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@@ -1594,3 +1594,5 @@ evalkit_cambrian/lib/libstdc++.so.6.0.29 filter=lfs diff=lfs merge=lfs -text
 evalkit_internvl/lib/python3.10/site-packages/transformers/models/oneformer/__pycache__/modeling_oneformer.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text
 evalkit_internvl/lib/python3.10/site-packages/transformers/models/seamless_m4t/__pycache__/modeling_seamless_m4t.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text
 evalkit_tf449/lib/python3.10/site-packages/torch/lib/libtorch_python.so filter=lfs diff=lfs merge=lfs -text
+evalkit_tf437/lib/python3.10/site-packages/pip/_vendor/idna/__pycache__/idnadata.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text
+evalkit_tf437/lib/python3.10/site-packages/pip/_vendor/idna/__pycache__/uts46data.cpython-310.pyc filter=lfs diff=lfs merge=lfs -text

evalkit_internvl/lib/python3.10/site-packages/transformers/models/siglip/configuration_siglip.py

@@ -0,0 +1,302 @@
+# coding=utf-8
+# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+""" Siglip model configuration"""
+
+import os
+from typing import Union
+
+from ...configuration_utils import PretrainedConfig
+from ...utils import logging
+
+
+logger = logging.get_logger(__name__)
+
+SIGLIP_PRETRAINED_CONFIG_ARCHIVE_MAP = {
+    "google/siglip-base-patch16-224": "https://huggingface.co/google/siglip-base-patch16-224/resolve/main/config.json",
+}
+
+
+class SiglipTextConfig(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`SiglipTextModel`]. It is used to instantiate a
+    Siglip text encoder according to the specified arguments, defining the model architecture. Instantiating a
+    configuration with the defaults will yield a similar configuration to that of the text encoder of the Siglip
+    [google/siglip-base-patch16-224](https://huggingface.co/google/siglip-base-patch16-224) architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+    Args:
+        vocab_size (`int`, *optional*, defaults to 32000):
+            Vocabulary size of the Siglip text model. Defines the number of different tokens that can be represented by
+            the `inputs_ids` passed when calling [`SiglipModel`].
+        hidden_size (`int`, *optional*, defaults to 768):
+            Dimensionality of the encoder layers and the pooler layer.
+        intermediate_size (`int`, *optional*, defaults to 3072):
+            Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
+        num_hidden_layers (`int`, *optional*, defaults to 12):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 12):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        max_position_embeddings (`int`, *optional*, defaults to 64):
+            The maximum sequence length that this model might ever be used with. Typically set this to something large
+            just in case (e.g., 512 or 1024 or 2048).
+        hidden_act (`str` or `function`, *optional*, defaults to `"gelu_pytorch_tanh"`):
+            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
+            `"relu"`, `"selu"` and `"gelu_new"` `"quick_gelu"` are supported.
+        layer_norm_eps (`float`, *optional*, defaults to 1e-06):
+            The epsilon used by the layer normalization layers.
+        attention_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout ratio for the attention probabilities.
+        pad_token_id (`int`, *optional*, defaults to 1):
+            The id of the padding token in the vocabulary.
+        bos_token_id (`int`, *optional*, defaults to 49406):
+            The id of the beginning-of-sequence token in the vocabulary.
+        eos_token_id (`int`, *optional*, defaults to 49407):
+            The id of the end-of-sequence token in the vocabulary.
+
+    Example:
+
+    ```python
+    >>> from transformers import SiglipTextConfig, SiglipTextModel
+
+    >>> # Initializing a SiglipTextConfig with google/siglip-base-patch16-224 style configuration
+    >>> configuration = SiglipTextConfig()
+
+    >>> # Initializing a SiglipTextModel (with random weights) from the google/siglip-base-patch16-224 style configuration
+    >>> model = SiglipTextModel(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "siglip_text_model"
+
+    def __init__(
+        self,
+        vocab_size=32000,
+        hidden_size=768,
+        intermediate_size=3072,
+        num_hidden_layers=12,
+        num_attention_heads=12,
+        max_position_embeddings=64,
+        hidden_act="gelu_pytorch_tanh",
+        layer_norm_eps=1e-6,
+        attention_dropout=0.0,
+        # This differs from `CLIPTokenizer`'s default and from openai/siglip
+        # See https://github.com/huggingface/transformers/pull/24773#issuecomment-1632287538
+        pad_token_id=1,
+        bos_token_id=49406,
+        eos_token_id=49407,
+        **kwargs,
+    ):
+        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
+
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.max_position_embeddings = max_position_embeddings
+        self.layer_norm_eps = layer_norm_eps
+        self.hidden_act = hidden_act
+        self.attention_dropout = attention_dropout
+
+    @classmethod
+    def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> "PretrainedConfig":
+        cls._set_token_in_kwargs(kwargs)
+
+        config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
+
+        # get the text config dict if we are loading from SiglipConfig
+        if config_dict.get("model_type") == "siglip":
+            config_dict = config_dict["text_config"]
+
+        if "model_type" in config_dict and hasattr(cls, "model_type") and config_dict["model_type"] != cls.model_type:
+            logger.warning(
+                f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
+                f"{cls.model_type}. This is not supported for all configurations of models and can yield errors."
+            )
+
+        return cls.from_dict(config_dict, **kwargs)
+
+
+class SiglipVisionConfig(PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`SiglipVisionModel`]. It is used to instantiate a
+    Siglip vision encoder according to the specified arguments, defining the model architecture. Instantiating a
+    configuration with the defaults will yield a similar configuration to that of the vision encoder of the Siglip
