add code to convert cf-style schema to pydantic

app.py

@@ -31,13 +31,15 @@ async def forward_request(
 
     try:
         # convert attributes to schema
-        attributes = import_for_schema + attributes
+        attributes = "attributes_object = {" + attributes + "}"
         try:
-            exec(attributes, globals())
+            attributes = exec(attributes, globals())
         except:
             raise gr.Error(
                 "Invalid `Attribute Schema`. Please insert valid schema following the example."
             )
+        for key, value in attributes_object.items():  # type: ignore
+            attributes_object[key] = Attribute(**value)  # type: ignore
 
         if product_data == "":
             product_data = "{}"
@@ -87,14 +89,15 @@ async def forward_request(
 
         try:
             json_attributes, reevaluated = await service.extract_attributes_with_validation(
-                Product,  # type: ignore
+                attributes_object,  # type: ignore
                 ai_model,
                 None,
                 product_taxonomy,
                 product_data_object,  # type: ignore
                 img_paths=img_paths,
             )
-        except:
+        except Exception as e:
+            print(e)
             raise gr.Error("Failed to extract attributes. Something went wrong.")
     finally:
         # remove temp folder anyway
@@ -141,12 +144,7 @@ class Style(BaseModel):
     smock: int = Field(..., description="Smock: Loose-fitting with gathered or shirred sections, usually on bodice or neckline.")
     corset: int = Field(..., description="Corset: Structured bodice with boning or lacing that shapes the waist.")
     jumper_dress: int = Field(..., description="Jumper Dress: Layered dress style similar to a pinafore, often more casual or thick-strapped.")
-    blazer_dress: int = Field(..., description="Blazer Dress: Tailored like a blazer or suit jacket, often double-breasted or lapelled.")
-    asymmetric: int = Field(..., description="Asymmetric: Dress with a non-symmetrical hem, neckline, or sleeve design.")
     shift: int = Field(..., description="Shift: Simple, straight dress with no defined waist, typically above the knee.")
-    drop_waist: int = Field(..., description="Drop waist: Waistline sits low on the hips, usually with a loose top and flared skirt.")
-    empire: int = Field(..., description="Empire: High waistline just below the bust, flowing skirt from there downward.")
-    modest: int = Field(..., description="Modest: Covers most of the body, with high neckline, long sleeves, and longer hemline.")
 
 
 class SleeveLength(BaseModel):
@@ -161,14 +159,11 @@ class Neckline(BaseModel):
     v_neck: int = Field(..., description="V Neck: Neckline dips down in the shape of a 'V', varying from shallow to deep.")
     sweetheart: int = Field(..., description="Sweetheart: A heart-shaped neckline, often curving over the bust and dipping in the center.")
     round_neck: int = Field(..., description="Round Neck: Circular neckline sitting around the base of the neck.")
-    halter_neck: int = Field(..., description="Halter Neck: Straps go around the neck, leaving shoulders and upper back exposed.")
     square_neck: int = Field(..., description="Square Neck: Straight horizontal cut across the chest with vertical sides, forming a square.")
     high_neck: int = Field(..., description="High Neck: Extends up the neck slightly but not folded like a turtle neck.")
     crew_neck: int = Field(..., description="Crew Neck: High, rounded neckline that sits close to the neck.")
     turtle_neck: int = Field(..., description="Turtle Neck: High neckline that folds over and covers the neck completely.")
     off_the_shoulder: int = Field(..., description="Off the Shoulder: Sits below the shoulders, exposing the shoulders and collarbone.")
-    one_shoulder: int = Field(..., description="One Shoulder: Covers one shoulder only, leaving the other bare.")
-    boat_neck: int = Field(..., description="Boat Neck: Wide, shallow neckline that runs almost horizontally from shoulder to shoulder.")
 
 
 class Pattern(BaseModel):
@@ -178,7 +173,6 @@ class Pattern(BaseModel):
     plain: int = Field(..., description="Plain")
     geometric: int = Field(..., description="Geometric pattern")
     logo: int = Field(..., description="Logo print")
-    graphic_print: int = Field(..., description="Graphic print")
     other: int = Field(..., description="Other pattern")
 
