Update app.py

app.py

@@ -15,19 +15,53 @@ from typing import Optional
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-app = FastAPI(title="AI Web Services")
+# Initialize FastAPI app
+app = FastAPI(
+    title="AI Web Services",
+    description="API for various AI services including text summarization, image captioning, and document analysis",
+    version="1.0.0"
+)
+
+# Mount static files
 app.mount("/static", StaticFiles(directory="static"), name="static")
 
-# Initialize models (Spaces will cache these)
+# Load AI models
 try:
     logger.info("Loading AI models...")
-    image_pipeline = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
-    text_pipeline = pipeline("text2text-generation", model="t5-small")
+    image_pipeline = pipeline(
+        "image-to-text", 
+        model="Salesforce/blip-image-captioning-base",
+        device="cpu"
+    )
+    text_pipeline = pipeline(
+        "text2text-generation", 
+        model="t5-small",
+        device="cpu"
+    )
     logger.info("Models loaded successfully")
 except Exception as e:
-    logger.error(f"Model loading Failed: {e}")
+    logger.error(f"Model loading failed: {e}")
     raise RuntimeError("Failed to initialize AI models")
 
+# Helper function for text extraction
+async def extract_text(file: UploadFile) -> str:
+    """Extract text from PDF or DOCX files"""
+    try:
+        content = await file.read()
+        
+        if file.filename.endswith(".pdf"):
+            with fitz.open(stream=content, filetype="pdf") as doc:
+                return " ".join(page.get_text() for page in doc)
+        elif file.filename.endswith(".docx"):
+            doc = Document(io.BytesIO(content))
+            return "\n".join(p.text for p in doc.paragraphs)
+        else:
+            raise ValueError("Unsupported file format")
+    except Exception as e:
+        logger.error(f"Text extraction failed: {e}")
+        raise HTTPException(400, f"Could not extract text: {e}")
+
+# API Endpoints
 @app.get("/", response_class=HTMLResponse)
 async def home():
     """Serve the frontend interface"""
@@ -134,27 +168,24 @@ plt.show()"""
         logger.error(f"Visualization error: {e}")
         raise HTTPException(500, "Visualization code generation failed")
 
-async def extract_text(file: UploadFile) -> str:
-    """Extract text from PDF or DOCX files"""
-    try:
-        content = await file.read()
-        
-        if file.filename.endswith(".pdf"):
-            with fitz.open(stream=content, filetype="pdf") as doc:
-                return " ".join(page.get_text() for page in doc)
-        elif file.filename.endswith(".docx"):
-            doc = Document(io.BytesIO(content))
-            return "\n".join(p.text for p in doc.paragraphs)
-        else:
-            raise ValueError("Unsupported file format")
-    except Exception as e:
-        logger.error(f"Text extraction failed: {e}")
-        raise HTTPException(400, f"Could not extract text: {e}")
-
-# Health check endpoint
 @app.get("/health")
 async def health_check():
-    return JSONResponse({"status": "healthy", "models": "loaded"})
-    if __name__ == "__main__":
+    """Health check endpoint"""
+    return JSONResponse({
+        "status": "healthy",
+        "models": {
+            "image_captioning": "loaded",
+            "text_generation": "loaded"
+        }
+    })
+
+# Server initialization
+if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    uvicorn.run(
+        app,
+        host="0.0.0.0",
+        port=8000,
+        log_level="info",
+        reload=True
+    )