2v6P/QNeiBIBE6zsAPYpc/23/A6EDAABkw+EfoBchAoDbfwFiyvj23+Hp/oHoAQAAsuH0P9AjAcD2P0BQKW7/O/wD9C7/AJBifQegdzHrv+4fGNG4kb8FsjB37tzO2wUTdqCBGlWaOimqCUkxLjbq7wNpiR4AnP/JVY+/mVp/E6izkJkUG74R2f4HOpF5AMiyvlPLdtTaf5eEAWi+/Or/iJVH9w90KPMAMDzb/3mofgztpBCkLrl4oNoABQodAEhaE46fSgJAQ9j+BzqXcwBIboOHhFr/tn/ZxABoiMzqv9oCFCvnADA853+S08C+fwgDAUhCZvHA9j8wWnEDAAlpfus/hIEAUBSVBChcth8Elt8GT1jJdf9r+EsItYj2T8/2PzBaQScAzv8kId3Wfw2jAGiatOKBR38CZQgaAAjY+vdPnfb7V160cMTvGfHbRksMAKJpYDIZ/jdLAxecx0YYzZRnAEhrg4eS6t2abr73/7aQPDBnzhwZAMqWU/23/Q+UJM8AQNjuv5emv8OX7SUMyAAAQO0iBgA3AOTX+pfU9w//Xt0lAceBoEY5zQds/wNdy/YpQATp/vunTquy+y/qrXPqQoAy2CYAypNhANBaBen+a2z9C1mGv6hQOP+sAIIGgOE5/5NB99+Q1r/3JWlWoEoJ/Ytz+y9QqnABgKS7/wa2/j0uL6GOBADIQ8SbgEm09e9LRCcfOLA2twUDo2L7H+hRbhMA+6lJyLj7X8MoACqWzT8i2wFA2WJNANwAkJwUW/+uRwFAebKJB7b/gd7lNgEgp+3/pLv/Lv4U2TQoQNds/wMVEACoVLTufzUZAABojqwCgOYpj+6/4Y/66U7nfyh/jaELQf7hOP8DFCKrADA8NwCk0v335UsGgFqk8m/K+R+gGoECADXS/a8hAwAA9RIAaIoI3X+0PylQIOd/gKIIADRi+z9aT9zJn9cQAEJx/geoTD4BQLfUTLr/dZEBoCj+pQAEDQDDcwdwEp/4SyudDfQoj39Ezv8ABYoSAGismNv/q0X+swMAdREAKIvDP51wEAhwAwBQMQGA2uj+V/NzAIbn/A9QLAGAUjj9XyxDAACgKGMjtEfuAK6Ywz+j5SAQdG34fxr+4QBkGwBIi+6/lZ8JhOUGAKBiAgAFc/inPPYyISA3AACFEwComq3udfGTAQAqIAAAAEAgAgCVnv+xyd3jz8cpIMiMGwCA6gkAANBQbgAAypBDAPAM0Iaw/V8IQwDonGeAAgQNAAAAQIcEACpi+79zflYAQHkEAIrh8f9VcrABAOiaAEAVbGmPlp8YROARQEAtBAAAaCKPAAJKIgBQAOd/qucUEADQHQGA0jnN0h0/NwCgDAIAAAAEIgAAAEAgyQcAHwNcOzcA1MVtAATnY4ABggYAGs5B9l746QEAhRMAAKAGPgQAqIsAAACN40MAgPIIAAAAEIgAAAAAgQgAlPgIIPew9m74n6HnnAAAoyUAAABAIGPsIELDRxZzFy0c5qseJELX1H9ImvpP18Z1/59CdoZvtQEAMuAIEAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAICN8ENjU2f1VrSSoRfPmDvPV/v6m//znzp2b2QfrAqup/2XLvP43b/3JLXjENUPXfBIwND20SCwAQIEcAQIAgEAEAHoy/MzU1nXvhv8ZDgwMVLgWACAHAgAAAAQiAAAAQCACAAA0jse/AOURAACgBh60CtRFAKBc7gPuhZ8eAFA4AYBeNfPDUyLwCCAAoAsCAAAABCIAAABAIAIApXOQvTt+bgBAGQQACuA2gOq5AQAA6I4AAABN5KMAgJIIAFTBaZbR8hODCHwUAFALAYBiOAVUJed/AICuCQBUxJZ25/ysAIDyCAAAABCIAEB1p4BsbHdixJ+S8z8AQC8EAABoKA8CAsogAFAkQ4Ae2f6HaDwICKieAAAAAIEIAFTNEGBd/GQAgAoIABTMBwKUx/kfCMhtAEDhBABqYKu7lZ8JhOU2AKBiAgD1DAH0u6P9adj+BwAKIQBQCgeBiqX7BwCKIgBQG0OA1fwcgOG5DQAolgBAWRwE6oTDP4DbAICKCQDULHIGiPxnBwDqIgBQIncC9M72P+AUEFAsAYByOQi0Lg7/AAC1EAAonQzQSvcPDOE2AKAyAgBNEScDxPmTAgVyCggoigBAg24GiNAZd/hntP0PAJREAKAiMoDuHxieU0BANQQAmpgB8osBnf+hdP/AujgFBBRCAKChDwbNKQN0/mfR/QMAZRMAqFq0DKD7BzrnFBBQAQGARkv6OFDSiweaySkgoHcCAAl8QnCKbfRo12z7H1jNEAAo27jS3wHWnQE638pa3U/3T53W13haf6BUc+fOHe02CsDaTABIbBTQ5GlAF8vT/QMAFRMAqFkX+1gNjAHdLUn3D3R3CsidAEAvBADq190suyExoOtl6P4BgFoIADRC1+dZa4wBvby17h8YnluBgfK4CZhUbwte25pGvIK7hHvMG1p/oBBuBQa6JgDQLP39/b2cbV27Oy8wDBQ1ZND9AwC1EwDILQOsq2sfVR4o41iR7h8Ylamz+xfNG64YGgIA3REAyO04UI89vdYfoHfJPacouQVDL9wETHP1/0Ffygb+oO5VAKnyPFCgDAIATZduBtD6AxWQAYDRcgSIoCeCSqX1Byq7EwBgtAQA0hsFNDYJ6PuBWrgbGBgVAYD0NHAgoPUHymMIABRLACBVTRgI6PuBhjAEADonAJC86pOAvh+omCEAUCABgHysvftVeBjQ9AP18rlgQFEEAPLU+ltwVJFAuw+kSAYAOiEAEEUntw7r+4Ema9RBoBSThl8BsJoPAgOAfDTqCWlAMwkAAJCMqbNH3neXAYDhCQAAkFsGABiGAAAAuTEEAIYhAABAYhwEAnohAABAnmQAoC0BAADS404AoGsCAAAkyUEgoDsCAACkSgYAuiAAAEDmZABgbQIAACTMzQDAaAkAAJA2B4GAUREAACB5MgDQOQEAAKKQAQABAABi3QwgAwACAABkQgYAOiEAAEA+ZABgRAIAAGRFBgCGJwAAQFAyAMQkAABA3E8HkwEgIAEAADIkAwDrIgAAQJ5kAKAtAQAAsiUDAK0EAADImQwADCEAAEDmZABgbQIAAORPBgDWEAAAIIRRZQAxADImAABAFJ1nAKMAyJgAAACByACAAAAAsYw2A4gBkBkBAADCGVUGMAqAzAgAABCRDABhCQAAENTU2f2OA0FAAgAAhGYUANEIAAAQXRcZQAyAdAkAAMCoM4BRAKRLAAAAurklwCgAEiUAAAC9jgLEAEiIAAAA9JoBxABIiAAAABRwHGg1GQCaTwAAANozCoAsCQAAQMEZQAyAJhtX9wIAgAQywKJ53XTzazJAf3+XQQIonAkAAFDiXQGrGQhAcwgAAECneskAYgA0hCNAAEBFJ4JWcy4I6iUAAAA1xABJAOoiAAAAXZo6u7/HDLCaJABVEgAAgJpHAWtIAlABAQAAaFYMGPKJwsIAFEsAAAAaGgNWEwagWAIAAJBADFit9SmiIgGMlgAAAJT4iQElJYE11vXBAoIBrIsA0Gg+LQWA1JU6EBiG36GwLgIAAJDPQAAY0diRvwUAoCBTZ/evCQNALUwAAICqGQhAjQQAAKA2kgBUTwAAAOq39rkgYQBKJQAAAM0iDECpBAAAoLmEASicAAAApEEYgEIIAABASrT+0CMBoGaehVxL6R8YGChoLQBUR/2HQggApETpB4hJ/YcCCQCkQekHiEn9h8IJADSd0g8Qk/oPJREAaC6lHyAm9R9KJQDQREo/QEzqP1RAAKBZlH6AmNR/qIwAQFMo/QAxqf9QMQGA+in9ADGp/1ALAYA6Kf0AMan/UCMBgHoo/QAxqf9QOwGAqin9ADGp/9AQAgDVUfoBYlL/oVEEAKqg9APEpP5DAwkAlEvpB4hJ/YfGEgAoi9IPEJP6Dw0nAFA8pR8gJvUfkiAAUCSlHyAm9R8SIgBQDKUfICb1H5IjANArpR8gJvUfEiUA0D2lHyAm9R+SJgDQDaUfICb1HzIgADA6Sj9ATOo/ZEMAoFNKP0BM6j9kRgBgZEo/QEzqP2RJAGA4Sj9ATOo/ZEwAoD2lHyAm9R+yJwAwlNIPEJP6D0EIAPyJ0g8Qk/oPoQgAFFP6VX+AFKn/EJAAEJ3SDxCT+g9hCQBxKf0AMan/EJwAEJHSDxCT+g8IAOEo/QAxqf/AGgJAFEo/QEzqPzCEAJA/pR8gJvUfaEsAyJnSDxCT+g8MQwDIk9IPEJP6D4xIAMiN0g8Qk/oPdEgAyIfSDxCT+g+MigCQA6UfICb1H+iCAJA2pR8gJvUf6JoAkCqlHyAm9R/okQCQHqUfICb1HyiEAJASpR8gJvUfKJAAkAalHyAm9R8onADQdEo/QEzqP1ASAaC5lH6AmNR/oFQCQBMp/QAxqf9ABQSAZlH6AWJS/4HKCABNofQDxKT+AxUTAOqn9APEpP4DtRAA6qT0A8Sk/gM1EgDqofQDxKT+A7UTAKqm9APEpP4DDSEAVEfpB4hJ/QcaRQCogtIPEJP6DzSQAFAupR8gJvUfaCwBoCxKP0BM6j/QcAJA8ZR+gJjUfyAJAkCRlH6AmNR/ICECQDGUfoCY1H8gOQJAr5R+gJjUfyBRAkD3lH6AmNR/IGkCQDeUfoCY1H8gAwLA6Cj9ADGp/0A2BIBOKf0AMan/QGYEgJEp/QAxqf9AlgSA4Sj9ADGp/0DGBID2lH6AmNR/IHsCwFBKP0BM6j8QhADwJ0o/QEzqPxCKAPB7Sj9ATOo/EFD0AKD0A8Sk/gNhxQ0ASj9ATOo/EFzEAKD0A8Sk/gOECwBKP0BM6j9AuACg9APEpP4DhAsASj9ATOo/QLgAoPQDxKT+A4QLAEo/QEzqP0C4AKD0A8Sk/gOECwBKP0BM6j9AuACg9APEpP4DhAsASj9ATOo/QLgAoPQDxKT+A4QLAEo/QEzqP0C4AKD0A8Sk/gOECwBKP0BM6j9AuACg9APEpP4DhAsASj9ATOo/QLgAoPQDxKT+A4QLAEo/QEzqP0C4AKD0A8Sk/gOECwBKP0BM6j9AuABQSOlX/QGSo/4DhAsASj9ATOo/QLgAoPQDxKT+A4QLAEo/QEzqP0C4AKD0A8Sk/gOECwBKP0BM6j9AuACg9APEpP4DhAsASj9ATOo/QLgAoPQDxKT+A4QLAEo/QEzqP0C4AKD0A8Sk/gOECwBKP0BM6j9AuACg9APEpP4DhAsASj9ATOo/QLgAoPQDxKT+A4QLAEo/QEzqP0DEAFBI9Vf6AZKj/gPkqvhPAl6b0g8Qk/oPEC4AKP0AMan/AOECgNIPEJP6DxAuACj9ADGp/wDhAoDSDxCT+g8QLgAo/QAxqf8A4QKA0g8Qk/oPEC4AKP0AMan/AOECgNIPEJP6DxAuACj9ADGp/wDhAoDSDxCT+g8QLgAo/QAxqf8A4QKA0g8Qk/oPEC4AKP0AMan/AOECgNIPEJP6DxDKmMHBwbrXAAAAVGRsVW8EAADUTwAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQMbVvQCozooVK2644YZrr732l7/85YIFC+6///6nn356yZIlzz333MSJEydPnrzllltuvfXWO++886677rrnnntuv/32dS8ZAKBgYwYHB4t+TWiWFStWXHDBBaeccsrll1++fPnyzv/DHXfc8fDDD3/HO96x4447lrlAAEbtzDPPHNX3jxkzZuzYseutt96ECRMmTpy48cYbb7bZZtOnT584cWJpa4SGEgDI2dKlS7/61a9+4QtfWLhwYS+vc8ghh3ziE5942cteVtzSAOjJmDFjCnmdbbbZZsaMGbvtttvee++91157bbjhhoW8LDSZAEC2zjzzzA996EMPP/xwIa82duzY97///Z/97Gf9bgDIKQCsbcKECfvtt99b3vKWww47bPz48YW/PjSEAECGHnvssaOPPvq8884r/JVf/OIXn3feeS9+8YsLf2UAag8Aa2y99dbHHnvsBz7wAQeEyJIAQG5+/vOfH3LIIb/+9a+H+Z4XvehFu++++84777z55ptvtNFGy5Yte/zxxxctWjR//vzrr79+0aJFw/y3U6ZM+d73vrfHHnuUsHYAGhEAVtt2220///nPH3nkkWW/EVRMACAr11133f7777948eK2X91mm23e+973vuUtb3n+85+/rlcYHBycP3/+f//3f59yyilPP/102++ZMmXKlVdeudtuuxW3cAAaFwBWmzNnzoknnrjppptW83ZQAQGAfPzkJz/ZZ5992nb/G2+88cc//vEPfvCDnZ/pfPLJJ48//vgTTjih7b+RbbbZ5sYbb9xyyy17XjUAhQWA4buaZ599dtWqVUuXLn366acXLlx4zz33/OxnP7vpppt+8IMfrGvnaLUXvOAFF1100U477VTEwqF+AgCZuPvuu1/xilc8/vjjrV96xSte0d/f391D/S+//PKjjjqq7Z3E++677/e///2uFgtADQFgXVauXHnFFVd8/etfv+CCC5577rm23zN16tRLLrnE+U/yIACQg6VLl86aNeu2225r/dKhhx7a39+//vrrd/3id9xxx9577902Wpx00knvfOc7u35lAJoQANaYP3/+3//9369rc2eTTTa58sorPRKaDAgA5ODoo4/+1re+1Xr9kEMOOeecc8aN6/UTr2+66aa/+Iu/WLFixZDr06dPX7BgweTJk3t8fQCaEABW+/rXv37ssceuXLmy9UtbbrnlzTff7PwnqRtb9wKgV5dffnnb7n/XXXc9/fTTe+/+Vx8i+vjHP956/aGHHjrxxBN7f30AmuM973nPFVdcMWXKlNYvPfjgg3Pnzl21alUd64LCmACQthUrVuy8886/+c1vhlyfNGnSrbfeuuOOOxb1Rs8888zuu+8+f/78Iddf8IIX3HXXXWPHytIAmUwAVrv++utf//rXL126tPVLX/ziFz/84Q8X9UZQPV0LaTvxxBNbu/++vr7PfOYzBXb/fX1948ePP/7441uv33333dddd12BbwRAE7z61a/+5je/2fZLxx9//P3331/5iqAwAgAJW7Zs2ec+97nW6zvttNMxxxxT+Nu96U1v2mabbVqvn3vuuYW/FwC1O/LII//yL/+y9frTTz/d9rcPpEIAIGHf/e53H3roodbr//Iv/7LeeusV/nbrrbfee97zntbrV111VeHvBUAT/Ou//uvEiRNbr3/zm99s+wsIkiAAkLCTTjqp9eIOO+zwpje9qaR3POigg1ov3n777UuWLCnpHQGo0bbbbvsP//APrdeXL19+8skn17EiKIAAQKruuOOOm266qfX6+9///vJuyd11112nTZs25OKqVavuvPPOkt4RgHr97d/+7YQJE1qvn3rqqXUsBwogAJCq8847r/XimDFjjjzyyPLedMyYMfvss0/r9bvuuqu8NwWgRlOmTGk7/v3FH9SxIuhVAY9Ih1pcfPHFrRdnzZq11VZblfq+Rx55ZOtj5jbaaKNS3xSAGr31rW8955xzWq9ffvnlO++8cx0rgp74HACS9PTTT2+yySatH8Xy8Y9//FOf+lRNiwIgn88BWNvKlSunTp3a+pkAhx122Lx588p4RyiVI0Ak6ZZbbmn7QYx77713HcsBIGfrr7/+Lrvs0nr91ltvrWM50CsBgCT99Kc/bXt95syZla8FgPy1/f1yzz33PPXUU3UsB3oiAJCkn//8560Xp0+fvtlmm9WxHAAiBoDBwcFf//rXdSwHeiIAkKT77ruv9eILXvCCOtYCQP5mzJjR9vrvfve7ytcCvRIAyCcAbLnllnWsBYD8bbLJJm2vP/jgg5WvBXolAJCkRx99tPVi60d0AUAhNt5447bXFy9eXPlaoFcCAElqfRZbX1/fxIkT61gLAPmbMmVK2+vLli2rfC3QKwGAJC1fvrz14gYbbFDHWgDI37omACtWrKh8LdArAYAkPfvss60XfaodACVp++EzfX1948ePr3wt0CsBgCRNmDChw7EAAPRuXTv9hs+kSAAgSW2P+7e9MQAAereuD/yaNGlS5WuBXgkAJGmjjTZqvbhw4cI61gJA/h5++OG216dPn175WqBXAgBJ2mqrrVovPvTQQ3WsBYD8ret5/1tvvXXla4FeCQAkqW3Bvfvuu+tYCwD5+9WvftX2+nbbbVf5WqBXAgBJev7zn9968eGHH3788cfrWA4AmfvlL3/ZenHatGmOAJEiAYAkvfSlL217/bbbbqt8LQDk74Ybbmi9uOuuu9axFuiVAECS1lVzf/jDH1a+FgAy9+STT95xxx2t12fNmlXHcqBX43p+BajBjBkzpkyZ8uSTTw65ftVVV/3zP/9zqW/9N3/zN0OeN7r++uufeuqppb4pADW65JJL2n4Q2L777lvHcqBXY3x4KomaPXv2ueeeO+Tieuut99BDD22++eYlvemvf/3rF77whUMubr/99r/5zW9KekcA2hozZkzrxZK6mjlz5px99tlDLm6yySaPPPKITwImRY4Akar99tuv9eKqVavOOeec8t70sssua73YGgkAyMYjjzxy3nnntV4/4ogjdP8kSgAgVbNnz25beb/2ta+V96aXX35568VddtmlvHcEoF5f+cpXnnnmmdbrb3/72+tYDhRAACBVm2+++f777996/bbbbrvqqqvKeMdly5ZdccUVrdf33HPPMt4OgNo99thjX/7yl1uv77HHHq9+9avrWBEUQAAgYe95z3vaXv+nf/qnMt7u9NNPf+KJJ4ZcHD9+/Ote97oy3g6A2n3kIx9ZvHhx6/V//Md/rGM5UAwBgIQdcMABM2fObL1+/fXXn3XWWYW/3Ve/+tXWi/vss8+mm25a+HsBULuLLrro29/+duv1Pffc8+CDD65jRVAMAYC0fexjH2t7/QMf+MCjjz5a4BudffbZt9xyS+v1d73rXQW+CwANsWDBgre97W2t19dbb72vfvWrbZ9BBKkQAEjbm9/85rYncBYuXPi2t73tueeeK+RdnnjiiWOPPbb1+g477HDooYcW8hYANMf999+/7777Llq0qPVLxx13nA8AJnUCAMn7yle+0vZxQJdeeulHPvKR3l9/cHDwfe9734MPPtj6pc9+9rPrrbde728BQHPMnz9/1qxZ99xzT+uXXvOa13ziE5+oY1FQJAGA5M2YMeOzn/1s2y/9+7//+3HHHdfj6x9zzDFnnnlm6/XXv/71c+bM6fHFAWiOwcHBE0888VWvetV9993X+tUddtihv7/fvg8Z8EnA5GBwcPCQQw658MIL2371yCOP/MY3vjF58uTRvuySJUs++MEPfvOb32z90tSpU2+//fZtttmmq/UC0LhPAr7yyiuPO+64G2+8se1Xt9hii2uvvXaHHXbo+vWhOQQAMrF48eLXvva1be/TXb1t86Uvfemggw7q/AWvueaao48+esGCBa1fGjdu3KWXXrrPPvv0sF4AGhEA7rzzzvPPP/873/nO/Pnz1/U922+//WWXXeZz38mGAEA+Hnnkkb322uuuu+5a1zfssccexx577MEHH7zRRhut63sWL1584YUXnnDCCT/+8Y/bfsPYsWNPPvnkto+GAKDeAHDGGWcM85+sWrVq5cqVS5YsWbRo0UMPPbRgwYKf/vSnIz4y7tWvfvU555yz5ZZb9rxkaAoBgKw88sgjhxxyyLp699XWX3/9V73qVbvssssLX/jCKVOmjB8/ftEf/O53v7vhhhvmz58/zLODxo8ff/LJJ7/lLW8pZ/kAdKqCB3GOHTv2wx/+8Gc+85m2j5qAdAkA5GbZsmXvfe97Tz311MJfeYsttjjnnHP23HPPwl8ZgKYFgFe+8pX/9V//tfvuu5f6LlALTwEiNxMnTjzllFPOPffc6dOnF/iyb33rW++44w7dP0D2Zs2adf755//4xz/W/ZMrEwCytWTJkq985Stf+MIXHnvssV5e5w1veMMnP/nJV73qVcUtDYDGTQBmzJhx6KGHHnXUUTNmzCj2laFpBAAyt2zZsnPPPfeUU0656qqrnnnmmc7/wxe96EWHHXbYO97xjhe/+MVlLhCAigLA2LFjx40bt8EGG0yePHmTTTaZNm3atttuu9NOO73kJS+ZNWvWFltsUc5KoXEEAKJYsmTJddddd+211955550LFix48MEHn3766SVLlgwODk6cOHHy5MlbbrnlNttss9NOO82cOXPPPffcfvvt614yAEDxBAAAAAjETcAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgYyZM2dO3WuAphgYGKh7CVAd9R/WUP8JxQQAICgdD0BMAgAAAAQiAADEZQgAEJAAAAAAgQgAAKEZAgBEIwAAAEAgAgBAdIYAAKEIAAAAEIgAAIAhAEAg44b/8tTZ/VWtBKqwaN7cupcAqfIbgaSp/7CGCQAAHQ0B9E8AeRAAAAAgEAEAgD8yBACIQAAAAIBABAAA/sQQACB7AgAAAAQiAADwfxgCAORNAAAAgEAEAACGMgQAyJgAAAAAgQgAALRhCACQKwEAAAACEQAAaM8QACBLAgAAAAQiAACwToYAAPkRAAAAIBABAIDhGAIAZEYAAACAQAQAAEZgCACQEwEAAAACEQAAGJkhAEA2BAAAAAhEAACgI4YAAHkQAAAAIBABAIBOGQIAZEAAAACAQAQAAEbBEAAgdQIAAAAEIgAAMDqGAABJEwAAACAQAQCAUTMEAEiXAAAAAIEIAAB0wxAAIFECAAAABCIAANAlQwCAFAkAAAAQiAAAQPcMAQCSIwAAAEAgAgAAPTEEAEiLAAAAAIEIAAD0yhAAICECAAAABCIAAFAAQwCAVAgAAAAQiAAAQDEMAQCSIAAAAEAgAgAAhTEEAGg+AQAAAAIRAAAokiEAQMMJAAAAEIgAAEDBDAEAmkwAAACAQAQAAIpnCADQWOP6EudXCACwhsYA8g8AU2f3+6cO0EADAwNz5swZ5hsWzZs7dXZ/hSsiE37vQ/QAAADkSq8PZcghABgCADSTIQCj4rc5VCOHAAAApEjHD7XI5ClANpAAmsnjgBhi0by5a/5X91ogKBMAAKBcen1olEwmAIYAAI1lCBCTnX5oLBMAAKAw2n1ovnwmAIYAAI1lCJA9m/2QkHATACEhOL+cAPIuqut68uyIKRTiyC0AjPiZAJ45DVALnwmQk3r7/uH/IgHhAgAAkE3fr9eHMmQYAAwBAJrJECBdlbX+On6oQIYBAABIpe/X8UP18gwAhgAAzWQIkIpSW39NP9QrzwAAADSq9df0Q3NkGwAMAQCayRCgmfT9EEe2AQAAqKX11/RDw2X1ScBDjLiB1MCPLwGIwAcDN0Sxn907538V9YJASUwAACCcYvv+ol4KqEbOEwBDAIDGMgTIYNfffj8kygQAAEIosO8v5HWAumQ+ATAEAGgsQ4DKFLXrb8sf8mACAAA567311/RDZvKfABgCADSWIUDDN/5t+UOWTAAAIDd2/YHoEwBDAIDGMgRo1K6/Z/lDBCYAAJCJHlv/QtcCNFeUCYAhAEBjGQLUu/Fvyx+iMQEAgLT10voXvRYgAYEmAIYAAI1lCFDxxr9df4gsVgAAgGzY+Ae6Ey4AGAIANJMhQOds/AO9cA8AAKSk69a/hLUASQo3ATAEAGgsQ4AyNv7t+gNDRAwAAJAcG/9AUYIGAEMAgGYyBGjLxj9QIPcAAEBurX85awEyEXQCYAgA0FiGAGvo/oEymAAAQA7dv9Yf6FDcCYAhAEBjBR8CdPG0H90/0DkTAABoEK0/ULbQEwBDAIDGijkE0P0DFYgeAACgIXT/QDUEAEMAgIaKMwQY7aF/z/gHeiEAAECdbPwDFRMAfs8QAKCZsh8C6P6B6nkKEADUY7THfspcCxCICcAfGQIANFOuQwDdP1AXAQAAqqb7B2okAPyJIQBAM2U2BOh8tZ72A5RBAACAhnb/Ja8FCEoA+D8MAQCaKY8hgO4faAJPAQKA0jn0DzSHCcBQhgAAzZTuEED3DzSKAAAAJdL9A00jALRhCADQTMkNAXT/QAO5BwAASuGWX6CZTADaMwQAaKbkhgAj0v0DFRMAAKB4HeYQ3T9QPQFgnQwBAJqp+UMA3T/QZAIAABRJ9w80nAAwHEMAgGZq7BBA9w80n6cAkTMJDWhs9z9ihgEoiQAwgqmz+4cv6IvmzR1xUEDZNPoQ0MDAwPD76BXXZ3v/QCoEANKj3QeaRvcPJMQ9ACNzJ0ATLJo3d83/6l4L0BQNuRNA9w+kxQSA5tLrA82n+weSYwLQEUOAytjpB1IcAgAkxASARvAbGkiR7X8gRSYAnTIEKIPNfiDdIYDuH0iUCQD10PQDSdP9A+kyARgFQ4De2fIHMhgC6P6BpJkAUJG6mv4hv4B99CZQjR67//5+HzFZsLlz7T3BHwkAo+ODgRvb99tpg+Aq+2DgTsqaigQ0mQBAkq2/X65ALXT/QAYEgFEzBKir9fc7Fah3COD+JSAPAgBFKvy3o6YfSIuqBTSfpwB1w+OAWhX7bJ85/6uoFwSCKO9xQA7/ANkwAaAARbX+fncCzaT7B3JiAtAlQ4ACN/7t9wNNHgIEqedAHCYAdKmQvr+gtQDUTEEDEmIC0L3IQ4Ae/2j2+4FUhgAO/wD5MQGg6ta/uLUAlEv3D2TJBKAnoYYAvRz3d8ofyOZxQACpMwGgI720/kWvBaAKtv+BXJkA9CrCEKC7P4ItfyDdIYDuH8iYCQDDsfEP0JYqB6TLBKAAuQ4BbPwDMYcAiRZtgA6ZANBeF7//9P1ABhz+AbJnAlCMnIYAXTztx64/EOdxQModkDoBgP/Dxj8QWUKbNQBdEwAKk8EQwMY/EHkI4PAPEIQAwB8ZggMMT90D8iAAFCnRIcBoD/3b+AeS44OBAdYQAKKz8Q/QCdUPyIYAEHoIoPsH4hhxCAAQhM8BiGu0x37KXAtAo6mBQE5MAIIOAXT/QEDdDQHUQCAzAkBEun8AgLAEgHBDgM7f2tN+gPyMdgigDAL5EQBiGVX3X/JaAACogQAQaAig+wcY1RBAMQSyJABEofsHAEAAiDIE0P0DjHYIoB4CuRIA8qf7BxhtuVMPgYwJAJkPAXT/AACsTQDIme4foJXtfyA4ASD/IcCI/KoDAIhDAMhWh7lC9w+EYvsfQADIcwig+wcAoC0BIEO6f4C2bP8DCAAZDgF0/wAADEMAiEj3D9BKbQSCEACyGgJ08gp+wwExqX4AqwkA+dD9AwAwIgEgkyFA7R8mANBkbv8FWEMACMSvNwAABIAchgAO/wAMw/Y/wNoEgOTp/gEA6JwAkPYQwNF/gB7ZIgGiEQDy53cbEJkaCDCEAJDwEMDhHwAARksAyJnuHwjO7b8ArQSAVIcATv8DANAFASBJDv8A9E6dBGISAPL8YGC/1QBUQoC2xrW/TIM16vDPwMBA3UsAoAZz5zbol1FAc+bM8SuYrpkAZDgEsOkFMCKlskf9/SP8/qIkc/6g7lWQNhOAxIyYBxQFAMWQLPlbTVFMAFIaAjTq8A9AujRShTAEqIxdf4plApAV1QEAcuI3O2UwAUhmCGD7H6BDeqbKGAKUx64/5TEByIcyAdAJ1ZKG81eUspkAJDMEAIAGMgQokF1/qmECkAn1AmA19ZAU+XtLlUwAchgCqBoAHVIwy2AI0Au7/lTPBIBYvxJ8dCVAzN8IDaz/+n7qYgKQ/BBA+QBYQ0lsbH/fwP67Rnb9qZcJAABARfT9NIEJQNpDAHUEoHNqZqkMAYZn15/mMAEAACiRvp+mMQFoIp8JANAFbVbtDAGGsOtPMwkACVNTADqnZpJW61/7c5PImADQUIYAAKTIEKCQ1l/3T6ncA5AqW1kAkNnvZX0/1TABaKhF8zLfIAEolm2R5og2BCjkoL9df6pkApAkv+cARkXZpAx2/UmUCUAT2f4HIGnZDwHs+pM0EwAAgE7Z9ScDJgDpMcgGGEJhbKD8hgB2/cmGCUDjOP8DUCzxgB7Z9SczJgAAQCkyGALY9SdLJgCJsY8FABWw60/GTACaxfkfAHKS4hDArj/ZMwEAIG1GoxTFrj9BCAAp8UsOYLRUztr19/cPv80/d+7c2pvmQrb8C1oLlE4AAADontaf5LgHoEHcAABAllK8E6ATDvqTKBOAZJhiA0BD6PtJmgkAAFC6bIYAdv3JgAkAANlOR81OKZC+n2yYADSFGwAAyFu6QwC7/mTGBCANNrEAoHr6frJkAgAAVCShIYBdfzJmAgAA8Cf6frJnAtAIbgAAIIgmDwHs+hOECUAC3AAAAKXS9xOKCQAAqfIM0EQ1eQgAEQgAAAAQiAAAAFTNEABqJAAAAEAgAkD9PAIIgIAMAaAuAkDTuYkNAIACCQAAQD0MAaAWAgAAAAQiAAAAtTEEgOoJAAAAEIgAAECSfAxwNgwBoGICAAAABCIA1MyHAACAIQBUSQBoNCNsAACKJQAAAPUzBIDKCAAAABCIAAAANIIhAFRDAAAAgEDGuM0U1hgYGKh7CVAd9R+S5ncWXTMBAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBAxg3/5amz+/uabdG8uUmvP3XD//z7+xv38587d7gFA2uon2VLrn6Oqpw2cP0lLXjEXys+r5cGMgEAACjLnDlz6l4CDCUAAAB0qYGzDhiRAAAAUCJDAJpGAAAA6J4hAMkRAAAAymUIQKMIAAAAPTEEIC0CAABA6QwBaA4BAACgV4YAJEQAAACogiEADSEAAAAUwBCAVAgAAAAVMQSgCQQAAIBiGAKQBAEAAKA6hgDUTgAAACiMIQDNJwAAAFTKEIB6CQAAAEUyBKDhBAAAgKoZAlAjAQAAoGCGADTZuLoXAABQorlz5/Y10pw5cwYGBupeBRGZAAAAeZr7B3W9uyEAjWUCAADkprG7/kMYAlALEwAAIB/17voPYQhAM5kAAAA5aE7fPyqGAFTPBAAASFujdv2HMASggUwAAIBUNbbvHxVDACpmAgAApKfJu/5DGALQNCYAAEBKUun7R8UQgCqZAAAAaUho138IQwAaxQQAAGi6RPv+UTEEoDImAABAzrv+/X9Q3Iq6X0bdS4A/MgEAAPLc9U+u5zYEoBoCAADQLLm2/v39/RHOMtF8AgAA0BSF9MfN7P47ZAhABQQAAKB+QVp/QwCaQAAAAOoUpPXvnCEAZRMAAIB6xGz9DQGonQAAAFQtZuvfOUMASiUAAADV0fobAlA7AQAAqILWf1QMASiPAAAAlEvr38oQgBoJAABAWbT+vTAEoCQCAABQPK3/iAwBqIsAAAAUrPe+Nu/Wv3OGAJRhbCmvCgDQlf4/6Ishzp+URjEBAAAaQTfcliEAhTMBAABqFmrXf4iwf3BqZAIAANRG+9sJQwCKZQIAANQg8q7/EH4OVMwEAAColH63C4YAFEgAoEQebwxAEq2/X1iE4ggQABC6+0/FnDlz6l4CmTABAADKpfWHRhEAAICyaP2L5U4ACiEAAADF0/pDYwkAAECRtP6lMgSgdwIAAFAMrT8kQQAAAHql9a+SIQA9EgAAgO5p/SE5AgAA0A2tf40MAeiFAEBPps5OrPovmuezHgEKkFn3r5kmFJ8EDAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABDIuLoXABVZNG9u3UsAAKifAED+tP4AAGsIAORM6w8AMIQAQJ60/gAAbQkA5EbrDwAwDAGAfGj9AQBGJACQA60/AECHBADSpvUHABgVAYBUaf0BALogAJAerT8AQNcEAFKi9QcA6JEAQJTWf+rsfhECAEAAIErrDwCAAECjaf0BAAonANBEWn8AgJIIADSL1h8AoFQCAE2h9QcAqIAAQP20/gAAlREAqJPWHwCgYgIA9dD6AwDUQgCgalp/AIAaCQBUR+sPAFA7AYAqaP0BABpCAKBcWn8AgEYRACiL1h8AoIEEAIqn9QcAaCwBgCJp/QEAGk4AoBhafwCAJAgA9ErrDwCQEAGA7mn9AQCSIwBQT+uv+wcAqIUAwOho/QEqMHduAcUWoC0BgE5p/QEAMiAAMDKtPwBANgQAhqP1BwDIjABAe1p/AIAsCQAMpfUHAMiYAMCfaP0BALInAPB7Wn8AgCAEgOi0/gAAoQgAcWn9AQACEgAi0voD1E4VreX318DAQEFrgYQJALFo/QFIkdYfCiQARKH1ByBFWn8onACQP60/ACnS+kNJBICcaf0BSJHWH0olAORJ6w9AirT+UAEBIDdafwBSpPWHyggA+dD6A5AirT9UTADIgdYfgBRp/aEWAkDatP4ApEjrDzUSAFKl9QcgRVp/qJ0AkB6tPwAp0vpDQwgAKdH6A5AirT80igCQBq0/ACnS+kMDCQBNp/UHIEVaf2gsAaC5tP4ApEjrDw0nADSR1h+AFGn9IQkCQLNo/QFIkdYfEiIANIXWH4AUaf0hOQJA/bT+AKRI6w+JEgDqpPUHIEVaf0iaAFAPrT8AKdL6QwYEgKpp/QFIkdYfsiEAVEfrD0CKtP6QGQGgClp/AFKk9YcsCQDl0voDkCKtP2RMACiL1h+AFGn9IXsCQPG0/gCkSOsPQQgARdL6A5AirT+EIgAUQ+sPQNjfX7p/SIsA0CutPwAp0vpDWAJA97T+AKRI6w/BCQDd0PoDkCKtPyAAjJrWH4AUaf2BNQSATmn9AUiR1h8YQgAYmdYfgBRp/YG2BIDhaP0BSJHWHxiGANCe1h+AFGn9gREJAENp/QFIkdYf6JAAUHDp1P0DUDGtPzAqAsDvaf0BSJHWH+hC9ACg9QcgRVp/oGtxA4DWH4AUaf2BHkUMAFp/AFKk9QcKESsAaP0BSJHWHyhQlACg9QcgRVp/oHD5BwCtPwAp0voDJck8APhULwCSo/UHSpV5AOiR1h+AKmn9gQoIAO1p/QGoktYfqIwAMJTWH4Aqaf2BigkAf6L1B6BKWn+gFgLA72n9AaiS1h+oUfQAoPUHoEpaf6B2cQOA1h+AKmn9gYaIGAC0/gBUSesPNEqsAKD1B6BKWn+ggaIEAK0/AFXS+gONlX8A0PoDUCWtP9BwOQcArT8AVdL6A0nIMwBo/QGoktYfSEhuAUDrD0CVtP5AcvIJAFp/AKqk9QcSlUMA0PoDUCWtP5C05AOA7h+Aymj9gQwkHwAAoAJafyAbAgAADEfrD2RGAACA9rT+QJYEAAAYSusPZEwAAIA/0foD2RMAAOD3tP5AEAIAANFp/YFQBAAA4tL6AwEJAABEpPUHwhIAAIhF6w8EJwAAEIXWH0AAACAErT/AGgIAADnT+gMMIQAAkCetP0BbAgAAudH6AwxDAAAgH1p/gBEJAADkQOsP0CEBAIC0af0BRkUAACBVWn+ALggAAKRH6w/QNQEAgJRo/QF6JAAAkAatP0AhBAAAmk7rD1AgAQCA5tL6AxROAACgibT+ACURAABoFq0/QKkEAACaQusPUAEBAID6af0BKiMAAFAnrT9AxQQAAOqh9QeohQAAQJKtv+4foDsCAADV0foD1E4AAKAKWn+AhhAAACiX1h+gUQQAAMqi9QdoIAEAgOJp/QEaSwAAoEhaf4CGEwAAKIbWHyAJAgAAvdL6AyREAACge1p/gOQIAAB0Q+sPkCgBAIDR0foDJE0AAKBTWn+ADAgAAIxM6w+QDQEAgOFo/QEyIwAA0J7WHyBLAgAAZXX/Wn+ABhIAACie1h+gsQQAAIqk9QdoOAEAgGJo/QGSIAAA0CutP0BCBAAAuqf1B0iOAABAN7T+AHkGgKIeAg1ANrT+AEkzAQCgU1p/gAwIAACMTOsPkA0BAIDhaP0BMiMAANCe1h8gSwIAAENp/QEyJgAA8Cdaf4DsCQAA/J7WHyAIAQAgOq0/QF8k/x/CVmmKrttkiAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_447