+    [google/siglip-base-patch16-224](https://huggingface.co/google/siglip-base-patch16-224) architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+    Args:
+        hidden_size (`int`, *optional*, defaults to 768):
+            Dimensionality of the encoder layers and the pooler layer.
+        intermediate_size (`int`, *optional*, defaults to 3072):
+            Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
+        num_hidden_layers (`int`, *optional*, defaults to 12):
+            Number of hidden layers in the Transformer encoder.
+        num_attention_heads (`int`, *optional*, defaults to 12):
+            Number of attention heads for each attention layer in the Transformer encoder.
+        num_channels (`int`, *optional*, defaults to 3):
+            Number of channels in the input images.
+        image_size (`int`, *optional*, defaults to 224):
+            The size (resolution) of each image.
+        patch_size (`int`, *optional*, defaults to 16):
+            The size (resolution) of each patch.
+        hidden_act (`str` or `function`, *optional*, defaults to `"gelu_pytorch_tanh"`):
+            The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`,
+            `"relu"`, `"selu"` and `"gelu_new"` ``"quick_gelu"` are supported.
+        layer_norm_eps (`float`, *optional*, defaults to 1e-06):
+            The epsilon used by the layer normalization layers.
+        attention_dropout (`float`, *optional*, defaults to 0.0):
+            The dropout ratio for the attention probabilities.
+
+    Example:
+
+    ```python
+    >>> from transformers import SiglipVisionConfig, SiglipVisionModel
+
+    >>> # Initializing a SiglipVisionConfig with google/siglip-base-patch16-224 style configuration
+    >>> configuration = SiglipVisionConfig()
+
+    >>> # Initializing a SiglipVisionModel (with random weights) from the google/siglip-base-patch16-224 style configuration
+    >>> model = SiglipVisionModel(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+    ```"""
+
+    model_type = "siglip_vision_model"
+
+    def __init__(
+        self,
+        hidden_size=768,
+        intermediate_size=3072,
+        num_hidden_layers=12,
+        num_attention_heads=12,
+        num_channels=3,
+        image_size=224,
+        patch_size=16,
+        hidden_act="gelu_pytorch_tanh",
+        layer_norm_eps=1e-6,
+        attention_dropout=0.0,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.num_channels = num_channels
+        self.patch_size = patch_size
+        self.image_size = image_size
+        self.attention_dropout = attention_dropout
+        self.layer_norm_eps = layer_norm_eps
+        self.hidden_act = hidden_act
+
+    @classmethod
+    def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> "PretrainedConfig":
+        cls._set_token_in_kwargs(kwargs)
+
+        config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
+
+        # get the vision config dict if we are loading from SiglipConfig
+        if config_dict.get("model_type") == "siglip":
+            config_dict = config_dict["vision_config"]
+
+        if "model_type" in config_dict and hasattr(cls, "model_type") and config_dict["model_type"] != cls.model_type:
+            logger.warning(
+                f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
+                f"{cls.model_type}. This is not supported for all configurations of models and can yield errors."
+            )
+
+        return cls.from_dict(config_dict, **kwargs)
+
+
+class SiglipConfig(PretrainedConfig):
+    r"""
+    [`SiglipConfig`] is the configuration class to store the configuration of a [`SiglipModel`]. It is used to
+    instantiate a Siglip model according to the specified arguments, defining the text model and vision model configs.
+    Instantiating a configuration with the defaults will yield a similar configuration to that of the Siglip
+    [google/siglip-base-patch16-224](https://huggingface.co/google/siglip-base-patch16-224) architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+    Args:
+        text_config (`dict`, *optional*):
+            Dictionary of configuration options used to initialize [`SiglipTextConfig`].
+        vision_config (`dict`, *optional*):
+            Dictionary of configuration options used to initialize [`SiglipVisionConfig`].
+        kwargs (*optional*):
+            Dictionary of keyword arguments.
+
+    Example:
+
+    ```python
+    >>> from transformers import SiglipConfig, SiglipModel
+
+    >>> # Initializing a SiglipConfig with google/siglip-base-patch16-224 style configuration
+    >>> configuration = SiglipConfig()
+
+    >>> # Initializing a SiglipModel (with random weights) from the google/siglip-base-patch16-224 style configuration
+    >>> model = SiglipModel(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+
+    >>> # We can also initialize a SiglipConfig from a SiglipTextConfig and a SiglipVisionConfig
+    >>> from transformers import SiglipTextConfig, SiglipVisionConfig
+
+    >>> # Initializing a SiglipText and SiglipVision configuration
+    >>> config_text = SiglipTextConfig()
+    >>> config_vision = SiglipVisionConfig()
+
+    >>> config = SiglipConfig.from_text_vision_configs(config_text, config_vision)
+    ```"""
+
+    model_type = "siglip"
+
+    def __init__(self, text_config=None, vision_config=None, **kwargs):
+        super().__init__(**kwargs)
+
+        if text_config is None:
+            text_config = {}
+            logger.info("`text_config` is `None`. Initializing the `SiglipTextConfig` with default values.")
+
+        if vision_config is None:
+            vision_config = {}
+            logger.info("`vision_config` is `None`. initializing the `SiglipVisionConfig` with default values.")
+
+        self.text_config = SiglipTextConfig(**text_config)
+        self.vision_config = SiglipVisionConfig(**vision_config)
+
+        self.initializer_factor = 1.0
+
+    @classmethod
+    def from_text_vision_configs(cls, text_config: SiglipTextConfig, vision_config: SiglipVisionConfig, **kwargs):
+        r"""
+        Instantiate a [`SiglipConfig`] (or a derived class) from siglip text model configuration and siglip vision
+        model configuration.
+
+        Returns:
+            [`SiglipConfig`]: An instance of a configuration object
+        """
+
+        return cls(text_config=text_config.to_dict(), vision_config=vision_config.to_dict(), **kwargs)

