initial commit

.gitignore

@@ -0,0 +1,58 @@
+# These are some examples of commonly ignored file patterns.
+# You should customize this list as applicable to your project.
+# Learn more about .gitignore:
+#     https://www.atlassian.com/git/tutorials/saving-changes/gitignore
+
+# Node artifact files
+node_modules/
+dist/
+
+# Compiled Java class files
+*.class
+
+# Compiled Python bytecode
+*.py[cod]
+
+# Log files
+*.log
+
+# Package files
+*.jar
+
+# Maven
+target/
+dist/
+
+# JetBrains IDE
+.idea/
+
+# Unit test reports
+TEST*.xml
+
+# Generated by MacOS
+.DS_Store
+
+# Generated by Windows
+Thumbs.db
+
+# Applications
+*.app
+*.exe
+*.war
+
+# Large media files
+*.mp4
+*.tiff
+*.avi
+*.flv
+*.mov
+*.wmv
+
+env/
+__pycache__/
+testcases/
+*.ipynb
+server.crt
+server.key
+server.csr
+sample_data.json

app.py

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+import json
+import gradio as gr
+from dotenv import load_dotenv
+from llm_api.exceptions import RefusalError
+# from llm_api.langchain_api import extract_info, follow_structure
+from llm_api.native_api import extract_info, follow_structure
+from openai import BadRequestError
+
+load_dotenv('.env', override=True)
+
+def extract_free_fn(gallery, provider, schema):
+    img_paths = [item[0] for item in gallery]
+    # write schema to file before calling extract_free_properties
+    try:
+        if schema is not None and isinstance(schema, str) and 'import' not in schema.replace("'import'", '').replace("'important'", ''):
+            with open('schema_free.py', 'r') as f:
+                default_schema = f.read()
+            import_part = default_schema.split('#####')[0]
+            print('Executing freestyle schema...')
+            full_schema = import_part + schema
+            with open('read_schema_free.py', 'w') as f:
+                f.write(full_schema)
+            exec(import_part + schema, globals())
+            print('Executed freestyle schema')
+        else:
+            print('SCHEMA ELSE')
+            raise Exception('Invalid schema')
+    except Exception as e:
+        print(e)
+        return 'Invalid schema! Please check the schema or Reload this page to restore default settings', {}, []
+
+    try:
+        free_attributes = extract_info(img_paths, provider, Garment)
+        free_attributes = free_attributes.model_dump_json()
+    except RefusalError as e:
+        return e.message, {}, []
+    except BadRequestError as e:
+        return e.message, {}, []
+
+    return f'OK - provider: {provider}', free_attributes, [1] * 100
+
+def follow_schema_fn(free_attributes, provider, probs, schema):
+    try:
+        if schema is not None and isinstance(schema, str) and 'import' not in schema.replace("'import'", '').replace("'important'", ''):
+            with open('schema_structured.py', 'r') as f:
+                default_schema = f.read()
+            import_part = default_schema.split('#####')[0]
+            print('executing structured schema\n')
+            full_schema = import_part + schema
+            with open('read_schema_structured.py', 'w') as f:
+                f.write(full_schema)
+            exec(full_schema, globals())
+            print('executed structured schema')
+        else:
+            print('SCHEMA ELSE')
+            raise Exception('Invalid schema')
+    except:
+        return 'Invalid schema! Please check the schema or Reload this page to restore default settings', {}
+
+    try:
+        schema_attributes = follow_structure(free_attributes, provider, Garment)
+        schema_attributes = schema_attributes.model_dump_json()
+    except RefusalError as e:
+        return e.message, {}
+    except BadRequestError as e:
+        return e.message, {}
+    
+    return f'OK - provider: {provider}', schema_attributes
+
+with gr.Blocks(title='Internal Demo for Attribution') as demo:
+    with gr.Row():
+        with gr.Column(scale=12):
+            gr.Markdown('''<div style="text-align: center; font-size: 24px;"><strong>Internal Demo for Attribution</strong></div>''')
+    with gr.Row():
+        with gr.Column(scale=4):
+            # gr.Markdown('''<div style="text-align: left; font-size: 18px;">Upload images of a garment and click Extract Freestyle</div>''')
+            gallery = gr.Gallery(label='Images', type='filepath')
+            probs_text = gr.Textbox(label='Probabilities', placeholder='Probabilities', visible=False)
+            provider = gr.Dropdown(label='Provider', choices=['openai', 'anthropic'], value='openai')
+            button_extract = gr.Button(value='Extract Freestyle')
+        with gr.Column(scale=4):
+            # gr.Markdown('''<div style="text-align: left; font-size: 18px;">Click Follow Schema to convert the freestyle output to predefined schema</div>''')
+            status_free_text = gr.Textbox(label='Request Status', placeholder='')
+            free_attributes = gr.JSON(label='Freestyle Attribute')
+            button_follow = gr.Button(value='Follow Schema')
+        with gr.Column(scale=4):
+            status_structured_text = gr.Textbox(label='Request Status', placeholder='')
+            schema_attributes = gr.JSON(label='Schema Attributes')
+    with gr.Row():
+        # free_schema = gr.Dataframe(row_count=(4, 'dynamic'), label='Freestyle Schema', col_count=(4, 'dynamic'), interactive=True)
+        # schema = gr.Dataframe(row_count=(4, 'dynamic'), label='Schema', col_count=(4, 'dynamic'), interactive=True)
+        with open('schema_free.py', 'r') as f:
+            schema_free_text = f.read()
+        schema_free_text = schema_free_text.split('#####')[1]
+        with open('schema_structured.py', 'r') as f:
+            schema_structured_text = f.read()
+        schema_structured_text = schema_structured_text.split('#####')[1]
+        free_schema = gr.TextArea(label='Freestyle Schema', placeholder='Freestyle Schema', visible=True, value=schema_free_text, interactive=True)
+        structured_schema = gr.TextArea(label='Structured Schema', placeholder='Schema', visible=True, value=schema_structured_text, interactive=True)
+    
+    button_extract.click(extract_free_fn, [gallery, provider, free_schema], [status_free_text, free_attributes, probs_text])
+    button_follow.click(follow_schema_fn, [free_attributes, provider, probs_text, structured_schema], [status_structured_text, schema_attributes])
+
+# demo.launch(server_name="0.0.0.0", server_port=7688, share=False, ssl_verify=True, ssl_certfile=None, ssl_keyfile=None, auth=None)
+# demo.launch(server_name="0.0.0.0", server_port=7860, share=False, ssl_verify=False, ssl_certfile="server.crt", ssl_keyfile="server.key", auth=None)
+demo.launch(server_name="0.0.0.0", server_port=7861)
+

