Delete app.py

app.py

@@ -1,228 +0,0 @@
-from fastapi import FastAPI, HTTPException, Request
-from fastapi.responses import JSONResponse
-from fastapi.exceptions import RequestValidationError
-from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel
-from typing import List
-import asyncio
-import os
-from concurrent.futures import ThreadPoolExecutor
-from dotenv import load_dotenv
-from Generate_caption import load_model_from_path, tokenizer_load
-from Color_extraction import extract_colors
-from Generate_productName_description import generate_product_name, generate_description, clean_response
-from huggingface_hub import hf_hub_download
-import tempfile
-
-app = FastAPI()
-
-# CORS Middleware
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["http://localhost:3000"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# Load environment variables
-load_dotenv()
-API_KEY = os.getenv("API_KEY")
-if not API_KEY:
-    raise ValueError("API_KEY not set. Please configure your .env file or system environment.")
-
-# Global variables for models and ThreadPool
-vgg16_model = None
-fifth_version_model = None
-tokenizer = None
-executor = ThreadPoolExecutor(max_workers=4)
-
-# Ensure ONNX model path is set
-os.environ["XDG_CACHE_HOME"] = "models/u2net.onnx"
-
-async def download_model_from_hf(repo_id: str, filename: str) -> str:
-    try:
-        # Create a temporary directory for model files
-        model_dir = os.path.join(tempfile.gettempdir(), "hf_models")
-        os.makedirs(model_dir, exist_ok=True)
-
-        # Download model
-        model_path = hf_hub_download(
-            repo_id=repo_id,
-            filename=filename,
-            cache_dir=model_dir,
-            local_dir=model_dir,
-            force_download=True
-        )
-        print(f"Downloaded {filename} to {model_path}")
-        return model_path
-    except Exception as e:
-        print(f"Error downloading {filename}: {str(e)}")
-        raise
-
-
-async def load_models():
-    global vgg16_model, fifth_version_model, tokenizer
-    if not all([vgg16_model, fifth_version_model, tokenizer]):
-        print("Downloading and loading models from Hugging Face Hub...")
-
-        try:
-            # Download models in parallel
-            vgg16_path, model_path, tokenizer_path = await asyncio.gather(
-                download_model_from_hf("abdallah-03/AI_product_helper_models", "vgg16_feature_extractor.keras"),
-                download_model_from_hf("abdallah-03/AI_product_helper_models", "fifth_version_model.keras"),
-                download_model_from_hf("abdallah-03/AI_product_helper_models", "tokenizer.pkl")
-            )
-
-            # Load models using the downloaded paths
-            vgg16_task = asyncio.to_thread(load_model_from_path, vgg16_path)
-            fifth_version_task = asyncio.to_thread(load_model_from_path, model_path)
-            tokenizer_task = asyncio.to_thread(tokenizer_load, tokenizer_path)
-
-            vgg16_model, fifth_version_model, tokenizer = await asyncio.gather(
-                vgg16_task, fifth_version_task, tokenizer_task
-            )
-            print("Models loaded successfully!")
-
-        except Exception as e:
-            print(f"Error loading models: {str(e)}")
-            raise
-
-
-@app.on_event("startup")
-async def startup_event():
-    asyncio.create_task(load_models())
-
-
-# Pydantic Models
-class ImagePathsRequest(BaseModel):
-    image_paths: List[str]
-
-
-class GenerateProductRequest(ImagePathsRequest):
-    Brand_name: str
-
-
-class GenerateDescriptionRequest(BaseModel):
-    product_name: str
-
-
-class AIproducthelper(ImagePathsRequest):
-    Brand_name: str
-
-
-# Exception Handlers
-@app.exception_handler(Exception)
-async def global_exception_handler(request: Request, exc: Exception):
-    return JSONResponse(
-        status_code=500,
-        content={"success": False, "message": "Internal Server Error", "error": repr(exc)},
-    )
-
-
-@app.exception_handler(HTTPException)
-async def http_exception_handler(request: Request, exc: HTTPException):
-    return JSONResponse(
-        status_code=exc.status_code,
-        content={"success": False, "message": exc.detail},
-    )
-
-
-@app.exception_handler(RequestValidationError)
-async def validation_exception_handler(request: Request, exc: RequestValidationError):
-    return JSONResponse(
-        status_code=422,
-        content={"success": False, "message": "Validation Error", "errors": exc.errors()},
-    )
-
-
-# Endpoints
-@app.get("/")
-async def read_root():
-    return {"message": "Hello from our API, models are loading in the background!"}
-
-
-@app.get("/status/")
-async def check_status():
-    if all([vgg16_model, fifth_version_model, tokenizer]):
-        return {
-            "success": True,
-            "message": "Models are ready!",
-            "models_loaded": {
-                "vgg16": vgg16_model is not None,
-                "fifth_version": fifth_version_model is not None,
-                "tokenizer": tokenizer is not None
-            }
-        }
-    return {
-        "success": False,
-        "message": "Models are still loading...",
-        "models_loaded": {
-            "vgg16": vgg16_model is not None,
-            "fifth_version": fifth_version_model is not None,
-            "tokenizer": tokenizer is not None
-        }
-    }
-
-
-@app.post("/extract-colors/")
-async def extract_colors_endpoint(request: ImagePathsRequest):
-    if not request.image_paths:
-        raise HTTPException(status_code=400, detail="Image list cannot be empty.")
-
-    try:
-        colors = await asyncio.get_event_loop().run_in_executor(executor, extract_colors, request.image_paths)
-        return {"success": True, "colors": colors}
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Error extracting colors: {repr(exc)}")
-
-
-@app.post("/generate-product-name/")
-async def generate_product_name_endpoint(request: GenerateProductRequest):
-    if not request.image_paths:
-        raise HTTPException(status_code=400, detail="Image list cannot be empty.")
-
-    try:
-        product_name = await asyncio.get_event_loop().run_in_executor(
-            executor, generate_product_name, request.image_paths, request.Brand_name,
-            vgg16_model, fifth_version_model, tokenizer, API_KEY
-        )
-        return {"success": True, "product_name": product_name}
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Error generating product name: {repr(exc)}")
-
-
-@app.post("/generate-description/")
-async def generate_description_endpoint(request: GenerateDescriptionRequest):
-    try:
-        description = await asyncio.get_event_loop().run_in_executor(
-            executor, generate_description, API_KEY, request.product_name,
-            vgg16_model, fifth_version_model, tokenizer
-        )
-        return {"success": True, "description": description}
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Error generating description: {repr(exc)}")
-
-
-@app.post("/AI-product_help/")
-async def ai_product_help_endpoint(request: AIproducthelper):
-    if not request.image_paths:
-        raise HTTPException(status_code=400, detail="Image list cannot be empty.")
-
-    try:
-        product_name = await asyncio.get_event_loop().run_in_executor(
-            executor, generate_product_name, request.image_paths, request.Brand_name,
-            vgg16_model, fifth_version_model, tokenizer, API_KEY
-        )
-        product_name = clean_response(product_name)
-
-        description = await asyncio.get_event_loop().run_in_executor(
-            executor, generate_description, API_KEY, product_name,
-            vgg16_model, fifth_version_model, tokenizer
-        )
-        description = clean_response(description)
-
-        return {"success": True, "product_name": product_name, "description": description}
-
-    except Exception as exc:
-        raise HTTPException(status_code=500, detail=f"Error in AI product helper: {repr(exc)}")