evalkit_internvl/lib/python3.10/site-packages/transformers/models/siglip/image_processing_siglip.py

@@ -0,0 +1,225 @@
+# coding=utf-8
+# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Image processor class for SigLIP."""
+
+from typing import Dict, List, Optional, Union
+
+from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
+from ...image_transforms import (
+    resize,
+    to_channel_dimension_format,
+)
+from ...image_utils import (
+    IMAGENET_STANDARD_MEAN,
+    IMAGENET_STANDARD_STD,
+    ChannelDimension,
+    ImageInput,
+    PILImageResampling,
+    infer_channel_dimension_format,
+    is_scaled_image,
+    make_list_of_images,
+    to_numpy_array,
+    valid_images,
+)
+from ...utils import TensorType, is_vision_available, logging
+
+
+logger = logging.get_logger(__name__)
+
+
+if is_vision_available():
+    import PIL
+
+
+class SiglipImageProcessor(BaseImageProcessor):
+    r"""
+    Constructs a SigLIP image processor.
+
+    Args:
+        do_resize (`bool`, *optional*, defaults to `True`):
+            Whether to resize the image's (height, width) dimensions to the specified `size`. Can be overridden by
+            `do_resize` in the `preprocess` method.
+        size (`Dict[str, int]` *optional*, defaults to `{"height": 224, "width": 224}`):
+            Size of the image after resizing. Can be overridden by `size` in the `preprocess` method.
+        resample (`PILImageResampling`, *optional*, defaults to `Resampling.BICUBIC`):
+            Resampling filter to use if resizing the image. Can be overridden by `resample` in the `preprocess` method.
+        do_rescale (`bool`, *optional*, defaults to `True`):
+            Whether to rescale the image by the specified scale `rescale_factor`. Can be overridden by `do_rescale` in
+            the `preprocess` method.
+        rescale_factor (`int` or `float`, *optional*, defaults to `1/255`):
+            Scale factor to use if rescaling the image. Can be overridden by `rescale_factor` in the `preprocess`
+            method.
+        do_normalize (`bool`, *optional*, defaults to `True`):
+            Whether to normalize the image by the specified mean and standard deviation. Can be overridden by
+            `do_normalize` in the `preprocess` method.
+        image_mean (`float` or `List[float]`, *optional*, defaults to `[0.5, 0.5, 0.5]`):
+            Mean to use if normalizing the image. This is a float or list of floats the length of the number of
+            channels in the image. Can be overridden by the `image_mean` parameter in the `preprocess` method.
+        image_std (`float` or `List[float]`, *optional*, defaults to `[0.5, 0.5, 0.5]`):
+            Standard deviation to use if normalizing the image. This is a float or list of floats the length of the
+            number of channels in the image. Can be overridden by the `image_std` parameter in the `preprocess` method.
+            Can be overridden by the `image_std` parameter in the `preprocess` method.
+    """
+
+    model_input_names = ["pixel_values"]
+
+    def __init__(
+        self,
+        do_resize: bool = True,
+        size: Dict[str, int] = None,
+        resample: PILImageResampling = PILImageResampling.BICUBIC,
+        do_rescale: bool = True,
+        rescale_factor: Union[int, float] = 1 / 255,
+        do_normalize: bool = True,
+        image_mean: Optional[Union[float, List[float]]] = None,
+        image_std: Optional[Union[float, List[float]]] = None,
+        **kwargs,
+    ) -> None:
+        super().__init__(**kwargs)
+        size = size if size is not None else {"height": 224, "width": 224}
+        image_mean = image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
+        image_std = image_std if image_std is not None else IMAGENET_STANDARD_STD
+
+        self.do_resize = do_resize
+        self.size = size
+        self.resample = resample
+        self.do_rescale = do_rescale
+        self.rescale_factor = rescale_factor
+        self.do_normalize = do_normalize
+        self.image_mean = image_mean
+        self.image_std = image_std
+
+    def preprocess(
+        self,
+        images: ImageInput,
+        do_resize: bool = None,
+        size: Dict[str, int] = None,
+        resample: PILImageResampling = None,
+        do_rescale: bool = None,
+        rescale_factor: float = None,
+        do_normalize: bool = None,
+        image_mean: Optional[Union[float, List[float]]] = None,
+        image_std: Optional[Union[float, List[float]]] = None,
+        return_tensors: Optional[Union[str, TensorType]] = None,
+        data_format: Optional[ChannelDimension] = ChannelDimension.FIRST,
+        input_data_format: Optional[Union[str, ChannelDimension]] = None,
+        **kwargs,
+    ) -> PIL.Image.Image:
+        """
+        Preprocess an image or batch of images.
+
+        Args:
+            images (`ImageInput`):
+                Image to preprocess. Expects a single or batch of images with pixel values ranging from 0 to 255. If
+                passing in images with pixel values between 0 and 1, set `do_rescale=False`.
+            do_resize (`bool`, *optional*, defaults to `self.do_resize`):
+                Whether to resize the image.
+            size (`Dict[str, int]`, *optional*, defaults to `self.size`):
+                Size of the image after resizing.
+            resample (`int`, *optional*, defaults to `self.resample`):
+                Resampling filter to use if resizing the image. This can be one of the enum `PILImageResampling`. Only
+                has an effect if `do_resize` is set to `True`.
+            do_rescale (`bool`, *optional*, defaults to `self.do_rescale`):
+                Whether to rescale the image.
+            rescale_factor (`float`, *optional*, defaults to `self.rescale_factor`):
+                Rescale factor to rescale the image by if `do_rescale` is set to `True`.
+            do_normalize (`bool`, *optional*, defaults to `self.do_normalize`):
+                Whether to normalize the image.
+            image_mean (`float` or `List[float]`, *optional*, defaults to `self.image_mean`):
+                Image mean to use for normalization. Only has an effect if `do_normalize` is set to `True`.
+            image_std (`float` or `List[float]`, *optional*, defaults to `self.image_std`):
+                Image standard deviation to use for normalization. Only has an effect if `do_normalize` is set to
+                `True`.
+            return_tensors (`str` or `TensorType`, *optional*):
+                The type of tensors to return. Can be one of:
+                - Unset: Return a list of `np.ndarray`.
+                - `TensorType.TENSORFLOW` or `'tf'`: Return a batch of type `tf.Tensor`.
+                - `TensorType.PYTORCH` or `'pt'`: Return a batch of type `torch.Tensor`.
+                - `TensorType.NUMPY` or `'np'`: Return a batch of type `np.ndarray`.
+                - `TensorType.JAX` or `'jax'`: Return a batch of type `jax.numpy.ndarray`.
+            data_format (`ChannelDimension` or `str`, *optional*, defaults to `ChannelDimension.FIRST`):
+                The channel dimension format for the output image. Can be one of:
+                - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format.
+                - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format.
+                - Unset: Use the channel dimension format of the input image.
+            input_data_format (`ChannelDimension` or `str`, *optional*):
+                The channel dimension format for the input image. If unset, the channel dimension format is inferred
+                from the input image. Can be one of:
+                - `"channels_first"` or `ChannelDimension.FIRST`: image in (num_channels, height, width) format.
+                - `"channels_last"` or `ChannelDimension.LAST`: image in (height, width, num_channels) format.
+                - `"none"` or `ChannelDimension.NONE`: image in (height, width) format.
+        """
+        do_resize = do_resize if do_resize is not None else self.do_resize
+        size = size if size is not None else self.size
+        size = get_size_dict(size, param_name="size", default_to_square=False)
+        resample = resample if resample is not None else self.resample
+        do_rescale = do_rescale if do_rescale is not None else self.do_rescale
+        rescale_factor = rescale_factor if rescale_factor is not None else self.rescale_factor
+        do_normalize = do_normalize if do_normalize is not None else self.do_normalize
+        image_mean = image_mean if image_mean is not None else self.image_mean
+        image_std = image_std if image_std is not None else self.image_std
+
+        images = make_list_of_images(images)
+
+        if not valid_images(images):
+            raise ValueError(
+                "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
+                "torch.Tensor, tf.Tensor or jax.ndarray."
+            )
+
+        if do_resize and size is None:
+            raise ValueError("Size must be specified if do_resize is True.")
+
+        if do_rescale and rescale_factor is None:
+            raise ValueError("Rescale factor must be specified if do_rescale is True.")
+
+        # All transformations expect numpy arrays.
+        images = [to_numpy_array(image) for image in images]
+
+        if is_scaled_image(images[0]) and do_rescale:
+            logger.warning_once(
+                "It looks like you are trying to rescale already rescaled images. If the input"
+                " images have pixel values between 0 and 1, set `do_rescale=False` to avoid rescaling them again."
+            )
+
+        if input_data_format is None:
+            # We assume that all images have the same channel dimension format.
+            input_data_format = infer_channel_dimension_format(images[0])
+
+        if do_resize:
+            height, width = size["height"], size["width"]
+            images = [
+                resize(image=image, size=(height, width), resample=resample, input_data_format=input_data_format)
+                for image in images
+            ]
+
+        if do_rescale:
+            images = [
+                self.rescale(image=image, scale=rescale_factor, input_data_format=input_data_format)
+                for image in images
+            ]
+
+        if do_normalize:
+            images = [
+                self.normalize(image=image, mean=image_mean, std=image_std, input_data_format=input_data_format)
+                for image in images
+            ]
+
+        images = [
+            to_channel_dimension_format(image, data_format, input_channel_dim=input_data_format) for image in images
+        ]
+
+        data = {"pixel_values": images}
+        return BatchFeature(data=data, tensor_type=return_tensors)

evalkit_tf437/lib/python3.10/site-packages/fastapi/__init__.py

@@ -0,0 +1,25 @@
+"""FastAPI framework, high performance, easy to learn, fast to code, ready for production"""
+
+__version__ = "0.103.2"
+
+from starlette import status as status
+
+from .applications import FastAPI as FastAPI
+from .background import BackgroundTasks as BackgroundTasks
+from .datastructures import UploadFile as UploadFile
+from .exceptions import HTTPException as HTTPException
+from .exceptions import WebSocketException as WebSocketException
+from .param_functions import Body as Body
+from .param_functions import Cookie as Cookie
+from .param_functions import Depends as Depends
+from .param_functions import File as File
+from .param_functions import Form as Form
+from .param_functions import Header as Header
+from .param_functions import Path as Path
+from .param_functions import Query as Query
+from .param_functions import Security as Security
+from .requests import Request as Request
+from .responses import Response as Response
+from .routing import APIRouter as APIRouter
+from .websockets import WebSocket as WebSocket
+from .websockets import WebSocketDisconnect as WebSocketDisconnect

