Update backend/app.py

backend/app.py

@@ -1,3 +1,4 @@
+import logging
 from fastapi import FastAPI, HTTPException
 from fastapi.staticfiles import StaticFiles
 from fastapi.middleware.cors import CORSMiddleware
@@ -8,16 +9,26 @@ import numpy as np
 import os
 from huggingface_hub import hf_hub_download
 
-# Global dictionary to hold loaded model assets
+# Configure logging to file and stdout
+logging.basicConfig(
+    level=logging.DEBUG,
+    format='%(asctime)s [%(levelname)s] %(message)s',
+    handlers=[
+        logging.FileHandler("space_runtime.log"),
+        logging.StreamHandler()
+    ]
+)
+
+# Global variable to hold model assets
 model_assets = {}
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
-    print("STARTUP: Beginning model assets download and load.")
+    logging.info("STARTUP: Loading model assets...")
     try:
         REPO_ID = "SateeshAmbesange/PragyanAI-Super30_ReactJS_RecommendationSystem"
         use_auth_token = os.environ.get("HUGGING_FACE_HUB_TOKEN") is not None
-        print(f"STARTUP: Downloading model files from repo '{REPO_ID}' with auth token: {use_auth_token}")
+        logging.info(f"Downloading model files from {REPO_ID} with auth token: {use_auth_token}")
 
         movies_file = hf_hub_download(repo_id=REPO_ID, filename="movies_df.joblib", use_auth_token=use_auth_token)
         cosine_file = hf_hub_download(repo_id=REPO_ID, filename="cosine_sim_matrix.joblib", use_auth_token=use_auth_token)
@@ -26,22 +37,24 @@ async def lifespan(app: FastAPI):
         model_assets['cosine_sim'] = joblib.load(cosine_file)
         model_assets['indices'] = pd.Series(model_assets['movies_df'].index, index=model_assets['movies_df']['title'])
 
-        print(f"STARTUP: Model assets loaded successfully with {len(model_assets['movies_df'])} movies.")
+        logging.info(f"Model assets loaded successfully: {len(model_assets['movies_df'])} movies")
     except Exception as e:
-        print(f"FATAL: Failed to download or load model assets: {e}")
+        logging.error(f"FATAL ERROR: Could not load model assets: {e}", exc_info=True)
         model_assets['movies_df'] = None
         model_assets['cosine_sim'] = None
         model_assets['indices'] = None
-        raise e  # Raise exception to prevent app startup on failure
+        raise e
+
     yield
-    print("SHUTDOWN: Clearing model assets.")
+
+    logging.info("SHUTDOWN: Clearing model assets.")
     model_assets.clear()
 
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],   # For production, restrict origins for security
+    allow_origins=["*"],  # For production, restrict this to your frontend domain
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
@@ -49,28 +62,29 @@ app.add_middleware(
 
 @app.get("/api/movies")
 async def get_movie_list():
-    print("API CALL: /api/movies")
+    logging.debug("API CALL: /api/movies")
     movies_df = model_assets.get('movies_df')
     if movies_df is None:
-        print("ERROR: model_assets['movies_df'] is None in /api/movies")
+        logging.error("Model assets unavailable in /api/movies")
         raise HTTPException(status_code=503, detail="Model assets not available.")
+
     titles = movies_df['title'].sort_values().unique().tolist()
-    print(f"API RESPONSE: Serving {len(titles)} movie titles.")
+    logging.debug(f"API RESPONSE: Serving {len(titles)} movie titles")
     return {"movies": titles}
 
 @app.get("/api/recommend")
 async def get_recommendations_api(title: str):
-    print(f"API CALL: /api/recommend for title '{title}'")
+    logging.debug(f"API CALL: /api/recommend for title '{title}'")
     movies_df = model_assets.get('movies_df')
     cosine_sim = model_assets.get('cosine_sim')
     indices = model_assets.get('indices')
 
     if not movies_df or not cosine_sim or not indices:
-        print("ERROR: Model assets missing in /api/recommend")
-        raise HTTPException(status_code=503, detail="Model assets not available.")
+        logging.error("Model assets missing in /api/recommend")
+        raise HTTPException(status_code=503, detail="Model assets are not available.")
 
     if title not in indices:
-        print(f"ERROR: Movie title '{title}' not found in indices")
+        logging.error(f"Movie title '{title}' not found in indices")
         raise HTTPException(status_code=404, detail="Movie not found")
 
     try:
@@ -82,17 +96,16 @@ async def get_recommendations_api(title: str):
             return score if isinstance(score, (int, float, np.number)) and np.isfinite(score) else -1
 
         sim_scores = sorted(sim_scores, key=sort_key, reverse=True)
-        sim_scores = sim_scores[1:11]  # exclude the queried movie itself
+        sim_scores = sim_scores[1:11]  # Exclude the queried movie itself
 
         movie_indices = [i[0] for i in sim_scores]
         recommendations = movies_df.iloc[movie_indices][['title', 'id']].to_dict(orient='records')
 
-        print(f"API RESPONSE: Returning {len(recommendations)} recommendations for '{title}'")
+        logging.debug(f"API RESPONSE: Returning {len(recommendations)} recommendations for '{title}'")
         return {"recommendations": recommendations}
     except Exception as e:
-        print(f"ERROR: Exception in /api/recommend: {e}")
+        logging.error(f"Exception in /api/recommend: {e}", exc_info=True)
         raise HTTPException(status_code=500, detail=f"Internal server error: {e}")
 
-# Serve React static files from 'static' directory
+# Serve React frontend static files from 'static' folder
 app.mount("/", StaticFiles(directory="static", html=True), name="static")
-