 
@@ -188,13 +182,8 @@ class Fabric(BaseModel):
     linen: int = Field(..., description="Linen")
     satin: int = Field(..., description="Satin")
     silk: int = Field(..., description="Silk")
-    sequin: int = Field(..., description="Sequin")
     leather: int = Field(..., description="Leather")
     velvet: int = Field(..., description="Velvet")
-    knit: int = Field(..., description="Knit")
-    lace: int = Field(..., description="Lace")
-    suede: int = Field(..., description="Suede")
-    sheer: int = Field(..., description="Sheer")
     polyester: int = Field(..., description="Polyester")
     viscose: int = Field(..., description="Viscose")
 
@@ -231,9 +220,6 @@ class Occasion(BaseModel):
     mother_of_the_bride: int = Field(..., description="Mother of the bride dress")
     party: int = Field(..., description="Party wear")
     prom: int = Field(..., description="Prom dress")
-    wedding_guest: int = Field(..., description="Wedding guest dress")
-    work: int = Field(..., description="Work attire")
-    sportswear: int = Field(..., description="Sportswear")
 
 
 class Season(BaseModel):
@@ -256,6 +242,158 @@ class Product(BaseModel):
     occasion: Occasion = Field(..., description="Can have multiple values ,Occasion of the dress")
     season: Season = Field(..., description="Single value ,Season of the dress")
 """
+
+cf_style_schema = """
+"Length": {
+    "description": "Length of dress",
+    "data_type": "string",
+    "allowed_values": [
+        "Maxi",
+        "Knee Length",
+        "Mini",
+        "Midi"
+    ]
+},
+"Style": {
+    "description": "Select the most appropriate dress style based on the garment's silhouette, fit, structural features, and overall design. Focus on how the dress is constructed and worn: whether it is fitted or loose, whether it has defining elements such as shirring, boning, buttons, collars, tiers, layering, or wrap ties. Ignore color, pattern, or fabric unless they directly influence the structure (e.g., stretch fabric for Bodycon). Use the visual cues of the neckline, sleeves, waistline, hemline, and closure type to guide your choice. Only select one style that best captures the dominant structural or design identity of the dress. Refer to the following definitions when uncertain: - 'A Line': Fitted at the top and gradually flares toward the hem, forming an 'A' shape.- 'Bodycon': Tight-fitting and figure-hugging, usually made with stretchy fabric.- 'Column': Straight silhouette from top to bottom, with minimal shaping or flare.- 'Shirt Dress': Structured like a shirt with buttons, collar, and sleeves; may include a belt.- 'Wrap Dress': Features a front closure that wraps and ties at the side or back.- 'Slip': Lightweight, spaghetti-strap dress with minimal structure, often bias-cut.- 'Kaftan': Very loose, flowing garment with wide sleeves and minimal shaping.- 'Smock': Loose-fitting with gathered or shirred sections (usually bodice or neckline).- 'Corset': Structured bodice with boning or lacing that shapes the waist.- 'Pinafore': Sleeveless over-dress, often worn layered over another top.- 'Jumper Dress': Layered dress style similar to a pinafore, often more casual or thick-strapped.- 'Blazer Dress': Tailored like a blazer or suit jacket, often double-breasted or lapelled.- 'Tunic': Loose and straight-cut, often worn short or over pants/leggings.- 'Gown': Full-length, formal dress with a structured or dramatic silhouette.- 'Asymmetric': Dress with a non-symmetrical hem, neckline, or sleeve design.- 'Shift': Simple, straight dress with no defined waist, typically above the knee.- 'Drop waist': Waistline sits low on the hips, usually with a loose top and flared skirt.- 'Empire': High waistline just below the bust, flowing skirt from there downward.- 'Modest': Covers most of the body, with high neckline, long sleeves, and longer hemline. Use structural cues over stylistic interpretation. Do not infer intent (e.g., party, formal) unless it’s directly tied to the construction.",
+    "data_type": "string",
+    "allowed_values": [
+        "A Line",
+        "Bodycon",
+        "Column",
+        "Shirt Dress",
+        "Wrap Dress",
+        "Smock",
+        "Corset",
+        "Tunic",
+        "Asymmetric",
+        "Shift",
+        "Modest"
+    ]
+},
+"Sleeve_length": {
+    "description": "Length of sleeves on dress",