evalkit_tf437/lib/python3.10/site-packages/fastapi/applications.py

@@ -0,0 +1,945 @@
+from enum import Enum
+from typing import (
+    Any,
+    Awaitable,
+    Callable,
+    Coroutine,
+    Dict,
+    List,
+    Optional,
+    Sequence,
+    Type,
+    TypeVar,
+    Union,
+)
+
+from fastapi import routing
+from fastapi.datastructures import Default, DefaultPlaceholder
+from fastapi.exception_handlers import (
+    http_exception_handler,
+    request_validation_exception_handler,
+    websocket_request_validation_exception_handler,
+)
+from fastapi.exceptions import RequestValidationError, WebSocketRequestValidationError
+from fastapi.logger import logger
+from fastapi.middleware.asyncexitstack import AsyncExitStackMiddleware
+from fastapi.openapi.docs import (
+    get_redoc_html,
+    get_swagger_ui_html,
+    get_swagger_ui_oauth2_redirect_html,
+)
+from fastapi.openapi.utils import get_openapi
+from fastapi.params import Depends
+from fastapi.types import DecoratedCallable, IncEx
+from fastapi.utils import generate_unique_id
+from starlette.applications import Starlette
+from starlette.datastructures import State
+from starlette.exceptions import HTTPException
+from starlette.middleware import Middleware
+from starlette.middleware.base import BaseHTTPMiddleware
+from starlette.middleware.errors import ServerErrorMiddleware
+from starlette.middleware.exceptions import ExceptionMiddleware
+from starlette.requests import Request
+from starlette.responses import HTMLResponse, JSONResponse, Response
+from starlette.routing import BaseRoute
+from starlette.types import ASGIApp, Lifespan, Receive, Scope, Send
+
+AppType = TypeVar("AppType", bound="FastAPI")
+
+
+class FastAPI(Starlette):
+    def __init__(
+        self: AppType,
+        *,
+        debug: bool = False,
+        routes: Optional[List[BaseRoute]] = None,
+        title: str = "FastAPI",
+        summary: Optional[str] = None,
+        description: str = "",
+        version: str = "0.1.0",
+        openapi_url: Optional[str] = "/openapi.json",
+        openapi_tags: Optional[List[Dict[str, Any]]] = None,
+        servers: Optional[List[Dict[str, Union[str, Any]]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        default_response_class: Type[Response] = Default(JSONResponse),
+        redirect_slashes: bool = True,
+        docs_url: Optional[str] = "/docs",
+        redoc_url: Optional[str] = "/redoc",
+        swagger_ui_oauth2_redirect_url: Optional[str] = "/docs/oauth2-redirect",
+        swagger_ui_init_oauth: Optional[Dict[str, Any]] = None,
+        middleware: Optional[Sequence[Middleware]] = None,
+        exception_handlers: Optional[
+            Dict[
+                Union[int, Type[Exception]],
+                Callable[[Request, Any], Coroutine[Any, Any, Response]],
+            ]
+        ] = None,
+        on_startup: Optional[Sequence[Callable[[], Any]]] = None,
+        on_shutdown: Optional[Sequence[Callable[[], Any]]] = None,
+        lifespan: Optional[Lifespan[AppType]] = None,
+        terms_of_service: Optional[str] = None,
+        contact: Optional[Dict[str, Union[str, Any]]] = None,
+        license_info: Optional[Dict[str, Union[str, Any]]] = None,
+        openapi_prefix: str = "",
+        root_path: str = "",
+        root_path_in_servers: bool = True,
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        webhooks: Optional[routing.APIRouter] = None,
+        deprecated: Optional[bool] = None,
+        include_in_schema: bool = True,
+        swagger_ui_parameters: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+        separate_input_output_schemas: bool = True,
+        **extra: Any,
+    ) -> None:
+        self.debug = debug
+        self.title = title
+        self.summary = summary
+        self.description = description
+        self.version = version
+        self.terms_of_service = terms_of_service
+        self.contact = contact
+        self.license_info = license_info
+        self.openapi_url = openapi_url
+        self.openapi_tags = openapi_tags
+        self.root_path_in_servers = root_path_in_servers
+        self.docs_url = docs_url
+        self.redoc_url = redoc_url
+        self.swagger_ui_oauth2_redirect_url = swagger_ui_oauth2_redirect_url
+        self.swagger_ui_init_oauth = swagger_ui_init_oauth
+        self.swagger_ui_parameters = swagger_ui_parameters
+        self.servers = servers or []
+        self.separate_input_output_schemas = separate_input_output_schemas
+        self.extra = extra
+        self.openapi_version = "3.1.0"
+        self.openapi_schema: Optional[Dict[str, Any]] = None
+        if self.openapi_url:
+            assert self.title, "A title must be provided for OpenAPI, e.g.: 'My API'"
+            assert self.version, "A version must be provided for OpenAPI, e.g.: '2.1.0'"
+        # TODO: remove when discarding the openapi_prefix parameter
+        if openapi_prefix:
+            logger.warning(
+                '"openapi_prefix" has been deprecated in favor of "root_path", which '
+                "follows more closely the ASGI standard, is simpler, and more "
+                "automatic. Check the docs at "
+                "https://fastapi.tiangolo.com/advanced/sub-applications/"
+            )
+        self.webhooks = webhooks or routing.APIRouter()
+        self.root_path = root_path or openapi_prefix
+        self.state: State = State()
+        self.dependency_overrides: Dict[Callable[..., Any], Callable[..., Any]] = {}
+        self.router: routing.APIRouter = routing.APIRouter(
+            routes=routes,
+            redirect_slashes=redirect_slashes,
+            dependency_overrides_provider=self,
+            on_startup=on_startup,
+            on_shutdown=on_shutdown,
+            lifespan=lifespan,
+            default_response_class=default_response_class,
+            dependencies=dependencies,
+            callbacks=callbacks,
+            deprecated=deprecated,
+            include_in_schema=include_in_schema,
+            responses=responses,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+        self.exception_handlers: Dict[
+            Any, Callable[[Request, Any], Union[Response, Awaitable[Response]]]
+        ] = ({} if exception_handlers is None else dict(exception_handlers))
+        self.exception_handlers.setdefault(HTTPException, http_exception_handler)
+        self.exception_handlers.setdefault(
+            RequestValidationError, request_validation_exception_handler
+        )
+        self.exception_handlers.setdefault(
+            WebSocketRequestValidationError,
+            # Starlette still has incorrect type specification for the handlers
+            websocket_request_validation_exception_handler,  # type: ignore
+        )
+
+        self.user_middleware: List[Middleware] = (
+            [] if middleware is None else list(middleware)
+        )
+        self.middleware_stack: Union[ASGIApp, None] = None
+        self.setup()
+
+    def build_middleware_stack(self) -> ASGIApp:
+        # Duplicate/override from Starlette to add AsyncExitStackMiddleware
+        # inside of ExceptionMiddleware, inside of custom user middlewares
+        debug = self.debug
+        error_handler = None
+        exception_handlers = {}
+
+        for key, value in self.exception_handlers.items():
+            if key in (500, Exception):
+                error_handler = value
+            else:
+                exception_handlers[key] = value
+
+        middleware = (
+            [Middleware(ServerErrorMiddleware, handler=error_handler, debug=debug)]
+            + self.user_middleware
+            + [
+                Middleware(
+                    ExceptionMiddleware, handlers=exception_handlers, debug=debug
+                ),
+                # Add FastAPI-specific AsyncExitStackMiddleware for dependencies with
+                # contextvars.
+                # This needs to happen after user middlewares because those create a
+                # new contextvars context copy by using a new AnyIO task group.
+                # The initial part of dependencies with 'yield' is executed in the
+                # FastAPI code, inside all the middlewares. However, the teardown part
+                # (after 'yield') is executed in the AsyncExitStack in this middleware.
+                # If the AsyncExitStack lived outside of the custom middlewares and
+                # contextvars were set in a dependency with 'yield' in that internal
+                # contextvars context, the values would not be available in the
+                # outer context of the AsyncExitStack.
+                # By placing the middleware and the AsyncExitStack here, inside all
+                # user middlewares, the code before and after 'yield' in dependencies
+                # with 'yield' is executed in the same contextvars context. Thus, all values
+                # set in contextvars before 'yield' are still available after 'yield,' as
+                # expected.
+                # Additionally, by having this AsyncExitStack here, after the
+                # ExceptionMiddleware, dependencies can now catch handled exceptions,
+                # e.g. HTTPException, to customize the teardown code (e.g. DB session
+                # rollback).
+                Middleware(AsyncExitStackMiddleware),
+            ]
+        )
+
+        app = self.router
+        for cls, options in reversed(middleware):
+            app = cls(app=app, **options)
+        return app
+
+    def openapi(self) -> Dict[str, Any]:
+        if not self.openapi_schema:
+            self.openapi_schema = get_openapi(
+                title=self.title,
+                version=self.version,
+                openapi_version=self.openapi_version,
+                summary=self.summary,
+                description=self.description,
+                terms_of_service=self.terms_of_service,
+                contact=self.contact,
+                license_info=self.license_info,
+                routes=self.routes,
+                webhooks=self.webhooks.routes,
+                tags=self.openapi_tags,
+                servers=self.servers,
+                separate_input_output_schemas=self.separate_input_output_schemas,
+            )
+        return self.openapi_schema
+
+    def setup(self) -> None:
+        if self.openapi_url:
+            urls = (server_data.get("url") for server_data in self.servers)
+            server_urls = {url for url in urls if url}
+
+            async def openapi(req: Request) -> JSONResponse:
+                root_path = req.scope.get("root_path", "").rstrip("/")