llm_api/anthropic_api.py

@@ -0,0 +1,122 @@
+from anthropic import Anthropic
+from dotenv import load_dotenv
+from llm_api.utils import get_data_format, get_image_data
+from .constants import EXTRACT_INFO_HUMAN_MESSAGE, EXTRACT_INFO_SYSTEM_MESSAGE,FOLLOW_SCHEMA_HUMAN_MESSAGE, FOLLOW_SCHEMA_SYSTEM_MESSAGE
+
+load_dotenv(override=True)
+client = Anthropic()
+
+def extract_info(img_paths, schema):
+    print('Extracting info via Anthropic...')
+    tools = [
+        {
+            "name": "extract_garment_info",
+            "description": "Extracts key information from the image.",
+            "input_schema": schema.model_json_schema(),
+            "cache_control": {"type": "ephemeral"}
+        }
+    ]
+
+    image_messages = [
+        {
+            "type": "image",
+            "source": {
+                "type": "base64",
+                "media_type": f"image/{get_data_format(img_path)}",
+                "data": get_image_data(img_path)
+            } 
+        } for img_path in img_paths
+    ]
+
+    system_message = [
+        {
+            "type": "text", 
+            "text": EXTRACT_INFO_SYSTEM_MESSAGE
+        }
+    ]
+
+    text_messages = [{
+        "type": "text",
+        "text": EXTRACT_INFO_HUMAN_MESSAGE,
+    }]
+
+    messages=[
+        {
+            "role": "user",
+            "content": text_messages + image_messages
+        }
+    ]
+
+    response = client.messages.create(
+        model="claude-3-5-sonnet-20240620",
+        extra_headers={
+            "anthropic-beta": "prompt-caching-2024-07-31"
+        },
+        max_tokens=2048,
+        system=system_message,
+        tools=tools,
+        messages=messages
+    )
+
+    for content in response.content:
+        if content.type == 'tool_use':
+            # print(content.input)
+            # print(type(content.input))
+            print('Found tool_use!')
+            return schema.model_validate(content.input)
+    
+    print('ERROR: No tool_use found!')
+
+
+def follow_structure(json_info, schema):
+    print('Following structure via Anthropic...')
+    tools = [
+        {
+            "name": "extract_garment_info",
+            "description": FOLLOW_SCHEMA_HUMAN_MESSAGE,
+            "input_schema": schema.model_json_schema(),
+            "cache_control": {"type": "ephemeral"}
+        }
+    ]
+
+    print('DEBUG: human message**************************')
+    print(FOLLOW_SCHEMA_HUMAN_MESSAGE.format(json_info=json_info))
+    text_messages = [{
+        "type": "text",
+        "text": FOLLOW_SCHEMA_HUMAN_MESSAGE.format(json_info=json_info),
+    }]
+
+    system_message = [
+        {
+            "type": "text", 
+            "text": FOLLOW_SCHEMA_SYSTEM_MESSAGE
+        }
+    ]
+
+    messages=[
+        {
+            "role": "user",
+            "content": text_messages
+        }
+    ]
+
+    response = client.messages.create(
+        model="claude-3-5-sonnet-20240620",
+        extra_headers={
+            "anthropic-beta": "prompt-caching-2024-07-31"
+        },
+        max_tokens=2048,
+        system=system_message,
+        tools=tools,
+        messages=messages
+    )
+
+    for content in response.content:
+        if content.type == 'tool_use':
+            # print(content.input)
+            # print(type(content.input))
+            print('Found tool_use!***********************')
+            print(content.input)
+            return schema.model_validate(content.input['json_info'])
+    
+    print('ERROR: No tool_use found!')