+    "data_type": "string",
+    "allowed_values": [
+        "Sleeveless",
+        "Three quarters Sleeve",
+        "Long Sleeve",
+        "Short Sleeve",
+        "Strapless"
+    ]
+},
+"Neckline": {
+    "description": "Identify the neckline style based on the visible shape and structure of the neckline area. Focus on the cut and contour around the collarbone, shoulders, and upper chest. Only choose the neckline that best represents the dominant design — ignore collars, patterns, or styling details unless they significantly alter the neckline shape. Use the following definitions for clarity: - 'V Neck': Neckline dips down in the shape of a 'V', varying from shallow to deep. - 'Sweetheart': A heart-shaped neckline, often curving over the bust and dipping in the center. - 'Round Neck': Circular neckline sitting around the base of the neck, not as high as a crew neck. - 'Halter Neck': Straps go around the neck, leaving shoulders and upper back exposed. - 'Square Neck': Straight horizontal cut across the chest with vertical sides, forming a square. - 'High Neck': Extends up the neck slightly but not folded like a turtle neck. - 'Crew Neck': High, rounded neckline that sits close to the neck (commonly found in T-shirts). - 'Cowl Neck': Draped or folded neckline that hangs in soft folds. - 'Turtle Neck': High neckline that folds over and covers the neck completely. - 'Off the Shoulder': Sits below the shoulders, exposing the shoulders and collarbone. - 'One Shoulder': Covers one shoulder only, leaving the other bare. - 'Bandeau': Straight, strapless neckline that wraps across the bust. - 'Boat Neck': Wide, shallow neckline that runs almost horizontally from shoulder to shoulder. - 'Scoop Neck': U-shaped neckline, typically deeper than a round neck. - Always prioritize structure over styling — for example, a dress with embellishment or a mesh overlay still counts as 'V Neck' if the main shape is a V. If a neckline is borderline between two types, choose the simpler or more dominant structure.",
+    "data_type": "string",
+    "allowed_values": [
+        "V Neck",
+        "Sweetheart",
+        "Round Neck",
+        "Halter Neck",
+        "Square Neck",
+        "Cowl Neck",
+        "Turtle Neck",
+        "Off the shoulder",
+        "Boat Neck",
+        "Scoop Neck"
+    ]
+},
+"pattern": {
+    "description": "Pattern of the garment",
+    "data_type": "string",
+    "allowed_values": [
+        "Floral",
+        "Stripe",
+        "Leopard Print",
+        "Spot",
+        "Plain",
+        "Geometric",
+        "Logo",
+        "Graphic print",
+        "Check",
+        "other"
+    ]
+},
+"fabric": {
+    "description": "Material of the garment",
+    "data_type": "string",
+    "allowed_values": [
+        "Cotton",
+        "Denim",
+        "Jersey",
+        "Linen",
+        "Satin",
+        "Silk",
+        "Leather",
+        "Velvet",
+        "Corduroy",
+        "Ponte",
+        "Knit",
+        "Lace",
+        "Polyester",
+        "Viscose"
+    ]
+},
+"features": {
+    "description": "special features of the garment",
+    "data_type": "list[string]",
+    "allowed_values": [
+        "Pockets",
+        "Lined",
+        "Cut Out",
+        "Backless",
+        "none"
+    ]
+},
+"Closure": {
+    "description": "Closure of the garment. How it is closed",
+    "data_type": "list[string]",
+    "allowed_values": [
+        "Button",
+        "Zip",
+        "Press Stud",
+        "Clasp"
+    ]
+},
+"Body_Fit": {
+    "description": "How the dress fits the body",
+    "data_type": "string",
+    "allowed_values": [
+        "Petite",
+        "Maternity",
+        "Regular",
+        "Tall",
+        "Plus Size"
+    ]
+},
+"Occasion": {
+    "description": "What occasions do the dress match",
+    "data_type": "list[string]",
+    "allowed_values": [
+        "Beach",
+        "Casual",
+        "Cocktail",
+        "Day",
+        "Bridal",
+        "Bridesmaid",
+        "Evening",
+        "Mother of the Bride",
+        "Party",
+        "Prom"
+    ]
+},
+"Season": {
+    "description": "What season do the dress match",
+    "data_type": "list[string]",
+    "allowed_values": [
+        "Spring",
+        "Summer",
+        "Autumn",
+        "Winter"
+    ]
+}
+"""[1:]
+
 description = """
 This is a simple demo for Attribution. Follow the steps below:
 