+                if root_path not in server_urls:
+                    if root_path and self.root_path_in_servers:
+                        self.servers.insert(0, {"url": root_path})
+                        server_urls.add(root_path)
+                return JSONResponse(self.openapi())
+
+            self.add_route(self.openapi_url, openapi, include_in_schema=False)
+        if self.openapi_url and self.docs_url:
+
+            async def swagger_ui_html(req: Request) -> HTMLResponse:
+                root_path = req.scope.get("root_path", "").rstrip("/")
+                openapi_url = root_path + self.openapi_url
+                oauth2_redirect_url = self.swagger_ui_oauth2_redirect_url
+                if oauth2_redirect_url:
+                    oauth2_redirect_url = root_path + oauth2_redirect_url
+                return get_swagger_ui_html(
+                    openapi_url=openapi_url,
+                    title=self.title + " - Swagger UI",
+                    oauth2_redirect_url=oauth2_redirect_url,
+                    init_oauth=self.swagger_ui_init_oauth,
+                    swagger_ui_parameters=self.swagger_ui_parameters,
+                )
+
+            self.add_route(self.docs_url, swagger_ui_html, include_in_schema=False)
+
+            if self.swagger_ui_oauth2_redirect_url:
+
+                async def swagger_ui_redirect(req: Request) -> HTMLResponse:
+                    return get_swagger_ui_oauth2_redirect_html()
+
+                self.add_route(
+                    self.swagger_ui_oauth2_redirect_url,
+                    swagger_ui_redirect,
+                    include_in_schema=False,
+                )
+        if self.openapi_url and self.redoc_url:
+
+            async def redoc_html(req: Request) -> HTMLResponse:
+                root_path = req.scope.get("root_path", "").rstrip("/")
+                openapi_url = root_path + self.openapi_url
+                return get_redoc_html(
+                    openapi_url=openapi_url, title=self.title + " - ReDoc"
+                )
+
+            self.add_route(self.redoc_url, redoc_html, include_in_schema=False)
+
+    async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
+        if self.root_path:
+            scope["root_path"] = self.root_path
+        await super().__call__(scope, receive, send)
+
+    def add_api_route(
+        self,
+        path: str,
+        endpoint: Callable[..., Coroutine[Any, Any, Response]],
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        methods: Optional[List[str]] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Union[Type[Response], DefaultPlaceholder] = Default(
+            JSONResponse
+        ),
+        name: Optional[str] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> None:
+        self.router.add_api_route(
+            path,
+            endpoint=endpoint,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            methods=methods,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def api_route(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        methods: Optional[List[str]] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        def decorator(func: DecoratedCallable) -> DecoratedCallable:
+            self.router.add_api_route(
+                path,
+                func,
+                response_model=response_model,
+                status_code=status_code,
+                tags=tags,
+                dependencies=dependencies,
+                summary=summary,
+                description=description,
+                response_description=response_description,
+                responses=responses,
+                deprecated=deprecated,
+                methods=methods,
+                operation_id=operation_id,
+                response_model_include=response_model_include,
+                response_model_exclude=response_model_exclude,
+                response_model_by_alias=response_model_by_alias,
+                response_model_exclude_unset=response_model_exclude_unset,
+                response_model_exclude_defaults=response_model_exclude_defaults,
+                response_model_exclude_none=response_model_exclude_none,
+                include_in_schema=include_in_schema,
+                response_class=response_class,
+                name=name,
+                openapi_extra=openapi_extra,
+                generate_unique_id_function=generate_unique_id_function,
+            )
+            return func
+
+        return decorator
+
+    def add_api_websocket_route(
+        self,
+        path: str,
+        endpoint: Callable[..., Any],
+        name: Optional[str] = None,
+        *,
+        dependencies: Optional[Sequence[Depends]] = None,
+    ) -> None:
+        self.router.add_api_websocket_route(
+            path,
+            endpoint,
+            name=name,
+            dependencies=dependencies,
+        )
+
+    def websocket(
+        self,
+        path: str,
+        name: Optional[str] = None,
+        *,
+        dependencies: Optional[Sequence[Depends]] = None,
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        def decorator(func: DecoratedCallable) -> DecoratedCallable:
+            self.add_api_websocket_route(
+                path,
+                func,
+                name=name,
+                dependencies=dependencies,
+            )
+            return func
+
+        return decorator
+
+    def include_router(
+        self,
+        router: routing.APIRouter,
+        *,
+        prefix: str = "",
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        include_in_schema: bool = True,
+        default_response_class: Type[Response] = Default(JSONResponse),
+        callbacks: Optional[List[BaseRoute]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> None:
+        self.router.include_router(
+            router,
+            prefix=prefix,
+            tags=tags,
+            dependencies=dependencies,
+            responses=responses,
+            deprecated=deprecated,
+            include_in_schema=include_in_schema,
+            default_response_class=default_response_class,
+            callbacks=callbacks,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def get(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.get(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def put(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.put(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def post(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.post(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def delete(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.delete(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def options(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.options(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def head(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.head(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def patch(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.patch(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def trace(
+        self,
+        path: str,
+        *,
+        response_model: Any = Default(None),
+        status_code: Optional[int] = None,
+        tags: Optional[List[Union[str, Enum]]] = None,
+        dependencies: Optional[Sequence[Depends]] = None,
+        summary: Optional[str] = None,
+        description: Optional[str] = None,
+        response_description: str = "Successful Response",
+        responses: Optional[Dict[Union[int, str], Dict[str, Any]]] = None,
+        deprecated: Optional[bool] = None,
+        operation_id: Optional[str] = None,
+        response_model_include: Optional[IncEx] = None,
+        response_model_exclude: Optional[IncEx] = None,
+        response_model_by_alias: bool = True,
+        response_model_exclude_unset: bool = False,
+        response_model_exclude_defaults: bool = False,
+        response_model_exclude_none: bool = False,
+        include_in_schema: bool = True,
+        response_class: Type[Response] = Default(JSONResponse),
+        name: Optional[str] = None,
+        callbacks: Optional[List[BaseRoute]] = None,
+        openapi_extra: Optional[Dict[str, Any]] = None,
+        generate_unique_id_function: Callable[[routing.APIRoute], str] = Default(
+            generate_unique_id
+        ),
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.trace(
+            path,
+            response_model=response_model,
+            status_code=status_code,
+            tags=tags,
+            dependencies=dependencies,
+            summary=summary,
+            description=description,
+            response_description=response_description,
+            responses=responses,
+            deprecated=deprecated,
+            operation_id=operation_id,
+            response_model_include=response_model_include,
+            response_model_exclude=response_model_exclude,
+            response_model_by_alias=response_model_by_alias,
+            response_model_exclude_unset=response_model_exclude_unset,
+            response_model_exclude_defaults=response_model_exclude_defaults,
+            response_model_exclude_none=response_model_exclude_none,
+            include_in_schema=include_in_schema,
+            response_class=response_class,
+            name=name,
+            callbacks=callbacks,
+            openapi_extra=openapi_extra,
+            generate_unique_id_function=generate_unique_id_function,
+        )
+
+    def websocket_route(
+        self, path: str, name: Union[str, None] = None
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        def decorator(func: DecoratedCallable) -> DecoratedCallable:
+            self.router.add_websocket_route(path, func, name=name)
+            return func
+
+        return decorator
+
+    def on_event(
+        self, event_type: str
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        return self.router.on_event(event_type)
+
+    def middleware(
+        self, middleware_type: str
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        def decorator(func: DecoratedCallable) -> DecoratedCallable:
+            self.add_middleware(BaseHTTPMiddleware, dispatch=func)
+            return func
+
+        return decorator
+
+    def exception_handler(
+        self, exc_class_or_status_code: Union[int, Type[Exception]]
+    ) -> Callable[[DecoratedCallable], DecoratedCallable]:
+        def decorator(func: DecoratedCallable) -> DecoratedCallable:
+            self.add_exception_handler(exc_class_or_status_code, func)
+            return func
+
+        return decorator