llm_api/constants.py

@@ -0,0 +1,20 @@
+EXTRACT_INFO_HUMAN_MESSAGE = \
+"Output properties of the product in the image."
+
+EXTRACT_INFO_SYSTEM_MESSAGE = \
+"You are an expert at structured data extraction. You will be given an image of a product and should output the its properties into the given structure."
+
+FOLLOW_SCHEMA_HUMAN_MESSAGE = \
+"""Convert following attributes to structured schema. Keep all the keys and number of values. Only replace the values themselves. :
+
+{json_info}"""
+
+FOLLOW_SCHEMA_SYSTEM_MESSAGE = \
+"You are an expert at structured data extraction. You will be given an dictionary of attributes of a product and should output the its properties into the given structure."
+
+
+if __name__ == '__main__':
+    print('Run test cases...')
+    print(FOLLOW_SCHEMA_HUMAN_MESSAGE.format(json_info='{"color": "red"}'))
+    print(FOLLOW_SCHEMA_HUMAN_MESSAGE.format(json_info='{"color": "red", "size": "small"}'))
+    print(FOLLOW_SCHEMA_HUMAN_MESSAGE.format(json_info='{"color": "red", "size": "small", "material": "cotton"}'))

llm_api/exceptions.py

@@ -0,0 +1,5 @@
+class RefusalError(Exception):
+    """Exception raised when the model refuses to respond."""
+    def __init__(self, message="The model refused to respond to the given input."):
+        self.message = message
+        super().__init__(self.message)

llm_api/langchain_api.py

@@ -0,0 +1,101 @@
+from .utils import get_data_format, get_image_data
+from langchain_anthropic import ChatAnthropic
+from langchain_openai import ChatOpenAI
+from dotenv import load_dotenv
+from langchain_core.messages import HumanMessage, SystemMessage
+from schema_structured import Garment as StructuredGarment
+from schema_free import Garment as FreeGarment
+
+
+load_dotenv()
+
+
+anthropic_llm = ChatAnthropic(
+    model="claude-3-5-sonnet-20240620",
+    temperature=0,
+    max_tokens=1024,
+    timeout=None,
+    max_retries=2,
+    # other params...
+)
+
+openai_llm = ChatOpenAI(
+    model="gpt-4o",
+    temperature=0,
+    max_tokens=None,
+    timeout=None,
+    max_retries=2,
+    # api_key="...",  # if you prefer to pass api key in directly instaed of using env vars
+    # base_url="...",
+    # organization="...",
+    # other params...
+)
+
+
+def extract_info(image_paths, provider, schema):
+    if provider == 'anthropic':
+        llm = anthropic_llm
+    elif provider == 'openai':
+        llm = openai_llm
+    else:
+        raise ValueError('Invalid provider')
+
+    text_message = [{"type": "text", "text": "describe the product in the set of images"}]
+    image_message = [
+        {
+            "type": "image_url",
+            "image_url": {"url": f"data:image/{get_data_format(image_path)};base64,{get_image_data(image_path)}"},
+        }
+        for image_path in image_paths
+    ]
+    system_text= "You are a helpful assistant that describes the product in the set of images."
+    human_message = HumanMessage(content=text_message + image_message)
+    structured_llm = llm.with_structured_output(schema)
+    if provider == 'anthropic':
+        ai_msg = structured_llm.invoke([human_message], system=system_text)
+    elif provider == 'openai':
+        system_message = SystemMessage(content=system_text)
+        ai_msg = structured_llm.invoke([system_message, human_message]) # add system message later
+    
+    return ai_msg
+
+
+def follow_structure(json_info, provider, schema):
+    if provider == 'anthropic':
+        llm = anthropic_llm
+    elif provider == 'openai':
+        llm = openai_llm
+    else:
+        raise ValueError('Invalid provider')
+
+    text_message = [{"type": "text", "text": f"Convert following attributes to structured schema. Keep all the keys and number of values. Only replace the values themselves. :\n\n{json_info}"}]
+    system_text= "You are an expert at structured data extraction. You will be given an dictionary of attributes of a product and should output the its properties into the given structure."
+    human_message = HumanMessage(content=text_message)
+    structured_llm = llm.with_structured_output(schema)
+    if provider == 'anthropic':
+        ai_msg = structured_llm.invoke([human_message], system=system_text)
+    elif provider == 'openai':
+        system_message = SystemMessage(content=system_text)
+        ai_msg = structured_llm.invoke([system_message, human_message]) # add system message later
+    
+    return ai_msg
+
+
+if __name__ == '__main__':
+    print('Running tests...')
+    print("Test 1: Provider Anthropic, Schema Structure")
+    info = extract_info(['1.png', '2.png'], provider='anthropic', schema=StructuredGarment)
+    json_info = info.model_dump_json()
+    print(json_info)
+    print('Test 2: Provider OpenAI, Schema Structure')
+    info = extract_info(['1.png', '2.png'], provider='openai', schema=StructuredGarment)
+    json_info = info.model_dump_json()
+    print(json_info)
+    print('Test 3: Provider Anthropic, Schema Free')
+    info = extract_info(['1.png', '2.png'], provider='anthropic', schema=FreeGarment)
+    json_info = info.model_dump_json()
+    print(json_info)
+    print('Test 4: Provider OpenAI, Schema Free')
+    info = extract_info(['1.png', '2.png'], provider='openai', schema=FreeGarment)
+    json_info = info.model_dump_json()
+    print(json_info)

