Uldated app.py

app.py

@@ -24,18 +24,24 @@ if not GOOGLE_API_KEY:
 genai.configure(api_key=GOOGLE_API_KEY)
 
 # ——— Load or fallback LeetCode data ——————————————————————————
+OUTPUT_FILE = "leetcode_downloaded.xlsx"
 GOOGLE_SHEET_URL = "https://docs.google.com/spreadsheets/d/1KK9Mnm15hV3ALJo-quJndftWfaujJ7K2_zHMCTo5mGE/"
 FILE_ID = GOOGLE_SHEET_URL.split("/d/")[1].split("/")[0]
 DOWNLOAD_URL = f"https://drive.google.com/uc?export=download&id={FILE_ID}"
-OUTPUT_FILE = "leetcode_downloaded.xlsx"
 
 try:
-    print("Downloading LeetCode data...")
-    gdown.download(DOWNLOAD_URL, OUTPUT_FILE, quiet=False)
-    LEETCODE_DATA = pd.read_excel(OUTPUT_FILE)
+    if os.path.exists(OUTPUT_FILE):
+        print(f"Loading LeetCode data from local file: {OUTPUT_FILE}")
+        LEETCODE_DATA = pd.read_excel(OUTPUT_FILE)
+    else:
+        print("Local LeetCode file not found. Attempting to download...")
+        print("Downloading LeetCode data...")
+        gdown.download(DOWNLOAD_URL, OUTPUT_FILE, quiet=False)
+        LEETCODE_DATA = pd.read_excel(OUTPUT_FILE)
     print(f"Loaded {len(LEETCODE_DATA)} problems")
-except Exception:
-    print("Failed to download/read. Using fallback.")
+except Exception as e:
+    print(f"Failed to load or download LeetCode data: {str(e)}")
+    print("Using fallback dataset.")
     LEETCODE_DATA = pd.DataFrame([
         {"problem_no": 3151, "problem_level": "Easy", "problem_statement": "special array",
          "problem_link": "https://leetcode.com/problems/special-array-i/?envType=daily-question&envId=2025-06-01"},
@@ -284,6 +290,7 @@ User Query: {query}
         user_sessions.setdefault(session_key, {"history": []})
 
         tool_name, args = self._classify_intent(query)
+        print(f"Selected tool: {tool_name}, args: {args}")  # Debug log
         
         if tool_name not in self.tools:
             return f"I couldn't understand your request. Please try asking for:\n- Daily coding question\n- Mock interview\n- Interview questions for a specific topic"
@@ -314,6 +321,7 @@ class ChatResponse(BaseModel):
 @app.post("/chat", response_model=ChatResponse)
 async def chat(req: ChatRequest):
     q = preprocess_query(req.question)
+    print(f"Preprocessed query: {q}")  # Debug log
     ans = agent.process_query(q, req.user_id, req.session_id)
     return ChatResponse(session_id=req.session_id, answer=ans)
 
@@ -330,4 +338,4 @@ def root():
 
 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)