evalkit_tf437/lib/python3.10/site-packages/fastapi/concurrency.py

@@ -0,0 +1,40 @@
+from contextlib import AsyncExitStack as AsyncExitStack  # noqa
+from contextlib import asynccontextmanager as asynccontextmanager
+from typing import AsyncGenerator, ContextManager, TypeVar
+
+import anyio
+from anyio import CapacityLimiter
+from starlette.concurrency import iterate_in_threadpool as iterate_in_threadpool  # noqa
+from starlette.concurrency import run_in_threadpool as run_in_threadpool  # noqa
+from starlette.concurrency import (  # noqa
+    run_until_first_complete as run_until_first_complete,
+)
+
+_T = TypeVar("_T")
+
+
+@asynccontextmanager
+async def contextmanager_in_threadpool(
+    cm: ContextManager[_T],
+) -> AsyncGenerator[_T, None]:
+    # blocking __exit__ from running waiting on a free thread
+    # can create race conditions/deadlocks if the context manager itself
+    # has its own internal pool (e.g. a database connection pool)
+    # to avoid this we let __exit__ run without a capacity limit
+    # since we're creating a new limiter for each call, any non-zero limit
+    # works (1 is arbitrary)
+    exit_limiter = CapacityLimiter(1)
+    try:
+        yield await run_in_threadpool(cm.__enter__)
+    except Exception as e:
+        ok = bool(
+            await anyio.to_thread.run_sync(
+                cm.__exit__, type(e), e, None, limiter=exit_limiter
+            )
+        )
+        if not ok:
+            raise e
+    else:
+        await anyio.to_thread.run_sync(
+            cm.__exit__, None, None, None, limiter=exit_limiter
+        )

evalkit_tf437/lib/python3.10/site-packages/fastapi/datastructures.py

@@ -0,0 +1,83 @@
+from typing import Any, Callable, Dict, Iterable, Type, TypeVar, cast
+
+from fastapi._compat import (
+    PYDANTIC_V2,
+    CoreSchema,
+    GetJsonSchemaHandler,
+    JsonSchemaValue,
+    with_info_plain_validator_function,
+)
+from starlette.datastructures import URL as URL  # noqa: F401
+from starlette.datastructures import Address as Address  # noqa: F401
+from starlette.datastructures import FormData as FormData  # noqa: F401
+from starlette.datastructures import Headers as Headers  # noqa: F401
+from starlette.datastructures import QueryParams as QueryParams  # noqa: F401
+from starlette.datastructures import State as State  # noqa: F401
+from starlette.datastructures import UploadFile as StarletteUploadFile
+
+
+class UploadFile(StarletteUploadFile):
+    @classmethod
+    def __get_validators__(cls: Type["UploadFile"]) -> Iterable[Callable[..., Any]]:
+        yield cls.validate
+
+    @classmethod
+    def validate(cls: Type["UploadFile"], v: Any) -> Any:
+        if not isinstance(v, StarletteUploadFile):
+            raise ValueError(f"Expected UploadFile, received: {type(v)}")
+        return v
+
+    @classmethod
+    def _validate(cls, __input_value: Any, _: Any) -> "UploadFile":
+        if not isinstance(__input_value, StarletteUploadFile):
+            raise ValueError(f"Expected UploadFile, received: {type(__input_value)}")
+        return cast(UploadFile, __input_value)
+
+    if not PYDANTIC_V2:
+
+        @classmethod
+        def __modify_schema__(cls, field_schema: Dict[str, Any]) -> None:
+            field_schema.update({"type": "string", "format": "binary"})
+
+    @classmethod
+    def __get_pydantic_json_schema__(
+        cls, core_schema: CoreSchema, handler: GetJsonSchemaHandler
+    ) -> JsonSchemaValue:
+        return {"type": "string", "format": "binary"}
+
+    @classmethod
+    def __get_pydantic_core_schema__(
+        cls, source: Type[Any], handler: Callable[[Any], CoreSchema]
+    ) -> CoreSchema:
+        return with_info_plain_validator_function(cls._validate)
+
+
+class DefaultPlaceholder:
+    """
+    You shouldn't use this class directly.
+
+    It's used internally to recognize when a default value has been overwritten, even
+    if the overridden default value was truthy.
+    """
+
+    def __init__(self, value: Any):
+        self.value = value
+
+    def __bool__(self) -> bool:
+        return bool(self.value)
+
+    def __eq__(self, o: object) -> bool:
+        return isinstance(o, DefaultPlaceholder) and o.value == self.value
+
+
+DefaultType = TypeVar("DefaultType")
+
+
+def Default(value: DefaultType) -> DefaultType:
+    """
+    You shouldn't use this function directly.
+
+    It's used internally to recognize when a default value has been overwritten, even
+    if the overridden default value was truthy.
+    """
+    return DefaultPlaceholder(value)  # type: ignore