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color yellow.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color yellow.\nthe 7th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 8th action is Colorize the top layer of the original shape with the color purple.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_446
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_384
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": null,
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Cut the right side of the shape\nthe 8th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_388
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 8th action is Colorize the top layer of the original shape with the color blue.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_137
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_372
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_105
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Colorize the top layer of the original shape with the color red.\n. Please select the correct answer from the options below. The options are: ",
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CT/B1MuDC4DAAWYnvDyH6BUGyX89k3/jcsAQG2/5iv/AQrO/8GMf89lACAjW4p0+Q9QjFkiffuW7stlAKC2D/eU/wCF5f9gjn/mMgAQUJMMl/8A+dpqhm+f+zFcBgBq+0ov+Q9QQP4PGt6LywBAQi2GtvwHyEiT0N7eymO7DACU2vWffgDyHyC7/B+0eKcuAwA96C6l5T9AZG2ldNMJwFq6QQAFt/ynkP8AGeX/oKOHcRkACBX9M8ay/AcoPv/bnACspRsEUHbXfyPyHyB4/g+2+qiLKztXl3dv6TFcBgC6jv7p4bylHJb/AGXn/5YnAKvLuxdXdg7/Y6s/hisBQBfRv6VMnpv8Bygj/wfzNYFG/z3HQ7oMALQY/UNttf+nH4n8Bygg/+cpAMYe1WUAIGH0bxrCLRYA8h+ggPwfNG8CzXgEWzosgEo0jP4u2v9D8h+g1PyfswDY6CBcBgD6jP4u2v9D8h+g1PwftNsEmvGA1uUyAFSirejvrv0/JP8Bisz/+QuATY/JZQCg0+jvrv0/JP8Bisz/QXdNoBGXAYDWo7/r9v+Q/AcoL/8bFQCzH6LLAFCtjqK/6/b/kPwHKC//B/00gUZcBoB6dBf9/bT/h+Q/QGH537QAmOOIXQaA4nUd/f20/4fkP0Bh+T/ovwk04jIAlKeH6O+z/T8k/wFKyv8WCoAmP4DLAFCM3qK/z/b/kPwHKCn/B2mbQCMuA0C++oz+/tv/Q/IfoJj8b6cAaOXncRkAstN/9Pff/h+S/wDF5P8gThNoxGUAiC9J9Kdq/w/Jf4CFIvK/tQKg3R/PZQAIK2H0p2r/D8l/oHJLpeT/IGYTaMRlAIgjbfSnbf8PyX+gTktl5X+bBUBHP63LAJBchOhP2/4fkv9AbZZKzP9B/CbQiMsAUG30R2j/D8l/oBJL5eZ/ywVA1z+8ywBQZ/RHaP8PyX+geEul5/8grybQiMsAUE/0x2n/D8l/oFRLdeR/+wVAb8+FywCQNvfjxF2QAiDOE7Iu+Q9sZKmy/B/k2wQacRkACo7+aO3/IfkPlGGpyvzvpADo/6lxGQBKjf5o7f8h+Q/kbqni/B+U0QQacRkASor+mO3/IfkPZGqp+vzvqgBI+Ey5DADFRH/M9v+Q/AeyI//bKQACNoFGXAaArKM/cvt/SP4DuZD/PRUAEZ44lwEg3+iP3P4fkv9AfPK/kwIgchNo7muAywDUHP1ZxFeQjJL/QFjyP00BEOdJdBmACmUd/fHb/0PyHwhI/vdRAMRvAo24DEANco/+XNr/Q/IfiEP+hygAAj6nc18GXAkgvjKiP5f2/5D8ByKQ/wkKgIyaQCMuA1CSYqI/r/b/kPwHEpL/EQuAyE+xywAUoLDoz6v9PyT/gSTkf/oCIMcm0IjLAOSovOjPsf0/JP+BPsn/DAqALJ5xlwHISKnRn2P7f0j+A/2Q/+EKgKybQCMuAxBZwdGfb/t/SP4DnZL/+RUAeb0ALgMQUPHRn2/7f0j+B3+BIF/yf1fwAqCMJtCIywBEUEP0597+H5L/ubxSkAv5v9BBqvRaAGT6ergMQEL1RH/u7f8h+Z/X6wWRyf/MCoDCmkAjLgPQp6qiv4z2/5D8z/SFgzjkf9cx0ncBkPvL4zIAPagw+sto/w/J/6xfPkhL/uddAJTaBBpxGYAu1Bn9JbX/h+R/Ga8j9En+95kbCQqAYl4tlwFoUc3RX1L7f0j+l/RqQtfk/8LG8isAim8CjbgMQBOVR3957f8h+T9dpi8rtEv+LyTK/zQFQHkvnssAzEH0F9n+H5L/s8j0xYXm5H/a/B/k3gSaO3Zhkotxb0R/2e3/3vI/1JJQBsAs5H+E/N++kEhbwb24slMNAGXnfsHRX2cXo8WN+/DZC7I8hocxxws6PC+UAZRN/ofK/2QFAFAV0U/rRg0gZQBEJv8DGpTxTtAKW2h0waW3C6K/tnf/95n/k09gqGXjTUFUTv6HzX8TAKArop+uTb4L1DQAIpD/wfUxATAEIBcut20R/bMovv2fagjQ7v23xTSASsj/LPLfBABok+inZ1M+CsI0APok/zPS0wTAEIAsuMQ2Ifrzav9UMgRo94HaYhpAYeR/dvlvAgA0JfpJa5bPgzYNgC7I/0z1NwEwBCA+l9WtEv35tn8qHAK0+4htMQ0gU/I/6/yvbgKwsrKS+hBIaXl5OfUhFEL0E8qWvhTSNACakP8F6HUCEGQIoAao2fQCwKV0FqK/jPZP5UOAdh+6LaYBBCf/i8n/6iYAwNxEP8UMAUZMA2AW8r8wfU8ADAFIywRgPqK/vPZPEjGHAK0fRitMAwhC/heZ/yYAwDSin+KHADEHAqYBJCf/C5ZgAmAIQEImALMT/WW3f1KJPwQIuJJNA+iZ/C8+/00AgHGinyKHALvOW1l68hY+B8w0gArJ/0qkmQAYApCKCcB0or+e9k+dQ4Bd5/0g9rdUBkRb4U1GHFUtM7ZK/leV/yYAwA+Ifur5TYA5yoACpgEGAmxE/lco2QTAEIAkTAAmif462z+VDwF+dCSmAVRM/leb/yYAUC/RT6lm/zgg04AOjosMyP/KpZwAGALQPxOAIdHfp5jtn+TiDAF+dEimAVRA/vcpbP6bAEBdRD+VmOM7AUwDOjguApH/RJkAGALQs5onAKI/ibDtnwgCDgFGTAMoifxPYjVw/psAQPlEP3Vq8sXApgEdHBcJyH+CTgAMAehTbRMA0Z9W5PZPEJGHACOmAeRI/qe1Gjv/TQCgQHPnvuinME2GACOmAR0cF12R/2QzATAEoDfFTwBEfxzB2z9xZDEEGDENICz5H8dq+Pw3AYBCiH7obggwYhrQwXHRlPwn1wmAIQD9KHICIPoDit/+CSWvIcCIaQDJyf+AVnPIfxMAyJjoh/6HACOmAR0cF7OS/xQyATAEoAfFTABEf2RZtH+iyXQIMGIaQG/kf2SrmeS/CQBkRvRDnCHAiGlAB8fFOPlPmRMAQwC6lvUEQPRnIZf2T0C5DwFGTANonfzPwmo++W8CABkQ/RB/CDBiGtDBcdVL/lPFBMAQgE5lNwEQ/XnJqP0TUzFDgBHTAOYm//OymlX+mwBAUKIf8h0CjJgGdHBc5ZP/1DgBMASg8gmA6M9UXu2fsMobAjSZBsQ5qU0D+iH/M7WaW/6bAEAgoh/KGwKM7DpvZY4aIMhAwDSga/KfPgWdABgCUNsEQPTnLrv2T2QFDwGajALinOymAe2S/7lbzTD/TQAgMdEP9QwB5v7FgCHTgMLIf1KJOwEwBKD4CUCT6Jf+oeTY/gmu+CFAGdOAhnVUzaeG/C/Gap75bwIACYh+qHwIUMY0oMkooNppgPwngtATAEMAypsAiP7yZNr+ia+eIcCIaUDZ5H95VrPNfxMA6Inoh1DiDAFGTAMib5iakP9EE30CYAhAARMA0V+wfNs/WahwCDBiGlAG+V+w1Zzz3wQAOiT6IbKAQ4AR04Dg+6dNyX8iy2ACYAhAjhMA0V+DrNs/uah5CDBiGpAX+V+D1czz3wQAWib6ISORhwAjpgHxt1ND8p9c5DEBMAQgiwmA6K9K7u2fjBgCrFXzNCDymSX/q7Kaf/6bAEALRD/Qj5qnATEHAvKfHGUzATAEIOYEQPTXqYD2T14MAdZlGrCQlPyv02oR+W8CAAlyX/QDzZkGJNlvyX8KkNMEwBCACBMA0U8Z7Z/sGAJMZxqw0D35z2op+W8CALMS/UBYpgGdbr/kP4XJbAJgCECSCYDop7z2T44MAWZkGrDQHvlPkflvAgDTiH4gO6YBrezG5D8Fy28CYAhAPxMA0U/Z7Z9MGQJslWnAHP9K/lN8/psAwDjRDxTDNGBLmzP5TyWynAAYAtDRBKA50V+wwto/+TIEmJtpwJQ/tfWnqvw3AYB2iH4gONOAdfdqtv5UKNcJgCEAcSYAor8G5bV/smYIkHAaECH02poG2PpTbf6bAMD8RD9Q2zQgwkCgrWlA82OATGU8ATAEIOEEQPRXpcj2T+4MAVpU+TQgux+ZPq0Wmv8mAIktLy8rIfIi+oHk2+44+t9/JyT/Kca2hZxNKbzaiqRNz/bmHeXlH2p4J/RgcWWn9K9Qqe2f3HWd/1NO9jI27myJ/K/Tarn5bwKQ2MrKynD3P/xf04CY5D5AneQ/Rcp7AjBdRkOAtXdlGhCKrk/lqnp7Q0kMAWhO/ldutej8z74AyHr+MjTZ9VcGRCD6qSF/sub5pyPyn+LzJ/sCoLwhwNr7VAYkIfqpof1TPEMA5iD/qST/txVfhGXxEk55678yoE+in9mjI/f2TxkKyH+CkP9Ulf8lFAD9SDIEWHvnygCA/hkCAOUppAAooAk0y+f/KAOgHzW0f4pRQP4DcazWkf+FFAA1DAHWPopKAKA3hgBAYcr5HoBdu3ZN+Wb41eXd8d/bN/pOgBn56gDoQiXtn5IUkP+TVnYemfoQSrO8+9rUh0B0q9XkvwlAlkOAsUc0DQDolCEAUJKiCoAC3gk6dztfGQCtqKf9U5gC8h9Ia7Wm/C+qAKh2CLD2oZUBAF0wBACKUVoBUEATqPl7+pUBMJ+q2j/lKSD/gVRWK8v/0gqAfkQeAqw9hgiHAVAMQwCgDAUWAGUPAXadt7X5gDIAZlRb+6dIBeQ/0L/V+vK/wAKg7CHA0pOXd523ogwASMIQAChAmQVADb8JoAyAFlXY/ilVAfkP9Gm1yvwvswAofggw+m9lAEDPDAGA3BVbAFT1cUDKAGiizvZPwQrIf6Afq7Xmf7EFQD1DgBFlAEA/DAGArJVcANT5nQDKANiSats/ZSsg/4GurVac/yUXABUOAUaUAQCdMgQA8lV4AVD5FwMrA2C6mts/xSsg/4HurNad/4UXADUPAZqXASoBgCkMAYBMlV8AVD4EaFIGGAhQtsrbPzUoIP+BLqxWn//lFwD9CD4EGFEGALTIEADIURUFQAFNoFaGACPKAND+qUQB+Q+0a1X+V1IA9COXIcCIMgCgOUMAIDu1FAAFNIHaHQKMzFEDKAPInfZPVQrIf6At8r+uAqAf2Q0BmowClAEAQ4YAQF4qKgAKaAJ1NAQYUgZQCe2fChWQ/0Bz8r/GAqAfmQ4BRpQBAHMwBAAyUlcBoAk0I2UApdL+qZb8h8rJ/3oLgAKGAFPeBdR6k0kZANAKQwAglOoKAE2grVIGUAztn8p1nf+bdn+AVOR/7QVAP4oZAowoAwCaMAQA4qixADAEmJsygHxp/5B8CKAGgCTk/6QaC4B+lDcEGFEGAADkq9ICwBCgOWUAGdH+YcQQAKoi/9dVaQHQj4KHAG2VASoBAICe1VsAGAJEKAMMBOiB9g9jDAGgEvJ/I/UWAP2oYQgwogwAAIiv6gLAEKALygBC0f5hXYYAUDz5P0XVBUA/qhoCjCgDAABiqr0AMATolDKAtLR/mMIQAAom/6ervQDoR51DgBFlAABAHAoAQ4CeKAPomfYPwYcAQEfk/6YUAD2pfAgwogwAAEhLAfADhgA9UwbQNe0fZmQIAIWR/7NQAPTHEGCMMgAAoH8KgH9iCJCKMoDWaf+wJYYAUAz5PyMFQK8MATaiDAAA6IcC4EcMAZJTBtCc9g9zMASAAsj/2SkA+mYIsCllAABAdxQA/4whQBzKAOag/cPcDAEga/J/SxQACRgCzG7uGmBUBqgEAADWUgCMMwQoaRQwpAyohPYPDRkCQKbk/1YpANIwBNgqZQAAQCsUAOswBCi4DKBU2j+0whAAsiP/56AASMYQYG7KAACAuSkA1mcIEJ8ygBHtH1pkCAAZkf/zUQCkZAjQnDIAAGBLFAAbMgTIiDKgZto/tM4QALIg/+emAEjMEKBFygAAgE0pAKYxBMiRMqAq2j90xBAAgpP/TSgACh8CTFHkEGBEGQAAsC4FQCPxhwBT3gVUA2VA2eKfgBTM8oOEnIANKQAWIsyPDAE6pQyolvkvTVg/kC/n73QKgNqHAJXUAMqA8sQ/9SieRQhJOPWaUwDUPgSAUmn/0JxVBDly5m5KAVBFJWoIQGHin3RUwlKEnjnpWqEAmIkhAORF+4e2WEuQF+fsLBQAtdSjhgAUI/7pRlUsSOiN060tCoBZGQJALrR/aJcVBblwts5IAVBRVWoIQAHin2hUyLKEHjjRWqQA2AJDAIhP+4cuWFcQn/N0dgqAumpTQwCyFv8Uo1oWJ3TKKdYuBcDWGAJAZNo/dMfqgsicoVuiAKiuQjUEIFPxTy4qZ4lCR5xcrVMAbJkhAMSk/UPXrDGIybm5VQqAGutUQwCyE/+0AgsVuuC06oICYB6GABCN9g/9sNIgGmflHBQAlVarhgBkJP4JBSOWK7TICdURBcCcDAEgDu0f+mS9QRzOx/koAOqtWQ0ByEL8UwnGWLTQCqdSdxQA8zMEgAi0f+ifVQcROBPnpgCounI1BCC4+CcRrMvShYacRJ1SADRiCABpaf+QirUHaTkHm1AA1F6/GgIQVvzTB6awgGFuTp+uKQCaMgSAVLR/SMsKhFScfQ0pADoXv4o1BCCg+CcObMoyhjk4cXqgAGiBIQD0T/uHCKxD6J/zrjkFQB/i17KGAIQS/5SBGVnMsCVOmX4oANphCAB90v4hDqsR+uSMa4UCoCfxK1pDAIKIf7LAlljSMCMnS28UAK0xBIB+aP8QjTUJ/XCutUUB0J/4da0hAMnFP01gDhY2bMpp0icFQJsMAaBr2j/EZGVC15xlLVIA9Cr36tYQgE7lfoLAFJY3TOEE6ZkCoGW5DwGmvwsI0tL+ITLrE7rj/GqXAqBvude4hgB0JPdTAzZlkcO6nBr9UwC0zxAAuqD9Q3xWKXTBmdU6BUACuVe6hgC0LveTAmZkqcMYJ0USCoBOGAJAu7R/yIW1Cu1yTnVBAZBG7vWuIQAtyv10gC2x4GHE6ZCKAqArhgDQFu0f8mLFQlucTR1RACSTe9VrCEArcj8RYA6WPTgR0lIAdMgQAJrT/iFH1i005zzqjgIgpdxrX0MAKj8FYG4WP5VzCqSlAOiWIQA0of1DvqxeaMIZ1CkFQGK5V8CGAFS7+AGYj/xPTgHQOUMAmI/2D7mzhmE+zp2uKQDSy70ONgSgwmUPwHzkfwQKgD4YAsBWaf9QBisZtspZ0wMFQAi5V8OGAFS14AGYj/wPQgHQE0MAmJ32DyWxnmF2zpd+KACiyL0mNgSgkqUOwHzkfxwKgP4YAsAstH8oj1UNs3Cm9EYBEEjulbEhAMUvcgDmI/9DUQD0yhAAptP+oVTWNkznHOmTAiCW3OtjQwAKXt4AzEf+RzNYyNzS0lLqQwDaof1D8VyzYF3yv2cmAAAAUBEFABCC9g81sM5hkvOifwoAAACoiAIASE/7h3pY7bCWMyIJBQAAAFREAQCk56NRqIfVDms5I5JQAAAAQEUUAEAImkDUwDqHSc6L/ikAAACgIoV/E/DKykqPx1KF5eXl2f/yys4jF4JZ3n3tlD9dXNnZ47FUZ5avgvdxENTc5mwYQZueYrvOq/qauPTkadcv+d8p+R+NCQDQE9dXSHiCVL77Jy35H40CgK7a/zAH7wSlVF2v7Vk6rBCZ/O+TAgDojyYQrEv7n+LJ/1AUAMxK+59+aAJRHu1/mIX8740CAOiVJhCM0f6nEvI/DgUAM9H+p0+aQJRE+x9mJ//7oQAA+qYJBCPa/1RF/gehAGBz2v/0TxOIMmj/w1bJ/x4oAIAENIFA+586yf8IFABsQvufVDSByJ32P8xH/ndNAQCkoQlE5bT/qZb8T04BwDTa/6SlCUS+tP+hCfnfKQUA89NeoiFNIKql/U/l5H9aCgA2pP1PBJpA5Ej7H5qT/91RADAn7SVaoQlEhbT/Qf6npQBgfdr/xKEJRF60/6Et8r8jCgDmob1EizSBqIr2P4zI/1QUAEAGNIHIhfY/tEv+d0EBwJbf/6O9ROs0gaiE9j+Mkf9JKACAPGgCEZ/2P3RB/rdOAcA47X+S0ASieNr/sC753z8FAJANTSAi0/6H7sj/dikA+Ge0/0lIE4iCaf/DFPK/ZwoAICeaQMSk/Q9dk/8tUgDwI9r/JKcJRJG0/2FT8r9PCgAgM5pARKP9D/2Q/21RAPBPtP8JQhOIwmj/w4zkf28UAEB+NIGIQ/sf+iT/W6EA4Ae0/wlFE4hiaP/Dlsj/figAgCxpAhGBdQj9c941pwBA+5+INIEoQPNlPP39P/KZIsn/HigAgFxpApGWFQipOPsaUgDUTvufsDSByJr2P8xN/ndNAQBkTBOIVKw9SMs52IQCoGra/wSnCUSmtP+hIfnfKQUAkDdNIPpn1UEEzsS5KQDqpf1PFjSByI72P7RC/ndHAQBkTxOIPllvEIfzcT4KgEpp/5MRTSAyov0PLZL/HVEAACXQBKIfVhpE46ycgwKgRtr/ZEcTiCxo/0Pr5H8XFABAITSB6Jo1BjE5N7dKAVAd7X8ypQlEcNr/0BH53zoFAAAAVEQBwI9oL5F7E8gUmO5MX13a/9Ap+d8uBUBdpr//BwCA4ikA+CfaS2RBE4gktP8hOfnfIgVARbT/AQBQAPAD2ktkRBOInmn/QxDyvy3bW7snYkvS/l/efW3/DwoAwBQmAGgvkR9NIHqj/Q+hyP9WKACq4N3/AAAMKQBqp71EpjSB6IH2PwQk/5tTAFTd/nd1AQCojQIAyJUmEJ3S/oew5H9DCoDCaf8DALCWAgDImCYQHdH+h+DkfxMKgJJp/wMAMEYBAORNE4jWaf9DFuT/3HwTcLH6af8nv1AtPdlXHAAAbIEJALlaevKy3T9DmkC0SPsfMiL/52MCUKay3/1v3w8AMDcTAHKi689GNIFohfY/ZEf+z8EEoEBFtv/t+wEAWmECQC1d/5UfauOICEoTiIa0/yFT8n+rTABKU1j7v62tfxvHAgBQAhMAim38D1v+dv9V0QRibtr/kDX5vyUmAEUpo/3fvOtv0w8AsBETAArs+rd3RORHE4iA7f/pMmrQQGTyf3YmAFWIf3XR9QcKNv39PwA9MwGo4v0/ken60zpNILZE+x+KIf9nZAJQvrBXF11/oAba/0A0JgCFyKv9r+tP1zSBmJH2PxRG/s/CBKBw0a4uuv5AVbT/gYBMAEqQRftf15+eaQKxKe1/KJL835QJQMmCXF10/YE6af8DMZkAZC9y+1/Xn7Q0gZhC+x8KJv+nMwEoVtqri64/UDntfyAsE4C8BWz/6/oTiiYQ69L+h+LJ/ylMAMqU5Oqi6w8wpP0PRGYCkLE47X9dfyLTBGKM9j9UQv5vxASgQH1eXXT9AcZo/wPBKQBylbz937zlv1DZM0ZCiys7p+/JlpaWdu3a1eMRkYz2P1RF/q9LAVCaHq4utv4AG9H+B+JTAGQp1Y7W1p98aQKh/V+t5u9WJWvyf5ICoCjdXV1s/QE2NWWTYfefhK0/rEsBkJ+et7a2/hRDE6hyadv/9MzWn7Xk/xgFQDlaby/Z+gPMTvs/CFt/2JQCIDP97HFt/SmVJlC1tP9rYOvPFPJ/LQVAIdpqL9n6A8xB+z8tW3/YEgVATjrd7Nr6UwlNoApp/xfM1p/Zyf8RBUAJGraXbP0BmtD+T8LWH+a2bf5/ShG73iYBuvJDCz1a/qE+H5Eibdrxnd4wJi/a/+VZevKy3T/zkf9DJgDZm7u91HDrv9Cv5vv+4TnvSzqBdmn/98m+H1qhAMhDu23vOrf+sKV3glID4ZARW3/asij/FQC522p7ydYfZlTPr4KVretpvvZ/D2z96dlSBfmvAKiFrT+M0QSqnJSoZ+vvLaCMWaw+/xUAGdhoNzxje8nWH+ZTQxOobNr/+Wp36w9btVR6/isASjZ3gPa/77f1JwlNoGqJi7Bs/enHYt35rwAos/1v6w+tKL4JVDDt/+zY+hPKUtH5rwAoja0/bEnlTaA6yY1obP1JYrHi/FcAlNP+t/WHLpTdBCqV9n8ubP2JbKnc/FcAlMDWH5qouQlUIQFS0tbfq0lDi7XmvwIg7/a/rT/0oOAmUJG0/4Oz9ScjS4XmvwIgV7b+0KJqm0C1kSRp2foT0GKV+a8AyK/9b+sP/Su1CVQe7f+Cd/8uBySxVGL+KwCqCFBbf9hUnU2gqoiUVGz9CW6xvvxXAETUfOs8YusPbSmyCVQY7f9obP0pw1Jx+a8AKJatP2xVhU2gesiWntn6k5fFyvJfARBO8z20rT90pLwmUEm6bv9Pof2/lq0/RVoqK/8VAEWx9YeGamsCVaKVkLEwNmXrT9YWa8p/BUAsc2+mbf2hH4U1gYqh/Z+WrT81WCoo/xUA2ct06y/uCauqJlANtP87ZetPSRaryX8FQCBb3VXb+kMSJTWByqD9n4StPxVaKiX/FQD5SbLvt/WnKvU0gYqn/d8FW38KtlhH/isAophle23rD0EU0wQqgPZ/n2z9YamI/FcA5MHWv7lZCvrh3wlywKRVSROobNr/Lcp66y//2ZLFCvJ/sFB07yfVvrnFfbatf3PzncZBDp7Ii6eAJlDBl4C2TuGN1kA97f/it/6T5D8Lpee/CUBctv7NNangdYOA4ruA01W49V/7b+U/BTMBSG9yw23rH+2yHeSHIomym0BZ0/7vTrVb/0nyv2ar5ea/CUAstv4xO3a6QVChOtv/tv7r3qf8pzCDsj/8If4EYLTztvXP5Wod5IelTwU3gfKl/d86W/9Nyf8KrRaa/yYA6dn659Wo0w2CGlTV/rf139JjyX8KMCj7s5/jTwCSsPVvS5AngR6U2gTKlPZ/W2z95yb/67FaYv6bANTF1r+LYwjyhAAlxUvXbP1bOQb5T6YGZX/1ownAiK3/RlV7W18jGuTJoTtFNoFypP3fkK2//Geryst/E4Dy2fpPP1fbugzoBkEZInSXY2790+ab/IfaJwCzn6uVTwBs/bdapusGUVsTKDva//Ox9Zf/NLRaVv6bAJTJ1n++k1M3CCpXXvvf1l/+QwkTgC2dnBVOAGz926rLdYOooQmUF+3/LbH1l/+0a7Wg/DcBKIetf7tno24Q1KaY9r+tv/yHoiYAWz0bK5kA2Pp3XYjrBlFqEygj2v+zsPWX/3RqtZT8NwHIm61/P6efbhAUL/f2v62//IcyJwBznH4FTwBs/VNV3rpBlNQEyoX2/xS2/vKfPq0Wkf8mAPmx9U97vukGQXkybf/b+st/KHwCMN/5VtgEwNY/YKndSkMoyItChU2gLGj/T7L1j3CWyf9qreaf/yYAebD1D3uCtdIQ0g2ChPJq/9v6y3+oZQIw99lVwATA1j9s9E/SDapNAU2g+LT/R2z9I59W8r82q5nnvwlAXLb+2Z1OukGQnSza/7b+8h+qmwBMb/9MT5ZMJwC2/tlF/yTdoErk3gQKTvvf1j/Hk0j+V2I15/w3AYjF1j+v82cK3SCIL3L739Zf/id/HSnYIPf2TzETAFv/YqJ/km5Q2bJuAkVWbfvf1r+ks0b+l2012/w3AUjP1j+jE2Y+ukEQUMD2v62//F+X/KeuCcAs7Z+sJwC2/sVH/yTdoCLl2wQKq7b2v61/DaeJ/C/Sap75bwKQhq1/LmdI63SDIII47X9bf/m/JfKfwicAM7Z/spsAlLT1byX964n+LrpBcVYCmTaBYqqk/Z/11l/+NyT/S7KaYf6bAPTH1j+LUyKvbpBWEOTY/rf1l//yn7TyKwByXOu2/mNE/1ouA2XY9GtJaK7rRd5D+9/WX/6vJf/LsJhh/m8v+BdlIrD1HyP6N+IyULalpSWLv7b8b3f3n/zUlv/dkf9lWwqZ/0ELgI1ktLht/ccEXP0BuQxkLccmUEayfve/rX9Lx1Iy+Z+1xdzyP2IBkHv7x9Z/jOjfKpeBIsVsAkWTe/63uPWPcP7K//7J/yItxcv/iAXARuKvZlv/MdGWe15cBnKUXRMoFzm2/239WzqWGsn/HC1mlf/hCoBM2z+2/mNEf1tcBkoSsAkUSqb5P8nWv6VjqZ38L8lSsPwPVwBsJOzytfUfE2p9F8NlICN5NYGykFH739a/pWPhR+R/Rhbzyf9YBUBe7R9b/zGiv2suAwWI1gSKI6/8n2Tr39KxsD75X4ClSPkfqwDYSLT1aus/Js6CroHLQHwZNYHii9/+t/Vv6VjYnPyPbzGT/A9UAGTR/rH1HyP6U3EZyFeoJlAQWeT/JFv/lo6FrZH/+VoKk/+BCoCNBFmgtv5jgqzgyrkMhJVLEyi4sO1/W/+WjoX5yf+wFnPI/ygFQOT2j63/GNEfjctAduI0gSKInP+TbP1bOhbaIf+zsxQj/6MUABtJuyJt/cdEWLJsxGUgmiyaQJFFa//b+rd0LLRP/kezGD7/QxQAAds/tv5jRH8uXAZyEaQJlFzA/J9k69/SsdAt+Z+LpQD5H6IA2EiSJWjrPyb5GqXJqzb3lcBloJImUFhB2v+2/i0dC/2R/0Esxs7/9AVAnPZPK1v/OOeM6Kd5Q8hloPgmUFpx8n+SrX9Lx0Iy8j+ypdT5n74A2Eifa87Wf4zoL4zLQELBm0AxpW3/2/q3dCyEIP8TWgyc/9srb//Y+o8R/QVzGQgoeROo5vyfZOvf0rEQjvwPaClp/gedAPSwyGz9x4j+SrgM9C9yEyigJO1/W/+WjoXQ5H//FqPm//YK2z+2/mNEf4VcBuKocwgQp/1v69/SsZAN+R9HwvyPOAHoblXZ+o8R/ZVzGehN2CZQze1/W/+WjoUsyf/K8397Je0fW/8xop8Rl4HkahsCJG//2/q3dCxkT/5Xm//hJgCtLyNb/zGin3W5DNTZBKqt/W/r39KxUBT5X2H+D5I86pRFttUF1MMTGmRNN/xJ5T69NWiDnDIBTT+LKzlJW8z/fq4LEdaz/Kc38r+S/I81AYi2boIcj+inZ7pB9TSB4gi4+4+whuU/PZP/leT/IPf2T0fPZpC1K/pJTjeo7CZQz3Jp/0dYt/Kf5OR/wfkfaAIQZKEEOQzRTxC6QWU3gYKIs/uPsFblP0HI/4Lzf5B7+6ewaa/oJzLdoPKaQH2K3P4PsjjlP2HJ/8LyP8oEIO3KCLIuRT/B6QaV1wSKIO3uP8iClP8EJ/8Ly/9B7u2fhs9jkLUo+smOblAZTaCa2/9BFqH8Jzvyv4D8DzEBSLIUgqw/0U+mdIPKaAIll2T3H2ThyX8yJf8LyP9B7u2fOZ7EIGtO9FMM3aB8m0C1tf+DLDb5TzHkf6b5n34C0OdrH2SdiX4KoxuUbxMorT53/0EWmPynMPI/0/wf5N7+0fWBUHSD8moC1dD+D7Ko5D/Fk/8Z5X/iCUAPL3aQ9ST6qYRuUF5NoIR62P0HWUjyn0rI/4zyf5B7+0f0Q1i6QfGbQKW2/4MsHvlPteR/8PxPOQHo7tUNsm5EP5XTDYrfBEqlu91/kAUj/6mc/A+e/4Pc2z9jz12QtSL6YYxuUIVDgJ7b/0EWifyHMfI/YP4nmwC0/nIGWR+iH9alG7SRCocAre/+gywM+Q/rkv8B839QQPsnyJoQ/dBPQyjIKd+iIocA8n92mb7EMB/5HyH/0xQAhb1+oh/m4zIwS4xkGhHyfxaZvrjQnPxPm/+DrNs/yYl+aM5loLwhgPzfVHavKXRB/i8kyv8EBUAZL5joh3a5DJQ0BJD/U2T3akLX5P9q7/nfVQFQcPtH9EN3ar4MFDMEkP8FvIjQP/nfZ3T0XQBk/QqJfuhHtZeBMoYA8j/rlw/Skv8ZFwDltX9EP/SvwstAAUMA+Z/jqwbRyP+uk6TXAiDHl0T0Q1q1XQZyHwLI/7xeL4hM/udUABTT/hH9EEc9l4GshwDyP4uXCfIi/7sIlv4KgIxeA9EPMVVyGch3CCD/g79AkC/5vytyAZB7+0f0Q3zFXwYyHQLI//aOBVif/F/IqwCI/6SLfshL2ZeBHIcA8h/oh/xvbnsL95E50Q85Gp56810Ghmd9/MsAXZP/kCP5H2sCkF37R/RDGYrsBuU1BJD/QBLyfz6VTgBEP5REN4jZyX8oifxPPAHIpf0j+qFsJXWDchkCyH8gAvk/u4omAE2iX+5DLnSDmCT/oQbyv+8JQPD2j+iHOhXQDYo/BJD/QEDyv/YJwNzpL/qh8m5QkGsAc5P/UC353/kEIGz7R/QDzbtBkaMseVjJfyA++V/LBED0A211g2p7Y2ju5D8wRv63PwGI1v4R/UB53aCYQwD5D2RH/pc2ARD9wIx0gwoj/4EZyf8WJgBB2j+iHyi+GxRtCCD/gdwtVZz/eU8ARD/QkG5QpuQ/0NCuivN/kGn7R/QDtXWD4gwB5D9QmKXK8j+/CYDoBzoySomtXgkK6AZlQf4DHdlVWf4PMmr/iH4gfkMoVQz2FnTyHyjeUun5n8cEQPQDubw9NNNuUFjyH+jfrtLzfxC8/SP6gQjidIPSDgHkP1CbpRLzP+4EQPQDcRTfDQpF/gNx7Cox/wcB2z+iH4gseTco1RBA/gOVWyol/2NNAEQ/EF+R3aDk5D8Q365S8n8QpP0j+oEcpeoG9T8EkP8AxeR/+gmA6AfyVUw3KAn5D+RrV875P0jY/hH9QEl67gb1OQSQ/wAl5X+aCYDoB8qTdTeoN/IfKM+u3PJ/0HP7R/QDNeinG9TPEED+AxSW//1NAEQ/UI/sukGdkv9APXblkP+DHto/oh+oWafdoK6HAPIfoLz873YCIPoBsugGtU7+A+yKmv+Djto/oh+gn25Qd0MA+Q9QZP63PwEQ/QDZdYNaIf8Bssj/QYvtH9EPkKQb1MUQQP4DlJr/7UwARD9A1t2gucl/gOzyf9Cw/SP6ASJ0g9odAsh/gILzf/4JgOgHKKYbNMfjzkH+A0TI/8Ec7R/RDxCwG9TWEED+A5Sd/1suAOYg9wG2qsUQbqsA6PpxAVjoJf8HnT6w6Adoov+9uPwHKD7/u/omYNEPkOq9oWnJf4Dg+b/OBKDhI4l+gC40vwxsms/yH6CG/G9zAiD6AbozytiAAwH5D5BR/o9PAOa7X9EP0LPW41r+A2SheVw3nQCIfoA6fz1A/gNkmv//bAKwpTsS/QBBNE9v+Q+Qo/nSe54JgOgHqHMaIP8BCsj/H00AZvmXoh8guDnCXP4DFGD2MJ91AiD6AeqcBsh/gMLy/58mAFP+qugHyNQs2S7/AcozPdunTQBEP0Cd0wD5D1Bw/g/W/TPRD1CYdaNe/gMUbzLqxycAoh+gzmmA/AeoJP8Ho/8j+gEqMVYGyH+AqvJ/sG/fvtRHAgAA9GRbXw8EAACkpwAAAICKKAAAAKAiCgAAAKiIAgAAACqiAAAAgIooAAAAoCIKAAAAqIgCAAAAKqIAAACAiigAAACgIgoAAACoiAIAAAAqogAAAICKKAAAAKAiCgAAAKiIAgAAACqiAAAAgIooAAAAoCIKAAAAqIgCAAAAKqIAAACAiigAAACgIgoAAACoiAIAAAAqogAAAICKKAAAAKAiCgAAAKiIAgAAACqiAAAAgIpsT30A0J+9e/defPHFH/nIRz772c9eccUVV1555Q033LBnz57bb799x44dBx988DHHHHPccceddNJJ97vf/U4//fQTTjgh9SEDALRssG/fvrbvE2LZu3fvO97xjte97nUXXHDBzTffPPs/vOc97/nEJz7xaU972j3vec8uDxCALXvjG9+4pb8/GAy2bdu23377HXjggTt27Dj00EPvdKc7HX300Tt27OjsGCEoBQAlu/HGG1/5yle+7GUvu/baa5vcz9lnn/2iF73o/ve/f3uHBkAjg8Gglfs5/vjjTz755Ac84AEPfehDH/KQhxxyyCGt3C1EpgCgWG984xt/4zd+45vf/GYr97Zt27ZnP/vZL33pS10bAEoqANY68MADH/GIRzzlKU95/OMfv//++7d+/xCEAoACffvb337605/+tre9rfV7vte97vW2t73tXve6V+v3DEDyAmDkuOOOe+5zn/trv/Zr3iBEkRQAlOYzn/nM2Wefvbq6OuXv/PiP//gDH/jAk0466c53vvMd73jHm2666Tvf+c7u3bsvu+yyj33sY7t3757ybw877LD3ve99p556agfHDkCIAmDoLne5y+///u+fc845XT8Q9EwBQFE++tGPPvKRj7z++uvX/dPjjz/+V37lV57ylKfc7W532+ge9u3bd9lll/3f//t/X/e6191www3r/p3DDjvswgsvfMADHtDegQMQrgAYWlpaetWrXnXEEUf083DQAwUA5fi7v/u7M844Y93d/6GHHvrbv/3bv/7rvz77ezqvu+66F77whS9/+cvXPUeOP/74j3/848ccc0zjowagtQJg+q7m+9///m233XbjjTfecMMN11577Ze//OV/+Id/+MQnPvHXf/3XG3WOhu5+97u/613vOvHEE9s4cEhPAUAhvvjFL/7kT/7kd77znck/+smf/MmVlZX5PtT/ggsueOpTn7rubxKfeeaZf/VXfzXXwQKQoADYyC233PKBD3zgT/7kT97xjnfcfvvt6/6dnTt3vuc97/H+T8qgAKAEN95442mnnfbpT3968o8e+9jHrqysHHDAAXPf+eWXX/7Qhz503dLi1a9+9TOe8Yy57xmACAXAyGWXXfYf/sN/2Ki5c/jhh1944YU+EpoCKAAowdOf/vQ/+7M/m7z97LPPPv/887dvb/qN15/4xCf+1b/6V3v37h27/eijj77iiisOPvjghvcPQIQCYOhP/uRPnvvc595yyy2Tf3TMMcd88pOf9P5Pcrct9QFAUxdccMG6u//73e9+5557bvPd//BNRL/92789efvVV1/9qle9qvn9AxDHs571rA984AOHHXbY5B994xvfWF5evu2221IcF7TGBIC87d2796STTvrSl740dvtBBx30qU996p73vGdbD3Trrbc+8IEPvOyyy8Zuv/vd7/6FL3xh2za1NEAhE4Chj33sYz/7sz974403Tv7RH/zBHzzvec9r64Ggf3Yt5O1Vr3rV5O5/YWHhJS95SYu7/4WFhf333/+FL3zh5O1f/OIXP/rRj7b4QABE8OAHP/g1r3nNun/0whe+8Morr+z9iKA1CgAydtNNN/3e7/3e5O0nnnjic57znNYf7nGPe9zxxx8/eftb3/rW1h8LgOTOOeecJz/5yZO333DDDetefSAXCgAy9pd/+ZdXX3315O3/7b/9t/3226/1h9tvv/2e9axnTd5+0UUXtf5YAETw3//7f9+xY8fk7a95zWvWvQBBFhQAZOzVr3715I2Li4uPe9zjOnrExzzmMZM3XnrppXv27OnoEQFI6C53uct//I//cfL2m2+++bWvfW2KI4IWKADI1eWXX/6JT3xi8vZnP/vZ3f1K7v3ud78jjzxy7Mbbbrvtc5/7XEePCEBa/+7f/bsDDzxw8vbXv/71KQ4HWqAAIFdve9vbJm8cDAbnnHNOdw86GAzOOOOMydu/8IUvdPegACR02GGHrTv+/ccfSnFE0FQLH5EOSbz73e+evPG000479thjO33cc845Z/Jj5u54xzt2+qAAJPQLv/AL559//uTtF1xwwUknnZTiiKAR3wNAlm644YbDDz988qtYfvu3f/t3fud3Eh0UAOV8D8Bat9xyy86dOye/E+Dxj3/8W97yli4eETrlLUBk6ZJLLln3ixgf+tCHpjgcAEp2wAEH3Oc+95m8/VOf+lSKw4GmFABk6e///u/Xvf2UU07p/VgAKN+615cvf/nL3/ve91IcDjSiACBLn/nMZyZvPProo+90pzulOBwAaiwA9u3bt7q6muJwoBEFAFn62te+Nnnj3e9+9xTHAkD5Tj755HVv//rXv977sUBTCgDKKQCOOeaYFMcCQPkOP/zwdW//xje+0fuxQFMKALL0rW99a/LGya/oAoBWHHrooevefv311/d+LNCUAoAsTX4W28LCwo4dO1IcCwDlO+yww9a9/aabbur9WKApBQBZuvnmmydvvMMd7pDiWAAo30YTgL179/Z+LNCUAoAsff/735+80bfaAdCRdb98ZmFhYf/99+/9WKApBQBZOvDAA2ccCwBAcxt1+g2fyZECgCyt+3b/dX8xAACa2+gLvw466KDejwWaUgCQpTve8Y6TN1577bUpjgWA8n3zm99c9/ajjz6692OBphQAZOnYY4+dvPHqq69OcSwAlG+jz/s/7rjjej8WaEoBQJbWDdwvfvGLKY4FgPJ9/vOfX/f2u971rr0fCzSlACBLd7vb3SZv/OY3v/md73wnxeEAULjPfvazkzceeeSR3gJEjhQAZOm+973vurd/+tOf7v1YACjfxRdfPHnj/e53vxTHAk0pAMjSRpn74Q9/uPdjAaBw11133eWXXz55+2mnnZbicKCp7Y3vARI4+eSTDzvssOuuu27s9osuuui//tf/2ulD/9t/+2/HPm/0gAMOeP3rX9/pgwKQ0Hve8551vwjszDPPTHE40NTAl6eSqSc84Qlvfetbx27cb7/9rr766jvf+c4dPejq6uo97nGPsRtPOOGEL33pSx09IgDrGgwGkzd2tKtZWlp685vfPHbj4Ycffs011/gmYHLkLUDk6hGPeMTkjbfddtv555/f3YO+//3vn7xxsiQAoBjXXHPN2972tsnbn/SkJ9n9kykFALl6whOesG7y/vEf/3F3D3rBBRdM3nif+9ynu0cEIK1XvOIVt9566+Ttv/RLv5TicKAFCgBydec73/mRj3zk5O2f/vSnL7rooi4e8aabbvrABz4wefvpp5/excMBkNy3v/3tP/qjP5q8/dRTT33wgx+c4oigBQoAMvasZz1r3dv/y3/5L1083Lnnnvvd73537Mb999//YQ97WBcPB0Byz3/+86+//vrJ2//zf/7PKQ4H2qEAIGOPetSjTjnllMnbP/axj73pTW9q/eFe+cpXTt54xhlnHHHEEa0/FgDJvetd7/rzP//zydtPP/30s846K8URQTsUAOTtt37rt9a9/dd+7de+9a1vtfhAb37zmy+55JLJ23/5l3+5xUcBIIgrrrjiF3/xFydv32+//V75yleu+xlEkAsFAHn7+Z//+XXfgXPttdf+4i/+4u23397Ko3z3u9997nOfO3n74uLiYx/72FYeAoA4rrzyyjPPPHP37t2Tf/SCF7zAFwCTOwUA2XvFK16x7scBvfe9733+85/f/P737dv3q7/6q9/4xjcm/+ilL33pfvvt1/whAIjjsssuO+2007785S9P/tFP//RPv+hFL0pxUNAmBQDZO/nkk1/60peu+0f/83/+zxe84AUN7/85z3nOG9/4xsnbf/Znf3ZpaanhnQMQx759+171qlc96EEP+trXvjb5p4uLiysrK/o+FMA3AVOCffv2nX322e985zvX/dNzzjnnT//0Tw8++OCt3u2ePXt+/dd//TWvec3kH+3cufPSSy89/vjj5zpeAMJ9E/CFF174ghe84OMf//i6f3rUUUd95CMfWVxcnPv+IQ4FAIW4/vrrf+Znfmbd39Mdtm3+8A//8DGPeczsd/ihD33o6U9/+hVXXDH5R9u3b3/ve997xhlnNDheAEIUAJ/73Ofe/va3/8Vf/MVll1220d854YQT3v/+9/ved4qhAKAc11xzzUMe8pAvfOELG/2FU0899bnPfe5ZZ511xzvecaO/c/3117/zne98+ctf/rd/+7fr/oVt27a99rWvXfejIQBIWwCcd955U/7Jbbfddsstt+zZs2f37t1XX331FVdc8fd///ebfmTcgx/84PPPP/+YY45pfMgQhQKAolxzzTVnn332Rnv3oQMOOOBBD3rQfe5zn3vc4x6HHXbY/vvvv/uHvv71r1988cWXXXbZlM8O2n///V/72tc+5SlP6ebwAZhVDx/EuW3btuc973kveclL1v2oCciXAoDS3HTTTb/yK7/y+te/vvV7Puqoo84///zTTz+99XsGIFoB8FM/9VP/5//8nwc+8IGdPgok4VOAKM2OHTte97rXvfWtbz366KNbvNtf+IVfuPzyy+3+AYp32mmnvf3tb//bv/1bu39KZQJAsfbs2fOKV7ziZS972be//e0m9/Pwhz/8xS9+8YMe9KD2Dg2AcBOAk08++bGPfexTn/rUk08+ud17hmgUABTupptueutb3/q6173uoosuuvXWW2f/hz/+4z/++Mc//mlPe9q97nWvLg8QgJ4KgG3btm3fvv0Od7jDwQcffPjhhx955JF3uctdTjzxxHvf+96nnXbaUUcd1c2RQjgKAGqxZ8+ej370ox/5yEc+97nPXXHFFd/4xjduuOGGPXv27Nu3b8eOHQcffPAxxxxz/PHHn3jiiaeccsrpp59+wgknpD5kAID2KQAAAKAifgkYAAAqogAAAICKKAAAAKAiCgAAAKiIAgAAACqiAAAAgIooAAAAoCIKAAAAqIgCAAAAKqIAAACAmiwtLaU+BAASkP8AdRqMLgC7du1KfTAAJNj6y3+AqvJ/MHYlcBkAKNhY4Mt/gEqsDfzt6/6ZywBAbW/4kf8AleT/YMqFwWUAoADTE17+A5Rqo4Tfvum/cRkAqO3XfOU/QMH5P5jx77kMAGRkS5Eu/wGKMUukb9/SfbkMANT24Z7yH6Cw/B/M8c9cBgACapLh8h8gX1vN8O1zP4bLAEBtX+kl/wEKyP9Bw3txGQBIqMXQlv8AGWkS2ttbeWyXAYBSu/7TD0D+A2SX/4MW79RlAKAH3aW0/AeIrK2UbjoBWEs3CKDglv8U8h8go/wfdPQwLgMAoaJ/xliW/wDF53+bE4C1dIMAyu76b0T+AwTP/8FWH3VxZefq8u4tPYbLAEDX0T89nLeUw/IfoOz83/IEYHV59+LKzuF/bPXHcCUA6CL6t5TJc5P/AGXk/2C+JtDov+d4SJcBgBajf6it9v/0I5H/AAXk/zwFwNijugwAJIz+TUO4xQJA/gMUkP+D5k2gGY9gS4cFUImG0d9F+39I/gOUmv9zFgAbHYTLAECf0d9F+39I/gOUmv+DdptAMx7QulwGgEq0Ff3dtf+H5D9Akfk/fwGw6TG5DAB0Gv3dtf+H5D9Akfk/6K4JNOIyANB69Hfd/h+S/wDl5X+jAmD2Q3QZAKrVUfR33f4fkv8A5eX/oJ8m0IjLAFCP7qK/n/b/kPwHKCz/mxYAcxyxywBQvK6jv5/2/5D8Bygs/wf9N4FGXAaA8vQQ/X22/4fkP0BJ+d9CAdDkB3AZAIrRW/T32f4fkv8AJeX/IG0TaMRlAMhXn9Hff/t/SP4DFJP/7RQArfw8LgNAdvqP/v7b/0PyH6CY/B/EaQKNuAwA8SWJ/lTt/yH5D7BQRP63VgC0++O5DABhJYz+VO3/IfkPVG6plPwfxGwCjbgMAHGkjf607f8h+Q/Uaams/G+zAOjop3UZAJKLEP1p2/9D8h+ozVKJ+T+I3wQacRkAqo3+CO3/IfkPVGKp3PxvuQDo+od3GQDqjP4I7f8h+Q8Ub6n0/B/k1QQacRkA6on+OO3/IfkPlGqpjvxvvwDo7blwGQDS5n6cuAtSAMR5QtYl/4GNLFWW/4N8m0AjLgNAwdEfrf0/JP+BMixVmf+dFAD9PzUuA0Cp0R+t/T8k/4HcLVWc/4MymkAjLgNASdEfs/0/JP+BTC1Vn/9dFQAJnymXAaCY6I/Z/h+S/0B25H87BUDAJtCIywCQdfRHbv8PyX8gF/K/pwIgwhPnMgDkG/2R2/9D8h+IT/53UgBEbgLNfQ1wGYCaoz+L+AqSUfIfCEv+pykA4jyJLgNQoayjP377f0j+AwHJ/z4KgPhNoBGXAahB7tGfS/t/SP4Dccj/EAVAwOd07suAKwHEV0b059L+H5L/QATyP0EBkFETaMRlAEpSTPTn1f4fkv9AQvI/YgEQ+Sl2GYACFBb9ebX/h+Q/kIT8T18A5NgEGnEZgByVF/05tv+H5D/QJ/mfQQGQxTPuMgAZKTX6c2z/D8l/oB/yP1wBkHUTaMRlACIrOPrzbf8PyX+gU/I/vwIgrxfAZQACKj76823/D8n/4C8Q5Ev+7wpeAJTRBBpxGYAIaoj+3Nv/Q/I/l1cKciH/FzpIlV4LgExfD5cBSKie6M+9/T8k//N6vSAy+Z9ZAVBYE2jEZQD6VFX0l9H+H5L/mb5wEIf87zpG+i4Acn95XAagBxVGfxnt/yH5n/XLB2nJ/7wLgFKbQCMuA9CFOqO/pPb/kPwv43WEPsn/PnMjQQFQzKvlMgAtqjn6S2r/D8n/kl5N6Jr8X9hYfgVA8U2gEZcBaKLy6C+v/T8k/6fL9GWFdsn/hUT5n6YAKO/FcxmAOYj+Itv/Q/J/Fpm+uNCc/E+b/4Pcm0Bzxy5McjHuTRnRv7q8u5VDKq/9PyT/yUjW51pe5H+E/N++kPkTt7iy0zUAys79mNEf8K5yIf+hQvJ/UsIES1YAAFUR/QB1kv8BDcp4J2hJLwkJGQF3oezob3iQRb77fy35Ty4KON0Ckv9h898EAOhK2dEPwEbkf3B9TAA0gciFDlBb6on+JgdcfPt/SP6ThWLOuOTkfxb5bwIAtKme6AdgLfmfkZ4mAJpAZEEHqIk6o3/ug0/e/umT/Ce+wk66nsn/7PLfBABoqs7oB0D+Z6q/CYAmEPHpAG2V6J/vB4nQ/umZ/Ce4Is+7Tsn/xZzzv7oJwNzrlTKI+LaIfrKzsrKS+hBIaXl5OfUhFEL+F2BbkL1XW6/BpmvL/g8aWvqhOf7h4srOUOm/urw7SfoHaf/0LEL+2/9BQ/K/mPyvbgIAzE3XB6BO8r8w2ypsApXaYIPu6Pq0eADVplOE/DcEgK2S/0XmvwkAMI2uD0Cd5H/BttXZBCq7zQat0PUpu/2TRIT8NwSATcn/4vPfBAAYp+szsrS0VMO+HGBI/o+srKwU3C/YVm0TyEUdJun6NH8qcmn/pBIh/wu+qMPc5P/Iyg8tFJ3/JgDAD+j6jPi2EKAq8r/CbwvZVnMTqJ6WG0yh69Nd1z9y+yehCPlvCADyv9Ouf/D8NwGAeun6jOj6A1WR/xV2/UNMAII0gWprvMGQrk8PXf/g7Z+0IuS/IQB1kv89dP3j578JANRF12dE1x+oivyvvOsfZQIQpAlUZ/uNCun69Nn1j9/+SS5C/hsCUAn532fXP4v8NwGA8un6jOj6A1WR/yO6/oEmAEGaQDU34Sibrk+Srn8W7Z8IIuS/IQClkv9Juv655L8JABSoyU43VO7r+gNsifxfS9c/7gQgSBMoeSkGrWjS5y6v65Ok659L+yeICPlvCEAZ5H/yrn9G+W8CAIXQ9VlL1x+oh/xfS9c/mwlAkCZQhIIM5qDrE6frn1H7J44I+W8IQKbkf5yuf175bwIAGdP1WSvCvh+gH/J/rQj7/rxEmQAEaQIFKctgU7o+Abv+ebV/QomQ/4YA5EL+B+z6Z5f/JgCQGV2ftULt+wE6Jf/XCrXvz06gCUCQJlCc4gzG6PpE7vpn1/6JJkL+GwIQlvyP3PXPMf9NACADuj5rxdz3A3RB/q8Vc9+fo1gTgCBNoFAlGpXT9cmi659j+yegCPlvCEAc8j+Lrn+m+W8CAEHp+qwVfN8P0CL5v1bwfX+mwk0AgjSBohVqVEXXJ6+uf6btn5gi5L8hAAnJ/7y6/vnmvwkABKLrs1Yu+36A5uT/Wrns+/MVcQIQpAkUsFyjYLo+mXb9823/hBUh/w0B6JP8z7Trn3X+mwBAYro+a2W37weYm/xfK7t9f9aCTgCCNIFiFm0Uo2GfO1T619n1z7r9E1mE/DcEoFPyP/euf+75bwIACTTc6UaL/ob3kO++H2Cr5P9a+e77cxd3AhCkCRS2dKPark+c9K+86597+ye4CPlvCEC75H8xXf8C8t8EAHqi67NWAft+gBnJ/7UK2PcXYLCQ82nT1imx6Wq2WSnG9HK8o2Jd9Gd9NjVZFZHbP1mIkP82K8WYPtKR/5uqcOu/3GAMGDz/TQCgQ6I/660/wNzkf9Zb/+JlMAEI0gSydylDbxMA0V/M6TP3qgje/slFhPy3dylDbxMA+V/M6bM87wQgfv6bAEDLRH8xW3+ALZH/xWz9i5fHBCBIE8hWpgCdTgBEf5Hny3yrIn77JyMR8t9WpgCdTgDkf5Hny/JcE4As8t8EAFpQTPS38gGLxWz9ATYl/4vc+hcvmwlAkCaQnU3uWp8AiP7iT5A5VkUW7Z+8RMh/O5vctT4BkP/FnyDLW58A5JL/JgCQZqdbWPQXufUHmCT/a9j6Fy+nCUCQJpCNTuUTANFf2xmx1XZOLu2f7ETIfxudyicA8r+2M2J5ixOAjPLfBABmJfpr2/oDDMn/2rb+xctsAhCkCWTfU9sEQPTXfApsqaOTUfsnRxHy376ntgmA/K/5FFjeygQgr/w3AYBpRH/NW3+gZvK/5q1/8fKbAARpAtkGFT8BEP1jql3zszd18mr/ZCpC/tsGFT8BkP9jql3zyzNPALLLfxMAGCf6x1S79QdqI//HVLv1L16WE4AgTSC7ohx1XaMXFv0W+exrJrv2T74i5L9dUT3f6lpt/lvkCzOvmRzz3wQA2lFY9Nv6A9SZ/7b+Nch1AhCkCWSTlJ0uyvSSot+Snm/N5Nj+yVqE/LdJyk4XE4CS8t+Snm/NZJr/JgAwv5Ki39YfoM78t/WvUMYTgCBNINumvLRVqZcU/dZwwzWTafsndxHy37apzglASflvDTdcM/nmvwlAYvkunWqVFP3Jt/67du1KfgxQ6u+k0rqS8t/Wv3J5TwCCNIEa7mDUALkoKfqTb7tHyz75kXT07dFUkv9NdlEKgIyUlP+2/l1/e3QWTACgruhPvuHOOjGB2pSU/7b+jGxbKFcrH4Y1y8nfcEOTfEPGFIsrO4Ok/+ry7oZLeumHFtLZ9UMJD4B69Jb/uvgFKyn/V36ovSMie9lPALyHmI4EyX1df9iI/KcjJeW/fT/VTQAMAZhPSV0fXX+qZQhA5fmv60/JE4BNm0Cry7uDnMzEF2ep6PrDLOQ/bYmzVHT96UHhE4AWGQLQD11/iMYQgH7o+tObEiYAmkCUQdcf5iD/KYCuPz0zAdgCQwA6ousPwRkC0BFdf5IoZAJQTxPISd5QtIu0rj80V2T+/95Oad+y/7S7tPy3JWBuJgCZDQGi7V+Zm64/5MUQgLbo+pNcOROAUptAlEfXH1on/8mCrj9BmABsmSEAc9P1h6wZAjA3XX9CKWoCoAlEWLr+0DX5T0y6/gRkAjAPQwBmp+sPJTEEYHa6/oRVYAEwfafS1pfDw6Zs/TWu6Jn8Jwhbf4IrsADohyEAU9j6u3pRMEMAprD1Jwul/Q7AkHeCkor3+uv6k5b8JxXv9ScjJgDzMwRgLV1/jSvqYQjAWrr+ZKfMCYAmEH3S9de4IhT5T290/cmUCUAjhgCV0/XXuKJahgCV0/Una8VOADSB6JSuv8YVkcl/uqPrTwFMAJoyBKiNrr/GFQwZAtRG159ilDwB0ASiXbr+GldkRP7TIl1/CmMC0AJDgOLp+mtcwboMAYqn60+RCp8AaALRkK6/xhX5kv80oetPwUwA2mEIUB5df40rmIUhQHl0/Sle+RMATSC2Stdf44piyH+2RNefSpgAtMYQoAC6/hpXMAdDgALo+lOVKiYAmkD0QNcfYpL/dE14kh0TgDYZAtRJ1x8wBKiT8CRTtUwANIHogq4/ZEH+0zrhSdZMAFpmCFAJXX9gjCFAJYQnBahoAqAJRCuS7/ub34lLFxWS/zQnPCmGCUD7DAFKlbbr37zlr3EFXTMEKJXwpDB1TQA0gZiPrj8UQP4zB+FJkUwAOmEIUAxdf2BLDAGKITwpWHUTAE0gZqTrD+WR/8xCeFI8E4CuGALkS9cfaMIQIF/Ck0rUOAHQBGIjuv5QPPnPuoQnVTEB6JAhADPS9YfCGAIAkdVbAEzfb60u7+7xWKiXrT/0T/4Dlau3AOiHIQAbsfWHsnkrERBW1QWAJhBJ2PpDcvIfqFnVBUA/DAFoces/3Pfb+kMWDAGAmGovADSByGvr394RQe3kP1Ct2guAfhgC1MzWH2pmCAAEpADQBKIrtv4QnPwH6qQA6IkhQFVs/YERQwAgGgXAD2gC0RZbf8iL/AcqpADojyFA2Wz9gY0YAgChKAD+iSYQc7P1h6zJf6A2CoBeGQIUxtYfmJEhABCHAuBHNIGYna0/lET+A1VRAPTNECB3tv7AfAwBgCAUAP+MJhBT2PpDweQ/UA8FQAKGANmx9QdaYQgARKAAGKcJxFq2/lAP+Q9UQgGQhiFAfLb+QBcMAYDkFADr0ASqnK0/VEv+AzVQACRjCBCQrT/QA0MAIC0FwPo0gdgqW38og/wHiqcASMkQoAy2/sBWGQIACSkANqQJNIvKS4jkW//Kn3/oiPwvzH/avfyfdktL+JHta/6bBBZXdk6/luzatWvTRv4US0tL069ky8vLDbewwz1obS3w5D+vrT/Auuz1YVMKgIW5N9+ry7vNcFdWVoY70XrKgOQ/49qtf/KDgVLJ/7zY9MOWKADSK2AIsPauCt6VJv+5dP0B1rLvh/koABrRBFo7BCi4DIj5Rv+SnmHIjvxPyL4fGvJLwAudfg5PzR8HtPz/W8hZ2l/zLeAJhHz1k/9siV/nhVaYADSlCbTuEKCAgUDMrv9Ids8nlEf+98amH9plArA5Q4Damtm6/sCQIUByWv7QBQVAC3wm9OwN6eC721y2/tr/EIT875StP3REATATQ4B2BS8D+ucJgbAMAZLQ+IdO+R2Adngn6Ka/CVDM7wa0aL5Nf83PGAQk/9vVxb5/GJv6LDBiAjArQ4CO1Nn8rvOnhkwZAmS3+1/551q5TyiJCUBrNIHmGAJUOA1ouO+v4SmC7Mj/CLt/8QizMwHYAkOArpXx1QEbKfhHg+IZAoR9x782P8xBAdAmHwfRVg+msL1yWz+OKxyEJf/n1nDr3/bhQBUUAFtjCNCnAsqAAn4EYMgQIM7u39YfGlIAtEwTaHqjeo7IznQPPcdhT39yXO0gOPnfw+7f1h9aoQDYMkOAJpaXl+eL71zKgPl+jWH4nGTxA0LNDAES7v5t/aFFPgWofT4OortPZY78YUE+1B+Q/x1t/Ts7FqiUCcA8DAGa5PXauy1jGjDf8Yz97NPvwfUPgjAEaMjuHyIwAeiEJlAl0wBdf2CM/G+LqITumADMyRCgrSFAK9OAXL7AeKOfUfsfMmII0EP7X+5BpxQAXfFxEPOZO/R7KwPmfiDXM6iE/F+X3T/EoQCYnyFA60OA0b8KWAY0GTVM/4m0/yE7hgAd7f591A/0w+8AdMg7Qfv/xYAufj2goxIIKJj8n2/33/2xAD9gAtCIIcCm5u58R5gGNLmHGY9c+x8yZQgwI7t/CMgEoFuaQJlOA3T9gYbk/+zEJvTMBKApQ4CuhwA9TwN66Pqvfazp9zbfYQD9MARopf0v66B/CoDO+TiIdjUsAxr+hY34xTVgUuX5b/cPYSkAWmAI0NsQYO0dBrlszH0k2v9QAEOAtr7xF+iTAqAPlTeBupO2DIhThABhyf8pRCikogBohyFA/0OAtffc81Wk+SNq/0MxDAEmefMPBKcA6IkmUNf6KQN0/YGtkv+TBCmkpQBojSFAwiHALA8R5861/6EwhgBrefc/xKcA6I8mUD+6aNJr/ANN1JP/3vwDWVAAtMkQoIl277atLXvrW/+Onj0gLUOAGdn9QwQKgF7V0wTaSEa/rZuk6+/SCKWqIf+9+QdyoQBomSFAEx3d7Va38t1t/bX/oWCGAJvS44AgFAB9q6EJ1OQC0N0WeZZtfadd/01/NJdGKJv8B4JQALTPEACgTjUPATZ9/48eB8ShAEhAEyjVECAh7X9A/gNBKAA6YQgAUKc6hwDa/5AXBUAamkBVDQG0/4ER+Q8kpwDoiiEAQJ3qHAJMoccB0SgAktEEqmQIoP0PlJ3/Pv4fsqMA6JAhAECdDAFG9DggIAVASoU1geZQ/BBA+x9Yl/wHElIAdMsQAKBOlQwBvP8HcqQASEwTqOAhgPY/UDkpBzEpADpnCABQp0qGAEB2FADpGQIUOQTQ/gcAYlIA9MEQAKBOZQ8B/AIAZEoBEIIhQGGlRXYHDNA6c04ISwHQE0OA6Wq7TtT280LNyh4CADlSAERhCFBMTz2jQwUAKqQA6I8hwHT1NMXr+UmBIUMAIBQFQCCGAAV01rM4SACgZgqAXhkCTFdDa7yGnxGoYQgw/SOAZB1EpgCIxRAg6/568MMDAFhYWBgsZG7TbjRAd8pr69Ip1ywoxq6c898EAAAAKqIAAICeZN0yBIqhAAAAgIooAACgP4YAQHIKAAAAqIgCAAD644OAgOQUAAAAUBEFAAD0RPsfiEABAAAAFdm+ULT4vZbpHwexsrKyUJnl5eXpf6HhczL9/ju98yYPsek9N1zqm34syeLKzoXGVpd3Nz8SyNem52krJxrzRZAnv1PyPxoTAHISvCJKeHhd5+Ys2b0p11eYwglCwSzvaBQABDJLB73On7Hr0iLOrCzOkUC7rG2YzjnSJwUA2Qje/h8yBJhOEwjW5dSgeBZ5KAoAyIMhAOTLqoZZOFN6owAgik5/PbdPmx5qd+90MgSAHDkpqISlHocCALJhCAA5sp5hds6XfigACKGY9v+QIcB0mkAw4nSgKhZ8EAoAyIkhAOTFSoatctb0QAFAeoW1/4cMAabTBAInAnWy7CNQAEBmDAEgF9YwzMe50zUFAIkV2f4fMgSYThOIyjkFqJbFn5wCAPJjCADxWb3QhDOoUwoAUiq4/T9kCDCdJhDVsvipnFMgLQUAZMkQACKzbqE551F3FAAkU3z7f8gQYDpNICpk2YMTIS0FAOTKEABismKhLc6mjigASKOS9v+QIcB0mkBUxYKHEadDKgoAyJghAERjrUK7nFNdUAAQTmHt/+Q/lCEAxGGpwxgnRRIKABLo7h0vFT4nhgAQh1UKXXBmtU4BQCzdbWeXf6j535mbIcB0mkAUzyKHdTk1+qcAoG9TdtgdbZG3uq3vrgyY/gMaAmR0JDDJ+oTuOL/apQCgZE228p1OA/pnCABpWd4whROkZwoAymz/t7V9b70MMAQo5khgLSsTuuYsa5ECgNJ00bkvYxpgCACpWNiwKadJnxQAFNX+73Sb3tadGwIUcyQwZE1CP5xrbVEAUIh+mvS5jwIMAaB/ljTMyMnSGwUA2bf/+9+UN39EQ4BijgSsRuiTM64VCgAylrYfn+k0wBAA+mQxw5Y4ZfqhACDL9n+czffcR2IIUMyRUDPrEPrnvGtOAUBm4mz94x/VRgwBoB+WMczBidMDBQApbald3fU77/v/bYSOuvWGANAPKxBScfY1pACgc81b461s/WfcFs/+N3v4DrKFzhgCQNcsYJib06drCgCSmWWf3efWv/m/muPIDQGKORJqY+1BWs7BJhQAdGvu7XuqrX+799DwpzAE0AQiU5YuNOQk6pQCgDSmbKwjbP3bvbfpP5EhQDFHQj2sOojAmTg3BQAdmmMfH2rrP3nPTe58vh/NEEATiOxYtNAKp1J3FAAksO42umHjv7utf4sPtNHPaAhQzJFQA+sN4nA+zkcBQFdm38032fo3b8w3edz5/u1Wf15DAE0gMmK5QoucUB1RANC3tfvm5lv/9o6r72MY+9kNAYo5EspmpUE0zso5KADoxKbb+ty3/j1PAwwBNIHIgoUKrXNadUEBQK9WVlZK2vq3WwYYAhRzJJTKGoOYnJtbpQCgfVP290Vu/dv6nYTpT44hgCYQwVmi0BEnV+sUAESXy9Y/8mHXMwQAADalAKBlLTaqQ+2hI/wIhgCbNoGUInRn+urSoYROyf92KQCIqICtf7QfxxAAABhSABBIqg/170f8H80QADai/Q/Jyf8WKQBoU/G/49tcw5+04ZclL3RJ8gJAFhQAJFbP1j+Ln9oQACZp/0MQ8r8tCgBas9XmdNhNcPC3PBkCAABNKABIIMnWv8kXkHUtVC1kCABraf9DKPK/FQoA2jHj3trWv5UnxxAAAJibAoCe2PpnNA0wBIAh7X8ISP43pwCgBdM32bb+c9j0STMEAADmowCgtA/1z33rH2QaYAgA2v8QlvxvaHvTO6B6k7vtVHvWYvb9Gz2fYz/g8vLy3E/1yspKp0/X0tJS1yUEADAfEwBK6FiX1PWP8/QaAlAz7X8ITv43oQCgkdG229a/N2ufar8JAABslQKApmz9C37aDQGok/Y/ZEH+z00BQCO2/lk//4YAAFAhBQA5sfXvnyEAtdH+h4zI//koAKhl67/0Q+0dUSEMAQCgNgoAorP1T84QgHpo/0N25P8cFADEZevfD0MAAKiKAoCIbP2jMQSgBtr/kCn5v1UKAGKx9U/CEAAA6qEAIApb/+AMASib9j9kTf5viQKA9Gz9IzAEAIBKKABIydY/L4YAlEr7Hwog/2enACANW/+ADAEAoAYKAPpm6581QwDKo/0PxZD/M1IA0B9b//gMAQCgeAoA8tj62zvGYQhASbT/oTDyfxYKAPLY+jtde2MIAABlUwDQFVv/ghkCUAbtfyiS/N+UAoD22frnzhAAAAqmAKBNtv71MAQgd9r/UDD5P50CgHbY+hfGEAAASqUAoClb/2oZApAv7X8onvyfQgHA/Gz9y2YIAABFUgAwD1t/hgwByJH2P1RC/m9EAcDW2PpXxRAAAMqjAKCWrf+uH0ry0GUzBCAv2v9QFfm/ru3r3wxrNN/3pz3B7PubWFlZaWUBbGRpackLBAB9MgFgGl1/ZmEIQC60/6FC8n+SCQDr0/VnxBAAAEpiAsA4XX/mYAhAfNr/UC35P8YEgB/R9WcjhgAAUAwTAH5A15/mDAGITPsfKif/1zIBqJ2uPzMyBACAMpgA1EvXn9YZAhCT9j8g/9cyAaiRrj/zMQQAgAKYANRF15+uGQIQjfY/MCL/h0wAaqHrPzznW9k+1swQAABypwAon62/Dl/Pdu3a1emCWV3e3fw1XVzZqRpEOECFFuW/twCVzRt+Fld2usC3bmVlpdP7DzJ+DXIYNOR1BLZqqYLcMAEok66/fX9ahgDEJyWgWovV578JQGl0/XX9e2AIQBa8gsB8lkpPDxOAcuj62/eHYghAZOICKrdYd/6bAJRA11/Xv3+GAATntQOaWCo6Q0wA8qbrb98fmSEAMckNYKHu/DcByJWuv65/coYAhOVVA5pbKjdJTADyo+tv358RQwCiESDASLX5bwKQE11/Xf9oDAEIyOsFtGWp0DwxAciDrr99f74MAYhDkgBj6sx/E4DodP11/YMzBCAUrxTQrqUSU0UBEFrWjX9bf1ocAU3XSvPGYiuelxhY12J94aAAKFmqxr+tf20MAQjCawR0Yam4bFEAlMnWn2gMAUjLiwtMsVhZRCgASmPrTxKGACTn1QG6s1RWwigAymHrT3CGAKTiZQU2tVhTUCgASmDrTwSGACTkdQG6tlRQzigA8pbv1r+2UpshQwD65wUFZrRYTVz4IrBcJfxwz4JPsFY+d5XuLC0tdV1CZHQYFNmWAyJbKiX/TQDyk3vXP+zun34YAtAnLyWwJYt1hIYCICe2/hCk1xvkMPBaAD1bKiJzvAUoD97wE6QxTCt27drV6ZJeXd7dfNUtruy0ZnIXJHxIbpZzefh3rBkW6sh/E4DodP2bW13eXfyZXJXezojpq7eMJlDuprwKEcKH7PLf9YJK8t8EIC5d/+bkeFhZDAGAfDXJf9MAimcCEJGuf3O6OGUzBED7n67z33WkcotF578JQCy6/s3J61wYAgDx8980gCINFnK26e4hfn022nnb+jdn65+dhst+09Xb1sqcvrTK+Ezo7Gj/03/+W1oVWi00/00A0rP1b87WP1OGAEBG+W8aQDEyngDMsm+IPwFIwtZ/IxZMdgwB6qT9T/LWj5VWj9US898EoC62/tTGEADKEyH/TQPIWq4TgBk7tRq6I7b+s7BgcmQIUBvt/5q1lf/DE7atzLfwirdaXP6bAJTP1p/KGQJAAdrd+rdbBpgGkJ0sJwCzn6uVN3Rt/beq8gWTL0OAemj/V6iLrf8k0wCqyn8TgDLZ+nc98CUvhgCQo362/mv/jmkAlchvArClk7PC3Z6t//TnZPqSqHDBFMMQoAba//Xoc+s/yTSA4vPfBKActv65n410yhAAshAh/00DKF5mE4Ctno2VNHRt/Wd/TkwACmYIUDbt/+JF2PpPMg2gyPw3AcibrX/Wpx89MwSAmCLnv2kARcppAjDH6VdwQ9fWf77nxASgbIYApdL+L1Xkrf8k0wAWSsl/E4D82Prne76RnCEABJFj/psGUIxsJgDznW+FNXRt/Zs/JyYAxTMEKI/2f2Fy3Pp3d8mwhnO0mn/+mwDkwdY/0xOMgAwBIJXC8r+VgYBpAEnkMQGY++wqoKFr69/uc2ICUANDgJJo/5chQv53yjSgNquZ578JQFy2/tmdTuTCEAB6U0n+mwaQl0Hu7Z/pyZJpQ9fWv7voNwGohCFAGbT/sxYt/3tjGlCJ1Zzz3wQgFlv/vM4f8mUIAN2pPP9NA4hvkHv7p5gJgK1/P9FvAlAPQ4Dcaf/nKHL+J2EaULbVbPPfBCA9W/+MThhKYggALZL/6zINIKZB7u2frCcAtv79R78JQFUMAfKl/Z+RXPI/OdOAIq3mmf8mAGnY+udyhlA2QwBoQv5viWkAcQxyb/9kNwEoaevfSvr3HP0mALUxBMiR9n8Wssv/UJpfbpwLcaxmmP8mAP2x9c/ilKA2hgCwVfI/wjTAKIC6CoAc17qt/xjRT2+Wlpb6WW+bfi0JJcVgteR/u5QBZVjMMP+DFgDFvBPD1n+M6KfOIUBvdUgBisn/wsj/7igDyrYUMv+DFgAbyWhx2/qPCbj6qYQhQBni5GFt5H8/lAFZW8wt/yMWALm3f2z9x4h+4jMECCL3/C+M/O+fMqBIS/HyP2IBsJH4q9nWf0y05U61DAFyFycYKyH/01IG5Ggxq/wPVwBk2v6x9R8j+smOIUBymeZ/YeR/HMqAkiwFy/9wBcBGwi5fW/8xodY3jBgC5CtOQpZN/sekDMjIYj75H6sAyKv9Y+s/RvSTO0OAhPLK/8LI//iUAQVYipT/sQqAjURbr7b+Y+IsaJjCECBHcaKySPI/L8qA+BYzyf9ABUAW7R9b/zGin8IYAiSRRf4XRv7nSxmQr6Uw+R+oANhIkAVq6z8myAqGLTEEyEuczCyJ/C+DMiCsxRzyP0oBELn9Y+s/RvRTNkOAnkXO/8LI//IoA7KzFCP/oxQAG0m7Im39x0RYstCQIUAu4oRnAeR/2ZQB0SyGz/8QBUDA9o+t/xjRT1UMAWrO/8LI/3ooA3KxFCD/QxQAG0myBG39xyRfo9A6Q4D44qRovuR/nUav2tyVgDKghvxPXwDEaf+0lXRBzhnRD00YAlSV/4WR/zQfCCgDys7/9AXARvpcc7b+Y0Q/xTMEiCxIluZI/jNGGZDQYuD83155+8fWf4zohxFDgLLzvzDynymUAQEtJc3/oBOAHhaZrf8Y0U9tDAFiChKqGZH/zEgZ0L/FqPm/vcL2j63/GNEPGzEE6Ij2fyvkP3NQBsSRMP8jTgC6W1W2/mNEP5UzBIgmSLrGJ/9pSBnQm5j5v72S9o+t/xjRDzMyBGid9n8T8p8WKQOSS5X/4SYArS8jW/8xoh/WMgSII0jMhiX/6YgyoML83152+6ekb/VquHTkPszNEKBF2v9zkP/0QBmQSpL8jzUBiLZughyP6IdOGQJEECRvo5H/9EwZUEn+JygAsmj/BFm7oh+CMASoJ/+DkP8kpAzoWf/5H2gCEGShBDkM0Q99MgRIK0jwBiH/CUIZUHD+910ARG7/BFmjoh9iMgQoOP+DkP8EpAzoR8/5H2UCkHZlBFmXoh8SMgSoPIHTkv8EpwwoLP+3V97+CbIWRT9kwRCgpPwPQv6TEWVAMfkfYgKQZCkEWX+iPxTPJ7U1gZILEsVJyH8ypQwoIP8HvT3SlIXSZBHM8SQGWXOiPwltSJprJUOmJ0BhJ3hH+Z8v+U8xGl5VJUCqEzz9BKDP1z7IOhP9QJAmUFpBMrlP8p/CmAZkmv+D3Ns/Mz6DQdaW6E/OBIBWGALMTvt/SP5TPNOAjPI/8QSghxc7yHoS/UDAJlBCQcK5B/KfSpgGZJT/g9zbP1OeviBrSPSHYgJAWwwBZlF5+1/+Uy3TgOD5n3IC0N2rG2TdiH4geBMolSAp3R35T+VMA4Ln/yD39s/YcxdkrYj+sEwAaJEhwHR1tv/lP4wxDQiY/8kmAK2/nEHWh+gHtqTCIUCQuG6d/Id1mQYEzP9B7u2fHr6Yc0aiPwsmALTLEGAjVbX/5T/0cyGuLT12dRYOaQqAwl4/0Q/zcRmYJUYyjQj5P4tMX1xoTv6nzf8OC4Aa2j+iH5pzGShvCCD/N5XdawpdkP8LifI/QQFQxgsm+qFdLgMlDQHk/xTZvZrQNfm/2nv+d1UAFNz+Ef3QnZovA8UMAeR/AS8i9E/+9xkdfRcAWb9Coh/6Ue1loIwhgPzP+uWDtOR/xgVAee0f0Q/9q/AyUMAQQP7n+KpBNPK/6yTptQDI8SUR/ZBWbZeB3IcA8j+v1wsik/85FQDFtH9EP8RRz2Ug6yGA/M/iZYK8yP8ugqW/AiCj10D0Q0yVXAbyHQLI/+AvEORL/u+KXADk3v4R/RBf8ZeBTIcA8r+9YwHWJ/8X8ioA4j/poh/yUvZlIMchgPwH+iH/m9vewn1kTvRDjoan3nyXgeFZH/8yQNfkP+RI/seaAGTX/hH9UIYiu0F5DQHkP5CE/J9PpRMA0Q8l0Q1idvIfSiL/E08Acmn/iH4oW0ndoFyGAPIfiED+z66iCUCT6Jf7kAvdICbJf6iB/O97AhC8/SP6oU4FdIPiDwHkPxCQ/K99AjB3+ot+qLwbFOQawNzkP1RL/nc+AQjb/hH9QPNuUOQoSx5W8h+IT/7XMgEQ/UBb3aDa3hiaO/kPjJH/7U8AorV/RD9QXjco5hBA/gPZkf+lTQBEPzAj3aDCyH9gRvK/hQlAkPaP6AeK7wZFGwLIfyB3SxXnf94TANEPNKQblCn5DzS0q+L8H2Ta/hH9QG3doDhDAPkPFGapsvzPbwIg+oGOjFJiq1eCArpBWZD/QEd2VZb/g4zaP6IfiN8QShWDvQWd/AeKt1R6/ucxARD9QC5vD820GxSW/Af6t6v0/B8Eb/+IfiCCON2gtEMA+Q/UZqnE/I87ARD9QBzFd4NCkf9AHLtKzP9BwPaP6AciS94NSjUEkP9A5ZZKyf9YEwDRD8RXZDcoOfkPxLerlPwfBGn/iH4gR6m6Qf0PAeQ/QDH5n34CIPqBfBXTDUpC/gP52pVz/g8Stn9EP1CSnrtBfQ4B5D9ASfmfZgIg+oHyZN0N6o38B8qzK7f8H/Tc/hH9QA366Qb1MwSQ/wCF5X9/EwDRD9Qju25Qp+Q/UI9dOeT/oIf2j+gHatZpN6jrIYD8Bygv/7udAIh+gCy6Qa2T/wC7oub/oKP2j+gH6Kcb1N0QQP4DFJn/7U8ARD9Adt2gVsh/gCzyf9Bi+0f0AyTpBnUxBJD/AKXmfzsTANEPkHU3aG7yHyC7/B80bP+IfoAI3aB2hwDyH6Dg/J9/AiD6AYrpBs3xuHOQ/wAR8n8wR/tH9AME7Aa1NQSQ/wBl5/+WC4A5yH2ArWoxhNsqALp+XAAWesn/QacPLPoBmuh/Ly7/AYrP/66+CVj0A6R6b2ha8h8geP6vMwFo+EiiH6ALzS8Dm+az/AeoIf/bnACIfoDujDI24EBA/gNklP/jE4D57lf0A/Ss9biW/wBZaB7XTScAoh+gzl8PkP8Ameb/P5sAbOmORD9AEM3TW/4D5Gi+9J5nAiD6AeqcBsh/gALy/0cTgFn+pegHCG6OMJf/AAWYPcxnnQCIfoA6pwHyH6Cw/P+nCcCUvyr6ATI1S7bLf4DyTM/2aRMA0Q9Q5zRA/gMUnP+Ddf9M9AMUZt2ol/8AxZuM+vEJgOgHqHMaIP8BKsn/wej/iH6ASoyVAfIfYKEOw/z//wCI/ffwYKFuUgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_331
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You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_385
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color yellow.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_417
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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"text": "This is the original shape, with its image:.",
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color blue.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_439
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 3th action is Colorize the top layer of the original shape with the color blue.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color yellow.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_489
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 5th action is Colorize the top layer of the original shape with the color cyan.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_17
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_466
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"type": "image_url"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_243
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color green.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_410
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_212
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color yellow.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_159
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is Cut the right side of the shape\nthe 8th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
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rV4LNC4DXNbBvypeoZQxpkALGQaAAAAGQeA8RKwGAAAACEmAAuJAQAAkF8AqLgNTgwAAIAQE4CFxAAAAMgmAAwYAlw4NTP8s4sBAACQlNWj/oWNcxvmM8DGuQ1D/pVeBnCPLQAASHQL0IrF+oVTMyNNAwwEAAAgy2sAFvb+xQAAACgkAAy/Y0cMAACAku8CtOQFAGIAAADkHQDGuGxXDAAAgAK/B2DwXYDEAAAAyDIAVLl3pxgAAADlfBPwkF8FIAYAAEBOAaCWL/ASAwAAIO8JwEjfBzxPDAAAgAwCQC1DgB4xAAAAspwAjDEE6BEDAAAg3QBQ7xCgRwwAAICcJgBVhgA9YgAAACQXABoaAvSIAQAAkMEEoJYhQI8YAAAAqQSApocAPWIAAACkOwGodwjQIwYAAEDHAaC1IUCPGAAAAMlNABoaAvSIAQAA0E0AaH8I0CMGAABAKhOApocAPWIAAAC0GgA6HAL0iAEAANDxBKC1IUCPGAAAAG0EgBSGAD1iAAAAdDMBaH8I0CMGAABAgwEgqSFAjxgAAACtTgA6HAL0iAEAAFB/AEhzCNAzagYQAwAAKFiDE4AUhgBjjwLEAAAAilRPAEh8CDBPDAAAgNVN/4CNcxvGKLubM38wo44mehkgi6gDAACNbwHKqzIebxpgIAAAQO6avQYgqSsB+okBAABEU2cAyGsI0CMGAAAQRxsTgJSHAD1iAAAAEdQcADIdAvSIAQAAlK2lCUAWQ4AeMQAAgFLVHwByHwL0iAEAAJSnvQlAXkOAHjEAAICSNBIAihkC9IgBAACUodUJQKZDgB4xAACA3DUVAMobAvSIAQAA5KvtCUDuQ4AeMQAAgBw1GAAKHgL0iAEAAOSlgwlAMUOAHjEAAIBcTDb9A5YrcMermNM3draJMDBp03jJym+BUAZ/TGam1rV4LFCbDXNb6n1CpwbK01kAKDgDiAHtaGJ44vUnFAGATNVe4lfhxEGOVnd9AGWazzZjxID587HVZBEbpQBiSqrWH/4M5TxO9AlA2CFAj2lARuV+2NecmEwASE365f7YnF9IiglA40wDVqTBDxBTwRX/4DNdhJM70ScAhgA9pgGJF/3lvc4wgAkAnYhT9A/JqYf2mQC0Kvg0IM2iH4CmKfqHPDnmfqInFy1NAAwBwk4D8ir683ptoSITABql6K/IKYnmmAB0puxpQF51PwB1UffXfiZN/IxPjtqbABgCRJgG5F73p/Z6QqNMAKiRur8FTlLUxQQgCblPAxKs+5erXZyiAGqU4KK6fmZqycc3b5gb42+t+BfbZCZAlhMAQ4DCpgHd1v3jtScHn6ssqYRiAkCmdf+AYn2AsQNAladtmtMW4zEBSE7604D2636FCEDMun/surzbI2wtFZgJkMcEwBAg62lAa6V/cxW/CQD0mACQYOnfXMXf0ASg+o+ukbMYQzIBSFoi04AW6n6lBkDMuj/9Hn/t/8bm8oCBAOlOAAwBMpoGNFr6d1L0mwBAjwkAXZX+nRT9HU4AuhoOOKmxHBOAbLQ8DWio9FdSAMQs/SN0+iu+LLWHgURuFUiCupkAGAJ0NQ1YcSEovu43AYAeEwBC1f1pTgDaHAs4x9FjAhBrGjCgH1B76a96AIhZ+idVTOeoobGAgQDdTwAMAdKZBtRb+ide95sAQI8JAPWW/onX/RlNAFoYCzjfBWcCkL3q04BaqBUAYpb+6ZfOZei9zrUkAdOA4FZ1+LMHvO2qdLVjunBqpquxyczUOtU/QC42zG2pq/pfPzOl+m9fjS/79E/U8lTkxQSgKFWmAaNS9APkpca6v5bnIZGBgGlAQF1OAAwBMp0GaPkDxOz6a/knqK5fimlAKCYAxap9GqDoB8hR9dJf0R9nIDA9PW0UEEHHEwBDgKbVMgrQ8geI2fjX8s9O9V+ZUUAEJgAlq56g1P0AOdL1D27+11dlGuDCgLIlEQBmZ2eXy5ob5zb4ToD2S391P0Cmqrf86zsWst8XJAaUKokAQDrVv9IfIGb1r/QvWMWBgAsDypNKADAEqIXSHyAmpT+NxgCjgMKkEgDosPpX+gPErP6V/gFVjAEyQBkSCgCGAGNT+gPEpPSn5RhgFFCG7m8DSkWqf4CYVP9UNPY7wX1Cc5fQBMAQYFRKf4CYlP7UxSggprQCAE1X/0p/gJjVv9KfhmKADJCj5AKAIcCKlP4AMSn9STAGGAXkyDUAmVH9A8Sk+qcd471nXBWQlxQDwIAQWfELbnM3xj9/Zmqd6h8gYPW/fmZK9c94xnvzyAAZSW4LEDWW/s0cCwCpl/7NHAuxjLEjyHagXKQ4ATAEWET1DxCT6p/OGQUUyQSgtOpf6Q8Qs/pX+pPUKMAcIGWJTgAMAeb/map/gIA2zG1R/ZOaUd9j0z/R2OFQiQlAopT+ADEp/UmWUUAx0p0ARB4CqP4BYlL9U+QooLFjocQAEJPqHyAm1T+5kAFyl/oWoFBfDKz0B4hJ6U/x24HcITQpJgCpUP0DxKT6J19GAZnKIABEuBJA9Q8Qk+qf3MkAOUp9C1AEI1X/Sn+AmNW/0p+StgPZC9StDCYAZQ8BVP8AMan+KcxI71JzgG7lEQBKpfoHiEn1T5FkgFxkEwDKGwIMf9gzU+tU/wABq//1M1Oqf/Iy0ptWBuhKNgGgMCNV/w0fCwCJVv8NHws0RQZIXE4BoJghgOofICbVP3HIAClzF6BW2fQPEJNN/wS0fmZqyFsD+ZqwluU0Ach9CKD6B4hJ9U9YLgtOU2YBIF+qf4CYVP8EJwMkKL8AkOMQQPUPEJPqH2SABLkGoHEu+QWIySW/MN63Bfuq4KblNwHIdAiwItU/QEyqf+Lwbk9ElgEgI0MGEtU/QMz2v3qIaIZ8z9sI1KhcA0AWQwDVP0BMqn8YQAboXK4BIH2qf4CYVP+wIhmgWxkHgJSHAKp/gJhU/zAkGaBD7gLUcfU/0h3iAEiZ6h+a+KpgNwWqXcYTgDSHAKP2/g0BAMqg+ocxmAN0Iu8AkBo7fwBiUv3D2GSA9pUcAFoeAoxd/csDAFlT/UNFMkDLsg8AiewJ0/sHiEn1D7WQAdqUfQAYrPPbAQ1JMAAAoB0lBIDBQ4AWMoD2P0BM2v9QI0OA1pQQALpVV/UvHgDkRfUPtZMB2lFIAOhqCKD3DxCT6h8aIgO0oJAA0Inaq385ASALqn9olAzQtHK+CXh2dnbA+2Dj3IYLp2YmWld7TT+7qYN/RUmmz83junAgd6p/aOFLghmPCUCD7f8xqv8V/4r6FSD99r/qH6ob5nNkCDCeogJAa1cCNFT9A5A41T+0SQZoSFEBoB1N31fUEAAg663/QMtkgOgBoPPvBJin/Q8Qk/Y/1MtnqgmlBYCmtbP5xxAAIDU2/0BXbASqXYEBoLkhgK3/ADGp/qFbMkC9CgwADWlt+9A8QwCARNj6D7mQAUIHgK6uBND+B4hJ+x+a5lNWozIDQO062fxjCADQOZt/IB02AtWl2ABQ4xDA1n+AmFT/kBoZoBbFBoAyGAIAAFCvkgNALUMA7X+AmLT/IU2GANWVHACqS6H6NwQAaJ/qH1ImA1RUeABo+nZAev8AMan+oVs+g1UUHgAyuvH/AIYAAG1y438ogyFA3AAw3hAghc0/ALTP5h/IhY1AYys/ADSk5erfEAAgEap/SIfP43hCBIBRhwDpbP4BoE02/0B5DAGCBoCRJLv5xxAAoFE2/0CObAQaQ5QAUOPtgGz9B4hJ9Q9p8tkcVZQAMKTEN/8YAgA0xOYfKJshQNAAUMsQQPsfICYtRkiZT+hIAgWA3Nv/8wwBAGqn/Q8RGAIEDQCDhwAr0v4HiElzEdLnczq8WAGgjOrfEACgzfa/qgJyseKn1RAgaACoOAQAoCQ2/0A00zJAwACQe/t/niEAQDu0/yEvPrPDiBgADAEA0P6HsKbDDwEiBoDc2//zDAEAmqaVCDnyyV1R0ABgCAAQnPY/RDYdewgQNADk3v6fZwgA0BxNRMiXz+9gcQPAMEOAlKt/AMbm1p9QPLcEHSBuACiDIQAAACOJGwBWjH3a/wBF0v6HIAwBlhM3ABTDEAAAgOEFDQDa/wAxaf9DKIYASwoaAApjCAAAwJAiBgDtf4CYtP8hIEOAfhEDQJEMAQAAGIYAsJj2P0BM2v9QKp/u6AGg4CmPIQBAlf0/QFjT5daHSwoXAAAAILJYAaD4y38NAQCW5PJfCM6lwHEDAAAABBcoABTf/p9nCACwiPY/YAgQNAAAAAACQFHt/3mGAADD0/6HOHzeYwWAODMdABZy909geNMxKsYoASAaQwAAAOIGgCCX/wKwiMt/gUXWuxQ4SACIyRAAAIB+AoD2P0BQ2v8Q0/rwn/3yA0CEOc5yDAGAyFz+C4xnuvTqcXXXBwAtGSbt9D7ws7OzzR8RAEAHogeA4vf/zEytG9wDmz53w+ymmYniVBxu9Ed/kQAKYw8ARLZ+ZmrzhrmJqAoPAMVPcGhtR9PC95IwAOmz/weoYnp6uuDTfeEBIHj7P8gQoP0rGewUgtxp/wPrAw8BQgcAspbCFcySAACQnZLvAmT/T6m3A5o+d0NqBzz9E10fBfDP7P8Bqpsu98wedwIQZP9PSVIr+vsZCEAW7P8Bgu8CKnkCQDFDgARb/oMZCAAAySo2ACi/ipFX6b+QNyF0wv4foC7ThZ7Kiw0Ag8Xc/5PdECC7xn8/owBIjf0/wEIx14S41wCQsibq/vlP+OCtfr1VoN4dgfMZwIUBAEAKygwAeq5ZfydAXdV/lUy/6O/WkgfK/koRSIT9P0C9pks8fZcZAMhXxeq/oUHewqetEgaKXEQAgLxEDAAxLwBIfwhQpfRvcwNfxW1CtgNBh2Ju9gUGWx/vZqBBLwImNWNX/+tnpro6o1f50XapAQBdKTAAKK2yux3QeD+uw9K/lsPwRoXauQAAaMJ0cafsAgPAYMH3/yRojOo/kdK/+iGVt6BAylJbN4B0rA+2PoQLACQ1BBj1pyRY+lc8PBkAAGhZxIuAScEYpf9EJob5woGFXBYMALSptAmAfmoWQ4CCq/8eowBomQsAgOZMl3WaLi0ADOYCgOwkvuen4IOHwvgwAoOtj7RKxAoApDAEGP45y/goDv+vKKy7AACkSQCgVdGq/3kyAACQjqICgOIp8SHAkE9V5M6Z4f9R3sYwBhcAAE2bLugEXVQAGMwFAN0avvqfKJcMAJ0oe2EB6rI+zFoRKADQ4RBA9d8jAwAA3RIASEWE6j/avxQASJAAQONDgGH+brSaeJh/ryEAANCEcgKAailNqv/lyABQF1cAA+2YLuW8XE4AGMwVwJ0MAZr7LuE4illroCsxWwzAeNbHWDGiBACSFeSTtqTI/3YAoCsCAE0NAWz+GYaNQABAywQAOqP6n+d1AADaJADQyBDA7v96GQIAAHVZFaE8cgVwy2z+GZWNQNDQLYAsNcCo1g9cN8o4HRcSAMjri4Gdkvt5TQCAdggA1Mzmn+aU0XUAALolAND2EECrezleGQCgBQIAAAAEIgBQ5xBgxcmAJnfF18cuIACgIgEAAAACKSEAuAdoIkMA7f9aGALA8NwDFGjC+tLvBFpCAAAAAIYkANDS7YC04obntQIAmiMAUA+3/29TAcNHAKArAgBtDAG0tEflFQMAGiIAAABAIAIAHX8xMOOxCwgAGI8AQOPsZhmP1w0AaIIAwFB8nQIAQBkEAAAACCT7AOBrgFvjxUyNywAIztcAA81ZX/SXAWcfAEicc3AVXj0AoHYCACMwBAAAyJ0AAAAAgQgAjMYQAAAgawIAAAAEIgDQ4BDANazVlX0XAgCgfQIAAAAEsnoi8F2iadrmDXNdHwIQdP20/gAEDQAwEhUDQEzWf0KxBQgAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIJDCvwhsZmrdRM7ftTm7aWYibdPnbhjwp+tnpibS49teYN7s7OxEzqanp7Nbf+iW9R9CBAAYVYJFgzMWQMz1n25tLvf8awsQAAAEIgBQyeBNSgVH59YMfg1z38IBALRPAAAAgEAEAAAACEQAAACAQAQAAAAIRACgWa4DrsKrBwDULvsAMPguKIO/ZotapP9tZaVyCyCCG/wRkJ+BKjYXfRe+7AMAAAAwPAEAAAACEQBonEH8eLxuAEATBABq4DKA9uW++xAA6IoAAAAAgQgAtMFullF5xQCAhggA1MMuoDbZ/wMAjE0AoCVa2sPzWgEAzREAAAAgkBICgC8DzmUXkMb2MFZ8lez/gR5fBgw0YXPRXwNcSAAAAACGJABQJ0OAirT/AYCmCQAAABCIAEDbDAGW45UBAFogAFAzXwjQHPt/AIDqBAA6oNXdz2sCALSjkADgTqDZDQHUu6O+Gtr/sCR3AgXqtbn0e4CWEwBIjY1A9SpjuQEAUiAA0BmduXleBwCgTQIATbERaBg2/wAALRMA6FjkDBD53w4AdCVKAHAdcCdcCVCd9j9UJGkDw9scY8UoJwCok9JkI9BybP6BuvikAO2YLWW1KScAkCwZoJ/qHwDoigBAKuJkgDj/UgAgQQIACV0MEKEyHvLfqP0PADQkUABwHXC3ZADVP3Sl7IUFqMvmMGtFUQFA2VRMBijvEzj8P8rbGMbggwM0bbagdaaoAEBJNwYtKQMM/28paXEBANIkANC2aBlA9Q8AJCVWAHAZQHay3g6U9cFDYXwYgcE2R1olSgsAeqhFfkNwjp/JUY/ZWxcq8iECmjNb1gqzuusDIHQGmD53w0j19PqZqYnkKf0BgJSVNgGg+FFAytOAMQ5P9Q8AtCxcAHAZQO4ZIM0YMN4hqf6hTamtG0A6NgdbHwoMAIqqCBkgnRgw9mF4o0LtfKyAJswWt7YUGACIkwG6jQFVfnR5SwkAkIuIFwFvmNsyM7Wu66Og6mXBC/UK8RauEq6YN5T+0KHNG+ayuJcA0KbNCWwoaFnEAEDKZjfNjJcB+j/DNZ7m61oaVP8AQOfKDACzs7PT09NdHwXdZIDlqvaR8kATzQDVP7TA+g/Ua7bE03eZAYDI24Eq1vRKfwCgbEEvAnYz0CzMbpoZ++LgRMz+RNdHAYTe7AsMsDnkmlBsAFB1FSPfDOBNCJ3w0QPqMlvoemILEEF3BDWq1PUCAChA3ADgZqD5jgKSTQLqfsiCm4ECkff/lLwFSDVWsASvDbDXH5Li8whUN1vuShJ3AkDuUhgIFLw0AAClKnkCsCL3AipD+9OA+X6/6h/yFXbuD/REXgcKnwD4Rpjitdb+V+5DXqz/QBWzRZ/3Cw8AK3IpcL4aLf3L/tgDLgWG4DYHbv8LAGRJ6Q8AMLbyrwFQz5Vk+twNFat/Ax+Iw/oPjGe29NXDBMAuoChdf79lYBG7gCCmzbH3/wgAZEDpDwBQo/K3AA0zx3E/0II3/Kj+IbIV13+NQIhm80qf+uL3/5gAkChdfwCAhoSYAAQJc2XQ9QfqZf0HhjcbY8UwAfhnLgXunK4/0AmXAkMcdv3NEwDontIfAKA1UbYAuRQ4TTb8AC1wKTDg8t+FTADohq4/AEAnAk0ADAESoesPtM8QAILT/l/IBID26PoDAHQu1gQgWrwrqeuv+gcqsv4Dy5kNtj6YACzmfqD1ql73K/2BdrgfKJTKHr9FBACaovQHAEhQuC1ALgXOaMOP6h+ol0uBISCX//YzAaBOuv4AAImLOAEwBGiCrj+QBUMACEX7f0kmAFSl6w8AkJGgEwBDgFro+gM5MgSAILT/lxN3AjA9Pd31IWRM1x8AIFNxJwDDMATop+sPFMAQAIqn/T9A0AnA8O1/3wvWo+sPhOJ7wSBfMvxgQQMAI1H6A+WZnZ21FxTCmg3c/g8aAEZd8SMPAZT+QGSGAJAj7f8VRQwADEPpDxTPEABimo3d/o8YAMZb60MNAZT+AD2GAJAX7f9hhAsADKD0B6IxBIBoZsO3/8PdBrTKKl/2LUHd3BMIyy1BoRhu/TkkE4DoG4F0/QFWZCMQpE9WH16gADC4/X/h1MzExMTGuRqq4Vwo/QHm2QgEEWj/RwwAtShjCKD0BxiVIQCkTPt/JFGuARim/b/wf5TKXn+AJWkNQtl8xhcyAYgyBND1B6jIEADSpP0/qigTgAEWdf2HGQLkdUcgXX+AuhqE6gxIzTCfSu3/iAFg1Eu7itkIpPQHGIkqAcrjc90v+hagsWv9xDcC2fAD0BAbgSAdhnLjKX8CMN6d3fLdCKTrD1CFjUCQC5t/xlZ+ABi7ys9uI5DSH6AWKgYog89y0C1ATX+xSyIbgWz4AWiZjUDQLYO4KuJOAIZp8Ke/EUjXH6AJNgJBymz+qajkAFBL+z/ZDKD0B2iUDABpUv1XV/gWoGL29y9kww8AAGMrdgJQ4+7/dIYAuv4AbTIEgNRo/9ei2ABQb/u/8wyg9AfohAwA6VD916XMLUBN3/ynzZsC2fADkD43BYKmSdo1CjcBGHv3fyeXDaj+ATqnoQi58GmNGwCaa/93vhFoVPb8ANTCRiDols0/9SowADTaxc8lAyj9AeolA0BXVP+1Ky0AdLX7P50MoPQH6JAMAPXymWpCaQGghU38yX6HgNIfoFFajJAmn83QAaC19n9qG4GU/gDtsBEI2mTzT0OKCgBttu0TyQBKf4CWyQDQDtV/c8oJAIns/m8tAyj9AVImA0AVPkGNKicAtL9rf8inrT0DKP0BujVk01EFA+MZ8rOj/R89AHTV/m85Ayj9ARIhA0BDVP8tKCQAdHjTnnYygNIfIDUyANRO9d+OVWW3/9u5ZWejGUDpD5AsGQBqpPpvzer2fhQjUvcDAFC77CcAnbf/mxgC6PoD5MIQAGqh/d+m7ANAOmrJAEp/gOzIAFCR6r9leQeARNr/tWQApT9AvmQAGJvqv315B4AEjZEBlP4ABZABYAyq/05kHABSa/+PlwGU/gDFkAFgJKr/rmQcAFLW1ZcEA9AtGQCGpPrvUK4BINn2f48MABCTDAArUv13K9cAkAUZACAmGQAGUP13LssAkH77v0cGAIhJBoAlqf5TkGUAKJIMABCTDEAc3u2JyC8AZNT+H/WoNsxtEQMAijF8C3PzhjmFEWUb6U2u/d+0/AJAjkZKJjIAQDFGqmNkAEo10ntb9d+CzAJAdu3/HhkAICYZgOBU/wnKLABkTQYAiEkGICzVf5omJ/KRb/t/kY1zG4b8L31PcBMGhyurD9DJiWyR9TNTDR9LRIOLUa957Wz6T5YJQOqXBTd8LAAkellww8cCzVL9pyybAFBM+3+eDAAQkwxABKr/xGUTAMrj9qAAMbk9KAVzu88s5BEACmv/97gsGCAmlwVTJJf85iKPAFAwGQAgJhmAwqj+M5JBACi1/T92BhADAGJmADGANI365lT9dy6DABDBqElGBgAow6iVkAxAakZ9T6r+U5B6ACi+/d8jAwDEJAOQL9V/plZ3fQAszgDDf03YfAbwZWEAuZuviob/mrD5qssXV9EhpX/Wkp4AxGn/L2QUABCTUQC5UP3nLukAEJYMABCTDED6VP8FSDcAxGz/V8kAYgBAzAwgBtCOMd5sqv80pRsAuHBqxigAIKDZnxjpr8gANG2M0l/1n6z8AkCE9v9CRgEAMRkFkAiN//IkGgCGvxNCBGNkHhkAoABjVFEyAPUa4x2l+k9fZrcBjdb+H/sOoW4SChDzDqFuEkpdlP4FS3ECoP1f7yjANAAg5ijANIDxjPfmUf1nJMUAsJyw7f/qL4IMAJC78aorGYB23jOq/7wktwVI+7+J7UB2BAHE3A5kRxDDU/rHkc0EQPu/rlGAaQBAzFGAaQC1vz1U/5lKawKg/d/CKMA0ACDmKMA0gH5jx0Klf9bymABo/zfx4hgFAGRt7ArMKIB5qv+wEpoAaP+PzSgAICajAMaj9A8ugwmA9n8LowDTAICYowDTgGiq/NJV/8VIZQKg/d/tKMA0ACDmKMA0II4qYU/pX5jUJwDa/y2/aKYBAPmqUqWZBhSs4i9X9V+eJCYA2v9JjQIWXh9sIAAQZxSwsElsIFCA6olO6V+qJALAcrT/K7pwambsDDDPviCAgDHAvqDcKf1JPQBo/zekYum/kBgAkCMxICClP3kEgOVo/6dQ+i9kXxBAjmZnZyv22uwLSl9d12+o/oPoOABo/2dR+i9iIAAQbRQwz0AgQUp/ypkAaP+nWfovZCAAEDkGSALdqvGWTUr/gLoMANr/mZb+ixgIAASMAQYCXVH6U+YEQPu/tdK/xtOAgQBA5BggCTSt3m9pUPoH11kA0P5PofRf+L/r+o1IAgC5qHf9lwSaUPu3syn9SXECoP3fZunf/3iNwWzhNwoLAwDJqn39X1izCgNjaOgrmZX+dBwAtP/bL/2H/Nj3/rN6f0fGAgCJa2j9NxYYnrqfoBMA7f8OS/8l/1btUc1YACBxDa3/xgJtFv3zlP4kFAC0/xMv/fufoaFfmTAAkKxG1//gYaDRon+e0p9sJgDa/0mV/ks+W3PhbWEYkAcAEtHC+r+oGi4yD7RQ8c9T95NoAND+z6v0X/LJW/glygMASWlt/S8jD7RW8fco/clyAqD9n3jpv+QPai3OLcoD86QCgJa1v/4vWUknlQrar/UXUveTQQDQ/s+99F/u53bym10yFfSIBwClrv+Da+7a40G3Jf6S1P1UNDnRouWWicjt/0xL/4IzXmovKUAWClj/0+cMRX4BYMDSEDMAFFb6F3MmSPyFBUhcvut/spyYKDAABKz+yy79cz8T5PXyAiQru/U/Nc5HZB8AtP8Dlv6Zngxyf5EBEpTF+p8C5yBCBIA41X/w0j+jk0F5LzVAUpJd/7vivEOZASB4+1/pn9fJIMILDpCIpNb/NjnXEDcAFF/9K/1zPB+EfdkBOldwHnByIVYAiNn+V/rne0rw4gOkI9NI4FRC4joLAKVW/0r/3M8KfgUAiUsqFThrkKNmA0Co9r/Sv4zTg18EQNZqjwfOC5SnmwBQWPWv9AcAIBerg0zoGqL0BwAgLw0GgOWU0f5X+gMAkKOmAkDB7X+lPwAA+Wp7ApB1+1/pDwBA7hoJAOW1/5X+AACUodUJQI7tf6U/AAAlqT8AFNP+V/oDAFCe9iYAGbX/lf4AAJSq5gCQe/tf6Q8AQNlamgCk3/5X+gMAEEEHXwSWGqU/AABxTLaw/yfZ9r/SHwCAaIJOAJT+AADENBmt/a/0BwAgskATgCqlv7ofAIAyTEZo/yv9AQAgygRg7Opf6Q8AQHkmC27/K/0BACDEBEDpDwAAjUwAUmv/K/0BACDEBEDpDwAAzU4AEmn/K/0BACDEBEDpDwAALU0Aum3/K/0BACDEBEDpDwAAbU8AOmn/K/0BACDEBEDpDwAAnU0A2mz/K/0BACDEBEDpDwAA3U8AWmj/K/0BACDEBEDpDwAACU0Ammv/K/0BACDEBEDpDwAAKU4Aam//K/0BACDEBEDpDwAASU8A6mr/K/0BACDEBEDpDwAAeUwAKrb/lf4AABBiAqD0BwCAzCYA47X/lf4AABBiAqD0BwCAXCcAI7X/lf4AABBiAqD0BwCA7CcAw7T/lf4AABBiAqD0BwCAciYAA9r/Sn8AAIgyARij+lf3AwBA0hOA5dr/o1L6AwBAiG8CVvoDAEAeE4CK7X+lPwAAhJgAKP0BACCzCcB47X+lPwAAhJgAKP0BACDXCcBI7X+lPwAAhJgAKP0BACD7CcAw7X+lPwAAhJgAKP0BAKCcCcCA9r/SHwAAQkwAlP4AAFDgBKC//a/0BwCAEBMApT8AABRsstf+V/oDAEDxJnfs2NH1MQAAAC1Z1dYPAgAAuicAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCCruz4AaM+2bdtuuummG2644atf/eodd9xx1113Pfzww1u3bn3yySfXrFmzdu3agw466JBDDjnqqKOOOeaYE0888fDDD+/6kAEAaja5Y8eOup8T0rJt27aPfOQjH/jAB6699trHHnts+L94xBFHvOIVr3j1q199xBFHNHmAAIzskksuGem/n5ycXLVq1U477bTrrruuWbNmr7322m+//Q488MA1a9Y0doyQKAGAkj3yyCPvec973vnOd27ZsqXK85x55plvfetbn/Oc59R3aABUMjk5WcvzHHrooUcfffRzn/vcF77whS94wQv22GOPWp4WUiYAUKxLLrnkd37nd+69995anm3VqlVveMMb3vGOdzg3AJQUABbaddddX/KSl7zyla982ctetvPOO9f+/JAIAYAC/fCHP3zNa15z5ZVX1v7Mz3jGM6688spnPOMZtT8zAJ0HgJ5DDjnk/PPP/63f+i0bhCiSAEBpvvzlL5955pmbN28e8N/89E//9HHHHXfUUUftv//+e+6556OPPvqjH/1obm7utttu+9znPjc3Nzfg7+69996f+MQnjj/++AaOHYAkAsC8ww477A//8A/POeecpn8QtEwAoCg33njjKaec8uCDDy75p4ceeuhv/MZvvPKVr3zqU5+63DPs2LHjtttu+z//5/984AMfePjhh5f8b/bee+/rrrvuuc99bn0HDkByAWDe9PT0e9/73n333bedHwctEAAoxz/8wz+cdNJJS1b/e+2111ve8pbf/u3fHn5P5wMPPHDBBRe8613vWvIzcuihh958880HHXRQ5aMGoLYAMLiq+fGPf/zEE0888sgjDz/88JYtW771rW/90z/90+c///m//du/Xa5zNO9pT3vaNddcc+SRR9Zx4NA9AYBC3HnnnT/7sz/7ox/9qP+PfvZnf3ZmZma8m/pfe+21r3rVq5a8kvjkk0/+m7/5m7EOFoAOAsBytm/f/qlPferP/uzPPvKRjzz55JNL/jdTU1Mf+9jH7P+kDAIAJXjkkUdOOOGEL33pS/1/dNZZZ83MzOyyyy5jP/ntt9/+whe+cMlo8b73ve+1r33t2M8MQAoBoOe22277D//hPyzX3Nlnn32uu+46t4SmAAIAJXjNa17zF3/xF/2Pn3nmmZdffvnq1VW/8frzn//8v/pX/2rbtm2LHj/wwAPvuOOOtWvXVnx+AFIIAPP+7M/+7Pzzz9++fXv/Hx100EFf+MIX7P8kd6u6PgCo6tprr12y+j/mmGMuvvji6tX//Cait7zlLf2P33PPPe9973urPz8A6Xj961//qU99au+99+7/o+9///sbNmx44oknujguqI0JAHnbtm3bUUcd9c1vfnPR47vvvvsXv/jFI444oq4f9Pjjjx933HG33Xbbosef9rSnfeMb31i1SpYGKGQCMO9zn/vcL/7iLz7yyCP9f/RHf/RHb3zjG+v6QdA+VQt5e+9739tf/U9MTLz97W+vsfqfmJjYeeedL7jggv7H77zzzhtvvLHGHwRACp7//Oe///3vX/KPLrjggrvuuqv1I4LaCABk7NFHH73wwgv7Hz/yyCPPO++82n/cS1/60kMPPbT/8SuuuKL2nwVA584555xzzz23//GHH354ybMP5EIAIGN//dd/fc899/Q//l//63/daaedav9xO+200+tf//r+x6+//vrafxYAKfhv/+2/rVmzpv/x97///UuegCALAgAZe9/73tf/4Pr161/60pc29BNPP/30/gdvvfXWrVu3NvQTAejQYYcd9h//43/sf/yxxx676KKLujgiqIEAQK5uv/32z3/+8/2Pv+ENb2juktxjjjlm3bp1ix584oknvva1rzX0EwHo1r/7d/9u11137X/8gx/8YBeHAzUQAMjVlVde2f/g5OTkOeec09wPnZycPOmkk/of/8Y3vtHcDwWgQ3vvvfeS49+v/EQXRwRV1XCLdOjERz/60f4HTzjhhIMPPrjRn3vOOef032Zuzz33bPSHAtChX/mVX7n88sv7H7/22muPOuqoLo4IKvE9AGTp4Ycf3mefffq/iuUtb3nL7//+73d0UACU8z0AC23fvn1qaqr/OwFe9rKXffjDH27iJ0KjbAEiS7fccsuSX8T4whe+sIvDAaBku+yyy7Oe9az+x7/4xS92cThQlQBAlv7xH/9xycePPfbY1o8FgPIteX751re+9dBDD3VxOFCJAECWvvzlL/c/eOCBB+63335dHA4AEQPAjh07Nm/e3MXhQCUCAFn67ne/2//g0572tC6OBYDyHX300Us+/r3vfa/1Y4GqBADKCQAHHXRQF8cCQPn22WefJR///ve/3/qxQFUCAFn6wQ9+0P9g/1d0AUAt9tprryUff/DBB1s/FqhKACBL/fdim5iYWLNmTRfHAkD59t577yUff/TRR1s/FqhKACBLjz32WP+Du+22WxfHAkD5lpsAbNu2rfVjgaoEALL04x//uP9B32oHQEOW/PKZiYmJnXfeufVjgaoEALK06667DjkWAIDqluv0Gz6TIwGALC253X/JCwMAoLrlvvBr9913b/1YoCoBgCztueee/Q9u2bKli2MBoHz33nvvko8feOCBrR8LVCUAkKWDDz64/8F77rmni2MBoHzL3e//kEMOaf1YoCoBgCwtueDeeeedXRwLAOX7+te/vuTjT3nKU1o/FqhKACBLT33qU/sfvPfee3/0ox91cTgAFO6rX/1q/4Pr1q2zBYgcCQBk6dnPfvaSj3/pS19q/VgAKN9NN93U/+AxxxzTxbFAVQIAWVpuzf3sZz/b+rEAULgHHnjg9ttv73/8hBNO6OJwoKrVlZ8BOnD00UfvvffeDzzwwKLHr7/++v/yX/5Loz/63/7bf7vofqO77LLLBz/4wUZ/KAAd+tjHPrbkF4GdfPLJXRwOVDXpy1PJ1Mtf/vIrrrhi0YM77bTTPffcs//++zf0Qzdv3vz0pz990YOHH374N7/5zYZ+IgBLmpyc7H+woapmenr6sssuW/TgPvvsc9999/kmYHJkCxC5eslLXtL/4BNPPHH55Zc390M/+clP9j/YHwkAKMZ999135ZVX9j9+9tlnq/7JlABArl7+8pcvufL+6Z/+aXM/9Nprr+1/8FnPelZzPxGAbr373e9+/PHH+x//tV/7tS4OB2ogAJCr/fff/5RTTul//Etf+tL111/fxE989NFHP/WpT/U/fuKJJzbx4wDo3A9/+MM/+ZM/6X/8+OOPf/7zn9/FEUENBAAy9vrXv37Jx//zf/7PTfy4iy+++P7771/04M477/yiF72oiR8HQOfe9KY3Pfjgg/2P/6f/9J+6OByohwBAxk499dRjjz22//HPfe5zl156ae0/7j3veU//gyeddNK+++5b+88CoHPXXHPNX/7lX/Y/fuKJJ55xxhldHBHUQwAgb7/3e7+35OO/9Vu/9YMf/KDGH3TZZZfdcsst/Y//+q//eo0/BYBE3HHHHb/6q7/a//hOO+30nve8Z8l7EEEuBADy9su//MtL7sDZsmXLr/7qrz755JO1/JT777///PPP7398/fr1Z511Vi0/AoB03HXXXSeffPLc3Fz/H735zW/2BcDkTgAge+9+97uXvB3Qxz/+8Te96U3Vn3/Hjh2/+Zu/+f3vf7//j97xjnfstNNO1X8EAOm47bbbTjjhhG9961v9f/TzP//zb33rW7s4KKiTAED2jj766He84x1L/tH/+B//481vfnPF5z/vvPMuueSS/sd/8Rd/cXp6uuKTA5COHTt2vPe9733e85733e9+t/9P169fPzMzo+9DAXwTMCXYsWPHmWeeefXVVy/5p+ecc86f//mfr127dtSn3bp162//9m+///3v7/+jqampW2+99dBDDx3reAFI7puAr7vuuje/+c0333zzkn96wAEH3HDDDevXrx/7+SEdAgCFePDBB3/hF35hyet059s2f/zHf3z66acP/4Sf+cxnXvOa19xxxx39f7R69eqPf/zjJ510UoXjBSCJAPC1r33tqquu+qu/+qvbbrttuf/m8MMP/+QnP+l73ymGAEA57rvvvhe84AXf+MY3lvsPjj/++PPPP/+MM87Yc889l/tvHnzwwauvvvpd73rX3//93y/5H6xateqiiy5a8tYQAHQbADZt2jTgrzzxxBPbt2/funXr3NzcPffcc8cdd/zjP/7jireMe/7zn3/55ZcfdNBBlQ8ZUiEAUJT77rvvzDPPXK52n7fLLrs873nPe9aznvX0pz9977333nnnned+4nvf+95NN9102223Dbh30M4773zRRRe98pWvbObwARhWCzfiXLVq1Rvf+Ma3v/3tS95qAvIlAFCaRx999Dd+4zc++MEP1v7MBxxwwOWXX37iiSfW/swApBYAfu7nfu5//+//fdxxxzX6U6AT7gJEadasWfOBD3zgiiuuOPDAA2t82l/5lV+5/fbbVf8AxTvhhBOuuuqqv//7v1f9UyoTAIq1devWd7/73e985zt/+MMfVnmeF7/4xW9729ue97zn1XdoACQ3ATj66KPPOuusV73qVUcffXS9zwypEQAo3KOPPnrFFVd84AMfuP766x9//PHh/+JP//RPv+xlL3v1q1/9jGc8o8kDBKClALBq1arVq1fvtttua9eu3WeffdatW3fYYYcdeeSRz3zmM0844YQDDjigmSOF5AgARLF169Ybb7zxhhtu+NrXvnbHHXd8//vff/jhh7du3bpjx441a9asXbv2oIMOOvTQQ4888shjjz32xBNPPPzww7s+ZACA+gkAAAAQiIuAAQAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAACKZnp7u+hAA6ID1HyCmyd4JYHZ2tuuDAaA91n+AmCv/5KImkNMAQBzWf4CAC/7iADDPaQAgAus/QMClfnLATlCnAYDiWf8Boq3wq1f8O04DANFY/wEKvs3D5JD/ndMAQKms/wChlvTVIz2X0wBANNZ/gMJu7jw5xl9zGgAojPUfIM4avnrsn+E0ABCN9R+ggK90nKz4LE4DAGWw/gMEWbRX1/KznQYAorH+A2TU9R80AajypE4DAFmz/gNEWKWrTgAW0g0CiMn6D5Byy3/lCUAtP8ZpACBH1n+Awkr//mW5zgnAQrpBADFZ/wES7PqvPAEY8FMvnJrZOLdhpJ/hNACQEes/QEal/+DFecl1eOQAMP9jJiYmRj0NOBMAZMH6D5BL6b/imjxaABjcBOr9b6cBgPJY/wHSL/3njdr+HzMALPqpTgMAhbH+A6Rf+o/X/l8hAAzZBBryCEY6LAC6Zf0HSLn0H7v9P34AWO4gnAYAymD9B0i59B+7/b9yABi1CTTkAS3JaQAgKdZ/gDRL/yrt/0oBYMVjchoAyJr1HyDN0r9K+3+oADB2E6jHaQAgU9Z/gNRK/4rt/6oBYPhDdBoAyJH1HyC10r9i+3/YAFC9CdTjNACQF+s/QDqlf/X2fw0BYIwjdhoAyIj1HyCd0r96+3+EAFBjE6jHaQAgC9Z/gBRK/1ra//UEgCr/AKcBgPRZ/wFSKP1raf+PFgCaaAL1OA0ApMz6D9Bt6V9X+7+2AFDLv8dpACBZ1n+Abkv/utr/IweARptAPU4DAAmy/gNMdFT619j+rzMA1PvPcxoASI31HwhuurvSv8b2/zgBoJ0mUI/TAEA6rP9ATNOdlv71tv9rDgAN/WudBgASYf0HoplOoPSvt/0/ZgBouQnU4zQA0DnrPxDEdBqlf+3t//oDQNP/eKcBgG5Z/4HiTadU+tfe/h8/AHTVBOpxGgDoivUfKNV0YqV/E+3/RgJAa6+F0wBAJ6z/QPC6fyKZ5a7tANB5E6jHaQCgZdZ/oAzTCZf+DbX/mwoA7b80TgMAbbL+A7mbTr70b6j9XzUApNME6nEaAGiH9R/I1HQOpX9z7f8GA0CHr5TTAEALrP9AdjIq/Scaa//XEAASbAL1OA0ANMr6D+Qir9K/0fZ/swEghRfOaQCgOdZ/IH05lv4TTbb/6wkAKTeBxj4HOA0ADMP6D5RU+k/ksHxVX6OaDQDpvIhOAwBNsP4DCcq69J9ouP1fWwBIvwnU4zQAUC/rP5CO3Ev/Ftr/bQSABF/TsU8DzgQA/az/QArKKP0nmm//1xkAMmoC9TgNANTC+g90qJjSv532f0sBIOWX2GkAoDrrP9CJwkr/iVba/zUHgBybQD1OAwBVWP+BNpVX+rfW/m8vAGTxijsNAIzN+g+0o9TSf6Kt9n/9ASDrJlCP0wDAGKz/QKMKLv3bbP+3GgDy+gU4DQCMyvpv/YeGFF/6T7TY/m8kAJTRBOpxGgAYnvXf+g/1ilD6t9z+bzsAZPr7cBoAGJL1v8f6DxXFKf0n2m3/NxUACmsC9TgNAKzI+r+Q9R/GEKr0b7/930EAyP3X4zQAMJj1v5/1H4YUsPSfaL3932AAKLUJ1OM0ALAc6/+SrP8wQMzSv5P2fzcBoJjfltMAwJKs/wNY/2GRyKX/RBft/2YDQPFNoB6nAYBFrP+DWf9B6d9V+7+zAFDeL89pAGAh6/8wrP+EpfTvsP3feACI0wTqcRrIemXxW4AaWf+HZOVJYf0fwC+oXkr/ztv/XQaAgn+XTgOZLvFef6iX9X8k1p9u1/+x+cU1/VsLu1zMNvnWWt3cU0c2/2Yd4zQw//GwmqS81gMMYP2Ptv4veYR+jwsp/RPU+AQgbBOoRzcoo+U+7GsODbH+j/cXw65F6Zf7Y4v5O1X6p9n+NwFog25Q5BUfiMz6v6I46/+if2nxv1ylf+LamABoAvXoBiW+6Jf3OkPnrP/zrP+Jr/8dKuxXrPRPv/1vAtC24N0giz4QlvW/60PI48XJ+het9M9ISxMATaCw3aC8Fv28XlvIhfV/Ees/hf26lf55tf9NALpUdjfIug+wHOs/I72SKf/Glf6Zam8CoAkUoRuU+7qf2usJxbD+L8f6T6a/dKV/vu1/E4BU5N4NSnDdn9209Poyfe6Y51qAJlj/azcztW7JxzfMbRnjb634FwPOBJT+BWh1AqAJVFg3qNt1f7kSf7DBAaDzUykUzPq/Iuv/kAYU6wOMHQCqPG3TWv7VK/3LaP+bAKQo/W5Q++v+eLU+QF6s/zXW5d0eYWupoLWZgNK/MG1PADSBsu4Gtbb0N1fxmwBAh6z/wwu7/jdX8Tc0Aaj+o2vUxG9f6V9e+98EIHWJdINaWPf1+AFirv/p9/hr/zc2lwfqHQgo/QvWwQRAEyijblCjS38nRb8JAHTL+j+G8tb/Tor+DicAXQ0Hxn4DKP3Lbv+bAOSk5W5QQ0u/Tj9AzPU/Qqe/4stSexgY4w2g9A+imwmAJlBX3aAVF4Li634TAOic9T/U+p9O3Z/mBKDNsUBDbwAf2+za/yYA4bpBA/oBtS/96RT9AMXIYv1PqpjOUUNjgdrfAEr/fHU2AdAESqcbVO/Sn3jdbwIAKbD+F7n+J173ZzQBaGEsUPEN4HOadfvfBKAE1btBEep+gPIksv6nXzqXofc615IElP7BdTkB0ARKqhsUpPQ3AYBEWP8LWP/zKv1znwB0/g3EPpjFtP9NAEpTpRtUdt0PULY21//sauUi1TsQGEzpX56OJwCaQM1p7jSQdelvAgDpsP43pLn1P+vSv7AJwCINxQCfxCLb/yYAJau9G5R13Q8QR+3rf+7FcQS1DwSU/mVb1fUBDApAnexoLEwtH+DZTTOqf6B21v/01/+ZqXWq/7z4lSViY8LtfxOAwlU/g6r7AWKu/4rIrM3/+qpMA+bfQuYAper+GoB5doImtfQXXPe7BgBSY/1Pav0vuO4v+xqAwSruC/JJLKz9bwJQpkpfDVNu6Q9QvCrrf9kVcHAVBwIb5zbIAIVJZQKgCVQLpf+KTAAgQdb/6pT+K4o8AahrGuDzWEb73wSgKGOv/kFKf4BSjb3+x6l6qWUaYBRQjIQmAJpAY1P6D88EANJk/R+P0n94JgA1TgN8KrNu/ydxG1AqUv0DxKT6p6Kx3wlu1Ju7tCYAmkAjUfqPwQQAkmX9H57SfwwmAAMYBYRq/7sGINzqH7n0B4i8/gcvcGnowgBXBWQquQmAJtCKlP5VmABAyqz/gyn9qzABaHQa4BO6MZ/2v2sA8qP6B4hJ9U87xnvPuCogLykGgAEhKfjba4x//uymGdU/kAvrf43//Jmpdap/xjPemyfyh3RjVu1/1wAUXvo3cywApF76N3MsxDLGhQHzb1fbgdKX4gRAE2gR1T8Qh/V/IdU/nTMKKK/9bwKQgVE/RUp/gJjrv9KfpEYB5gApS3QCoAk0/89U/QMBWf/HWP9V/zRt1PfYGG/jHG3MsP1vApAupT9ATEp/kmUUUIx0JwCRm0CqfyA46/+QVP9kMQqYKNTGPNv/qQeAmFT/ADGp/smFDJC7FL8JOOwXQyr9W+CbgCEj1v/lKP3H4JuAU/ja4JI+uRuzbf+bACRE9Q8Qk+qffBkFZCqDABBhJ6jqH6Cf9b+f6p/UxMwAG3Nu/7sLUBJG+iQo/QFirv9Kf4q5O5BbA3UugwlA2U0g1T/AANb/eap/0jfSuzTrz+/GzNv/2QSAUqn+AWJS/VOkOBkgd9kEgPKaQMMf9uymGdU/EFbk9X9map3qn7yM9KbN8SO8Mf/2f04BoDAjVf8NHwsAiVb/DR8LNKXsDFCAnAJAMU0g1T/ASAKu/6p/cldkBthYRPvfXYDaZtM/QEw2/RPQzNS6IW8NNP8BcWug1uQ0Aci9CaT6BxhbnPVf9U9JSroseGMp7f/8AkC+VP8AMan+Ca6kDFCM/AJAjk0g1T9AdcWv/6p/SlVABthYUPvfNQBtcMkvQEwu+YXxvi3YVwU3Lb8JQKZNoBWp/gFirv+qf+LI9N2+saz2f64BICNDnpBU/wAx1/9M6yEY25Dv+XwjfRZyDQBZNIFU/wC1K2n9V/0TU14ZYGNx7f+MA0D6VP8AMan+obAMUJ6MA0DKTSDVP0BzClj/Vf+QRQbYWGL7312AGqH6T8f0uaOtGtPT0yV9vIGUq/8hb4cCRdowt2Vmat2QXxXspkC1m5zI3JIV27xO3iuq/ywK/VoIBtCtTNf/hV1PGSAdZjKt6b3te6/5kB+E9j/XGwtt/5sA1Ez1X3C5P0zxkfVaAFRh5w+saLlC3xygfSVPAFoOi6r/CEX/8IQBaFp26/+S1b8hQCJks0Yt+T5f9JqnNgfYuNLnOusTffYBIJEpsOq/CdkV/UWuEZCyjNb/5epLASARAkBDBrzD+1/zpDLAxnL3/5S/Bci0KDvFFP3L1Si5LxmQi1zW/yE3P0B2sn5jb+z6fmJNK2EC0PkgWPu/uiLr/sEkAYiz/g/uLmddJxXDBKBGQ76lq2yKa/SjvbHozT8hJgAtUP1XEbDu769aClhHIKa6Lvw1BKAY1d/JLghuRyETgK6aQKr/sUUu/ZckBkCR6/+QfWUBoHMmABWN8R4e8Jp3OAfYGKD9bwJQiep/DOr+5RgIQOSbfhoCkK8m3rrmAE0rZwLQfhNomBOA6r/z0n/9zNTC/3fzhrnh/+MV//vmiAGQ+/o/akd5xXLHCaXR05AJQPul/4qv+TDPX++ne2OM9r8JwPhU/6nV/f21e6NP23QwMBCAZDVR/Q/T8pw+d4PTColoZ2A1zBzAEGA8RU0AWmsCqf47L/3HLvdHnQDU9cwViQGQ0fo/di/ZEKBRJgCplf41XiFTywd8Y5j2vwnAOIq/NWyypX9DPf4mDq/2MDBf2ZS09ECOml7/DQFIWcqXqZgDjGrVRFkGV0it1e5hF+jpczfUW/2vn5nq/d9EPho67OmfqPEJoSSJrP8ayZRnw9yWDqv/dj5TGyO1/00ARmbzz3Jqr/snStH7t9Q1FjANgE40uvln4TMYApCORLr+LgaoXWkTgEabQKr/pqv/HJv9Xf3rjAIgtfVf75+SVO/611sRDfP5GvszvjFY+98EYAS2/jdX+pda8Tc9EzAKgCLXf0MAcu/6d/j+NAeIOwHocCdoqBW5+nb/svv9rb0CLgyAFNZ/7X8KUEvXv7laqKFP2cZ47f9iA0DtbP5ZpJbSv77DyV4tMaC+wwE63vyz4hP6VnVClf7tbAQKpdgAUGMTSPVfY+Nf6d/ci2MUAJ2s/3r/ZC2X0r+hDLAxZPvfNQCMoGLdX+uxlKziFQIuDIAyuBKApmW915+Kip0A1NUE0v6vWP1r+Y+tyktnFEBwra3/2v/kKLuuf0NDgI1R2/+FB4DqVP9Vqn+lfy3GfhllAKgiherflQDULvfSv8fFABUVHgCavh1ECp+BNHf8K/3rNXYGEAMIq+n1X++fvBRT+tf1GdwYuP1ffgCoQnDU+E+KUQAEXP8NAaiuvNI/x89yasoPAOM1gWz+GeOkovRvwXgvsgxATM2t/9r/ZKH40n/sjUAbY7f/3QVofCl/Hjop/Zs5Fga94CPdJsjdgaAuLVf/bgfEGOLc4WfFDwhBJwBjNIEiD4xU/xkxCoAVWf+Jpviu/xgWfa43hm//RwkAI4m8+WfU6t+en86N8SuQAWA5yW7+cSUAwwhb+rsj0BiiBIAabweR42ejoeq/sWNhNDIAtLP+2/pPmsKW/mN8NrX/57kG4P8RMyAq/QNeFeCSAMhr/XclAMH3+le3cW7DhVNR/rErijIBqKsJVN7nRPVfEqMAaG791/4nKbr+TWwEmg3TFwsUAHJv/zRB9V8eGQBKXf9dCcA8pT/VxQoAFYNdYZ+WkU4VrvfNyKi/LBmACCqu/9r/JFL3K/2b+5zOhmn/hwsAVQSv/ps8FhohA0Bd0qn+DQFiql73F1/6J/hpTVy4ABAq3i1H9R+EDAALWf/JjtK/NbPB1odwAWA8JX1yhq/+bfspwEi/RBkA0m8oGgIEofQv5jObpogBIFrIG7v6b/hYaI8MAPMir//kQunfvtl4K0PEADCqYj5Cqv/IZAAoppVoCFAqpX/Zn9ykBA0AAaOe6h8ZAGKu/6RP6d+h2ZBrQtAAMLwyPkuqf+bJAFBGE9EQoBhK/4Cf3xTEDQDDBL4yPk6qfxaSAWCY9V/1QNOU/k0b5lM8G7L9HzoABKH6p58MAAUwBMiX0p/OxQ0AK1Y2BXyuVP8sRwYgshXf1dr/NETpn1xOng56jlvd9QHQPdV/TOtnpjZvmOv6KIDxzUytG1xNTp+7QaWYiFrq/pqOBaJOALT/e1T/kQ352w/bIKFI2v9k1/XX8q/CEGBJQQNA8VT/DEkGgKy5EiBlSn+SFTEAFN/+V/0zEhmAOLT/aYfSPymGAP0iBoCyqf4ZgwwA+TIESIrSnyy4CHixCJ861T/9XBMM2v9U4TLfrK+YjybcBKDsFuYwbR7VP1XeG2V/gihbwe9eQ4Bu6foXYLrc9WFJ4QJAwVT/VCcDAAxP6U+mYgWAgi//1d2hTTIA2Sn+8l9DgJYp/bPjUuCFXAMQiPY/w3AxAMAA9vpTgEATgODtf9U/w7MRiMIU3/6fZwjQNF3/3BkCRAwApVL90wQZAKBH6U9hBIB/lunHUjuHbskAFKCM9v88Q4DaKf0LU9LnvYooASBymaL9z3i8cyhD5PWfKpT+MU3HWDGiBIAi2fxD02wEguwYAlSn9Kd4IQJAwZf/Dqb6pzrvIrIW5PJf6qL0j2DGpcBBAkCRtHBIR4S1EjJiCDAGpT+hCABZtv9t/qFNNgJRKu1/aqH0z85M+M9++QEgZl2i+qde3lHkKOb6P88QoB1K/1JNl756+Cbg/Fi1SdP09PTs7GzXRwHQBnU/WSt/AhDwA6xZSxO8ryhM8XsADAEaoutfhpnSV4DQAaC8Cc6K67Uqjeas+O4q7xNHvrwbqZ3SP5TpoteQwgPAYNl9jHVrSF/ZKybFCNL8MwSoi9K/SDMx1oEluQagKNr/NG39zNTmDXNdHwVAS9T9FKnkCUBhnUh9GnJR2EePHHkT9hgCjE3Xn+lyV5KSA8Bg5X2qtf9ph3cauYs892cYSv84ZqKuBnEDQF50aMhLwV0TyI4hwPCU/gRRbACIVn9oytIm7zdSFm39pxZKf0KtJ8UGgMHy+pC79ScJcktQMhVz4m8IAMuZCbkmBA0AAAAQU5kBoKTWo/Y/yTIEIEHedcsxBIDxTJe4qpQZAAAAgCVFDAB5XQAwmPY/3fIOJC8xN/v2GALAkmbirQwRA0BGrMXkrsjJKQBkrcAAoOAAiMn6vyJDABhDeWtLgQGgmP0/Lv8lCy4FJhcBp/zAkGaCrQ/hAgAARGYIAAgAudL+Jx3ejQCQkdICQDGbDTRgKEkxH0xS5m02PEMACL7ClBYAirkAYDANV1LjPUniom3wBUY1E2mViBUAcqH1QnkK651A7gwBIDIBAAAAAikqAARpMdprQZq8M+lQkPW/XoYAEHadKSoAlHEBgAWXUpW0dJKXUFt7gbHNhFkrAgUAAGAhQwCISQDIjF0WpMz7EwDSJwCkRa+FstkFBKkxBICAygkACguAmKz/QDumS1ltygkAZVwBPJj9FaTPu5TUxLmqb2yGABBtxYgSAAAAAAEgLVosRFDM/BRKYggAoQgA2bCzglx4rwJAygQAAMAQAAJZFWFTQRlXAAMw6vof5Ho+oEYzA9eNMjayFhIACqCzQhxlrJ5QHkMACEIAyINN1eTFOxYAkiUAAAD/zBAAIhAAAAAgEAEgCRoqROMyAEiWIQAUTwDIgO3U5Mj7FgDSVEIAcA9QgJjcA7QhhgAEN1P6nUBLCAAAAMCQBAAAYDFDACiYAAAAAIEIAN3TRCGmAvZQQtkMAaBUAkDq3EqFfHn3AkCCBAAAYGmGAFAkAQAAAAIRAACAZRkCQHkEAAAACCT7AOBrgAFi8jXArTEEIKCZor8MOPsAAAAADE8A6JiuCZHl3kGBOAwBoCQCQNLcRp3ceQ8DQGoEAABgZYYAUAwBAAAAAhEAAIChGAJAGQQAAAAIZPVE0XJvRWzeMNf1IQBkacPclq4PIahMz7yZHjaMp/AAACORuACgHVJ6h2wBAgCAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIpPAvApvdNDOR81cPrp+ZavFYovBtX1CG2dnZrg+BjE1PT3d9CNCZwgMAjEroqp3EBSRIgCQyW4AAACAQAQAAAAIRAAAAIBABAAAAAhEAkubqSXLnPQwAqREAOpb+jUqhOe7CAQDtEwAAACCQVWV3EAd/zRYAAESTfQAAAACGJwAAAEAgAgAAAAQiAAAAQCACQOrcRp18efcCQIIEgO75KgBi8iUAANAJAQAAAAIRAAAAIBABAAAAAikhAPgyYAAACBQAiudWKuTI+xYA0iQAJMGNgIjGLYAAoCsCAAAABCIAAABAIAJAHmynJi/esQCQLAEgFS4DIA4XAABAhwoJAO4ECgAAgQIAAAAwDAEgGzZVkwvvVQBImQCQEJcBEIELAACgWwIAAAAEEiUAlHEdsJ0VpM+7FAASV04AsK8AAAACBYAyuAyAsgnqANA5ASAz9leQMu9PAEifAAAAAIEECgC5XAdsFxClsv8HAFJQVAAIUl7YZUGavDMBIAtFBQAAAGAwASBFdgFRniADOgBIX6wAkMtlACuy14LUeE8CQC5KCwDFdBkNAShJMR9MAChAaQEgDg1X0uHdCAAZEQAAACCQcAEgo8sAVtwFpO1KClZ8H9r/AwBJKTAAqDYAACBQACiJS4HJnUAOAKmJGAAy2gW0IruA6JZ3IABkJ2IAAACAsMoMACXtOnApMMly+S8A5KjMAAAAACwpaADI6zIAQwASpP0PAJkqNgBEKz5kANrk/QYA+So2ABTG/UDJS7QEDgAZiRsA8toFNAxNWdrhnQYAWSs5ABTWgzQEIBeFffQAoDAlB4CAtGZpmvcYAOQudADIbheQIQDp0/4HgMQVHgDKq0XcEpQOufUnABSg8ABQ3hBgGDIATfC+AoAyRA8AObIRiDRp/wNAFsoPADGLEs1a6uUdBQDFKD8AFLkLaJghgIqNugzzXoqZtAEgRwJArmwEIh2qfwDISIgAsGJ1kuMQYBiGAFTnXQQAhQkRAEplIxBNs/kHAMoTJQBErlFkAMbjnQMARYoSAFaU6S4gVwLQrcjRGgAyJQBkz0YgmmDzDwCUKlAAKPhSYBmAeqn+AaBggQIAMgDD8D4BgLLFCgDBhwBQF+1/AMhXrABQNhuBqM7mHwAoXrgAUHbtIgNQheofACIIFwBWlO8uoOHJAPTzrgCAIASA0gx5MYBqjzHeD9r/AFCAiAGg4EuB58kAjET1DwChRAwAEcgADEn1DwDRBA0AxQ8BZACGofoHgICCBgAWkgFi8nsHgJjiBgBDgIXUgtEM/xvX/geAwsQNANPT0xMByAD0U/0DQGRxA8AwChgCyAAsovoHgOCCBoDh2/8yACVR/QMAQQNAQDIAqn8AIGgAGHX3fxlDABkgONU/ABA3AEQmA8Sk+gcA4gaA8W7+U8wQYNQMIAbkbqRfouofACIIFwAYKQMYBWRtpN+d6h8AgogVAKrc+7+kIYAMEIHqHwBYUqwAUFHwDCAG5GLUX5bqHwBCCRQABrf/L5yauXBqhII4YAYwCsjCqL8j1T8ARBMoANSisCGADFAY1T8AsKLJiRhWbP/3/vfGuQ31VsylZpv1M1MTeRpcJWf671L6AwBDMgEYWXlDgHlGAflS/QMAwxMA/p/2f///uyQZYJ4rgzs3xq9A9Q8AwYUIAKPe/TPg1cBVNjjJAF0Z45VX/QMAqydiG7vWnz53Q6kXA8z/u0aacsxXopnuns+R0h8AGFv5E4Dxvvwr8kagKqMA04Cmjfciq/4BgEABYOwqP/JGoHnjjTjEgIaM/cKq/gGAQAFgvPb/CM9f9BBgPgOMHQMaOJy4xi79Vf8AQKwAULHBbyPQPKOADmn8AwD1KjkA1NL+lwHmjX3FsxgwtiovneofAFhO0LsA2d/fzt2BenqFrDsFrahiXlL6AwCDTU6EbP+PGgA2zq1c9ZZ6V9Amhh7dxoDBFXaHx6b0BwBaUPIWoBrb/zYC1Zt27Auq/QVR/QMAobcANX3zn4DfDlbvjqB59gXVkoKU/gDASMoMAE3s/r9wamaYjUDRVI8BAZNAXdMPpT8AMIYCrwGod/f/Ii4GaGcHVKNJoKtrAOrd9aT6BwDGEysA1HLzHxmgzQshmijHWw4AtV/toPQHAKoobQtQV7v/I18MUPuOoOWq54w2CDV0ibPSHwCorrQA0MK9/10M0H4MyCIMNHpfI6U/AFCXorYANbr7fxEbgYbU2t1Rh48EtWwBau02pkp/AKBeUQJAE1/9KwOMpKvvSegv6EcKAF19X4G6HwBoSDkBoM32/7whNwLJAGG/Lm08Sn8AoFEhAkAT1f88GWBsksAi6n4AoB2FBID22/89MkAVYoDSHwBoWfkBoNHqf54MUF3AJKDuBwA6UUIA6Lb6nycD1KX4JKDuBwC6Feh7AMjCwoxUTBhQ9AMA6ch+ApBC+3+eIUCjsgsDin4AIE0CQJ1kgOBhQNEPAKQv7wCQVPU/TwaIEwmU+wBAjgSA+skAhQUDhT4AUJKMA0Ca1f88GSDfVKDcBwDKtqrrAyjTkAkk2b3sAACUKtcAkHL7f54MAABAgnINAFmQAQAASE2WASD99n+PDAAAQFKyDABFkgEAAGhBfgEgo/b/qEc1fe4GMQAAgEblFwByNFIykQEAAGhOZgEgu/Z/jwwAAEAKMgsAWZMBAADoXE4BIN/2f8+FUzMjXRLQ8OEAABBOTgGgGDIAAABdySYAFND+X0gGAACgE9kEgPK4PSgAAO3LIwAU1v7vcVkwAAAtyyMAFEwGAACgTRkEgFLb/2NnADEAAICSA0AEoyYZGQAAgDIDQPHt/x4ZAACAFqQeAEIZ6WvCbAcCAKC0ABCn/b+QUQAAAEEDQFgyAAAA4QJAzPZ/lQwgBgAAkHEAYNRLAowCAAAoMABEaP8vZBQAAED5AWDA/p+Axsg8MgAAADkFgOVEa/9X3A4kBgAAkEEA0P6vdxQgBgAAkHQAWE7Y9n/1F0EGAAAg0QCg/d/EdiCjAAAAEg0Ay9H+r2sUIAYAAESWVgDQ/m9hFCAGAABEllYAWI72fxMvjgwAABBQQgFA+39sRgEAAOQXAJaj/d/CKEAMAAAIIpUAoP3f7ShADAAACCKVALAc7f+WXzQxAACgbKsnEqD931AG2Dg3ZinfywCzmwQwAICiJD0B0P7v/AU0EAAAKEz3EwDt/4aM3f7vN58BTAMAAArQfQBYjvZ/CqX/QvYFAQAUoOMAoP2fRem/iIEAAEC+Ep0AaP+nWfovZCAAAJCjLgOA9n+mpf8iBgIAABlJcQKg/d9a6T87O1tXEjMQAADIQmcBQPs/hdJ/4f+u6zciCQAApCy5CYD2f5ulf//jNQazhV8gIAwAAIQOANr/7Zf+y9X9y/1n9f6OjAUAABKR1gRA+7/D0n/Jv1V7VDMWAAAIFwC0/xMv/fufoaFfmTAAABB6AqD9n1Tpv+SzNRfeFoYBeQAAoJwAoP2fV+m/5JO38EuUBwAACp8AaP8nXvov+YNai3OL8sA/H4ZUAACQeADQ/s+99F/u53bym10yFfSIBwAAS5qcaNFyZWLk9n+mpX/BGS+1lxQAINcJQAGlYb0KK/1TmAkAAJDBNQAB2/9Flv6LSAIAAKEDgCowTuk/4Ji9DQAAok8A4rT/A5b+/YQBAIAQASB4qaf0X5IwAAAQbgJQfPtf6T/ev1QeAADIOADELOaU/vX+82O+iwAAipoAlNr+V/o3YcmXRSoAAEguAIQq0ZT+LRv8ioV67wEApPJNwEG++lfpDwBALhqcAERowSr9AQDISwfXAJTR/lf6AwCQo6YCQMHtf6U/AAD5ansCkHX7X+kPAEDuGgkA5bX/lf4AAJSh1QlAju1/pT8AACWpPwAU0/5X+gMAUJ72JgAZtf+V/gAAlKrmAJB7+1/pDwBA2VqaAKTf/lf6AwAQQQdfBJYapT8AAHFMtrD/J9n2v9IfAIBogk4AlP4AAMQ0Ga39r/QHACCyQBOAKqW/uh8AgDJMRmj/K/0BACDKBGDs6l/pDwBAeSYLbv8r/QEAIMQEQOkPAACNTABSa/8r/QEAIMQEQOkPAADNTgASaf8r/QEAIMQEQOkPAAAtTQC6bf8r/QEAIMQEQOkPAABtTwA6af8r/QEAIMQEQOkPAACdTQDabP8r/QEAIMQEQOkPAADdTwBaaP8r/QEAIMQEQOkPAAAJTQCaa/8r/QEAIMQEQOkPAAApTgBqb/8r/QEAIMQEQOkPAABJTwDqav8r/QEAIMQEQOkPAAB5TAAqtv+V/gAAEGICoPQHAIDMJgDjtf+V/gAAEGICoPQHAIBcJwAjtf+V/gAAEGICoPQHAIDsJwDDtP+V/gAAEGICoPQHAIByJgAD2v9KfwAAiDIBGKP6V/cDAEDSE4Dl2v+jUvoDAECIbwJW+gMAQB4TgIrtf6U/AACEmAAo/QEAILMJwHjtf6U/AACEmAAo/QEAINcJwEjtf6U/AACEmAAo/QEAIPsJwDDtf6U/AACEmAAo/QEAoJwJwID2v9IfAABCTACU/gAAUOAEoL/9r/QHAIAQEwClPwAAFGyy1/5X+gMAwETp/j9kB+Nl4MkV6QAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_144
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is Colorize the top layer of the original shape with the color cyan.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_283
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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33/vg+gUAA4/AAQFAAOPwAEBYDDDwBBAeDwA0BQADj8ABAUAA4/AAQFgMMPAEEB4PADwKcI/wNBD7ezBT53AgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color yellow.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_121
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
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[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color cyan.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_257