llm_api/native_api.py

@@ -0,0 +1,30 @@
+import base64
+from dotenv import load_dotenv
+from . import openai_api as openai_info_extractor
+from . import anthropic_api as anthropic_extractor
+
+def encode_image(image_path):
+  with open(image_path, "rb") as image_file:
+    return base64.b64encode(image_file.read()).decode('utf-8')
+
+
+def extract_info(image_paths, provider, schema):
+    if provider == 'anthropic':
+        extractor = anthropic_extractor
+    elif provider == 'openai':
+        extractor = openai_info_extractor
+    else:
+        raise ValueError('Invalid provider')
+    
+    return extractor.extract_info(image_paths, schema)
+
+
+def follow_structure(json_info, provider, schema):
+    if provider == 'anthropic':
+        extractor = anthropic_extractor
+    elif provider == 'openai':
+        extractor = openai_info_extractor
+    else:
+        raise ValueError('Invalid provider')
+    
+    return extractor.follow_structure(json_info, schema)

llm_api/openai_api.py

@@ -0,0 +1,94 @@
+import json
+from dotenv import load_dotenv
+from .utils import get_data_format, get_image_data
+from openai import OpenAI, BadRequestError
+from .exceptions import RefusalError
+from .constants import EXTRACT_INFO_HUMAN_MESSAGE, EXTRACT_INFO_SYSTEM_MESSAGE,FOLLOW_SCHEMA_HUMAN_MESSAGE, FOLLOW_SCHEMA_SYSTEM_MESSAGE
+
+load_dotenv(override=True)
+client = OpenAI()
+
+
+def extract_info(img_paths, schema):
+    print('Extracting info via OpenAI...')
+    text_content = [
+        {
+            "type": "text",
+            "text": EXTRACT_INFO_HUMAN_MESSAGE,
+        },
+    ]
+    image_content = [
+        {
+            "type": "image_url",
+            "image_url": {
+            "url": f"data:image/{get_image_data(img_path)};base64,{get_image_data(img_path)}",
+            },
+        }
+        for img_path in img_paths
+    ]
+    response = client.beta.chat.completions.parse(
+    model="gpt-4o-2024-08-06",
+        messages=[
+            {
+                "role": "system",
+                "content": EXTRACT_INFO_SYSTEM_MESSAGE,
+            },
+            {
+                "role": "user",
+                "content": text_content + image_content,
+            }
+        ],
+        max_tokens=1000,
+        response_format=schema,
+        logprobs=True,
+        top_logprobs=2,
+        temperature=0.0,
+        # top_p=.0000000000000000000001
+    )
+    if response.choices[0].message.refusal:
+        raise RefusalError('OpenAI refused to respond to the request')
+
+    content = response.choices[0].message.content
+    parsed_data = json.loads(content) 
+    model_data = schema.model_validate(parsed_data)
+
+    return model_data
+
+
+def follow_structure(json_info, schema):
+    print('Following structure via OpenAI...')
+    text_content = [
+        {
+            "type": "text",
+            "text": FOLLOW_SCHEMA_HUMAN_MESSAGE.format(json_info=json_info),
+        },
+    ]
+    response = client.beta.chat.completions.parse(
+    model="gpt-4o-2024-08-06",
+        messages=[
+            {
+                "role": "system",
+                "content": FOLLOW_SCHEMA_SYSTEM_MESSAGE,
+            },
+            {
+                "role": "user",
+                "content": text_content,
+            }
+        ],
+        max_tokens=1000,
+        response_format=schema,
+        logprobs=True,
+        top_logprobs=2,
+        temperature=0.0,
+        # top_p=.0000000000000000000001
+    )
+
+    if response.choices[0].message.refusal:
+        raise RefusalError('OpenAI refused to respond to the request')
+
+    content = response.choices[0].message.content
+    parsed_data = json.loads(content) 
+    model_data = schema.model_validate(parsed_data)
+
+    return model_data
+     

llm_api/utils.py

@@ -0,0 +1,14 @@
+import base64
+
+
+def get_image_data(image_path):
+    with open(image_path, "rb") as f:
+        image_data = base64.b64encode(f.read()).decode("utf-8")
+    return image_data
+
+
+def get_data_format(image_path):
+    image_format = image_path.split(".")[-1]
+    if image_format == "jpg":
+        image_format = "jpeg"
+    return image_format

read_schema_free.py

@@ -0,0 +1,57 @@
+from enum import Enum
+from typing import Union
+from pydantic import BaseModel, Field
+
+
+# avoid using the 'import' string, including words like 'important', etc.
+class UpperGarmentProperties(BaseModel):
+    upper_category: str
+    neck: str
+    sleeve: str
+    shoulder: str
+    waist: str
+    length: str
+
+
+class LowerGarmentProperties(BaseModel):
+    lower_category: str
+    waist: str
+    hip: str
+    rise: str
+    leg: str
+
+
+class HatProperties(BaseModel):
+    style: str
+    brim: str
+
+class TargetAudience(BaseModel):
+    age_range: str
+    style_preference: str
+    lifestyle: str
+
+class Closure(BaseModel):
+    color: str
+    type: str
+    location: str
+
+class Pattern(BaseModel):
+    type: str
+    color: list[str]
+
+class Garment(BaseModel):  # don't rename this class
+    category: str = Field(..., description='Category of the garment')
+    gender: str
+    material: str
+    color: list[str] = Field(..., description='Color of the garment')
+    pattern: Pattern
+    style: str
+    closure: Closure
+    fit: str = Field(..., description='Should be one of slim fit, regular fit, loose fit')
+    season: list[str]
+    occasion: list[str]
+    special_occasion: list[str] = Field(..., description='List up to three special occasions, such as weddings, halloween or graduation')
+    usage: list[str]
+    pairing: list[str]
+    target_audience: list[TargetAudience]
+    properties: Union[UpperGarmentProperties, LowerGarmentProperties, HatProperties]