@@ -339,7 +477,7 @@ with gr.Blocks(title="Internal Demo for Attribution") as demo:
                 with gr.Column():
                     attributes = gr.TextArea(
                         label="Attribute Schema",
-                        value=sample_schema,
+                        value=cf_style_schema,
                         placeholder="Enter schema here or use Add Attributes below",
                         interactive=True,
                         lines=30,

app/services/base.py

@@ -11,115 +11,47 @@ from app.schemas.schema_tools import (
 )
 
 
-example_data = example_data = {
-    "length": {
-        "maxi": 100,
-        "knee_length": 0,
-        "mini": 0,
-        "midi": 0
-    },
-    "style": {
-        "a_line": 0,
-        "bodycon": 0,
-        "shirt_dress": 0,
-        "wrap_dress": 0,
-        "slip": 0,
-        "smock": 0,
-        "corset": 100,
-        "jumper_dress": 0,
-        "blazer_dress": 0,
-        "asymmetric": 0,
-        "shift": 0,
-        "drop_waist": 0,
-        "empire": 0,
-        "modest": 0
-    },
-    "sleeve_length": {
-        "sleeveless": 0,
-        "three_quarters_sleeve": 0,
-        "long_sleeve": 0,
-        "short_sleeve": 0,
-        "strapless": 100
-    },
-    "neckline": {
-        "v_neck": 0,
-        "sweetheart": 100,
-        "round_neck": 0,
-        "halter_neck": 0,
-        "square_neck": 0,
-        "high_neck": 0,
-        "crew_neck": 0,
-        "turtle_neck": 0,
-        "off_the_shoulder": 0,
-        "one_shoulder": 0,
-        "boat_neck": 0
-    },
-    "pattern": {
-        "floral": 0,
-        "stripe": 0,
-        "leopard_print": 0,
-        "plain": 100,
-        "geometric": 0,
-        "logo": 0,
-        "graphic_print": 0,
-        "other": 0
-    },
-    "fabric": {
-        "cotton": 0,
-        "denim": 0,
-        "linen": 0,
-        "satin": 0,
-        "silk": 0,
-        "sequin": 0,
-        "leather": 0,
-        "velvet": 100,
-        "knit": 0,
-        "lace": 0,
-        "suede": 0,
-        "sheer": 0,
-        "polyester": 0,
-        "viscose": 0
-    },
-    "features": {
-        "pockets": 0,
-        "lined": 0,
-        "cut_out": 0,
-        "backless": 0,
-        "none": 100
-    },
-    "closure": {
-        "button": 0,
-        "zip": 0,
-        "press_stud": 0,
-        "clasp": 0
-    },
-    "body_fit": {
-        "petite": 0,
-        "maternity": 0,
-        "regular": 100,
-        "tall": 0,
-        "plus_size": 0
-    },
-    "occasion": {
-        "beach": 0,
-        "casual": 0,
-        "cocktail": 0,
-        "day": 0,
-        "evening": 100,
-        "mother_of_the_bride": 0,
-        "party": 0,
-        "prom": 0,
-        "wedding_guest": 0,
-        "work": 0,
-        "sportswear": 0
-    },
-    "season": {
-        "spring": 0,
-        "summer": 0,
-        "autumn": 0,
-        "winter": 100
-    }
-}
+def cf_style_to_pydantic_percentage_shema(
+    cf_style_schema: dict,
+) -> str:
+    """
+    Convert CF style schema to Pydantic schema
+    """
+    print(f'{cf_style_schema}')
+    attributes_line_in_product = []
+    values_classes = []
+    for attribute, attribute_info in cf_style_schema.items():
+        multiple = False
+        if "list" in attribute_info.data_type:
+            multiple = True
+        else:
+            multiple = False
+        class_name = "Class_" + attribute.capitalize()
+        multiple_desc = "Can have multiple values" if multiple else "Single value only"
+        attribute_desc = attribute_info.description
+        attribute_line = f'{attribute}: {class_name} = Field("", description="{multiple_desc}, {attribute_desc}")'
+
+        class_code = f"""
+class {class_name}(BaseModel):
+
+"""
+        for value in attribute_info.allowed_values:
+            class_code += f"    {value.lower().replace(' ', '_').replace('-', '_')}: int\n"
+        
+        values_classes.append(class_code)
+        attributes_line_in_product.append(attribute_line)
+    attributes_line = "\n    ".join(attributes_line_in_product)
+    values_classes_code = "\n".join(values_classes)
+    pydantic_schema = f"""
+from pydantic import BaseModel, Field
+{values_classes_code}
+class Product(BaseModel):
+    {attributes_line}
+"""
+    pydantic_code = pydantic_schema.strip()
+    exec(pydantic_code, globals())
+    return Product
+
 
