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Update main.py
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main.py
CHANGED
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@@ -38,17 +38,22 @@ BASE_DIR = Path(__file__).parent
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UPLOAD_FOLDER = BASE_DIR / "uploads"
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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# Modèles Hugging Face
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HF_TOKEN = os.getenv("HF_TOKEN")
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client = InferenceClient(token=HF_TOKEN)
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MODELS = {
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"summary": "facebook/bart-large-cnn",
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"caption": "Salesforce/blip-image-captioning-large",
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"qa": "distilbert-base-cased-distilled-squad" #
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}
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# Pipeline QA pour distilbert-base-cased-distilled-squad
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qa_pipeline = pipeline("question-answering", model=MODELS["qa"], tokenizer=MODELS["qa"])
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# Modèles Pydantic
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class FileInfo(BaseModel):
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@@ -69,7 +74,7 @@ class QARequest(BaseModel):
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file_id: Optional[str] = None
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question: str
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# Fonctions utilitaires
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def extract_text_from_pdf(file_path: str) -> str:
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try:
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doc = fitz.open(file_path)
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@@ -144,11 +149,7 @@ async def process_uploaded_file(file: UploadFile) -> FileInfo:
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async def test_api():
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return {"status": "API working", "environment": "Hugging Face" if os.environ.get("HF_SPACE") else "Local"}
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# Endpoints
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@app.get("/api")
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async def api_root():
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return {"status": "API is running"}
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@app.post("/api/upload")
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async def upload_files(files: List[UploadFile] = File(...)):
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logger.info(f"Upload request received with {len(files)} files")
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@@ -163,47 +164,6 @@ async def upload_files(files: List[UploadFile] = File(...)):
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logger.error(f"Upload error: {e}")
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raise HTTPException(500, f"Erreur lors de l'upload: {str(e)}")
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@app.post("/api/summarize")
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async def summarize_document(request: SummaryRequest):
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try:
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file_path = next(f for f in UPLOAD_FOLDER.glob(f"{request.file_id}*"))
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text = ""
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if file_path.suffix == ".pdf":
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text = extract_text_from_pdf(str(file_path))
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else:
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with open(file_path, "r", encoding="utf-8") as f:
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text = f.read()
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summary = client.summarization(
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text=text,
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model=MODELS["summary"],
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parameters={"max_length": request.max_length}
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)
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return {"summary": summary}
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except Exception as e:
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logger.error(f"Summarization error: {e}")
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raise HTTPException(500, f"Erreur de résumé: {str(e)}")
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@app.post("/api/caption")
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async def caption_image(request: CaptionRequest):
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try:
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file_path = next(f for f in UPLOAD_FOLDER.glob(f"{request.file_id}*"))
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with open(file_path, "rb") as image_file:
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image_data = image_file.read()
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caption = client.image_to_text(
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image=image_data,
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model=MODELS["caption"]
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)
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return {"caption": caption}
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except Exception as e:
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logger.error(f"Captioning error: {e}")
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raise HTTPException(500, f"Erreur de description: {str(e)}")
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@app.post("/api/answer")
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async def answer_question(request: QARequest):
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try:
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@@ -236,15 +196,6 @@ async def answer_question(request: QARequest):
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logger.error(f"QA error: {e}")
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raise HTTPException(500, f"Erreur de réponse: {str(e)}")
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@app.get("/api/file/{file_id}")
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async def get_file(file_id: str):
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try:
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file_path = next(f for f in UPLOAD_FOLDER.glob(f"{file_id}*"))
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return FileResponse(file_path)
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except Exception as e:
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logger.error(f"File retrieval error: {e}")
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raise HTTPException(404, "Fichier non trouvé")
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# Gestion des erreurs
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@app.exception_handler(HTTPException)
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async def http_exception_handler(request, exc):
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UPLOAD_FOLDER = BASE_DIR / "uploads"
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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# Configuration du cache pour Hugging Face
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TEMP_CACHE_DIR = "/tmp/huggingface_cache"
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os.environ["TRANSFORMERS_CACHE"] = TEMP_CACHE_DIR
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os.environ["HF_HOME"] = TEMP_CACHE_DIR
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# Modèles Hugging Face
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HF_TOKEN = os.getenv("HF_TOKEN")
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client = InferenceClient(token=HF_TOKEN)
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MODELS = {
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"summary": "facebook/bart-large-cnn",
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"caption": "Salesforce/blip-image-captioning-large",
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"qa": "distilbert-base-cased-distilled-squad" # Modèle QA léger
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}
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# Pipeline QA pour distilbert-base-cased-distilled-squad
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qa_pipeline = pipeline("question-answering", model=MODELS["qa"], tokenizer=MODELS["qa"], cache_dir=TEMP_CACHE_DIR)
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# Modèles Pydantic
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class FileInfo(BaseModel):
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file_id: Optional[str] = None
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question: str
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# Fonctions utilitaires (extraction de texte, etc.)
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def extract_text_from_pdf(file_path: str) -> str:
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try:
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doc = fitz.open(file_path)
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async def test_api():
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return {"status": "API working", "environment": "Hugging Face" if os.environ.get("HF_SPACE") else "Local"}
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# Endpoints (upload, summarize, caption, answer, etc.)
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@app.post("/api/upload")
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async def upload_files(files: List[UploadFile] = File(...)):
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logger.info(f"Upload request received with {len(files)} files")
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logger.error(f"Upload error: {e}")
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raise HTTPException(500, f"Erreur lors de l'upload: {str(e)}")
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@app.post("/api/answer")
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async def answer_question(request: QARequest):
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try:
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logger.error(f"QA error: {e}")
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raise HTTPException(500, f"Erreur de réponse: {str(e)}")
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# Gestion des erreurs
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@app.exception_handler(HTTPException)
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async def http_exception_handler(request, exc):
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