read_schema_structured.py

@@ -0,0 +1,301 @@
+from enum import Enum
+from typing import Union
+from pydantic import BaseModel, Field
+
+
+
+# avoid using the 'import' string, including words like 'important', etc.
+class NeckType(str, Enum):
+    ROUND = "Round neck"
+    V_NECK = "V-neck"
+    COLLAR = "Collar"
+    OFF_SHOULDER = "Off-shoulder"
+    HALTER = "Halter"
+    OTHER = "Other"
+
+class Color(str, Enum):
+    SCARLET = "Scarlet"  # A bright red color
+    AZURE = "Azure"  # A bright blue color
+    EMERALD = "Emerald"  # A bright green color
+    AMBER = "Amber"  # A yellow-orange color
+    EBONY = "Ebony"  # A dark black color
+    IVORY = "Ivory"  # A creamy white color
+    FUCHSIA = "Fuchsia"  # A bright pink-purple color
+    VIOLET = "Violet"  # A purple color
+    TANGERINE = "Tangerine"  # A bright orange color
+    CHESTNUT = "Chestnut"  # A reddish-brown color
+    SLATE = "Slate"  # A gray color
+    NAVY = "Navy"  # A dark blue color
+    SILVER = "Silver"  # A metallic gray color
+    GOLD = "Gold"  # A metallic yellow color
+    BEIGE = "Beige"  # A light brown color
+    MULTI = "Multicolor"  # Multiple colors
+    OTHER = "Other"  # Any other color
+
+# class Color(str, Enum):
+#     RED = "Red"
+#     ORANGE = "Orange"
+#     YELLOW = "Yellow"
+#     GREEN = "Green"
+#     BLUE = "Blue"
+#     PURPLE = "Purple"
+#     PINK = "Pink"
+#     BROWN = "Brown"
+#     BLACK = "Black"
+#     WHITE = "White"
+#     GRAY = "Gray"
+#     # OTHER = "Other"
+
+class Sleeve(str, Enum):
+    SHORT = "Short"
+    LONG = "Long"
+    SLEEVELESS = "Sleeveless"
+    OTHER = "Other"
+
+class Shoulder(str, Enum):
+    REGULAR = "Regular"
+    DROP = "Drop"
+    PUFF = "Puff"
+    COLD_SHOULDER = "Cold shoulder"
+    OTHER = "Other"
+
+class Waist(str, Enum):
+    REGULAR = "Regular"
+    HIGH = "High"
+    LOW = "Low"
+    OTHER = "Other"
+
+class UpperLength(str, Enum):
+    CROPPED = "Cropped"
+    REGULAR = "Regular"
+    LONG = "Long"
+    OTHER = "Other"
+
+class UpperGarmentSubcategory(str, Enum):
+    T_SHIRT = "T-shirt"
+    BLOUSE = "Blouse"
+    SHIRT = "Shirt"
+    SWEATER = "Sweater"
+    JACKET = "Jacket"
+    HOODIE = "Hoodie"
+    DRESS = "Dress"
+    OTHER = "Other"
+
+class LowerGarmentCategory(str, Enum):
+    SHORTS = "Shorts"
+    PANTS = "Pants"
+    SKIRT = "Skirt"
+    JEANS = "Jeans"
+    OTHER = "Other"
+
+class PatternType(str, Enum):
+    SOLID = "Solid"
+    STRIPED = "Striped"
+    CHECKERED = "Checkered"
+    FLORAL = "Floral"
+    POLKA_DOT = "Polka dot"
+    OTHER = "Other"
+
+class Pattern(BaseModel):
+    type: PatternType
+    color: list[Color]
+
+class HipSize(str, Enum):
+    REGULAR = "Regular"
+    WIDE = "Wide"
+    SKINNY = "Skinny"
+    OTHER = "Other"
+
+class Rise(str, Enum):
+    REGULAR = "Regular"
+    HIGH = "High"
+    LOW = "Low"
+    OTHER = "Other"
+
+class LegWidth(str, Enum):
+    REGULAR = "Regular"
+    WIDE = "Wide"
+    SKINNY = "Skinny"
+    OTHER = "Other"
+
+class UpperGarmentProperties(BaseModel):
+    upper_category: UpperGarmentSubcategory
+    neck: NeckType
+    sleeve: Sleeve
+    shoulder: Shoulder
+    waist: Waist
+    length: UpperLength
+
+class LowerGarmentProperties(BaseModel):
+    lower_category: LowerGarmentCategory
+    waist: Waist
+    hip: HipSize
+    rise: Rise
+    leg: LegWidth
+
+class HatStyle(str, Enum):
+    BEANIE = "Beanie"
+    BERET = "Beret"
+    BUCKET = "Bucket"
+    CAP = "Cap"
+    FEDORA = "Fedora"
+    VISOR = "Visor"
+    OTHER = "Other"
+
+class Brim(str, Enum):
+    NONE = "None"