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 3th action is Colorize the top layer of the original shape with the color green.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 5th action is Colorize the top layer of the original shape with the color cyan.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:8)_472
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": 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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color white.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_165
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color blue.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 7th action is Colorize the top layer of the original shape with the color red.\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
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},
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q96whPqOT9rHb/Qq4gYANCiYYq2CQAAgzANAGjF8Bsy3QMAwMjAS3n3BgA0ZuCSO6vCmwAAMCzTAID6VN5nMQEA4H8MuYI3DQCoViV1tbu2mwAAUCXTAIDh1dpPMQEA4H/Ns3AfH1/A22SZBgAMZqH1c/7i3LOqmwAA0JexsbHpy8zY2Hxvp7uhmWuYgQDARi20b7LQmjxDAADg/5iYmJj/IjTAJce+IIDKl/4bNVfVFQAAWPAQQAwASGHpP0D7XwAAYJAhwAwxACCprv+MecqsAADAgEOAGWIAQPNL/8Ha/wIAAMMOAWaIAQDtdv1nzF9XBQAAKhgCzBADABpY+g/c/hcAAKhyCDBDDABouOs/Y6OFVAAAoOIhwAwxAIisU9vSf5j2vwAAQF1DgBliABBNp/Gu/4x+KqcAAECNQ4AZYgAQQQNL/yHb/wIAAE0MAWaIAUCpOu11/Wf0WSoFAAAaGgLMEAOAknQaXPoP3/4XAABoeggwQwwActdJoOs/o//aKAAA0MIQYIYYAOSo08bSv5L2vwAAQJtDgBliAJCLTkpd/xkLKoYCAAAtDwFmiAFAyjqtLv2rav8LAACkMgSYIQYAqekk2fWfsdDqJwAAkNAQYIYYAKSgk8bSv8L2vwAAQIpDgBliABB86b9RA5Q7AQCARIcAM8QAIPLSf6zS9r8AAEDqQ4AZYgAQbem/UYPVNwEAgAyGADPEAKBynYX3NRpb+lfe/hcAAMhpCDBDDACKX/pv1MAFTQAAILMhwAwxACh76T9WQ/tfAAAg1yHADDEAKG/pv1HDVDABAICMhwAzxACgsKX/WD3tfwEAgBKGADPEAKCApf9GDVmyBAAAChkCzBADgNyX/mO1tf9HRkYW1/ejAShb4svlAS7hnXvVczpA0wZ7RY8nsPqvu/aaAABQ4BBg4FGAaQAUYLAkP55A1Wqg/S8AAFDgnQCziAEQR+5L/42qpCgJAACUPASoJAZIApC+Ypb+YzW3/wUAAEIMAYaMAQYCkLJilv4bVVUJEgAAiDIEmCEGQBnKW/qP1d/+FwAACDcEmCEGQL7KW/pvVIU1RwAAIOIQYIYYAHkpeOk/1kj7XwAAIPQQYIYYAOkreOm/UdUWGQEAgOhDgBliAKQpwtJ/rKn2vwAAQGVyHwLMEAMgHRGW/htVeVURAACoXUZDgBliALQr1NJ/rMH2vwAAQJWKGQLMEAOgeaGW/htVRxkRAABoQo5DgBliADQj5tJ/rNn2vwAAQMXKGwLMEAOgPjGX/htVU90QAABoSNZDgBliAFQr+NJ/rPH2vwAAQPUKHgLMEANgeMGX/htVX6EQAABoThlDgBliAAzG0r/F9r8AAP/HaybnfB2eOFpa0YFaRRgCzBADklL5E88fqFqW/ik88QQAGDYbiAcQeQgwQwxoTMPZcv6H84er+69WZLlot/0vAECN8UAqgIDEgGqlP0fqeYb+jhuy9E/Qovn/KlYwhGrk180LiqSe8w2sUea5xES4tA/c3gu7fEx/uT+wmH9TS/+B60PdTxgTAGhtKSYPQNlMAyKv+Of/lxb/x7X0T5wJALG0OwGYh9caRU4ADAFmmAYEXPTH/BNb+qff/jcBgBRXacIAlCf4NMCiv89fTtZ/aEv/jJgAEEuyE4C5eA2S+wTAECDsNMCif0gZ/bkt/fNq/5sAQDarN0kAilH2NMC6v/LfZMp/cUv/TJkAEEt2E4BuXpVkNwEwBIgwDbDub0BSf3RL/3zb/yYA8H+MHj1nVZo8K5XkYCYAJcl9GpDgun+uSj5/Gc+i/icyE7D0L4AJALHMPwGY5wIwv3YvD16npD8BMAQobBrQ7rp/sFo9cAAY5sfWLZ1X8fy8xpNq/5sAQDV6XjkauyqYCUAZ0p8GNL/uH3hdHqT+NzYTsPQvjAkAsdQ0AehHY9cDL1vSnAAYAmQ9DWhs6V9fHa5pAjD8Q1eojr++pX957X8TAGjOrKtLfdcDAwEoQCLTgAbW/en3+DOq/9UOBCz9C2YCQCwtTgDaag55FQeX1ATAECCjaUCtS/9Wim2LE4C26v/ATwBL/7Lb/yYAkIQNLzyVXwym139iAOSr4WlATUv/CJ3+1Or/AE8AS/8gTACIJc0JQJNtIS/qaFKbABgCtDUN2OhfvPh1f5oTgCbrf01PAC/b7Nr/JgAQri1kIAAxpwHz9IMrX/ontZjOUU31v/IngKV/vkwAiCWjCUADbSEv8AgSnAAYAqQzDah26Z94Cc1oAtBA/R/yCeB1mnX73wQAMjNziarkSmAaAMGnAZVIf+lchmrrv6V/cIvbPgFgEKNHj1d10X3N5Nj8gxGo3DxNr2G62jGN3yv3QkT6v/YWn2n5Gkuy/W8CAHmrsCFkGgBhpwELZdFf3kBgftb95TEBgBJU1RAyDaAxhgA59mi1/BNU6x9F17/I9r8JABSlqobQaybHjAIgX5VPAyz6Aw4ErPvLZgIABRq+IWQUQAMMAWpVyQJOyz87/mSJGEu4/W8CACWbvgYM0w1yYwBkavgEZREZvP5PP4XMAUolAEDhhp8LiwHUZ2JiYq63IxwbG7P4aH7pb91fkuHrvxhQZPvfFiAIZMi5sB1BUPbq39aRgg35x7UlrzwCAMQyzGXAjQHUwZ0AlRi712D/raV/EMP8oYd5gkUzlnz7XwCAoIaMAVWfDjAUS38aiwFVnw7tEAAgroEvA0YBVMsQYGAD92Ut/YMb+AlgFFBA+18AAAa/508GgHwb/1WfC1kyCghLAACMAmifIcCCaPxTFaOAgO1/AQCoJgbUcDpAb5b+JBUDajgdaicAABVcBowCGJ4hQE09V0t/an2qGAVk1/4XAIDejAKgmMZ/DedCyYwCIhAAgIpHAfWcDiEYAsxF458sRgEjUY1l1f4fGRlZ0vYJAEmbvgYs6GPkpzPAiaNWHtDa0r+ecyGWAer/9NN1fNwzMHUmAMDGGQXQGEOADVn90zqjgPLa/wIAUONEWAaAYSx0FWXPDzUZ4KkVLQNkRwAAFmCADCAGsFCGAAO8rYqlP3UbIANEeMGOZdj+FwCABTMKgFpp/JMso4BiCADAIGQAahV2CKDxT/pkgNzb/wIAMDgZAKpl9U8uZIDcCQBAc+NgtwTQv1BDgIXulrbth9Yt9ElY3i0BY9m2/wUAoAJGATAMjX/yZRSQKQEAqIAMQB0iDAGs/sldzAwwlnP7XwAA2twOVOfpQAZs+yHsdqA6T4eNEwCAKskAVKvgIcBCV/91ngtUIE4GGMu8/S8AANWTAWCjrP4pUpwMkDsBAGh5HCwDEG0I0P9p2/ZDdhb0pM3xJTyWf/tfAABqJAPAkKv/ms8F6lJ2BiiAAADUSAagEsUMAaz+iaPIDDBWRPtfAADSygBiAKVa0KcgWf0TMANkFAMKIAAAtXNbMMGHAG75JaySbgseK6X9LwAADZEBCMvqn+BKygDFEACAhsgABBwCWP1DGRlgrKD2vwAANMrbgxKKt/uEOG8PmhcBAGiahQ6hhgAb5RVBHJk+28fKav8LAEDS1wBDAPLVZyDJdD0EA+vzOZ9vpM+CAAC0Qwag4CGA1T8UkwHGimv/CwBAm2QAimT1D4VlgPIIAECbZAAKGwJY/UNJGWCsxPb/yMjIkrZPIDrLmqRMnuXP0c77QvTzm3/N5NiJo9ZMJM3qHxakz/o/NjY2Pu5VUyUTAKB95gAUMASw+ofC5gBjhbb/BQAgFTIAWbP6hyIzQKkEACAVMgBVaXihYPUP5WWAsaLzhgAAJEQGoH+JzN+t/qHUDJB+/RmYAABAgRJZJQA5Giu9gAgAQFoMAaiqCdfAJVz7H8obAoxt7Ofn3v4XAIAUyQBkweofSs0AxRMAgBTJACQ+BLD6hyIzwFiA9r8AAKRLBiBZVv9QK3OAuvkk4KSNj65o+xRKMza5Zp6v+oU3/zuv5EMiCW5iYqLT6aT2GaJW/zCMVur/WIz2vwkAkLp+VlGGADSpn6aj1T8Mr5/XkSHAYAQAIHUyAOncCWD1D6VmgLEw7X8BACiHDEDd9BohTV6bCyUAABnQUiX9zwSY5rkKOb6mxiK1/wUAIBs2AtEum3+gLW4GqJwAAGRDBqCtIYDVPxScAcaCtf8FAKBAMgDV0lmEXHi19kkAAHKiyUqadwJ4ZkLdanqVjcVr/wsAQH5sBKJJNv9AOtwMUBUBAMiPDEAzQwCrfyg7A4yFbP8LAAAAEIsAAGTJEIC6hwDa/1D2EGAsavtfAAAyJgNQH6t/SJmbAYYkAAAZswKjrbcD8tyDdg35GhwL3P4XAIDyGQKwUBqHUAav5bkIAEDebASi2iGAzT9Q/EagsdjtfwEAKIHVGE3yfIN0eD0ORgAAQjAEiGmhQwAbBqA8s17XY+Hb/wIAUAgbgRiezT+QI+8INAABACiElRl1vx2Q5xikqf/Xpvb/NAEACMQQgLloEELZvMY3JAAA5dCgpb4hgGcXFL8RaCJG+18AAMIxBKCb1iAQigAAFEWbljoae55XkL4hX6cTYdr/AgAQ8RpgCMCCWP1DLrxa+yQAABHJAAGFau8BCzIRrD4IAECBNIGoiucS5MVrth8CABCUIUBA0Zp8QD8m4lUGAQAokyYQw/Msghx55W6UAADEZQgQUMBWHzCPiZA1QQAAiqUJxDA8fyBfXr/zEwCAknlLUAZr+Fk9QO76eRVPhGz/CwAAABCLAAAUzhCAWTqdzvzfoP0PZdjoa7mzsWpQKgEAAAACEQCA8hkCMEP7H0IxBOhJAAAAgEAEACAEQwC0/yEmQ4BuAgAAAAQiAABRaO4yP88QKJVX9ywCAMD/sAuobAGn/ECfOsHqgwAAAACBCABAIG4FDsvtvxCcW4E3JAAAAEAgAgAQiyFAQNr/gCHAhgQAAAAIRAAAwtHuZUOeDxCH1/s0AQBgNruAShJnpg8MrxOjYggAAAAQiAAARORW4CDc/gvMMupWYAEAAABCEQCAoLR+8RyAmEbDv/YFAIDe7ALKXYQ5PlCHTunVY0nbJwANGZtc0//3jI+uqP+MAABaIAAQd7m/oP9cJCjS6NHjk2dp8wdlDwBENhq7/gsAlGPIRX//P1wYiOM1k2MnjlomZqn4CT5Qq06nMzExMVIoAYDs1brun/8RJYECBG8ChaX9D4wGrv8CALlqft0/zzlIAgBALrwLEPkZm1yTwuo/8VOiKt4LKEf2/wDD65RbSUwAyEb6K2wDgUxFngLHZP8PELz+CwBkIP2lf88TFgMAgATZAkTqslv9F3DmzGIXUF4KntoDDesUWk8EANJVwMb6Av4JQdgTEoe/NbChmDXBFiBSVMeieTrEz/+evjNBv9q3/rUjCABIhwBAsav/YcZ2s/7bSvLA2OQaGSBfPhEsF6XO64G2dEr8RDABgKJW/zVd+zf8scNUARkAAGidAEAJS/8me35DbhOyHShZYd8MLpSYm32B+Y3Gq/8CAHmv/lsc9/dzU8FcjAIAgLZ4FyByXf137lXD6TR0Gt4dKDveDDR9KdQEoDyd4mqLAEDLBlgHJ7L0H/6UZIDU2B9SNn9fYC6jweqDLUC0aaEr4NTW/cNvCrIXCABomABAOwpb+g8TA9wWDAA0yRYgWlDw6n/gc7YdKAtuA0hZjoUCyEWnrAojAJC0BLf7Bzn5sKJtA43DXxaY32ikKiEA0LT+W91lrJ77/1cYAgAADRAAaFS01f80GQAASIcAQHP6XN0WuXOm/3+UDJA4twGkqbyiAaSmU1CdEQBIbvU/Ui4ZIAuhtoEG4W8K9GM0TK0QAGiC1f8MGQAAaJcAQCoirP6j/UsBgAQJANSun2Z2tDVxP/9eQwAAoA4CAPWy+p+LDJAv9wGnJmYNAZrXKaXaCADUyPp1eH6HrYhzH1gE/ppA/0ZjVAwBgJYVE6YHEPnfDgC0RQCgLjb/9MNGIACgYQIArbH6n+b3AAA0SQCgFprW1fL7BACqIgBQPZt/FspGoOzuA/NGQLm8fILczwdUaHTeulHGAkYAoAVlvHiq5XcCADRDAKBiGtX18bsFAIYnANA0re65+M0AAA0QAAAAIBABgEb3qGhyD/n7sQsIABiSAAAAAIEIAFRG+78ShgDp8E6g6fMeoEAdRkt/J1ABAAAAAhEAaEgBcbkxflcAQH0EAKphX0qT/LYBgIEJADRBS3uh/MYAgJoIAAAAEIgAQAXsSGme3zkAMBgBgNrZzTIYvzcAoA4CAAAABCIAAABAIAIAw7IZvS1+8w3wYcAp8zHAQH1Gi/4wYAGAeuX+CmmX3x4AUDkBAAAAAhEAAAAgEAEAAAACEQAAACAQAYAa34jGPazDm/936I2AAICFEgAAACCQJfN/2btctyv3/u7ExETbp1C+3J8kuVMkkzV5lj8NwEABAEKRWJpnlQakQC0iFFuAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAAC2cgHgZ04Ot7UmQQ1/8eIjo+uGMn5Y2g7nc5Iegr7tK/cnyS5S79Ihv2s4tGjU//T0Dyf9gXTfBIwpB5aCkss2S2ggSCERuIkRluAAAAgEAGAGveflN26bsb8v8P09/8AAKkRAAAAIBABAAAAAhEAAAAgEAEAAAACEQCol/uAh+G3BwBUTgBgWN6Ipi1+8wQ3f0Iu+A28gQZMzltDcu/QCQAAABCIAAAAAIEIANQu9zFZW/zeAIA6CABUwGb05vmdAwCDEQAAACAQAYAm2M2yUH5jAEBNBACqYUdKk/y2AYCBCQA0REu7f35XAEB9BAAAAAhEAKC5fSka2/3Y6G/J/h+Y4cOAgTpMFv0xwAIAAADEIgBQJUOAIWn/AwB1EwAAACAQAYCmGQLMxW8GAGiAAEDF7FGpj98tADA8AYAWaHV38zsBAJohANBOo9p6d6G/De1/6Mk7gQLVmiz9PUAFAOpitVotv08AoCoCAK0pI0MPz+8BAGiSAEBdbATqh80/AEDDBABaFjkDRP63AwBtEQCokdb18PwOYUjuAwb6NxmjYggA1MtGoLnY/ANViVlDgOZNlFJtBABqJwN0s/oHANoiAJCKOBkgzr8UAEiQAEAT+mxmR1gZ9/lv1P4HAGoiANAQGcDqH9oS5K4+YEiTYWqFAECKGaC8GND/P8rqHwZQXtEAUjNRUJ0RAGhU/6vbkl5m/f9brP4BgLoJADQtWgaw+gcAkrKk7ROAja+eO53OSIbKCDBQhsmzxkaPHm/7LIB0TYa5AcAEgHYstNWd40p6oees/Q9DyrFQALmYKKvCmADQjun17tjkmvJGAZb+AEDKBADaND66ov8MkH4MGKA9YPUPADTMFiBaNsAKOMH3CR3slKz+oUmhNvgCCzIZrD4IALRvsHVwIjFg4NOw+ofKpVATgPJMFFdbbAEiy71AKWwKGqYcWP0DAG0RAMj1tuCea/EGksCQbQBLf2iRNwMFukXb/yMAUM4ooHt1XmEYqGr2Z/UPALROAKC0DDDXqn1BeaCO3X5W/9CAiYmJZN8oDMjRRHE3AAgAFLgdaMgXsKU/AFA27wJEusZHV+S+dC7gnwCFCbjZF5jHZMiaIACQunwX0PmeOWStyHk90IqJQuuJLUAE3RFUK0t/ACBZAgAj2a2qk00C1v2QBW8GCkTe/2MLEFlKcGN9gqcEkZU6tQeaNFFuJTEBIFcpDAQs+gGA7JgAkL3p7nuTa/HmH7Fgr5kMOn6lXWHn/sCMyHXABIBybLgir3wsYLkPefGJYMAwJsrd/yMAUKzu9fqCIoHlfpNeMzl24qg7MmmaW4EhssnA7X8BgED6eS9R634AoHjuAQDa504A6lD2BB+oz0Tp1UMAACCo4HsAIKzJ8K99AQBIgiEAADRDAAAg7hxfIxCimdzYq774/T8CAJAQQwAAaIAAAEDJIjTzgKpMxKgYAgCQEEMAmmcXEMTh9T5NAAAAgEAEAAAK51ZgwO2/GxIAgLTYBQQAtRIAACifIQAEp/2/IQEASI4hAADURwAAIIRQ7T1gQSaC1QcBAEiRIQDNswsISuXVPYsAAAAAgQgAQKIMAaicW4EhILf/dhMAAAAgEAEASJchAJUzBIBQtP97EgCANo0ePd72KQBALAIAkDRDACpnCABBaP/PRQAAWmYIQMM6nU7bpwAkoRO1GggAQOoMAWieIQDkzqt4HgIA0D5DABJs+Fk9QL76f/12Qg4BBAAgA4YAAFAVAQBIgiEADVhoq88QAHK00FduJ94QQAAA8sgAhgAAUAkBAIAQBmvyGQJAXgZ7zXaCDQEEACAhhgAAUDcBAIDyDdPeMwSAXAzzau1EGgIIAEBaDAFIkAwA6fM67Z8AAEDh5m/sjd+rwdMB2rHRV3onzBBAAACSYwhAgjQXIWVeoQsiAAAQuv0/638ARZp+jRsCTBMAgBQZApAgLUZIk9fmQgkAAAQ1qxfYzxDAOgNS08+rcsNX97hxnwAAJMsQgOEtdJpvZQDlWejruhNgF5AAAEBEA6/1DQEgHYO9HsfDR30BAEiXIQDDGKyNZyMQlLr5p3+d0ocAAgAA4cy/JtAdhDLM81oej/0yFwCApBkCMJi6G3iGANCuul+DnaKHAAIAALH00/mzEQiK3/wzHngIIAAAqTMEoJXWnQwA0bb+xxkCCAAABBK55wfMMh61IAgAQAYMAWilaWcIAGHb/2UPAQQAAKIYYFkgA0DZq//xkEMAAQDIgyEAKbfrZAAo9VXWKXEIIAAAEMLAfb6YDULI0WCv1vF4r3EBAMiGIQBtNepsBIJQW/+LHwIIAACUb/iVgQwABa/+x4MNAQQAoJwhAJEl0qKTAaDI11QnjQpTFQEAKIddQNTa24vWI4RcVPLaHI/0AhcAgMwYAtBic85GIIiz9b/gIYAAABTFEIC6FwcyAJS6+h8PMwRY0vYJMJ+xyTVtn0IsfuG5GD163AKLxNtyk2eNmVbBwNIs8p1OZ2JiYiR/JgBAaQwBqLuf1+ePTXMFA+nr87VTxwt8PMYQQAAAsqS3SrvtfxkAylv95ztyXCgBACiQIQANrA9kAChy9T8eYAggAAC5MgRgnlZcM5dwGQAKW/338xAFDAEEAKBMhgAA0JMAAGTMECCy1tv/C3osQwDIpf0fYQggAADFMgSgGTIAFLb6L54AAOTNECCmRNr/C31QGQAyWv2PlzsEEACAkhkC0BgZAEpa/ZfNJwG37MRRT+iEloN5/TmGXNqW1Dj3wcDRpNb+3/DRx8Y2/lT0IcGQy+p/fN4Xdb4fDGwCALk6cXR8mMQyedZYkEWzIQBNMgeAYlb/BRMAIG9iwDT91DiSbf/PkAGgpNX/eIl3AggAUAIxYH6GADRMBoAyVv+lEgCgHMFjgCFABOm3/2fIAFDM6n+8uCGAAAClCR4D5mIIQLKKfMVBT57tiRAAoEwxY4AhQNkyav8v9KwyfcVB/xb0JE/wFT1e1hBAAICSxYwBczEEoHkLWseU9HKDgZ/bCa7+yyMAQPlCxQBDgFJl1/6fIQMQXDGr//GChgACAEQRKgbMxRCAVsgAhFXM6r8wAgDEEiEGGAKUJ9/2/4zxe/X5zem/yqAfC9r0n8VrebyUIYAAABFFiAFzMQSgRTIAcWR9y2/xBACIq+AYYAhQkgLa/xuSAYig4NX/eBFDAAEAois4BszFEIB2eXtQCpb7230GIQAAZcYAQ4AyFNb+n+G2YIoU5Jbf8fyHAAIAMDsGDJwEEowBczEEoHUyAIUJsvovgwAA9FBGDDAEyF2p7f+BM0AirywY8slZwOt3PPMhgAAAFB4D5mIIQAoWuhJK/GVFQAt9Thaw+i+AAACUHAMMAfJVfPt/hgxAviKv/sdzHgIsafsEgDxMZ4DBuubTV4gE1+KvmRwb5tZnqHYlMTY2lvtrijgiL/0LYAIAFD4NsEjKUZz2/4aMAsiF1X/uQwABAAgRA+biTgCSIgOQPqv/AggAQPkxwBAgLzHb/8NkADGAZgzwZCv+NTue5xBAAACixIC5GAKQmvF7Leg/SeGlRNkGWPoXv/rPlwAAhIgBhgAFiLaYMAogERr/5f1jBQAglRhQ9emQpWQn5rksLLyUqNYAz6gcF8TRapoAAKQSA+ruX84zBLALKH1hlxSDbQcSA2ir8R/zpTqe279aAABixQBSlmarLN9RgJcSgxnsyZPdIjhyZRMAgEAxwBAgUxYWA/8SZACaec54kY5n9RvwScBAup8i7ONOQ0mwSZb7BwZP8zqiT5b+9el0OhMTEyPJMAEAYk0DDAGyY3lR1SjANIDKnx5enpn+NkwAgEaZBtCT9n8DowCvI7oNHAszWuwmopPSEMAEAAg3DTAEyIhFRh2/HKMApln9Vy6X34wJANAa0wCmaf8PzCiAwVj6Bx8CmAAAEacBhgBZsNRoYBRgGhDNMH90L8lifksmAEASZjLAQtffGpm50/5vdxTgRRTHMGEvi0VtFjppDAFMAIASBgID9LQMARJnwdHwL800oGBD/nG9GMv7jZkAAOXcHqCRmR3t/6RGARs2ib2OCjB8okt/IZujTgJDABMAIO40wBAgWZYdrf8CDQSyNvyfb/xe1Z1ROONp//ZMAIDUmQaUSvu/JgO3/7t5HWWnqtg2/SxKfBWbr07bQwABAAgdA0aPHp/revmaybHB3p6IIVlzpLD035B9QemraVwjBgxjfHy8ppfk8AQAICemAcXQ/q9WM+sML6UENbBTSwwobwggAADRY4AhQFIsMhaq+RajgUAKmr9DQwwoaQggAAC5Mg3Il/Z/JVpfWHg1taLdm7PFgDKGAAIAkLdKYoAhQCKsKhpb+k8vOypJYgYCOa77h3wCiAG5DwEEAKAEpgEZ0f5PYem/4f+u6i8iCWTR76/wCSAG5DsEEACAcgwZAwwB2mUZ0eTSv/t4hcFsw5eSMJDOJp+angBiQI5DAAEAKM0wMYC6af8PYMilQ5/9xZlvq/ZvZCyQ7Lq/57eJAUGGAAIAUKbBYsBcDAHqZt3Q4tK/539VeVQzFmi+9TDAE0AMCDIEEACAklUbAxiS9n/iS//un1DTnyx4GGhg3jjkE0AMKH4IIAAA5askBhgC1MdCIamlf8+fVl94m7UaLjIPNLbDsI6/vhhQ5BBAAACiMA1ol/Z/Xkv/nj+8gT9iGXmg+XuK6vvriwFFDgEEACCWYWKAIUAdrAwSX/r3fKDG4lzPlXRSqaDd9w9o+E8vBhQzBBAAgIhMAxqm/Z/70n+ux23lLzv/mrvyeJDgW4S1+3cXAwoYAggAQFwz7fz+k4AhQLUiLwUyXfonlQSqXa8nuNBP+Y8uBmQ9BBAAAAwE6pXO0jARZSz9008CxUj5Ly4GZDoEEAAAFhYDDAGqEvDaX+TSfxZJoCoZ/bnFgOyGAAIAwP9hGlAtq8A4S/95ztnToOA/tBiQ4xBAAABYcAwwBBhenIt9wKV/N2Gg+D+xGJDXEEAAAJiTacCQgi/1LP17EgYK/uOKAbkMAQQAgEFigCHAMIq/ulv6D/YvLTgPxPmbThMDEh8CCAAAfTENWKiCF3PzsPSv9p+f6bMo+N9xhhiQ7BBAAAAYMAYYAgym1Mu5pX8dev5akkoF/nAbJQYkOAQQAAAWzDRgo5JaotXN0r9h8//GKn/u+QOl8P6wBceAVoYAAgDAgLT/B1DY9dvSP0F+qwUPBMqLAeMtDQEEAAAqFqH9b+kPwxAD2h0CCAAANKSMC7alP1RFDBhpaQggAABQpYLb/5b+UAcxoPkhgAAAQBOyvkJb+kPdIseA8caHAAIAAJUpr/1v6Q9NihwDmhwCCAAA1C7HS7KlP7QlYAwYb3YIIAAAUI1i2v+W/pCCgDGgsSGAAABAvTK6Blv6Q2rixIDxBocAAgAAFci9/W/pDymLEwOaGQIIAADUKP2LrqU/5KL4GDDe1BBAAAAgKEt/yFHxMaABi5t4EACKNteVONmr7Ni9Bv7PJ+5V6RkBzb0Mx4arALWap2xWuNPSBACAQHT9oSSmAYMxAQAgRPtf1x9KVdg0YLz+IYAJAACFG3LdX+m5AHUxDeifCQAAxbb/h+ntaflDjsqYBozXPAQQAAAok6U/hDVkDBgpnQAAQGnt/4HbeJb+UJKBX9FjCYwCah0CuAcAgHIM0/Wv+lyAvO8NGCv3xgATAABKaP/r+gOFTQPGaxsCmAAAkDddf6BPpgHTTAAAyLX9r+sPlD0NGK9nCGACAEB+dP2BIU0EngaYAACQU/tf1x8INQ0Yr2EIYAIAQB50/YGaTPz/VWKhS+pMpwEmAACk3v7X9QeaMTFQ0ah7GlD5EMAEAIB06foDudweMJbPNMAEAIAU2/+6/kC7JlKaBlQ7BDABACAtuv5AOiZKnAaYAACQSvtf1x9I00QC04AKhwAmAAC0T9cfSN9EKdMAEwAA2mz/6/oDeZlobxpQ1RDABACAduj6A/mayHkaYAIAQNPtf11/oAwTjU8DKhkCmAAA0Bxdf6A8E7lNA0wAAGii/a/rD5RtoqlpwPBDABMAAOql6w/EMZHDNMAEAIC62v+6/kBMEzVPA4YcApgAAFA9XX+AiVSnASYAAFTZ/tf1B2hgGjDMEMAEAIBq6PoDZDENMAEAYNj2v64/QPPTgIGHACYAAAxO1x8gu2mACQAAg7T/df0BWp8GDDYEMAEAYGF0/QGyngYIAAD02/639AdIMAbMVZw7nU7P8isAANCXAVb/1v0AzcSABXEPAAD/a6EXnrnY6A+QQv3sWdVNAACoknU/QFvTgD6ZAADwP4a80uj6A1SrkrraXdtNAAAYlnU/QAM1tqqBgAkAAINfV3T9ARozcMmdVeFNAAAYhHU/QKa3Byyq6d4CADJawS/oWmDpD5CIwaq3CQAA/bL0ByhgGuAeAIDo+rly2OsPkKw+S/RMtTcBAGA+1v0AhU0DTAAAQpvnUqHrD5Cd+Uv3dM03AQBgNut+gIKnAd4FCCCoiYmJ7kuApT9AYXwSMAC9WfoDBJkGmAAARGfpDxDE9Mp/0dTUVNtnAgAANMS7AAEAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAASypO0TgOasW7fu0ksvvfjii3/0ox9dffXV11577W233bZ27dp77rln2bJly5cv32mnnXbZZZe99957n332OeCAA3bfffe2TxkAoGKLpqamqv6ZkJZ169Z96lOf+tjHPnbBBRfceeed/f+He+6559Of/vTnPve5e+65Z50nCMCCnXbaaQv6/kWLFi1evHiTTTZZunTpsmXLtt566+23337lypXLli2r7RwhUQIAJbv99tvf+973vv3tb1+zZs0wP+eII454wxve8LCHPay6UwNgKIsWLark5+y6666rVq16+MMf/rjHPe6xj33slltuWcmPhZQJABTrtNNOe8UrXnHDDTdU8tMWL1780pe+9K1vfatrA0BJAWBDS5cufcpTnvKMZzzjqKOO2nTTTSv/+ZAIAYAC/f73v3/e8553zjnnVP6TH/SgB51zzjkPetCDKv/JALQeAGbssssuxx9//Mte9jIbhCiSAEBpfvCDHxxxxBE/+9nP5vmeBz7wgfvtt9/ee++9ww47bLXVVnfccccf/vCHycnJK6+88utf//rk5OQ8/+0222zzuc99bv/996/h3AFIIgBM22233d72trcde+yxdT8QNEwAoCiXXHLJwQcffMstt/T86q677vriF7/4Gc94xv3ud7+5fsLU1NSVV175X//1Xx/72Mduu+22nt+zzTbbXHjhhQ9/+MOrO3EAkgsA0zqdzvvf//7tttuumYeDBggAlONb3/rWgQce2HP1v/XWW7/+9a9/+ctf3v+ezptvvvmEE05497vf3fM1suuuu1522WU77bTT0GcNQGUBYP5VzR//+Me777779ttvv+2229asWfOLX/zi+9///je/+c0vf/nLc3WOpt3//vc///zz99prrypOHNonAFCIa6655pGPfOQf/vCH7i898pGPHB8fH+xN/S+44IJnPetZPe8kPuiggz7/+c8PdLIAtBAA5rJ+/fovfvGLH/jABz71qU/dc889Pb9ndHT0M5/5jP2flEEAoAS333776tWrv/e973V/6cgjjxwfH99ss80G/uFXXXXV4x73uJ7R4oMf/ODzn//8gX8yACkEgBlXXnnl3/3d383V3Nl2220vvPBCbwlNAQQASvC85z3vIx/5SPfxI4444swzz1yyZNhPvP7mN7/5Z3/2Z+vWrZt1fOXKlVdfffXy5cuH/PkApBAApn3gAx84/vjj169f3/2lnXba6dvf/rb9n+RucdsnAMO64IILeq7+99lnn1NOOWX41f/0JqLXv/713cevv/7697///cP/fADS8aIXveiLX/ziNtts0/2l3/72t2NjY3fffXcb5wWVMQEgb+vWrdt7771//vOfzzq+xRZbfPe7391zzz2reqC77rprv/32u/LKK2cdv//97//Tn/508WJZGqCQCcC0r3/960984hNvv/327i+94x3veOUrX1nVA0HzrFrI2/vf//7u1f/IyMhb3vKWClf/IyMjm2666QknnNB9/JprrrnkkksqfCAAUvCYxzzmwx/+cM8vnXDCCddee23jZwSVEQDI2B133HHiiSd2H99rr72OO+64yh/uqU996q677tp9/Oyzz678sQBo3bHHHvsXf/EX3cdvu+22nlcfyIUAQMY++clPXn/99d3H//mf/3mTTTap/OE22WSTF73oRd3HL7roosofC4AU/Mu//MuyZcu6j3/4wx/ueQGCLAgAZOyDH/xg98E99tjjqU99ak2PeNhhh3UfvOKKK9auXVvTIwLQot122+3v//7vu4/feeedJ510UhtnBBUQAMjVVVdd9c1vfrP7+Etf+tL6bsndZ599VqxYMevg3Xff/eMf/7imRwSgXX/zN3+zdOnS7uMf//jH2zgdqIAAQK7OOeec7oOLFi069thj63vQRYsWHXjggd3Hf/rTn9b3oAC0aJtttuk5/v3hvdo4IxhWBW+RDq349Kc/3X1w9erVO++8c62Pe+yxx3a/zdxWW21V64MC0KJnPvOZZ555ZvfxCy64YO+9927jjGAoPgeALN12223bbrtt90exvP71r3/Tm97U0kkBUM7nAGxo/fr1o6Oj3Z8JcNRRR5111ll1PCLUyhYgsnT55Zf3/CDGxz3ucW2cDgAl22yzzR7ykId0H//ud7/bxunAsAQAsvSd73yn5/F999238XMBoHw9ry+/+MUvbr311jZOB4YiAJClH/zgB90HV65cuf3227dxOgBEDABTU1M/+9nP2jgdGIoAQJZ+/etfdx+8//3v38a5AFC+VatW9Tz+m9/8pvFzgWEJAJQTAHbaaac2zgWA8m277bY9j//2t79t/FxgWAIAWfrd737XfbD7I7oAoBJbb711z+O33HJL4+cCwxIAyFL3e7GNjIwsW7asjXMBoHzbbLNNz+N33HFH4+cCwxIAyNKdd97ZfXDzzTdv41wAKN9cE4B169Y1fi4wLAGALP3xj3/sPuhT7QCoSc8PnxkZGdl0000bPxcYlgBAlpYuXdrnWAAAhjdXp9/wmRwJAGSp53b/njcGAMDw5vrAry222KLxc4FhCQBkaauttuo+uGbNmjbOBYDy3XDDDT2Pr1y5svFzgWEJAGRp55137j54/fXXt3EuAJRvrvf732WXXRo/FxiWAECWehbca665po1zAaB8P/nJT3oev+9979v4ucCwBACydL/73a/74A033PCHP/yhjdMBoHA/+tGPug+uWLHCFiByJACQpYc+9KE9j3/ve99r/FwAKN+ll17afXCfffZp41xgWAIAWZqr5n71q19t/FwAKNzNN9981VVXdR9fvXp1G6cDw1oy9E+AFqxatWqbbba5+eabZx2/6KKL/umf/qnWh/7rv/7rWe83utlmm3384x+v9UEBaNFnPvOZnh8EdtBBB7VxOjCsRT48lUwdffTRZ5999qyDm2yyyfXXX7/DDjvU9KA/+9nPHvCAB8w6uPvuu//85z+v6REB6GnRokXdB2ta1XQ6nTPOOGPWwW233fbGG2/0ScDkyBYgcvWUpzyl++Ddd9995pln1vegX/jCF7oPdkcCAIpx4403nnPOOd3HjznmGKt/MiUAkKujjz66Z+V93/veV9+DXnDBBd0HH/KQh9T3iAC06z3vec9dd93Vffw5z3lOG6cDFRAAyNUOO+xw8MEHdx//3ve+d9FFF9XxiHfccccXv/jF7uMHHHBAHQ8HQOt+//vfv+td7+o+vv/++z/mMY9p44ygAgIAGXvRi17U8/g//uM/1vFwp5xyyk033TTr4KabbvqEJzyhjocDoHWvetWrbrnllu7j//AP/9DG6UA1BAAydsghh+y7777dx7/+9a+ffvrplT/ce9/73u6DBx544HbbbVf5YwHQuvPPP/+jH/1o9/EDDjjg8MMPb+OMoBoCAHl73ete1/P4y172st/97ncVPtAZZ5xx+eWXdx9/wQteUOGjAJCIq6+++tnPfnb38U022