 class BaseAttributionService(ABC):
     @abstractmethod
@@ -152,7 +84,7 @@ class BaseAttributionService(ABC):
 
     async def extract_attributes_with_validation(
         self,
-        attributes_model: Type[BaseModel],
+        attributes: Dict[str, Any],
         ai_model: str,
         img_urls: List[str],
         product_taxonomy: str,
@@ -163,9 +95,21 @@ class BaseAttributionService(ABC):
         # validate_json_schema(schema)
 
         # create mappings for keys of attributes, to make the key following naming convention of python variables
-        schema = attributes_model.model_json_schema()
+        forward_mapping = {}
+        reverse_mapping = {}
+        for i, key in enumerate(attributes.keys()):
+            forward_mapping[key] = f'{to_snake_case(key)}_{i}'
+            reverse_mapping[f'{to_snake_case(key)}_{i}'] = key
+        
+        transformed_attributes = {}
+        for key, value in attributes.items():
+            transformed_attributes[forward_mapping[key]] = value
+
+        # attributes_model = convert_attribute_to_model(transformed_attributes)
+        attributes_percentage_model = cf_style_to_pydantic_percentage_shema(transformed_attributes)
+        schema = attributes_percentage_model.model_json_schema()
         data = await self.extract_attributes(
-            attributes_model,
+            attributes_percentage_model,
             ai_model,
             img_urls,
             product_taxonomy if product_taxonomy != "" else "main",
@@ -173,12 +117,11 @@ class BaseAttributionService(ABC):
             # pil_images=pil_images, # temporarily removed to save cost
             img_paths=img_paths,
         )
-        # data = example_data
         validate_json_data(data, schema)
 
         str_data = str(data)
         reevaluate_data = await self.reevaluate_atributes(
-            attributes_model,
+            attributes_percentage_model,
             ai_model,
             img_urls,
             product_taxonomy if product_taxonomy != "" else "main",
@@ -188,7 +131,7 @@ class BaseAttributionService(ABC):
         )
 
         init_reevaluate_data = {}
-        for field_name, field in attributes_model.model_fields.items(): # type: ignore
+        for field_name, field in attributes_percentage_model.model_fields.items(): # type: ignore
             print(f"{field_name}: {field.description}")
             if "single value" in field.description.lower():
                 max_percentage = 0
@@ -203,7 +146,12 @@ class BaseAttributionService(ABC):
                         init_list.append(k)
                 init_reevaluate_data[field_name] = init_list
 
-        return data, init_reevaluate_data
+        # reverse the key mapping to the original keys
+        reverse_data = {}
+        for key, value in init_reevaluate_data.items():
+            reverse_data[reverse_mapping[key]] = value
+
+        return data, reverse_data
 
     async def follow_schema_with_validation(
         self, schema: Dict[str, Any], data: Dict[str, Any]