evalkit_tf437/lib/python3.10/site-packages/fastapi/dependencies/models.py

@@ -0,0 +1,58 @@
+from typing import Any, Callable, List, Optional, Sequence
+
+from fastapi._compat import ModelField
+from fastapi.security.base import SecurityBase
+
+
+class SecurityRequirement:
+    def __init__(
+        self, security_scheme: SecurityBase, scopes: Optional[Sequence[str]] = None
+    ):
+        self.security_scheme = security_scheme
+        self.scopes = scopes
+
+
+class Dependant:
+    def __init__(
+        self,
+        *,
+        path_params: Optional[List[ModelField]] = None,
+        query_params: Optional[List[ModelField]] = None,
+        header_params: Optional[List[ModelField]] = None,
+        cookie_params: Optional[List[ModelField]] = None,
+        body_params: Optional[List[ModelField]] = None,
+        dependencies: Optional[List["Dependant"]] = None,
+        security_schemes: Optional[List[SecurityRequirement]] = None,
+        name: Optional[str] = None,
+        call: Optional[Callable[..., Any]] = None,
+        request_param_name: Optional[str] = None,
+        websocket_param_name: Optional[str] = None,
+        http_connection_param_name: Optional[str] = None,
+        response_param_name: Optional[str] = None,
+        background_tasks_param_name: Optional[str] = None,
+        security_scopes_param_name: Optional[str] = None,
+        security_scopes: Optional[List[str]] = None,
+        use_cache: bool = True,
+        path: Optional[str] = None,
+    ) -> None:
+        self.path_params = path_params or []
+        self.query_params = query_params or []
+        self.header_params = header_params or []
+        self.cookie_params = cookie_params or []
+        self.body_params = body_params or []
+        self.dependencies = dependencies or []
+        self.security_requirements = security_schemes or []
+        self.request_param_name = request_param_name
+        self.websocket_param_name = websocket_param_name
+        self.http_connection_param_name = http_connection_param_name
+        self.response_param_name = response_param_name
+        self.background_tasks_param_name = background_tasks_param_name
+        self.security_scopes = security_scopes
+        self.security_scopes_param_name = security_scopes_param_name
+        self.name = name
+        self.call = call
+        self.use_cache = use_cache
+        # Store the path to be able to re-generate a dependable from it in overrides
+        self.path = path
+        # Save the cache key at creation to optimize performance
+        self.cache_key = (self.call, tuple(sorted(set(self.security_scopes or []))))

evalkit_tf437/lib/python3.10/site-packages/fastapi/exceptions.py

@@ -0,0 +1,55 @@
+from typing import Any, Dict, Optional, Sequence, Type
+
+from pydantic import BaseModel, create_model
+from starlette.exceptions import HTTPException as StarletteHTTPException
+from starlette.exceptions import WebSocketException as WebSocketException  # noqa: F401
+
+
+class HTTPException(StarletteHTTPException):
+    def __init__(
+        self,
+        status_code: int,
+        detail: Any = None,
+        headers: Optional[Dict[str, str]] = None,
+    ) -> None:
+        super().__init__(status_code=status_code, detail=detail, headers=headers)
+
+
+RequestErrorModel: Type[BaseModel] = create_model("Request")
+WebSocketErrorModel: Type[BaseModel] = create_model("WebSocket")
+
+
+class FastAPIError(RuntimeError):
+    """
+    A generic, FastAPI-specific error.
+    """
+
+
+class ValidationException(Exception):
+    def __init__(self, errors: Sequence[Any]) -> None:
+        self._errors = errors
+
+    def errors(self) -> Sequence[Any]:
+        return self._errors
+
+
+class RequestValidationError(ValidationException):
+    def __init__(self, errors: Sequence[Any], *, body: Any = None) -> None:
+        super().__init__(errors)
+        self.body = body
+
+
+class WebSocketRequestValidationError(ValidationException):
+    pass
+
+
+class ResponseValidationError(ValidationException):
+    def __init__(self, errors: Sequence[Any], *, body: Any = None) -> None:
+        super().__init__(errors)
+        self.body = body
+
+    def __str__(self) -> str:
+        message = f"{len(self._errors)} validation errors:\n"
+        for err in self._errors:
+            message += f"  {err}\n"
+        return message

evalkit_tf437/lib/python3.10/site-packages/fastapi/logger.py

@@ -0,0 +1,3 @@
+import logging
+
+logger = logging.getLogger("fastapi")

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/__init__.py

@@ -0,0 +1 @@
+from starlette.middleware import Middleware as Middleware

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/asyncexitstack.py

@@ -0,0 +1,25 @@
+from typing import Optional
+
+from fastapi.concurrency import AsyncExitStack
+from starlette.types import ASGIApp, Receive, Scope, Send
+
+
+class AsyncExitStackMiddleware:
+    def __init__(self, app: ASGIApp, context_name: str = "fastapi_astack") -> None:
+        self.app = app
+        self.context_name = context_name
+
+    async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
+        dependency_exception: Optional[Exception] = None
+        async with AsyncExitStack() as stack:
+            scope[self.context_name] = stack
+            try:
+                await self.app(scope, receive, send)
+            except Exception as e:
+                dependency_exception = e
+                raise e
+        if dependency_exception:
+            # This exception was possibly handled by the dependency but it should
+            # still bubble up so that the ServerErrorMiddleware can return a 500
+            # or the ExceptionMiddleware can catch and handle any other exceptions
+            raise dependency_exception

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/cors.py

@@ -0,0 +1 @@
+from starlette.middleware.cors import CORSMiddleware as CORSMiddleware  # noqa

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/gzip.py

@@ -0,0 +1 @@
+from starlette.middleware.gzip import GZipMiddleware as GZipMiddleware  # noqa

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/httpsredirect.py

@@ -0,0 +1,3 @@
+from starlette.middleware.httpsredirect import (  # noqa
+    HTTPSRedirectMiddleware as HTTPSRedirectMiddleware,
+)