eS9731vz/cgglwIAOTtaU97Ws8dOGvWrHn2s599zz33VPIoN9100/HHH999fI899jjyyCMreQgA0nHttdcedNBBk5OT3V967Wtf6wOAyZ0AQPbe85739Hw7oM9+9rOvetWrhv/5U1NTL3nJS3772992f+mtb33rJptsMvxDAJCOK6+8cvXq1b/4xS+6v/Tnf/7nb3jDG9o4KaiSAED2Vq1a9da3vrXnl/7t3/7tta997ZA//7jjjjvttNO6jz/xiU/sdDpD/nAA0jE1NfX+97//0Y9+9K9//evur+6xxx7j4+P6PhTAJwFTgqmpqSOOOOK8887r+dVjjz32Qx/60PLlyxf6Y9euXfvyl7/8wx/+cPeXRkdHr7jiil133XWg8wUguU8CvvDCC1/72tdedtllPb+64447XnzxxXvsscfAPx/SIQBQiFtuueXxj398z/t0p9s273znOw877LD+f+BXvvKV5z3veVdffXX3l5YsWfLZz372wAMPHOJ8AUgiAPz4xz8+99xzP/GJT1x55ZVzfc/uu+/+hS98wee+UwwBgHLceOONj33sY3/605/O9Q3777//8ccff/jhh2+11VZzfc8tt9xy3nnnvfvd7/7GN77R8xsWL1580kkn9XxrCADaDQCnnnrqPP/J3XffvX79+rVr105OTl5//fVXX331d77znY2+ZdxjHvOYM888c6eddhr6lCEVAgBFufHGG4844oi51u7TNttss0c/+tEPechDHvCAB2yzzTabbrrp5L1+85vfXHrppVdeeeU87x206aabnnTSSc94xjPqOX0A+tXAG3EuXrz4la985Vve8paebzUB+RIAKM0dd9zx4he/+OMf/3jlP3nHHXc888wzDzjggMp/MgCpBYBHPepR//mf/7nffvvV+ijQCu8CRGmWLVv2sY997Oyzz165cmWFP/aZz3zmVVddZfUPULzVq1efe+653/jGN6z+KZUJAMVau3bte97znre//e2///3vh/k5T3rSk974xjc++tGPru7UAEhuArBq1aojjzzyWc961qpVq6r9yZAaAYDC3XHHHWefffbHPvaxiy666K677ur/P3zgAx941FFHPfe5z33Qgx5U5wkC0FAAWLx48ZIlSzbffPPly5dvu+22K1as2G233fbaa68HP/jBq1ev3nHHHes5U0iOAEAUa9euveSSSy6++OIf//jHV1999W9/+9vbbrtt7dq1U1NTy5YtW758+U477bTrrrvutdde++677wEHHLD77ru3fcoAANUTAAAAIBA3AQMAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEsqjtE4CKdTqdgf/biYmJSs8FgOao/9CnJf1+I2Re3AHIl/oPFRIASJFCDxCT+g8NEABomVoPEJP6D20RAGiaig8Qk/oPiRAAqJ2KDxCT+g9pEgConooPEJP6D1kQAKiGog8Qk/oP2REAGJyiDxCT+g9ZEwBYGEUfICb1H4ohAFBa3R8fXTHPV8cm1zR4LgDZU/+hPAIAOdX9+Ys7AFVR/6FgAgApFn2FHqB56j8EIQDQft1X7gFapP5DNAIALZR+FR8gBeo/xCQAxNVk3VfxAdKh/kNwAkA4zdR9FR8gNeo/ME0AiKKBuq/oAyRI/QdmEQDKV2vpV/QBkqX+Az0JACWrr/Sr+wApU/+BeQgABaqp7iv6AIlT/4F+CABFqaP0q/sA6VP/gf4JAIWovPSr+wBZUP+BhRIA8qbuA8Sk/gMDEwByVW3pV/cBcqH+A0MSAEKXfnUfICPqP1AJASAnSj9ATOo/UCEBIFbpV/cB8qL+A5UTAFKn9APEpP4DNREACi/96j5AdtR/oFYCQIqUfoCY1H+gAQJAWpR+gJjUf6AxAkBR1V/pB8iR+g80SQAoofSr+wCZUv+B5gkALVP6AWJS/4G2CACtUfoBYlL/gXYJAPlVf6UfIF/qP9A6AaBpSj9ATOo/kAgBoDlKP0BM6j+QFAEg9eqv9ANkTf0HUiMA1E7jByAm9R9IkwBQL40fgJjUfyBZAkBdlH6AmNR/IHECQELVX+kHyJ36D6RPAKiYxg9ATOo/kAsBoEoaPwAxqf9ARgSAaij9ADGp/0B2Frd9AiVQ/QFiUv+BHJkAtFD9lX6AAqj/QKYEgMFp/ADEpP4DWRMABqTxAxCT+g/kTgBoovor/QBlUP+BAggAC6PxAxCT+g8Uw7sALYDqDxCT+g+UxASgX8a+ADGp/0BhBICN0/gBiEn9B4okAGyExg9ATOo/UCr3AMxH9QeISf0HCiYAzEn1B4hJ/QfKZgtQD0o/QEzqPxCBCcBsqj9ATOo/EIQA8H+o/gAxqf9AHLYADVj9lX6AYqj/QCgmAP9D9QeISf0HohEA/h/VHyAm9R8IKPoWIKUfICb1Hwgr9ARA9QeISf0HIosbAFR/gJjUfyC4oAFA9QeISf0HiBgAVH+AmNR/gIgBQPUHiEn9B4j4LkD9V3+lH6Ak6j9AxAmA6g8Qk/oPEDEAqP4AMan/ABEDgOoPEJP6DxAxAKj+ADGp/wARA4DqDxCT+g8QMQCo/gAxqf8AEQOA6g8Qk/oPEDEAqP4AMan/ABEDgOoPEJP6DxAxAKj+ADGp/wARA4DqDxCT+g8QMQCo/gAxqf8AEQOA6g8Qk/oPEDEAqP4AMan/AEEDQJ9Uf4CY1H+AogJAn+0f1R+gMOo/QMQAoPoDxKT+A0QMAKo/QEzqP0DEAKD6A8Sk/gNEDACqP0BM6j9AxACg+gPEpP4DBA0A/VD9AWJS/wFKCwD9f+YLACVR/wEiBgDDX4CY1H+AiAFA9QeISf0HiBgAVH+AmNR/gKABoB+qP0BM6j9AaQGgn/aP6g9QHvUfIGIAUP0BYlL/ASIGAG/6BhCT+g8QNAD0Q/sHICb1H6C0AGD4CxCT+g8QMQCo/gAxqf8AEQOArZ8AMan/AEEDQD+0fwBiUv8BSgsAhr8AMan/ABEDgOoPEJP6D9CYhAKArZ8AMan/AEEDQD+0fwBiUv8BSgsAhr8AMan/ABEDgOoPEJP6DxA0AAAAAFECgPYPQEzqP0DEAKD6A8Sk/gPEnQAAAAAhAoD2D0BM6j9AxACg+gPEpP4DtCvdLUCqP0BM6j9AgQHAp74DxKT+A0QMAIa/ADGp/wApSHcLEAAAkH0A0P4BiEn9B0hEchMA1R8gJvUfoMAA4N4vgJjUf4CIAcDwFyAm9R8gKQltAVL9AWJS/wEKDACGvwAxqf8AqUllAqD9AxCT+g9QYADQ/gGISf0HSFASEwDtH4CY1H+AAgPARts/qj9AkdR/gIgBwPAXICb1HyBZLW8B0v4BiEn9BygwAGj/AMSk/gOkrM0JgPYPQEzqP0CBAUD7ByAm9R8gca1NALR/AGJS/wEKDADe+g0gJvUfIH1JfBAYAADQjOoDgPYPQEzqP0AWTAAAACCQigOA9g9ATOo/QC5MAAAAIJAqA4D2D0BM6j9ARkwAAAAgkMoCgPYPQEzqP0BeTAAAACCQagKA9g9ATOo/QHZMAAAAIJAmAoD2D0BM6j9AmQFgo/NfAIqk/gPkyBYgAAAIZNgA4PYvgJjUf4BMmQAAAEAgQwUA7R+AmNR/gHyZAAAAQCA1BgDtH4CY1H+AMgOAd38DiEn9B8haXRMA7R+AmNR/gDIDgPYPQEzqP0Du3AQMAACBDBIAvPsbQEzqP0ABTAAAACCQ6gOA9g9ATOo/QJkBwO1fADGp/wBlsAUIAAACqTgAmP8CxKT+A5QZAMx/AWJS/wGKUeUEQPsHICb1HyAj7gEAAIBAFhAAzH8BYlL/AUpS2QTA/BcgJvUfoMwAoP0DEJP6D1AY9wAAAEAg1QQA81+AmNR/gDIDgPkvQEzqP0B5bAECAIBAKggA5r8AMan/ADkyAQAAgEA2HgBsAAWISf0HKNKwEwDzX4CY1H+ATNkCBAAAgWwkAJj/AsSk/gOUaqgJgPkvQEzqP0C+bAECAIBA5gsA5r8AMan/AAUzAQAAgEAGDwA2gALEpP4DZM0EAAAAApkzANgAChCT+g9QtgEnAOa/ADGp/wC5swUIAAACEQAAAGAkegCwARQgJvUfoHiDTABsAAWISf0HKIAtQAAAEIgAAAAAsQOADaAAMan/ABEseAJgAyhATOo/QBlsAQIAgEAEAAAACEQAAACAwAHAHWAAMan/AEEsbALgDjCAmNR/gGLYAgQAAIEIAAAAEIgAAAAAUQOAO8AAYlL/AeJYwATAHWAAMan/ACWxBQgAAAIRAAAAIBABAAAAQgYAd4ABxKT+A4TS7wTAHWAAMan/AIWxBQgAAAIRAAAAIBABAAAAAhEAAAAgEAEAAADiBYD53wPOW0AAlEr9B4jGBAAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAIIFAG8CDRCT+g8QkAkAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABLK40+nM8+Xx0RUNngwAzVH/AWIyAQAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQJbM/+WxyTVNnQkACVH/AUplAgAAAIEIAAAAEIgAAAAAgQgAAAAQiAAA/6vT6bR9CgC0QP0nFAEAAAACEQAAACAQAQAAAAIRAAAAIJCNfBLw+OiKps4EGuLzTaEf6j/lUf9hmgkAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCCLJyYm5vmyD80GKJX6DxCTCQAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAECwATExPzfMfY5JoGzweA5qj/AAGZAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQLwA4K2gAWJS/wGiMQEAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQPoNAN4IAiAm9R+g2AAw/zvBAVAq9R8gFFuAAAAgEAEAAAACEQAAACCQBQQA94EBxKT+AxQbANwHBhCT+g8Qhy1AAAAQiAAAAACBCAAAABDIwgKA+8AAYlL/AYoNAO4DA4hJ/QcIwhYgAAAIRAAAAIBABAAAAAhkwQHAfWAAMan/AMUGAPeBAcSk/gNEYAsQAAAEIgAAAEAggwQA20ABYlL/AYoNALaBAsSk/gMUzxYgAAAIRAAAAIBABgwAtoECxKT+AxQbAGwDBYhJ/Qcomy1AAAAQyOABwBQYICb1HyBrJgAAABDIfAHANlCAmNR/gIKZAAAAQCBDBQDbQAFiUv8Big0ApsAAMan/AKWyBQgAAAIZNgCYAgPEpP4DFBsATIEBYlL/AYpkCxAAAARSQQAwBQaISf0HyJEJAAAABNJXALANFCAm9R+gPNVMAEyBAWJS/wGyYwsQAAAE0m8AMAUGiEn9ByhMZRMAU2CAmNR/gGIDgCYQQEzqP0BJ3AMAAACBVBkATIEBYlL/AYoNAKbAADGp/wDFqHgLkCYQQEzqP0Au3AMAAACBLDgAmAIDxKT+A5Sh+gmAKTBATOo/QBZsAQIAgEAW1zEF1gQCKJL6D1AAEwAAAAhkwADgVjCAmNR/gNzVNQEwBQaISf0HKDYAaAIBxKT+A2StxnsANIEAYlL/AVLmJmAAAAhkqADg/eAAYlL/AfJlAgAAAIEMGwA0gQBiUv8BMmUCAAAAgVQQALwfHEBM6j9AjpqYAJgCA8Sk/gMkyBYgAAAIpJoA4FYwgJjUf4DsmAAAAEAglQUATSCAmNR/gLyYAAAAQCBVBgBNIICY1H+AjJgAAABAIBUHAE0ggJjUf4BcmAAAAEAg1QcATSCAmNR/gCyYAAAAQCC1BABNIICY1H+A9LU2AXANAIhJ/QcoMwBstAkEQJHUf4DEtXkPgCYQQEzqP0CZAUATCCAm9R8gZS2/C5AmEEBM6j9AmQFAEwggJvUfIO4EwFvCAcSk/gOkKYkPAnMNAIhJ/QcoMwAYBAPEpP4DJCiJCYAmEEBY6j9AmQFAEwggJvUfIDWpTAA0gQDCUv8BygwA/TSBXAMAyqP+A8SdABgEA8Sk/gOkI6EtQNM0gQBiUv8BygwABsEAMan/AIlIbgIAAAAUFQA0gQBiUv8B4k4A3A0GEJP6D9C6dLcAaQIBxKT+A5QZAAyCAWJS/wHiTgBcAwBiUv8BWpTuFiAAAKC0AKAJBBCT+g8QdwLgGgAQk/oPEDQAAAAAsQKAJhBATOo/QNAA4BoAEJb6DxA0APTJNQAgJvUfoMAA4PPhAWJS/wGCBgCDYICw1H+AoAHANQAgLPUfIGgA6JNrAEBM6j9AgQHAZlCAmNR/gKABwCAYICz1HyBoAHANAAhL/QcIGgD65BoAEJP6D1BgALAZFCAm9R8gaAAwCAYIS/0HCBoAXAMAwlL/AYIGgD65BgDEpP4DFBgA+twM6hoAUBj1HyBoAHANAAhL/QcIGgBcAwDCUv8BggYAbwwHEJb6DxA0APRJEwggJvUfoMAAYBAMEJP6DxA0ALgGAISl/gMEDQCuAQBhqf8AQQOAawBAWOo/QNAA4BoAEJb6DxA0ALgGAISl/gMEDQD9cw0AiEn9BygtAPT/6TCuAQAlUf8BggYA1wCAsNR/gKABwDUAICz1HyBoAHANAAhL/QcIGgBcAwDCUv8BggYA1wCAsNR/gKABwDUAICz1HyBoAHANAAhL/QcIGgBcAwDCUv8BggYA1wCAsNR/gKABwDUAICz1HyBoAHANAAhL/QcIGgBcAwDCUv8BggYA1wCAsNR/gKABYKHXAJcBgGKo/wBBA8CCrgFaQQAlUf8BggYA1wCAsNR/gKABwDUAICz1HyBoAHANAAhL/QeCixsAXAMAwlL/gchCB4Dpa4C3hgAISP0HwooeAKZpBQHEpP4DAQkA/8M1ACAm9R+IRgAY/BrgMgBQBvUfCEUAGPwaoBUEUAz1H4hDAJjNNQAgJvUfCEIAGPatIYyDAYqh/gMRCABz0goCiEn9B8omAMzHNQAgJvUfKJgAUP01wGUAoADqP1AqAaD6LaFaQQBlUP+BIgkA/dIKAohJ/QcKIwDUeA3QCgIog/oPlEQAWBjjYICY1H+gGALAIIyDAWJS/4ECCACNjoNdBgByp/4DuRMAGh0HmwgDFED9B7ImAAxLKwggJvUfyJQA0M41QCsIoADqP5AjAaDlcbDLAEDW1H8gOwJAEq0glwGArKn/QEYEgCRaQSbCALlT/4FcCAC10AoCiEn9B9InAKTYCnIZAMiX+g8kTgCo12DXAJcBgNyp/0CyBIB0W0E2hgJkTf0H0iQANEQrCCAm9R9IjQCQTSvIZQAgU+o/kBQBoGkuAwAxqf9AIgSAdgx8DXAZAMia+g+0TgDIshXkMgCQL/UfaJcA0DKXAYCY1H+gLYtae2S6dDqdIX/C+OiKis6lZPNfMoe5HgMMRv1vhvoP00wAEjJ86dEQAsiR+g80SQAoaiI8zWUAIDvqP9AYASBFLgMAMan/QAPcA1D+xtBptofOsAcUyIL6Xzn1H6aZAIToBmkIAWRH/QdqYgIQsRsUvCGkAwRkR/2vhPoP00wAInaDNIQA8qL+AxUyAchVhd2gaA0hHSAga+r/wNR/mCYA5K3ay0CQK4ELAFAA9X8A6j9MEwAK4UrQPxcAoCTqf//Uf5gmABSl8stAkVcCFwCgPOp/P9R/mCYAFKiOy0BJVwIXAKBU6v/81H+YJgCUrKYrQe4XAxcAoHjqf0/qP0wTAMpX32Ug0yuBCwAQhPo/i/oP0wSAKGq9DOR1MXABAEJR/2eo/zBNAAingStB4hcDFwAgJvVf/YdpAkBczVwJErweuAAAwan/Pan/xCEA0OiVIIXrgQsAwDT1f0PqP3EIALR2GWjreuACALAh9X+a+k8cAgAJXQmauSS4AAD0pP7X99CQFAGA1C8GlV8YXAAANkr9h4IJAGR5JRjmIuECANA/9R/KIwBQ7JVgMC4AAD2p/1AMAYDBFXkxcAEA2Cj1H7ImAFCNYi4GLgAAC6L+Q3YEAKqX9cXABQBgYOo/ZEEAoHZ5XQ9cAACqov5DmgQAmpb49cAFAKAm6j8kQgCgZaldD1wAAJqh/kNbBABS1OJVwQUAoEXqPzRAACAnDVwYXAAAEqT+w0h1/j9HVYLWHVz8IgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_252
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color purple.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_422
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_123
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:8)_309
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color green.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color cyan.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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mqsIWfTfRXxfAGI9KKtAQBgENoAgEYUf0OmzwAAMDTwKO+zAQC1GfiSO+EKrwEAoChtAEB1St+zaAAA+JOCE7w2AKBcpVxXO6/tGgAAyqQNACiu0n2KBgCAp/UY3Efmze//drQBAIOZ7vWz98W561VdAwBAX4aXLhl/mRleuqTP/0v7NUwhADCl6e5NpntNbhMAAPgzo6OjvV+EBnjJ8b4ggNJH/ylNdtUVAACYdgkgBgCEMPoPsP4XAAAYpARoEwMAgtr6t/W4zAoAAAxYArSJAQD1j/6Drf8FAACKlgBtYgBAs1v/tt7XVQEAgBJKgDYxAKCG0X/g9b8AAECZJUCbGABQ89a/bcoLqQAAQMklQJsYAOSsVdnoX2T9LwAAUFUJ0CYGALlp1b71b+vnyikAAFBhCdAmBgA5qGH0L7j+FwAAqKMEaBMDgFS1mtv6t/V5qRQAAKipBGgTA4CUtGoc/Yuv/wUAAOouAdrEACB2rQC2/m39XxsFAAAaKAHaxAAgRq0mRv9S1v8CAABNlgBtYgAQi1ZIW/+2aV0MBQAAGi4B2sQAIGStRkf/stb/AgAAoZQAbWIAEJpWkFv/tule/QQAAAIqAdrEACAErTBG/xLX/wIAACGWAG1iAJD56D+lAS53AgAAgZYAbWIAkPPoP1zq+l8AACD0EqBNDAByG/2nNNj1TQAAIIISoE0MAErXmv5eo7bRv/T1vwAAQEwlQJsYACQ/+k9p4AuaAABAZCVAmxgApD36D1ew/hcAAIi1BGgTA4D0Rv8pFbmCCQAARFwCtIkBQGKj/3A1638BAIAUSoA2MQBIYPSfUsFLlgAAQCIlQJsYAMQ++g9Xtv4fGhqaWd1NA5C2wMflAV7CW0+p5nSAug32jB4JYPqv+tqrAQAgwRJg4CpAGwAJGCzJjwRw1aph/S8AAJDgJwEmEAMgH7GP/lMq5aIkAACQcglQSgyQBCB8yYz+wxWv/wUAALIoAQrGAIUAhCyZ0X9KZV2CBAAAcikB2sQASEN6o/9w9et/AQCA7EqANjEA4pXe6D+lEq85AgAAOZYAbWIAxCXh0X+4lvW/AABA1iVAmxgA4Ut49J9SuRcZAQCA3EuANjEAwpTD6D9c1/pfAACgNLGXAG1iAIQjh9F/SqVfVQQAACoXUQnQJgZAs7Ia/YdrXP8LAACUKZkSoE0MgPplNfpPqYrLiAAAQB1iLAHaxACoR56j/3C9638BAICSpVcCtIkBUJ08R/8pVXTdEAAAqEnUJUCbGADlynz0H659/S8AAFC+hEuANjEAist89J9SdRcKAQCA+qRRArSJATAYo3+D6/8UAkDrDcNNnwKQqVarZYBrsAQIJ0uIAZDb6D9c/fWn0itD9AFgdPGIDADULPn3t8Tywjk+cwcyGYgBUMVlM5AneBU7+6bW/ykEAIA6Gf3DMTJv/vjLpxgAIUty9B8J7NxyDABKAKAGRv8S3wVURXsuBkBokhz967nNqi8CKQQAgEoZ/cMvAdrEAAhB2qP/SGAnmW8AUAIAVTD6x1UCrHzj4bxIiwFkJe3RP431fzoBAKBcRv9YdJYAbWIA1CmT0X8ksLPNPQAoAYBSGP3TKAFWvpdwXrPFAJKUyeifzPo/qQAAUJDRP70SoE0MgCrkNvqPBHbaA0sqACgBgMEY/dMuAVa+u3BewsUAopbb6J/S+j+1ANCPI+eNNH0KNOmwpSIif8bon08J0CYGQBFpjP7D03/SBXX+Bc0cSsvo4inme/MfMK71lKbPIhc95tSmfhfm8NIlDf4azglG5s0fbLbwMKZOAz/eBn6EJ/bcHw5j/Z9jAwBgYErStEqANm0A9CPbrX+Yf5HiEgwAU34S4LClw94IBHky+jconE8CdD2BcF7jxQCCYvRPb/2fZgAA6GT0z8FgJUCYhYAYQOOM/mH+jUqR2mcAxvkkANDmTdLhCPCTAIF/PMBnA2iE9/qnvf5PNgAAlDIDebtgdHoMH9N9MIQzPYgB1CbP0b/V868czt+rRMm+BcgnASBnxYce14f0PgnQvutpLduSeVOQ9wXRW55v+GnV8pa50Nb/KQcAIE9Gf6b8JECeMcDHA5hMzqN/XH/HEs3o/fef8s30gZvyFwN7pc9N749/eF2MWkWjv8dMzf+xSnm57TEKTLjrAf4LhjMQFHmHkocuRv9+ngvF/6YBrv81AEAKbP0Z+OuAtAEVnBcRMPpH95ctV+INgBKACWxzE1PD6O8xk3wJ0KYNIAdG/5Xluf7XAACxsvWn9N8JoA2o4LwIiNE/3r916dJvAJQArMw2NwE1j/4eM1mVAG3aAFKSxhBc+ug/muv6XwMAxMTWn9p+MbA2oILzogFG/wT++lXIogFQAtBmmxupBkd/j5lsS4A2bQAxMvr3Nprx+l8DAITO1p+mSoA2bUAF50WI18wQHrENbv3D/HeoSC4NgBKAcba5EQlk9PeYqVoUJUCbNoBgGf37N5r3+l8DAIQokNGfNJRSArRpAyo4L4oy+pdoJKR/kOpk1AAoAbDNDV+Ao7/HTA3iKgHatAE0Lo3Rf4BHY3XP3JEM1v8aACAUAY7+JKPcEqBNG1DBedEvo38VRoL5l6laXg2AEgDb3AAFPvp7zNQj0hKgTRtAbYz+RVj/j9MAAI0JfPQnJRWVAG3agArOi4mM/pUaCeafqAbZNQBKgMzZ5gYiotHfY6Y2sZcAbdoASmf0L4X1f5sGAKhVRKM/iam6BGjTBlRwXvky+tdjJJh/q3rk2AAoAXJmm9ugSEd/j5k6JVMCtGkDGJjRv1zW/yvTAACVi3T0Jz21lQBt2oAKzit9Rv+ajQTzj1abTBsAJUC2bHNrlsDo7zFTs/RKgIKPlkBGE21APYz+FbH+n0ADAFQigdGfJNVfArS1Wq0B5oBACgFtQNWyHf0bXPyH9q9Xp3wbACVAnmxza5DY6O8xU7+ES4CCD5tAJhVtQLmM/lWz/u+kAQBKk9joT6oaLAEKbsS1AYkx+jduJJh/xppl3QAoATJkm1uRhEd/j5lGJF8CpNEGFMxROT99Cj7MQvivH8vob/3flQYAKCTh0Z+ENV4CpNEGFKkCsm0DjP7hGAnjH7MRuTcASoDc2OaWKJPR32OmKfmUAG3agLQZ/etn/T8ZDQAwbZmM/qQtnBKgTRsQ8sBUhNE/QCNh/Ks2RQPwJCVAPmxzC8pw9PeYaVCGJUCbNiANRv8GWf/3oAEA+pLh6E/yAiwB2rQBgc9PUzL6h2wkjH/eBmkA/kQJkAnb3AFkPvp7zDQr5xKgTRsQF6N/CKz/e9MAAJPKfPQnByGXAG3agPDHqXFG/yiMhPHv3CwNwNOUADmwze2T0b/NY6ZxSoCV5dwGhPyMS2D0LxjSgmL9PyUNAFDydTyZ0R8ClHMbEGYhYPQnRhqAP6MESJ5t7mSM/pPxmAmBEqArbcBQo4z+YbL+74cGAHJn9IdIaQMambeKXzON/jROAzCREiBttrkrM/r3w2MmEEqA3rQBQ9Uz+g8Fz/q/TxoAyJHRHxKjDah0/DL6l30uNEwD0IUSIGG2uUb/6fKYCYcSoE/agKHyGP2H4mH93z8NAOTC6A+Z0AaUMo0Z/cs+FwKiAehOCZCqPLe5Rv8i8nzMBEsJMF3agAH+X0b/oQhZ/0+LBgBSZvSHzGkDpvXXN/qXfS4ESgMwKSVAkvLZ5hr9y5LPYyYWSoCBaQN6/NToX/a51Mr6f7o0AJAaoz/QlTag61/f6F/2uRABDUAvSoD0pL3NLX4d95DO7TETKSVAcUUeuo3Pu2W1AUb/oSRY/w9AAwApMPoDtX1VTuOFQFltQPFzaJbRn4FpAKagBEhMettco3/V0nvMpEEJUKLM24Do/spG/5VZ/w9GAwCxMvoDpci8DZjufTXL6E8pNABTUwKkJI1trtG/Tmk8ZpKkBKiCNiDMv5rRvyvr/4FpACAmRn+gUtqArrfZLKM/pZtZ/k0mZ8oapPeCEErRekqRWzhy3ojpn0yUMgL2mPyi3vxVfcEZXrqk/vflr2xk3vxSpvaybqeIgf8xi79khK/Z9X/sNAAQOlt/6Gp0dDT5EadZ2bYBIcz9A/9/PSnqMRr5FkAD0BclAI2w9YeBKQHKklUb0PjWv8i/WA5b/zbr/4I0ABAiW38oXgIML13S+Co3Gcm3AY0/VGz9wzE81X+LBPK/BqBfSgDqYesPQVECJNMGBMvWP7T1fw40ABAKW38YgBKgflG3AUGx9Q/QcAbrfw3A9CgBqIitP4RMCdCVNqAIW/+BWf+XQgMATbL1h+KUAA3SBkyXrX/IhvNY/2sApk0JQFls/SEiSoDetAH9sPUvzvq/LBoAqJutP5ROCRACbcBkbP2jMJzN+l8DMAglAAOz9Yd4KQH6pA1Yma1/iaz/S6QBgDrY+kPVlABB0QbY+sdlOKf1vwZgQEoA+mfrD8lQAkxXnm2ArX8VrP/LpQGAqtj6Q82UAGHKpw2w9Y/UcGbrfw3A4JQA9GDrD6lSAgysyFUx/Dag4Bma/nuz/i+dBgDKZOsPzVICpFoFBNsGFEwmRv/GDee3/tcAFKIEYGW2/pAJJUCzV8tw2oDiW3/Tfz+s/6ugAYCibP0hKEqAKETdBtj6J2M4y/W/AFDU6OKR1ht6rfkPWzpstkuY0R/yNDJv/mRzQ+/4QRUxoM4kYPSvmfV/RQQAGITRH0KmBMgqBtRTCBj90zOc6/pfACiBEiA3Rn9ACZBPDCj+eQMPhoFZ/1dHAIB+Gf0hIkqASIUTA4z+aRvOeP3vW4DK4euAkucbfoBOvg4o5Ktuka/oKf5FQ77hpzjr/0ppAKAXW3+IlxIgdvW3Abb+mRjOe/0vAJTGJwHSY/QHpuSTABHFgOJ/pjf/uUtk/V81AQAmMvpDMpQAySgeA6pj9I/LcPbrf58BKJNPAiTAe/2B6fJJgDqF9t760M4nDdb/NdAAQDnM/RAmJUB6QmgDzP2Rsv4fpwEokxIgT7b+kDklQFbbd1v/Sln/10MDAIMz90MUlAAJq7MNMPfHzvq/TQNQMiVAJmz9gZUpAZpV9Vbe1r8e1v+10QDA9Jj7IUZKgBxU0QaY+5Nh/b8yDUD5lACpsvUHBpPVYNG4srb1tv418zSpkwAAUzP6Q/LjRfHfA6VDCEqR8d3oH6CCzy/r/wkEgEooAZJh9AdKkdt4EYjpjvJG/6Z4gtRMAIDujP6QnmZLACNOU/oZ643+DZryqWH9XzoBoCpKgHgZ/QGAhAkA8DSjPyRPCQBBsf5vhABQISUAAAChEQAAyIsSAAJh/d8UAaBaSgAAAIIiAACQHSUANM76v0ECQOWUAAAAhEMAACBHSgBokPV/swSAOigBAAAIhAAAQKaUANAI6//GCQA1UQIAABACAQCAfCkBoGbW/yEQAOqjBAAAoHECAABZUwJAbaz/AyEA1EoJAABAswQAAHKnBIAaWP+HQwComxIAAIAGCQAAoASAaln/B0UAaIASAACApggAAPAkJQBUxPo/NAJAM5QAAAA0QgAAgD9RAkDprP8DJAA0RgkAAED9BAAAeJoSAEpk/R8mAaBJSgAAAGomAADAn1ECQCms/4MlADRMCQAAQJ0EAACYSAkABVn/h0wAaJ4SAACA2ggAADBtSgAIef1PbwJAEJQAAKExgkO8PH97EwAAYBBKAOjK+j98AkAolAAAoTGCQ4w8c6ckAADAgJQAMIH1fxQEgIAoAQBCYwSHuHjO9kMAAIDBKQGgzfo/FgJAWJQAAKExgkMsPFv7JAAAQCFKALD+j4sAEBwlAEBojOAQPs/T/gkAAFCUEoDMWf/HRQAIkRIAIDRGcAiZZ+i0CAAAUAIlANmy/o+OABAoJQBAaIzgECbPzekSAACgHEoAMmT9HyMBIFxKAIDQGMEhNJ6VAxAAAKA0VW8rzToEpeoHpPV/RQSAoCkBAHKbeAq+XwKCUvXjWSQejAAAAGVSApAJ6/94CQChUwIAhEYJAP2w/g+WAAAAJVMCkDzr/6gJABFQAgCERgkAvVn/h0wAAIDyKQFImPV/7ASAOCgBAEKjBIDJWP8HTgAAgEooAUiS9X8CBIBoKAEAQqMEgE7W/+ETAACgKkoAEmP9nwYBICZKAIDQKAFgZdb/URAAAKBCSgCSYf2fDAEgMkoAgNAoAWCc9X8sBAAAqJYSgARY/6dEAIiPEgAgNEoAsP6PiAAAAJVTAhA16//ECABRUgIAhEYJQM6s/+MiAABAHZQARMr6Pz0CQKyUAAChUQKQJ+v/6AgAAFATJQDRsf5PkgAQMSUAQGiUAOTG+j9GAgAA1EcJQESs/1MlAMRNCQAQGiUA+bD+j5QAAAC1UgIQBev/hAkA0VMCAIRGCUAOrP/jJQAAQN2UAATO+j9tAkAKlAAAoVECkDbr/6gJAADQACUAwbL+T54AkAglAEBolACkyvo/dgIAADRDCUCArP9zIACkQwkAEBolAOmx/k+AAAAAjVECEBTr/0wIAElRAgCERglASqz/0yAAAECTlAAEwvo/HwJAapQAAKFRApAG6/9kCAAA0DAlAI2z/s+KAJAgJQBAaJQAxM76PyUCAAA0TwlAg6z/czOj1Wo1fQ4AsTJUMS1ec6Er19KaaQAAACAjAgAA1MSaEzp5XtRPAAAAgIwIAABQH8tOWJlnRCMEAAAAyIgAAAD18UVAsDLPiEYIAAAAkBEBAABqYtkJnTwv6icAAABARqb4TcCji0eGwtZ6w3CPnx45L/Tzp2aHLfWAmfY/i29pgHrWnCPz5he5/eGlSwqeQNp6X8fCH3hi1HtIm8ALTZ00AMDUMp8boAYFp/8peRYDbQIAkG/1AbWpev6ecv0PgZNR6yQAAH1xaYbqWP8DdRIAgCcpAaA61v/QD0m1NgIA0C+XZqiC9T9QMwEA+BMlAFTB+h/6J6/WQwAApsGlGcpl/Q/UTwAAnqYEgHJZ/8N0Sa01EACA6XFphrJY/wONEACAP6MEgLJY/8NgZNeqCQDAtLk0Q3HW/0BTBABgIiUAFGf9D0VIsJUSAIBBuDRDEdb/QIMEAKALJQAUYf0Pxcmx1REAgAG5NMNgrP+hhicCPQgAQHdKABiM9T+URZqtiAAADM6lGabL+h/alABNEQCASSkBYLqs/6FcMm0VBACgEJdm6J/1P0ygBGiEAAD0ogSA/ln/QxUk29IJAEBRLs3QD+t/6EoJUD8BAJiCEgD6Yf0P1ZFvyyUAACVwaYberP+hByVAzQQAYGpKAOjN+h+qJuWWSAAAyuHSDJOx/ocpKQHqJAAAfVECwGSs/6Eesm5ZBACgNC7N0Mn6H/qkBKiNAAD0SwkAnaz/oU4SbykEAKBMLs2wMut/mBYlQD0EAGAalACwMvM31M/zrjgBACiZSzOUtcvs/f4fzzWSpASogQAATI8SAMaZv6Epnn0FCQBA+VyawfofBqYEqJoAAEybEgDM39Asz8EiBACgEi7N5Mz6HwpSAlRKAAAGoQQgZ+ZvCIFn4sAEAKAqLs3kyfofSqEEqI4AAAxICUCezN8QDs/HwQgAQIVcmsmN9T+USAlQEQEAGJwSgNyYvyE0npUDEACAark0kw/rfyidEqAKAgBQiBKAfJi/IUyem9MlAACVc2kmB9b/UBElQOkEAKAoJQAAREQAAOpgeUnaj2Hrf6jUlE8xz5FpEQCAEigBACAWAgBQE+sZ4mX9D41TApRIAADKoQQAgCgIAEB9rGeIkfU/BEIJUBYBACiNEgAAwicAALWyniEu1v8QFCVAKQQAoExKAAAInAAA1M16hlhY/0OAlADFCQBAyZQAABAyAQBogPUM4bP+h2ApAQoSAIDyKQEAIFgCANAM6xlCZv0PVev9LJiSEqAIAQCohBIAAMIkAACNsZ4hTNb/UA8lQFMEAKAqSgAACJAAADTJeobQWP9DnZQAjRAAgAopAQAgNAIA0DDrGcJh/Q/1UwLUTwAAqqUEAICgCABA86xnCIH1PzRFCVAzAQConBIAAMIhAABBsJ6hWdb/0CwlQJ0EAKAOSgAACIQAAITCeoZU1/9F7h3okxKgfwIAUBMlANkq+N4GyIRnSm0EACAg1jPUz/ofkqEE6JMAANRHCUCGLDWhf54v9RAAgLBYz1An639IjBKgHwIAUCslAFmxzoTp8qypgQAABMd6hnpY/0OSlABTEgCAuikByIRFJgzGc6dqAgAQIusZqmb9DwlTAvQmAAANUAKQPCtMKMIzqFICABCozNczVMr6HxpX9RNBCdCDAAA0QwlAwiwvoTjPo+oIAEC4cl7PUB3rfwiEEqApAgDQGCUASbK2hLJ4NlVEACAXhy0dPmzpcNNnwbRlu56hItb/EBQlQCMEANJn9A+ZEoDEWFhCuTynqiAAkDKjfxryXM9QBev/PI0+pemzYFJKgPoJAKTJ6B8RJQA5rCoznDBCYPSPRe8niBKgdAIAqTH6J8nwROzrf2pm9GdlSoAJBADSYfSPlxKABFj/B8LoHyklQJ0EAFJg9M+BEYoirP9zYPSnByXAygQA4mb0T4YSgKhZ/zfL6J8GJUBtBABiZfTPkEGKwVj/J8zoT/+UAG0CAPEx+qdKCUCkrP8bYfRPkhKgHgIAMTH6Y5xiuqz/02P0Z2BKgHECALmM/qOLR0YXWzCHTglAdKz/62T0z4ESoAaz6rgTKKD4yt/cn