+    SHORT = "Short"
+    MEDIUM = "Medium"
+    LONG = "Long"
+    OTHER = "Other"
+
+class HatProperties(BaseModel):
+    style: HatStyle
+    brim: Brim
+
+class Category(str, Enum):
+    UPPER_GARMENT = "Upper garment"
+    LOWER_GARMENT = "Lower garment"
+    HAT = "Hat"
+    OTHER = "Other"
+
+class Gender(str, Enum):
+    MALE = "Male"
+    FEMALE = "Female"
+    UNISEX = "Unisex"
+    OTHER = "Other"
+
+class Material(str, Enum):
+    COTTON = "Cotton"
+    POLYESTER = "Polyester"
+    WOOL = "Wool"
+    SILK = "Silk"
+    LINEN = "Linen"
+    LEATHER = "Leather"
+    DENIM = "Denim"
+    OTHER = "Other"
+
+class TargetAudienceAgeRange(str, Enum):
+    KIDS = "Kids"
+    TEENS = "Teens"
+    ADULTS = "Adults"
+    SENIORS = "Seniors"
+    OTHER = "Other"
+
+class TargetAudienceStylePreference(str, Enum):
+    TRENDY = "Trendy"
+    CLASSIC = "Classic"
+    VINTAGE = "Vintage"
+    BOHEMIAN = "Bohemian"
+    OTHER = "Other"
+
+class TargetAudienceLifestyle(str, Enum):
+    ACTIVE = "Active"
+    CASUAL = "Casual"
+    FORMAL = "Formal"
+    PARTY = "Party"
+    OTHER = "Other"
+
+class TargetAudience(BaseModel):
+    age_range: TargetAudienceAgeRange
+    style_preference: TargetAudienceStylePreference
+    lifestyle: TargetAudienceLifestyle
+
+class Style(str, Enum):
+    CASUAL = "Casual"
+    FORMAL = "Formal"
+    SPORTS = "Sports"
+    PARTY = "Party"
+    OTHER = "Other"
+
+class ClosureType(str, Enum):
+    BUTTON = "Button"
+    ZIPPER = "Zipper"
+    LACE = "Lace"
+    HOOK = "Hook"
+    TIE = "Tie"
+    VELCRO = "Velcro"
+    BUCKLE = "Buckle"
+    NONE = "None"
+    OTHER = "Other"
+
+class ClosureLocation(str, Enum):
+    FRONT = "Front"
+    BACK = "Back"
+    SIDE = "Side"
+    NECK = "Neck"
+    WAIST = "Waist"
+    OTHER = "Other"
+
+class Closure(BaseModel):
+    color: Color
+    type: ClosureType
+    location: ClosureLocation
+
+class Fit(str, Enum):
+    REGULAR = "Regular"
+    SLIM = "Slim"
+    LOOSE = "Loose"
+    OTHER = "Other"
+
+class Season(str, Enum):
+    ALL_SEASONS = "All seasons"
+    SPRING = "Spring"
+    SUMMER = "Summer"
+    FALL = "Fall"
+    WINTER = "Winter"
+
+class Occasion(str, Enum):
+    CASUAL = "Casual"
+    FORMAL = "Formal"
+    PARTY = "Party"
+    SPORTS = "Sports"
+    WORK = "Work"
+    OTHER = "Other"
+
+class Usage(str, Enum):
+    DAILY = "Daily"
+    SPECIAL = "Special"
+    WORKOUT = "Workout"
+    SLEEP = "Sleep"
+    PARTY = "Party"
+    OTHER = "Other"
+
+class Pairing(str, Enum):
+    JEANS = "Jeans"
+    SHORTS = "Shorts"
+    SKIRT = "Skirt"
+    LEGGINGS = "Leggings"
+    TROUSERS = "Trousers"
+    DRESS = "Dress"
+    CLUTCH = "Clutch"
+    HEELS = "Heels"
+    SANDALS = "Sandals"
+    JEWELRY = "Jewelry"
+    OTHER = "Other"
+
+class SpecialOccasion(str, Enum):
+    WEDDING = "Wedding"
+    PROM = "Prom"
+    HALLOWEEN = "Halloween"
+    GRADUATION = "Graduation"
+    BIRTHDAY = "Birthday"
+    BRUNCH = "Brunch"
+    OTHER = "Other"
+
+class Garment(BaseModel):  # don't rename this class
+    category: Category
+    gender: Gender
+    material: Material
+    color: list[Color]
+    pattern: Pattern
+    style: Style
+    closure: Closure
+    fit: Fit
+    season: list[Season]
+    occasion: list[Occasion]
+    special_occasion: list[SpecialOccasion] = Field(..., description='List up to three special occasions, such as weddings, halloween or graduation')
+    usage: list[Usage]
+    pairing: list[Pairing]
+    target_audience: list[TargetAudience]
+    properties: Union[UpperGarmentProperties, LowerGarmentProperties, HatProperties]