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/trustedhost.py

@@ -0,0 +1,3 @@
+from starlette.middleware.trustedhost import (  # noqa
+    TrustedHostMiddleware as TrustedHostMiddleware,
+)

evalkit_tf437/lib/python3.10/site-packages/fastapi/middleware/wsgi.py

@@ -0,0 +1 @@
+from starlette.middleware.wsgi import WSGIMiddleware as WSGIMiddleware  # noqa

evalkit_tf437/lib/python3.10/site-packages/fastapi/requests.py

@@ -0,0 +1,2 @@
+from starlette.requests import HTTPConnection as HTTPConnection  # noqa: F401
+from starlette.requests import Request as Request  # noqa: F401

evalkit_tf437/lib/python3.10/site-packages/fastapi/security/api_key.py

@@ -0,0 +1,98 @@
+from typing import Optional
+
+from fastapi.openapi.models import APIKey, APIKeyIn
+from fastapi.security.base import SecurityBase
+from starlette.exceptions import HTTPException
+from starlette.requests import Request
+from starlette.status import HTTP_403_FORBIDDEN
+
+
+class APIKeyBase(SecurityBase):
+    pass
+
+
+class APIKeyQuery(APIKeyBase):
+    def __init__(
+        self,
+        *,
+        name: str,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model: APIKey = APIKey(
+            **{"in": APIKeyIn.query},  # type: ignore[arg-type]
+            name=name,
+            description=description,
+        )
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(self, request: Request) -> Optional[str]:
+        api_key = request.query_params.get(self.model.name)
+        if not api_key:
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        return api_key
+
+
+class APIKeyHeader(APIKeyBase):
+    def __init__(
+        self,
+        *,
+        name: str,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model: APIKey = APIKey(
+            **{"in": APIKeyIn.header},  # type: ignore[arg-type]
+            name=name,
+            description=description,
+        )
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(self, request: Request) -> Optional[str]:
+        api_key = request.headers.get(self.model.name)
+        if not api_key:
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        return api_key
+
+
+class APIKeyCookie(APIKeyBase):
+    def __init__(
+        self,
+        *,
+        name: str,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model: APIKey = APIKey(
+            **{"in": APIKeyIn.cookie},  # type: ignore[arg-type]
+            name=name,
+            description=description,
+        )
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(self, request: Request) -> Optional[str]:
+        api_key = request.cookies.get(self.model.name)
+        if not api_key:
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        return api_key

evalkit_tf437/lib/python3.10/site-packages/fastapi/security/base.py

@@ -0,0 +1,6 @@
+from fastapi.openapi.models import SecurityBase as SecurityBaseModel
+
+
+class SecurityBase:
+    model: SecurityBaseModel
+    scheme_name: str

evalkit_tf437/lib/python3.10/site-packages/fastapi/security/http.py

@@ -0,0 +1,165 @@
+import binascii
+from base64 import b64decode
+from typing import Optional
+
+from fastapi.exceptions import HTTPException
+from fastapi.openapi.models import HTTPBase as HTTPBaseModel
+from fastapi.openapi.models import HTTPBearer as HTTPBearerModel
+from fastapi.security.base import SecurityBase
+from fastapi.security.utils import get_authorization_scheme_param
+from pydantic import BaseModel
+from starlette.requests import Request
+from starlette.status import HTTP_401_UNAUTHORIZED, HTTP_403_FORBIDDEN
+
+
+class HTTPBasicCredentials(BaseModel):
+    username: str
+    password: str
+
+
+class HTTPAuthorizationCredentials(BaseModel):
+    scheme: str
+    credentials: str
+
+
+class HTTPBase(SecurityBase):
+    def __init__(
+        self,
+        *,
+        scheme: str,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model = HTTPBaseModel(scheme=scheme, description=description)
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(
+        self, request: Request
+    ) -> Optional[HTTPAuthorizationCredentials]:
+        authorization = request.headers.get("Authorization")
+        scheme, credentials = get_authorization_scheme_param(authorization)
+        if not (authorization and scheme and credentials):
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        return HTTPAuthorizationCredentials(scheme=scheme, credentials=credentials)
+
+
+class HTTPBasic(HTTPBase):
+    def __init__(
+        self,
+        *,
+        scheme_name: Optional[str] = None,
+        realm: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model = HTTPBaseModel(scheme="basic", description=description)
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.realm = realm
+        self.auto_error = auto_error
+
+    async def __call__(  # type: ignore
+        self, request: Request
+    ) -> Optional[HTTPBasicCredentials]:
+        authorization = request.headers.get("Authorization")
+        scheme, param = get_authorization_scheme_param(authorization)
+        if self.realm:
+            unauthorized_headers = {"WWW-Authenticate": f'Basic realm="{self.realm}"'}
+        else:
+            unauthorized_headers = {"WWW-Authenticate": "Basic"}
+        if not authorization or scheme.lower() != "basic":
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_401_UNAUTHORIZED,
+                    detail="Not authenticated",
+                    headers=unauthorized_headers,
+                )
+            else:
+                return None
+        invalid_user_credentials_exc = HTTPException(
+            status_code=HTTP_401_UNAUTHORIZED,
+            detail="Invalid authentication credentials",
+            headers=unauthorized_headers,
+        )
+        try:
+            data = b64decode(param).decode("ascii")
+        except (ValueError, UnicodeDecodeError, binascii.Error):
+            raise invalid_user_credentials_exc
+        username, separator, password = data.partition(":")
+        if not separator:
+            raise invalid_user_credentials_exc
+        return HTTPBasicCredentials(username=username, password=password)
+
+
+class HTTPBearer(HTTPBase):
+    def __init__(
+        self,
+        *,
+        bearerFormat: Optional[str] = None,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model = HTTPBearerModel(bearerFormat=bearerFormat, description=description)
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(
+        self, request: Request
+    ) -> Optional[HTTPAuthorizationCredentials]:
+        authorization = request.headers.get("Authorization")
+        scheme, credentials = get_authorization_scheme_param(authorization)
+        if not (authorization and scheme and credentials):
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        if scheme.lower() != "bearer":
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN,
+                    detail="Invalid authentication credentials",
+                )
+            else:
+                return None
+        return HTTPAuthorizationCredentials(scheme=scheme, credentials=credentials)
+
+
+class HTTPDigest(HTTPBase):
+    def __init__(
+        self,
+        *,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model = HTTPBaseModel(scheme="digest", description=description)
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(
+        self, request: Request
+    ) -> Optional[HTTPAuthorizationCredentials]:
+        authorization = request.headers.get("Authorization")
+        scheme, credentials = get_authorization_scheme_param(authorization)
+        if not (authorization and scheme and credentials):
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        if scheme.lower() != "digest":
+            raise HTTPException(
+                status_code=HTTP_403_FORBIDDEN,
+                detail="Invalid authentication credentials",
+            )
+        return HTTPAuthorizationCredentials(scheme=scheme, credentials=credentials)

evalkit_tf437/lib/python3.10/site-packages/fastapi/security/open_id_connect_url.py

@@ -0,0 +1,34 @@
+from typing import Optional
+
+from fastapi.openapi.models import OpenIdConnect as OpenIdConnectModel
+from fastapi.security.base import SecurityBase
+from starlette.exceptions import HTTPException
+from starlette.requests import Request
+from starlette.status import HTTP_403_FORBIDDEN
+
+
+class OpenIdConnect(SecurityBase):
+    def __init__(
+        self,
+        *,
+        openIdConnectUrl: str,
+        scheme_name: Optional[str] = None,
+        description: Optional[str] = None,
+        auto_error: bool = True,
+    ):
+        self.model = OpenIdConnectModel(
+            openIdConnectUrl=openIdConnectUrl, description=description
+        )
+        self.scheme_name = scheme_name or self.__class__.__name__
+        self.auto_error = auto_error
+
+    async def __call__(self, request: Request) -> Optional[str]:
+        authorization = request.headers.get("Authorization")
+        if not authorization:
+            if self.auto_error:
+                raise HTTPException(
+                    status_code=HTTP_403_FORBIDDEN, detail="Not authenticated"
+                )
+            else:
+                return None
+        return authorization