5hWq2UCoBTW/xHxrKcsI/PmSxEaAMJl658nJQAlqnoHb/1fA1v/DDVbArQyePJqAAiRrT+9KQEozvo/fGU9zcf/W1v60jaSfQkgABAWoz/jJYBPe1Oc9X+8yh39SW/RM7x0SaX/cVupr5kEAEJh9Gdakr86UylzYbCM/tRjJO8SQACgeUZ/OikBKMj6PzpGfyZQAlRHAKBJRn+KSPvqTHUMiKEx+tOIkYxLAAGAZhj9mZISgIFZ/8fC6E9vSoCKCADUzehPiRK+OlMRk2IgSnnm+q9JQSO5lgACAPUx+jNdSgAGYP0fOKM/06IEqIIAQB2M/lQn1aszVTA1NsvoT4BGsiwB/CZgquW3+VKQXwzMtFj/Jzz9j8ybb/rPk18MXDoNAFWx9ac2SgD6YXaMevQv6VygiwxLAAGA8hn9KZdPAtAn6//QGP0pi08ClEsAoExGf5qS3tWZcpkja2b0Jy4jmZUAAgDlMPpTKSUAU2pwB2/9vzKjP0kuelpprZkEAIoy+hOIxK7OlKiUgTKr7eBgjP40qPi7gEZyKgEEAAZn9KdOSgB6sP5vltGfeigByiIAMIhS5jDTP6VL6epMWaz/K2X0JxxKgP4JAEyP0Z8GKQHoyvq/EYmN/q03uLbEQQlQCgGAfhn9iUIyV2dKYf1fhcRGf1KiBOiTAMDUjP6EQwnABNb/dTL6EwIlQHECAL0Y/YlRGldnirP+L1HUo7//iFlRAvRDAKA7oz/BUgLQzw6+6nEzn/W/0Z8MFz0jPTNAAmsmAYCJjP4kIIGrMyHIfHw0+pNtCZA8AYCnGf2JhRIA6/9KGf0JnxKgCAGAJxn9SU/sV2cal+ccafQnDUqA3gSA3Bn9iZQSIHPW/6Uz+hMdJcDABIB8Gf1JXtRXZ5qV1UBp9CdJSoAeBIAcGf1JgxIgW9b/ZTH6D6zZybLg3z2lh7ESYDACQF6M/uQm3qszDcphqWz0L+UcmvpHGL/fgf8dxv/rpxQDJqMEmIwAkAujP0lSAmTI+r8go3+JE7AYEAIlwAAEgPQZ/clcpFdnct4uV6TgEyHqN710/UcQA1KKAZNRAnQlAKTM6E8OlABZsf4fjNG/xz+CGJBADFACTJcAkCajP8R+daYR6a3/jf59/iOIAQnEgMkoAToJAKkx+pMhJUAmrP+nxeg/wD+CGBBvDFACTIsAkA6jP/QQ3dWZ+iWz/jf6F/xHEAPijQGTUQJMIACkwOgPSoDkWf/3w+hfytccrXw7YkBETwElQP8EgLgZ/aF/cV2dqVns63+jf4mjf+dtigERxYDJKAFWJgDEyugPEygBEmb934PRv6LRv/P2xYDwnxFKgD4JAPEx+sPAIro6U6dI1/9G/xpG/877EgPCjwGTUQK0CQAxMfpDb0qAJFn/dzL61zz6d73fgg8PMaAiSoB+CABxMPpDWWK5OlObuNb/Rv8GR/8qhmAxoGZKgHECQOiM/jAtSoDEWP+3Gf3DGf1XJgYEGAOUAFMSAMJl9IeKRHF1ph5RrP+N/uE/YZOJAQP/JwswBkxmWAkgAITJ6A9FKAGSYf1v9A9/9E8sBhQsBMKJAUqA3gSAsBj9oR7hX53JfP1v9I/3GSoGhBMDJjOcfQkgAITC6A8lUgIkINv1v9E/3tF/ZWJA4zFACdCDANA8oz80IvCrMxmu/43+6T0lxYDGY8BkhvMuAQSAJhn9oTpKgKjltv43+qc3+q9MDGgqBigBJiMANMPoDyEI+epMJut/o38+z0ExILQ2YDjjEkAAqJvRH2qjBIhUJuv/qEf/Uqb/fEb/KmJAsw+AiGKAEqArAaA+Rn8IULBXZxJe/xv9PemKD8GNVwFxxYBgo1RTBIA6GP2hKUqAlCSw/jf6G/1XJgbUEwOaLQHCJABUy+gP4VMCBKXxjWB1ijzMjP4JEwNGR0cTfuK3gnyJEQCqYvSHQCgB0lDWcDPZgFLp/GH0L+lcUpZ5DKi6CugxhQ+X8S6g6EoAAaB8Rn+ITpgbmgyltwUc+HHV+Nxv9G+EGJDkdaAV3kuMAFAmoz+ESQkQuxjX/0b/ks4lR2JAFc9KJcDKBIByGP0hdgFuaHKTzNrP6F/SueRODEjpstAK7CVGACjK6A9RUALEK6L1v9G/pHPhaWJAiU9SJUCbADA4oz8kJrQNTVZi3/MZ/Us6F7oTAxK4SrRCeokRAAZh9IcYKQFiFP763+hf0rkwNTGg+HNWCTBOAJgeoz+kLagNTT4iXewZ/Us6F6ZHDIj3otEK5iVGAOiX0R8SoASIS7Drf6N/SefC4MSAgf/6LSWAANAPoz9kJZwNTSbi2uQZ/Us6F8qRUgwY4CEaYxvQCuMlRgDoxegP6VECxCK09b/Rv6RzoXxpxICBC4EB/vqt7EsAAaA7oz/kLJANTQ6iWN0Z/Us6F6olBsRySWkF8BIjAExk9IfkKQHCF8j63+hf0rlQn/Z/tYFH4UxiQCvvEkAAeFpZA4HpHxIQwoYmeSHv6oz+JZ0LjSm4Ec8kBmT7EiMAPMnoD7lRAoSs2fW/0b+kcyEIYkCPv3sr4xIg9wBg9AeC3dCkLcDlnNG/pHMhOGJAgBecVqMvMfkGAKM/ZE4JEKZG1v9G/5LOhaCJAZ1/91auJUCOAcDoD/RJCVCRcLZxRv+SzoVoiAGtYK4/Db7E5BUAjP7AypQAOa//jf4lnQtREgNa///vnmcJkEsAMPoDg1EClK7x9ZvRv6RzIXpiQKvpy1FTLzHpBwCjP9CDEiCr9b/Rv6RzISliQCu/EiDxAOC3egHFKQFK1OC+bbD/iAmM/h699EMMyOolJvEAUJDRH3KgBMhh/T+AxkcZoz/1yzkGTCbJEkAA6M7oD6xMCVCKxt9u26fGxxejP80SA5J/iREAJjL6Q4aUAM0KZ/3f+Mhi9CccYkDCJYAA8DSjP9CDEiDh9X/jM8o4oz8BEgOSfIkRAJ5k9AeUAHmu/xufS8YZ/QmcGDCcVgmQewAw+gP9UwKktP5vfBYZZ/QnImJAMi8x+QYAoz+dLIAhh/V/4/PHOKM/kUopBgxN55mYUgmQYwAw+gMDUwJEvf5vfOYYZ/QnAWnEgKHACoHaXmLyCgBGf4A81/8hzBlGf9KTWwwYTqUEyCUAGP2BsigB4lr/hzBbGP1JW24xIIGXmPQDgNEfIM/1fwjzhNGffGQSA4aTKAFSDgBGf6AiSoDA1/8hzBBGf/KUSQyI/SUmzQBg9AfIc/0fwtxg9Ie0Y8Bw/CVAagHA6A/UQwkQ2vo/hFnB6A/5xICoX2LSCQBGf4A81/8hzAdGf8gqBgxHXgKkEACM/kAjlACNr/9DmAmM/jCtx/lgF4cwY0C8LzHRBwDTPyXyMgxVK/H1O4RRwOgPdRYCocWA4poqAaIPAACEpvHv/q+B0R+KSCMGxFsCCAAA1CSNF2yjP5RFDBhqqAQQAAAoU8Lrf6M/VEEMqL8EEAAAqEPUr9BGf6hazjFgpPYSQAAAoDTprf+N/lCnnGNAnSWAAABA5WJ8STb6Q1MyjAEj9ZYAAgAA5Uhm/W/0hxBkGANqKwEEAACqFdFrsNEfQpNPDBipsQQQAAAoQezrf6M/hCyfGFBPCSAAAFCh8F90jf4Qi+RjwEhdJYAAAECmjP4Qo+RjQA1m1nEnACRtslfiYF9lh5cuKTL9jz6l1DMC6nsaDhe7AlSqx2WzxHdaagAAyIitP6REGzAYDQAAWaz/bf0hVYm1ASPVlwAaAAASV3DuL/VcgKpoA/qnAQAg2fV/kd2elT/EKI02YKTiEkADAECaioz+ZZ8LEFMbMBLGCqM6GgAAUlv/D7zGs/WHlAz8jB4OoAqotATQAACQDlt/oKw2YDjdDwZoAABIYf1v6w8k1gaMVFYCaAAAiJutP9AnbcA4DQAAsa7/bf2BtNuAkWpKAA0AAPGx9QcKGs24DdAAABDT+t/WH8iqDRipoATQAAAQB1t/oCKj//8qMd2ROtI2QAMAQOjrf1t/oB6jA100qm4DSi8BNAAAhMvWH4jl4wHD8bQBGgAAQlz/2/oDzRoNqQ0otwTQAAAQFlt/IByjKbYBGgAAQln/2/oDYRoNoA0osQTQAADQPFt/IHyjqbQBGgAAmlz/2/oDcRltrg0oqwTQAADQDFt/IF6jMbcBGgAA6l7/2/oDaRitvQ0opQTQAABQH1t/ID2jsbUBGgAA6lj/2/oDaRutqw0oXgJoAAColq0/kI/RGNoADQAAVa3/bf2BPI1W3AYULAE0AACUz9YfYDTUNkADAECZ639bf4Aa2oAiJYAGAIBy2PoDRNEGaAAAKLr+t/UHqL8NGLgE0AAAMDhbf4Do2gANAACDrP9t/QEabwMGKwE0AABMj60/QNRtgAAAQL/rf6M/QIAxYLKLc6vV6nr5FQAA6MsA07+5H6CeGDAtPgMAwNOm+8IzGW/0Bwjh+tn1qq4BAKBM5n6AptqAPmkAAPiTgq80tv4A5Srlutp5bdcAAFCUuR+ghmtsWYWABgCAwV9XbP0BajPwJXfCFV4DAMAgzP0AkX48YEZFny2AGBloyNa0Xgs8UwCivnprAADol9EfIIE2wGcAAHLXzyuH9/oDBKvPS3T7aq8BAKAXcz9AYm2ABgAgaz1eKmz9AaLT+9I9fs3XAAAwkbkfIOE2wLcAwdMMPeSm8yXAswAgMX4TMADdGf0BMmkDBACATLVfDIz+AFnFgBljY2NNnw8AAFAT3wIEAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMjKr6ROA+ixfvvzSSy+96KKLfvWrX91444233Xbbgw8+uGzZsieeeGLOnDlz587daKONNtlkk2222Wa77bbbeeedt9hii6ZPGQCgZDPGxsbKvk0Iy/Lly7/73e9+4xvfOOeccx555JH+/49bbbXV61//+re+9a1bbbVVlScIwLSdcMIJ0/rzM2bMmDlz5iqrrDJ79uw5c+asvfba66+//oIFC+bMmVPZOUKgBABS9tBDD33xi1/8zGc+s2TJkiK3s++++370ox99wQteUN6pAVDIjBkzSrmdTTfddOHChTvssMPLXvayXXbZZc011yzlZiFkAgDJOuGEE97//vffddddpdzazJkz3/Oe93zqU5/y2gCQUgBY2ezZs3ffffc3vvGNr33ta1ddddXSbx8CIQCQoD/+8Y8HH3zwqaeeWvotP/e5zz311FOf+9znln7LADQeANo22WSTQw899L3vfa83CJEkAYDU/OIXv9h3331/85vf9Pgzz3nOc3bcccdtttlmgw02WGuttR5++OF77rln6dKl11577SWXXLJ06dIe/9911lnn+9///k477VTBuQMQRAAYt9lmm336058+8MADq74jqJkAQFIuvvjiPfbY4/777+/600033fRd73rXG9/4xmc+85mT3cLY2Ni11177v//7v9/4xjcefPDBrn9mnXXWOe+883bYYYfyThyA4ALAuFardfTRR6+33nr13B3UQAAgHT/96U933XXXrtP/2muv/ZGPfOR973tf/+/pvO+++4444oijjjqq63Nk0003veyyyzbaaKPCZw1AaQGg91Tz2GOPPf744w899NCDDz64ZMmSm2+++ec///nll1/+wx/+cLLN0bhnPetZZ5xxxtZbb13GiUPzBAAScdNNN73oRS+65557On/0ohe9aGRkZLAv9T/nnHMOOuigrp8k3m233X7wgx8MdLIANBAAJrNixYpzzz33y1/+8ne/+90nnnii65+ZN2/emWee6f2fpEEAIAUPPfTQokWLrr766s4f7bfffiMjI6utttrAN37ddde97GUv6xotjjnmmLe97W0D3zIAIQSAtmuvvfYf//EfJ1vurLvuuuedd56vhCYBAgApOPjgg7/2ta91Ht93331PPvnkWbOK/sbryy+//K/+6q+WL18+4fiCBQtuvPHGuXPnFrx9AEIIAOO+/OUvH3rooStWrOj80UYbbXTFFVd4/yexm9n0CUBR55xzTtfpf7vttjv++OOLT//jbyL6yEc+0nn8zjvvPProo4vfPgDheOc733nuueeus846nT+64447hoeHH3/88SbOC0qjASBuy5cv32abbX77299OOL7GGmtcddVVW221VVl39Oijj+64447XXnvthOPPetazbrjhhpkzZWmARBqAcZdccskrX/nKhx56qPNHn/3sZz/wgQ+UdUdQP1MLcTv66KM7p/+hoaFPfvKTJU7/Q0NDq6666hFHHNF5/Kabbrr44otLvCMAQvDSl770q1/9atcfHXHEEbfddlvtZwSlEQCI2MMPP3zkkUd2Ht96660POeSQ0u/uNa95zaabbtp5/JRTTin9vgBo3IEHHviGN7yh8/iDDz7Y9dUHYiEAELFvf/vbd955Z+fxf/u3f1tllVVKv7tVVlnlne98Z+fx888/v/T7AiAE//7v/z5nzpzO41/96le7vgBBFAQAInbMMcd0Htxyyy1f85rXVHSPe++9d+fBa665ZtmyZRXdIwAN2myzzf7pn/6p8/gjjzxy7LHHNnFGUAIBgFhdd911l19+eefx97znPdV9JHe77babP3/+hIOPP/749ddfX9E9AtCsv//7v589e3bn8W9+85tNnA6UQAAgVqeeemrnwRkzZhx44IHV3emMGTN23XXXzuM33HBDdXcKQIPWWWedrvXvL5/SxBlBUSV8RTo04nvf+17nwUWLFm288caV3u+BBx7Y+TVza621VqV3CkCD3vSmN5188smdx88555xtttmmiTOCQvweAKL04IMPrrvuup2/iuUjH/nIxz/+8YZOCoB0fg/AylasWDFv3rzO3wnw2te+9jvf+U4V9wiV8hYgonTllVd2/UWML3vZy5o4HQBSttpqq2277badx6+66qomTgeKEgCI0s9+9rOux7fffvvazwWA9HV9fbn55psfeOCBJk4HChEAiNIvfvGLzoMLFixYf/31mzgdAHIMAGNjY7/5zW+aOB0oRAAgSrfeemvnwWc961lNnAsA6Vu4cGHX47///e9rPxcoSgAgnQCw0UYbNXEuAKRv3XXX7Xr8jjvuqP1coCgBgCj94Q9/6DzY+Su6AKAUa6+9dtfj999/f+3nAkUJAESp87vYhoaG5syZ08S5AJC+ddZZp+vxhx9+uPZzgaIEAKL0yCOPdB5cffXVmzgXANI3WQOwfPny2s8FihIAiNJjjz3WedBvtQOgIl1/+czQ0NCqq65a+7lAUQIAUZo9e3aftQAAFDfZpl/5TIwEAKLU9e3+XT8YAADFTfYLv9ZYY43azwWKEgCI0lprrdV5cMmSJU2cCwDpu+uuu7oeX7BgQe3nAkUJAERp44037jx45513NnEuAKRvsu/732STTWo/FyhKACBKXS+4N910UxPnAkD6fv3rX3c9vvnmm9d+LlCUAECUnvnMZ3YevOuuu+65554mTgeAxP3qV7/qPDh//nxvASJGAgBRev7zn9/1+NVXX137uQCQvksvvbTz4HbbbdfEuUBRAgBRmuya+6Mf/aj2cwEgcffdd991113XeXzRokVNnA4UNavwLUADFi5cuM4669x3330Tjp9//vn/+q//Wuld/93f/d2E7xtdbbXVvvnNb1Z6pwA06Mwzz+z6i8B22223Jk4Hiprhl6cSqf333/+UU06ZcHCVVVa58847N9hgg4ru9De/+c2zn/3sCQe32GKL3/72txXdIwBdzZgxo/NgRVNNq9U66aSTJhxcd9117777br8JmBh5CxCx2n333TsPPv744yeffHJ1d3r22Wd3HuyMBAAk4+677z711FM7jx9wwAGmfyIlABCr/fffv+uV90tf+lJ1d3rOOed0Htx2222ru0cAmvWFL3zh0Ucf7Tz+lre8pYnTgRIIAMRqgw022GOPPTqPX3311eeff34V9/jwww+fe+65ncd33nnnKu4OgMb98Y9//PznP995fKeddnrpS1/axBlBCQQAIvbOd76z6/F/+Zd/qeLujj/++HvvvXfCwVVXXfUVr3hFFXcHQOM++MEP3n///Z3H//mf/7mJ04FyCABEbM8999x+++07j19yySUnnnhi6Xf3xS9+sfPgrrvuut5665V+XwA07owzzvj617/eeXznnXfeZ599mjgjKIcAQNw+/OEPdz3+3ve+9w9/+EOJd3TSSSddeeWVncff/va3l3gvAATixhtvfPOb39x5fJVVVvniF7/Y9TuIIBYCAHF73ete1/UdOEuWLHnzm9/8xBNPlHIv995776GHHtp5fMstt9xvv/1KuQsAwnHbbbfttttuS5cu7fzR4Ycf7hcAEzsBgOh94Qtf6Pp1QGedddYHP/jB4rc/Njb27ne/+4477uj80ac+9alVVlml+F0AEI5rr7120aJFN998c+eP/vqv//qjH/1oEycFZRIAiN7ChQs/9alPdf3Rf/7nfx5++OEFb/+QQw454YQTOo+/8pWvbLVaBW8cgHCMjY0dffTRL3nJS2699dbOn2655ZYjIyP2PiTAbwImBWNjY/vuu+/pp5/e9acHHnjgV77ylblz5073ZpctW/a+973vq1/9aueP5s2bd80112y66aYDnS8Awf0m4PPOO+/www+/7LLLuv50ww03vOiii7bccsuBbx/CIQCQiPvvv//lL39518/pjq9tPve5z+2999793+CFF1548MEH33jjjZ0/mjVr1llnnbXrrrsWOF8AgggA119//Wmnnfatb33r2muvnezPbLHFFmeffbbf+04yBADScffdd++yyy433HDDZH9gp512OvTQQ/fZZ5+11lprsj9z//33n3766UcdddRPfvKTrn9g5syZxx57bNevhgCg2QCwePHiHv+Xxx9/fMWKFcuWLVu6dOmdd9554403/uxnP5vyK+Ne+tKXnnzyyRtttFHhU4ZQCAAk5e677953330nm93Hrbbaai95yUu23XbbZz/72euss86qq6669Cm///3vL7300muvvbbHdwetuuqqxx577Bvf+MZqTh+AftXwRZwzZ878wAc+8MlPfrLrV01AvAQAUvPwww+/613v+uY3v1n6LW+44YYnn3zyzjvvXPotAxBaAHjxi1/8P//zPzvuuGOl9wKN8C1ApGbOnDnf+MY3TjnllAULFpR4s29605uuu+460z9A8hYtWnTaaaf95Cc/Mf2TKg0AyVq2bNkXvvCFz3zmM3/84x+L3M6rXvWqj33sYy95yUvKOzUAgmsAFi5cuN9++x100EELFy4s95YhNAIAiXv44YdPOeWUb3zjG+eff/6jjz7a///xOc95zmtf+9q3vvWtz33uc6s8QQBqCgAzZ86cNWvW6quvPnfu3HXXXXf+/PmbbbbZ1ltv/bznPW/RokUbbrhhNWcKwREAyMWyZcsuvvjiiy666Prrr7/xxhvvuOOOBx98cNmyZWNjY3PmzJk7d+5GG2206aabbr311ttvv/3OO++8xRZbNH3KAADlEwAAACAjPgQMAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjM1qtVtPnAKEYHR1t+hQAAKo108QDkJvWU5o+CwCaMauh+wWgAeZ+AJ78DIASACB5tv4AjNMAACTO3A9Al28BUgIApMfWH4BOGgCABJn7AZj69wAoAQASYOsPQG8aAIBEmPsBmPZvAlYCAMTI1h+AChuAI+eNTPf/AuE4bOlw06cAZTL3A1CoAeinBDA/AYTA1h+AwfgMAEBkzP0AlNkAKAEAgmXrD0BxGgCACJj7AaiwAVACAITD1h+AcmkAAAJVfO4/ct6IfQ0AfTUASgCAqLf+R84b8a3NAHSlAQBIbetf0rkAkFkDoAQAqJOtPwD10AAANMzWH4BQGgAlAEClbP0BqJ8GAKABtv4ABNoAKAEAymXrD0CzNAAANbH1ByCOBkAJAFCQrT8A4dAAAFTI1h+AKBsAJQDAdNn6AxAmDQBAyWz9AUihAVACAEzJ1h+A8GkAAEpg6w9Agg2AEgCgk60/AHHRAAAMyNYfgPQbACUAgK0/AFHTAABMg60/ANk1AEoAIE+2/gCkQQMAMAVbfwBybwCUAEAmbP0BSI8GAKALW38AUjVgA6AEAFJl6w9A2jQAAH9i6w9ADgZvAJQAQDJs/QHIhwYAyJqtPwC5KdQAKAGAeNn6A5AnDQCQHVt/AHJWtAFQAgARsfUHAA0AkAVbfwAorQFQAgAhs/UHgJVpAIBk2foDQFUNgBIACIqtPwBMRgMAJMXWHwBqagCUAECzbP0BoB8aACB6tv4A0EwDoAQAambrDwDTpQEAomTrDwBBNABKAKBqtv4AUIQGAIiGrT8AhNgAKAGA0tn6A0BZNABA0Gz9ASCCBkAJABRn6w8AVdAAAMGx9QeA+BoAJQAwAFt/AKiaBgAIgq0/AETfACgBgH7Y+gNAnTQAQGNs/QEgtQZACQB0ZesPAE3RAAAxrfxt/QEg9AZACQCUsvK39QeAUmgAgGrZ+gNAdg2AEgDyZOsPAAHSAADls/UHgNwbACUAZMLWHwACpwEAymHrDwBRqK8BUAJAqmz9ASAiGgBgcLb+ABCdWhsAJQAkw9YfACKlAQCmx9YfAKLWQAAYHR3tPUActnTYcAABKmXlX9K5AAAD0gAAUzP6A0Ay6v4MwDifBIB83uvvjf4AEBQNANCdrT8AJKmZBkAJACGz9QeAhGkAgKfZ+gNA8hprAJQAEBRbfwDIhAYAcmfrDwBZabIBUAJAs2z9ASBDGgDIka0/AGSr4QZACQA1s/UHgMxpACAXtv4AQBANgBIAqmbrDwC0aQAgZbb+AECIDYASAEpn6w8AdKUBgNTY+gMAETQASgAoztYfAJiSBgBSYOsPAMTXACgBYAC2/gDAtGgAIFa2/gBA9A2AEgD6YesPAAxMAwAxsfUHAFJrAJQA0JWtPwBQCg0AhM7WHwBIvAFQAsA4W38AoHQaAAiRrT8AkFcDoAQgW7b+AEClNAAQClt/ACDrBkAJQD5s/QGA2mgAoEm2/gBAzYJuAJQAJMzWHwBohAYA6mbrDwA0KPQGQAlASmz9AYDGaQCgDrb+AEAgImgAlABEzdYfAAiKBgCqYusPAAQojgZACUBcbP0BgGBpAKBMtv4AQOCiaQCUAATO1h8AiIIGAIqy9QcAIhJTA6AEIDS2/gBAdDQAMAhbfwAgUpE1AEoAGmfrDwBETQMA/bL1BwASEF8DoASgfrb+AEAyNADQi60/AJCYKBsAJQA1sPUHAJKkAYCJbP0BgITNGEp6UDOHUXM15CFHRI/5KatUAJKkAYByGP0BgCjE+hmAcT4JQAi81x8AiIgGAAZn7gcAohN3A6AEoCm2/gBApDQAMD3mfgAgatE3AEoAamPrDwAkQAMAUzP3AwDJSKEBUAJQHVt/ACAxGgDoztwPACQpkQZACUCJbP0BgIRpAOBp5n4AIHnpNABKAAAAyCsAAAAAeQUAJQAAAGQUAAAAgLwCgBIAAAAyCgAAAEBeAUAJAAAAGQUAAAAgrwCgBAAAgIwCAAAAkFcAUAIAAEBGAQAAAMgrACgBAAAgowAAAADkFQCUAAAAkFEAAAAA8goASgAAAMgoAAAAAHkFACUAAABkFAAAAIC8AoASAAAAMgoAAABAXgFACQAAQObyCgAAAJC57AKAEgAAgJxlFwAAACBnOQYAJQAAANnKMQAAAEC2Mg0ASgAAAPKUaQAAAIA85RsAlAAAAGQo3wAAAAAZyjoAKAEAAMhN1gEAAAByk3sAUAIAAJCV3AMAAABkRQBQAgAAkBEBAAAAMiIAPEkJAABAJgQAAADIiADwJ0oAAAByIAAAAEBGBICnKQEAAEieAAAAABkRAP6MEgAAgLQJAAAAkBEBYCIlAAAACRMAAAAgIwJAF0oAAABSJQAAAEBGBIDulAAAACRJAAAAgIwIAJNSAgAAkB4BAAAAMiIA9KIEAAAgMQIAAABkRACYghIAAICUCAAAAJARAWBqSgAAAJIhAAAAQEYEgL4oAQAASIMAAAAAGREA+qUEAAAgAQIAAABkRACYBiUAAACxEwAAACAjAsD0KAEAAIiaAAAAABkRAKZNCQAAQLwEAAAAyIgAMAglAAAAkRIAAAAgIwLAgJQAAADESAAAAICMCACDUwIAABAdAQAAADIiABSiBAAAIC4CAAAAZEQAKEoJAABARAQAAADIiABQAiUAAACxEAAAACAjAkA5lAAAAERBAAAAgIwIAKVRAgAAED4BAAAAMiIAlEkJAABA4AQAAADIiABQMiUAAAAhEwAAACAjAkD5lAAAAARLAAAAgIwIAJVQAgAAECYBAAAAMiIAVEUJAABAgAQAAADIiABQISUAAAChEQAAACAjAkC1lAAAAARFAAAAgIwIAJVTAgAAEA4BAAAAMiIA1EEJAABAIAQAAADIiABQEyUAAAAhEAAAACAjAkB9lAAAADROAAAAgIwIALVSAgAA0CwBAAAAMiIA1E0JAABAgwQAAADIiADQACUAAABNEQAAACAjM1qtVtPnAECIbSQASdIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARmb1/vGR80bqOhOow2FLh3v81AO+kX92v5IWAOqkAQCa12q1mj4FAMiFAABUTrUCAOEQAIAgKAEAoB4CAFAHJQAABEIAAEKhBACAGggAQE2UAAAQAgEACIgSAACqJgAA9VECAEDjBAAgLEoAAKiUAADUSgkAAM0SAIDgKAEAoDoCAFA3JQAANEgAAEKkBACAiggAQAOUAADQFAEACJQSAACqIAAAzVACAEAjBAAgXEoAACidAAA0RgkAAPUTAICgKQEAoFwCANAkJQAA1EwAAEKnBACAEgkAQMOUAABQJwEAiIASAADKIgAAzVMCAEBtBAAgDkoAACiFAAAEQQkAAPUQAIBoKAEAoDgBAAiFEgAAaiAAADFRAgBAQQIAEBAlAABUTQAAIqMEAIAiBAAgLEoAAKiUAADERwkAAAMTAIDgKAEAoDoCABAlJQAADEYAAEKkBACAiggAQKyUAAAwAAEACJQSAACqIAAAEVMCAMB0CQBAuJQAAFA6AQCImxIAAKZFAACCpgQAgHIJAED0lAAA0D8BAAidEgAASiQAAClQAgBAnwQAIAJKAAAoiwAAJEIJAAD9EACAOCgBAKAUAgCQDiUAAExJAACioQQAgOIEACApSgAA6E0AAGKiBACAggQAIDVKAADoQQAAIqMEAIAiBAAgQUoAAJiMAADERwkAAAMTAIA0KQEAoCsBAIiSEgAABiMAAMlSAgBAJwEAiJUSAAAGIAAAKVMCAMAEAgAQMSUAAEyXAAAkTgkAACsTAIC4KQEAYFoEACB9SgAAaBMAgOgpAQCgfwIAkAUlAACMEwCAFCgBAKBPAgCQCyUAAAgAQDqUAADQDwEAyIgSAAAEACAdSgAAmJIAAORFCQBA5gQAIClKAADoTQAAsqMEACBnAgCQGiUAAPQgAAA5UgIAkC0BAEiQEgAAJiMAAJlSAgCQJwEASJMSAAC6EgCAfCkBAMiQAAAkSwkAAJ0EACBrSgAAciMAAClTAgDABAIAkDslAABZEQCAxCkBAGBlAgCAEgCAjAgAQPqUAADQJgAAPEkJAEAmBAAgC0oAABgnAAD8iRIAgBwIAEAulAAAIAAA/BklAADJEwCAjCgBAEAAAPgzSgAA0iYAAHlRAgCQOQEAYCIlAAAJEwCA7CgBAMiZAADQhRIAgFQJAECOlAAAZEsAAOhOCQBAkgQAIFNKAADyJAAATEoJAEB6BAAgX0oAADIkAAD0ogQAIDECAJA1JQAAuREAAKagBAAgJQIAkDslAABZEQAApqYEACAZAgCAEgCAjAgAAH1RAgCQBgEA4ElKAAAyIQAA9EsJAEACBACAP1ECAJADAYBcHLZ0+LClw02fBdFTAgAQOwGA9Bn96Z8SAIDkCQCkzOhPFZQAAERNACBNRn8GpgQAIG0CAKkx+lMDJQAA8RIASIfRn7IoAQBImABACoz+1E8JAECkBADiZvSnIkoAAFIlABAroz+NUwIAECMBgPgY/amHEgCAJAkAxMToT2iUAABERwAgl9F/9CnlnRFZUAIAkJ5ZTZ8ATKH4u33M/VSq1Wp5jAEQEQGAcBn9CcGR80Z85gSAlAgAhMjoT1yUAABERAAgLEZ/AqQEACAlAgChMPoTNSUAALEQAGie0Z/wKQEASIYAQJOM/qRECQBAFAQAmmH0JzpKAADSIABQN6M/CVMCABA+AYD6GP2JnRIAgAQIANTB6E8+lAAABE4AoFpGfxKjBAAgdgIAVTH6ky0lAAAhEwAon9GftCkBAIiaAECZjP4wTgkAQLAEAMph9CcrSgAA4iUAUJTRH7pSAgAQJgGAwRn9yZkSAIBICQAMwugP/VACABAgAYDpMfpDmxIAgBgJAPTL6A8DUAIAEBoBgKkZ/WEySgAAoiMA0IvRH4pTAgAQFAGA7oz+0CclAABxEQCYyOgPpVMCABAOAYCnGf1hMEoAACIys+kTIAiHLR02/UOlWq1W06cAAE/SAOSulLWl0R+UAADEQgDIl9EfauaTAACEQADIkdEfqqAEACAKAkBejP7QLCUAAI0TAHJh9IcaKAEACJ8AkD6jPwRFCQBAswSAlBn9oX5KAAACJwCkyegPIVMCANAgASA1Rn9onBIAgJAJAOkw+kNElAAANEUASIHRH0KjBAAgWAJA3Iz+EC8lAACNEABiZfSHwCkBAAiTABAfoz8kQwkAQP0EgJgY/SEuSgAAAiQAxMHoD6lSAgBQMwEgdEZ/iJoSAIDQCADhMvpDJpQAANRJAAiR0R9SogQAICgCQFiM/pAnJQAAtREAQmH0h4QpAQAIhwDQPKM/oAQAoDYCQJOM/pAPJQAAgRAAmmH0BzopAQCogQBQN6M/ZEsJAEAIBID6GP2BKSkBAKiaAFAHoz8wTgkAQOMEgGoZ/YHpUgIAUCkBoCpGf6ArJQAAzRIAymf0BwpSAgBQHQGgTEZ/oB9KAAAaJACUw+gPlEsJAEBFBICijP7AAJQAADRFABic0R+olBIAgCoIAIMw+gPFKQEAaIQAMD1Gf6BOSgAASicA9MvoD5ROCQBA/QSAqRn9gQYpAQAolwDQi9EfqJoSAICaCQDdGf2BcCgBACiRADCR0R+omRIAgDoJAE8z+gPBUgIAUBYB4ElGf6BZSgAAapN7ADD6A7FQAgBQinwDgNEfCIoSAIB65BgAjP5ApJQAABSXVwAw+gMhUwIAUINcAoDRH0iDEgCAgtIPAEZ/ICJKAACqlnIAMPoDSVICAFBEmgHA6A/ESwkAQKVSCwBGfyAHSgAABpZOADD6A8lQAgBQnRQCgNEfyJASAIAcA4DRH0iVEgCAisQaAIz+AEoAALIIAEZ/IBNKAAByDwBGf4AJlAAApBkAjP5AnpQAAGQXAIz+AL0pAQBIJAAY/QGUAABkEQCM/gDTogQAINYAYPQH6KQEACDBAGD0ByhCCQBANAHA6A8wJSUAAGWZOdScw5YOm/4BytJqtZo+BQAi0EwDUNYey+gP5EMJAECUAcDoD1AdnwQAIKAAYPQHKEgJAEAcAcDoD1AbJQAATQYAoz9AuZQAAAQaAIz+AE1RAgBQawAw+gNUSgkAQCgBwOgPEAglAADVBgCjP0CdlAAANBYAjP4AYVICAFByADD6AzRICQBAfQHA6A8QBSUAAEUDgNEfIBxKAAAqDABGf4AYKQEAmHYAMPoDBEsJAMB0zez941JeV0afUvx2ABhAq9Vq+hQASPo3Aa/M3A9QNSUAAGU2AAOz9QcIhxIAgAobAHM/QM2UAAA00wDY+gMESwkAQJkNgLkfoFlKAABqagBs/QFioQQAoFADYO4nPRaoAEDyBmkAbP0BIqUEAGB6DYC5HwAAsmgAbP0B0qAEAMjc1A2AuR8AALJoAGz9AZKkBADIWfcGwNwPAABZNAC2/gA5UAIAZOvpBsDcDwAAQ6n7fx8Ee33Save3AAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:8)_228
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGbklEQVR4nO3YwQ2DQAwAQYhokSsSikxa4HMXpJ15W7KfK28bAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAi+zneX5XLQPe777v/d83APN9FuwAAF5GAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACDoeDp4XdfcS4Cpxhj/PgF4ER8AAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAg6ng6OMeZeAgAs4wMAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACArecH008KELEDbqAAAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color yellow.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color yellow.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": 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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:8)_480
| 8
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
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"text": "This is the original shape, with its image:.",
"type": "text"
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"text": "If you perform 8 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color white.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\n. Please select the correct answer from the options below. The options are: ",
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"
},
"text": null,
"type": "image_url"
}
] |
A
|
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