schema_free.py

@@ -0,0 +1,57 @@
+from enum import Enum
+from typing import Union
+from pydantic import BaseModel, Field
+
+#####
+# avoid using the 'import' string, including words like 'important', etc.
+class UpperGarmentProperties(BaseModel):
+    upper_category: str
+    neck: str
+    sleeve: str
+    shoulder: str
+    waist: str
+    length: str
+
+
+class LowerGarmentProperties(BaseModel):
+    lower_category: str
+    waist: str
+    hip: str
+    rise: str
+    leg: str
+
+
+class HatProperties(BaseModel):
+    style: str
+    brim: str
+
+class TargetAudience(BaseModel):
+    age_range: str
+    style_preference: str
+    lifestyle: str
+
+class Closure(BaseModel):
+    color: str
+    type: str
+    location: str
+
+class Pattern(BaseModel):
+    type: str
+    color: list[str]
+
+class Garment(BaseModel):  # don't rename this class
+    category: str = Field(..., description='Category of the garment')
+    gender: str
+    material: str
+    color: list[str] = Field(..., description='Color of the garment')
+    pattern: Pattern
+    style: str
+    closure: Closure
+    fit: str = Field(..., description='Should be one of slim fit, regular fit, loose fit')
+    season: list[str]
+    occasion: list[str]
+    special_occasion: list[str] = Field(..., description='List up to three special occasions, such as weddings, halloween or graduation')
+    usage: list[str]
+    pairing: list[str]
+    target_audience: list[TargetAudience]
+    properties: Union[UpperGarmentProperties, LowerGarmentProperties, HatProperties]

schema_structured.py

@@ -0,0 +1,301 @@
+from enum import Enum
+from typing import Union
+from pydantic import BaseModel, Field
+
+
+#####
+# avoid using the 'import' string, including words like 'important', etc.
+class NeckType(str, Enum):
+    ROUND = "Round neck"
+    V_NECK = "V-neck"
+    COLLAR = "Collar"
+    OFF_SHOULDER = "Off-shoulder"
+    HALTER = "Halter"
+    OTHER = "Other"
+
+class Color(str, Enum):
+    SCARLET = "Scarlet"  # A bright red color
+    AZURE = "Azure"  # A bright blue color
+    EMERALD = "Emerald"  # A bright green color
+    AMBER = "Amber"  # A yellow-orange color
+    EBONY = "Ebony"  # A dark black color
+    IVORY = "Ivory"  # A creamy white color
+    FUCHSIA = "Fuchsia"  # A bright pink-purple color
+    VIOLET = "Violet"  # A purple color
+    TANGERINE = "Tangerine"  # A bright orange color
+    CHESTNUT = "Chestnut"  # A reddish-brown color
+    SLATE = "Slate"  # A gray color
+    NAVY = "Navy"  # A dark blue color
+    SILVER = "Silver"  # A metallic gray color
+    GOLD = "Gold"  # A metallic yellow color
+    BEIGE = "Beige"  # A light brown color
+    MULTI = "Multicolor"  # Multiple colors
+    OTHER = "Other"  # Any other color
+
+# class Color(str, Enum):
+#     RED = "Red"
+#     ORANGE = "Orange"
+#     YELLOW = "Yellow"
+#     GREEN = "Green"
+#     BLUE = "Blue"
+#     PURPLE = "Purple"
+#     PINK = "Pink"
+#     BROWN = "Brown"
+#     BLACK = "Black"
+#     WHITE = "White"
+#     GRAY = "Gray"
+#     # OTHER = "Other"
+
+class Sleeve(str, Enum):
+    SHORT = "Short"
+    LONG = "Long"
+    SLEEVELESS = "Sleeveless"
+    OTHER = "Other"
+
+class Shoulder(str, Enum):
+    REGULAR = "Regular"
+    DROP = "Drop"
+    PUFF = "Puff"
+    COLD_SHOULDER = "Cold shoulder"
+    OTHER = "Other"
+
+class Waist(str, Enum):
+    REGULAR = "Regular"
+    HIGH = "High"
+    LOW = "Low"
+    OTHER = "Other"
+
+class UpperLength(str, Enum):
+    CROPPED = "Cropped"
+    REGULAR = "Regular"
+    LONG = "Long"
+    OTHER = "Other"
+
+class UpperGarmentSubcategory(str, Enum):
+    T_SHIRT = "T-shirt"
+    BLOUSE = "Blouse"
+    SHIRT = "Shirt"
+    SWEATER = "Sweater"
+    JACKET = "Jacket"
+    HOODIE = "Hoodie"
+    DRESS = "Dress"
+    OTHER = "Other"
+
+class LowerGarmentCategory(str, Enum):
+    SHORTS = "Shorts"
+    PANTS = "Pants"
+    SKIRT = "Skirt"
+    JEANS = "Jeans"
+    OTHER = "Other"
+
+class PatternType(str, Enum):
+    SOLID = "Solid"
+    STRIPED = "Striped"
+    CHECKERED = "Checkered"
+    FLORAL = "Floral"
+    POLKA_DOT = "Polka dot"
+    OTHER = "Other"
+
+class Pattern(BaseModel):
+    type: PatternType
+    color: list[Color]
+
+class HipSize(str, Enum):
+    REGULAR = "Regular"
+    WIDE = "Wide"
+    SKINNY = "Skinny"
+    OTHER = "Other"
+
+class Rise(str, Enum):
+    REGULAR = "Regular"
+    HIGH = "High"
+    LOW = "Low"
+    OTHER = "Other"
+
+class LegWidth(str, Enum):
+    REGULAR = "Regular"
+    WIDE = "Wide"
+    SKINNY = "Skinny"
+    OTHER = "Other"
+
+class UpperGarmentProperties(BaseModel):
+    upper_category: UpperGarmentSubcategory
+    neck: NeckType
+    sleeve: Sleeve
+    shoulder: Shoulder
+    waist: Waist
+    length: UpperLength
+
+class LowerGarmentProperties(BaseModel):
+    lower_category: LowerGarmentCategory
+    waist: Waist
+    hip: HipSize
+    rise: Rise
+    leg: LegWidth
+
+class HatStyle(str, Enum):
+    BEANIE = "Beanie"
+    BERET = "Beret"
+    BUCKET = "Bucket"
+    CAP = "Cap"
+    FEDORA = "Fedora"
+    VISOR = "Visor"
+    OTHER = "Other"
+
+class Brim(str, Enum):
+    NONE = "None"
+    SHORT = "Short"
+    MEDIUM = "Medium"
+    LONG = "Long"
+    OTHER = "Other"
+
+class HatProperties(BaseModel):
+    style: HatStyle
+    brim: Brim
+
+class Category(str, Enum):
+    UPPER_GARMENT = "Upper garment"
+    LOWER_GARMENT = "Lower garment"
+    HAT = "Hat"
+    OTHER = "Other"
+
+class Gender(str, Enum):
+    MALE = "Male"
+    FEMALE = "Female"
+    UNISEX = "Unisex"
+    OTHER = "Other"
+
+class Material(str, Enum):
+    COTTON = "Cotton"
+    POLYESTER = "Polyester"
+    WOOL = "Wool"
+    SILK = "Silk"
+    LINEN = "Linen"
+    LEATHER = "Leather"
+    DENIM = "Denim"
+    OTHER = "Other"
+
+class TargetAudienceAgeRange(str, Enum):
+    KIDS = "Kids"
+    TEENS = "Teens"
+    ADULTS = "Adults"
+    SENIORS = "Seniors"
+    OTHER = "Other"
+
+class TargetAudienceStylePreference(str, Enum):
+    TRENDY = "Trendy"
+    CLASSIC = "Classic"
+    VINTAGE = "Vintage"
+    BOHEMIAN = "Bohemian"
+    OTHER = "Other"
+
+class TargetAudienceLifestyle(str, Enum):
+    ACTIVE = "Active"
+    CASUAL = "Casual"
+    FORMAL = "Formal"
+    PARTY = "Party"
+    OTHER = "Other"
+
+class TargetAudience(BaseModel):
+    age_range: TargetAudienceAgeRange
+    style_preference: TargetAudienceStylePreference
+    lifestyle: TargetAudienceLifestyle
+
+class Style(str, Enum):
+    CASUAL = "Casual"
+    FORMAL = "Formal"
+    SPORTS = "Sports"
+    PARTY = "Party"
+    OTHER = "Other"
+
+class ClosureType(str, Enum):
+    BUTTON = "Button"
+    ZIPPER = "Zipper"
+    LACE = "Lace"
+    HOOK = "Hook"
+    TIE = "Tie"
+    VELCRO = "Velcro"
+    BUCKLE = "Buckle"
+    NONE = "None"
+    OTHER = "Other"
+
+class ClosureLocation(str, Enum):
+    FRONT = "Front"
+    BACK = "Back"
+    SIDE = "Side"
+    NECK = "Neck"
+    WAIST = "Waist"
+    OTHER = "Other"
+
+class Closure(BaseModel):
+    color: Color
+    type: ClosureType
+    location: ClosureLocation
+
+class Fit(str, Enum):
+    REGULAR = "Regular"
+    SLIM = "Slim"
+    LOOSE = "Loose"
+    OTHER = "Other"
+
+class Season(str, Enum):
+    ALL_SEASONS = "All seasons"
+    SPRING = "Spring"
+    SUMMER = "Summer"
+    FALL = "Fall"
+    WINTER = "Winter"
+
+class Occasion(str, Enum):
+    CASUAL = "Casual"
+    FORMAL = "Formal"
+    PARTY = "Party"
+    SPORTS = "Sports"
+    WORK = "Work"
+    OTHER = "Other"
+
+class Usage(str, Enum):
+    DAILY = "Daily"
+    SPECIAL = "Special"
+    WORKOUT = "Workout"
+    SLEEP = "Sleep"
+    PARTY = "Party"
+    OTHER = "Other"
+
+class Pairing(str, Enum):
+    JEANS = "Jeans"
+    SHORTS = "Shorts"
+    SKIRT = "Skirt"
+    LEGGINGS = "Leggings"
+    TROUSERS = "Trousers"
+    DRESS = "Dress"
+    CLUTCH = "Clutch"
+    HEELS = "Heels"
+    SANDALS = "Sandals"
+    JEWELRY = "Jewelry"
+    OTHER = "Other"
+
+class SpecialOccasion(str, Enum):
+    WEDDING = "Wedding"
+    PROM = "Prom"
+    HALLOWEEN = "Halloween"
+    GRADUATION = "Graduation"
+    BIRTHDAY = "Birthday"
+    BRUNCH = "Brunch"
+    OTHER = "Other"
+
+class Garment(BaseModel):  # don't rename this class
+    category: Category
+    gender: Gender
+    material: Material
+    color: list[Color]
+    pattern: Pattern
+    style: Style
+    closure: Closure
+    fit: Fit
+    season: list[Season]
+    occasion: list[Occasion]
+    special_occasion: list[SpecialOccasion] = Field(..., description='List up to three special occasions, such as weddings, halloween or graduation')
+    usage: list[Usage]
+    pairing: list[Pairing]
+    target_audience: list[TargetAudience]
+    properties: Union[UpperGarmentProperties, LowerGarmentProperties, HatProperties]