Update app.py

app.py

@@ -1,24 +1,31 @@
+import os
 from fastapi import FastAPI, HTTPException, Query
 import duckdb
 
 app = FastAPI(title="Fast Mobile Search API")
 
-# Global DuckDB connection setup karo aur HTTPFS extension load karo remote files read karne ke liye
+# DuckDB connection setup aur httpfs extension load karo
 con = duckdb.connect()
 con.execute("INSTALL httpfs; LOAD httpfs;")
 
-# Tumhari Hugging Face Parquet file ka direct URL
+# Hugging Face Space ke Secret se token nikalna
+HF_TOKEN = os.environ.get("HF_TOKEN", "")
+
+# Base Parquet URL
 PARQUET_URL = "https://huggingface.co/datasets/tfqdeadlo/Inddatainone/resolve/main/users_data.parquet"
 
+# Agar token maujood hai, toh URL ke sath authenticated request ke liye append karo
+if HF_TOKEN:
+    PARQUET_URL += f"?token={HF_TOKEN}"
+
 @app.get("/")
 def home():
-    return {"message": "API is running. Use /search?mobile=YOUR_NUMBER to find data."}
+    return {"message": "API is running perfectly. Use /search?mobile=YOUR_NUMBER"}
 
 @app.get("/search")
 async def search_mobile(mobile: str = Query(..., description="Enter the mobile number to search")):
     try:
-        # Parameterized query use kar rahe hain taaki SQL injection na ho
-        # read_parquet() seedhe URL se data fetch karega bina download kiye
+        # DuckDB query jo seedhe authenticated URL se data fetch karegi
         query = f"""
             SELECT mobile, name, fname, address, alt, circle, id, email 
             FROM read_parquet('{PARQUET_URL}') 
@@ -26,7 +33,7 @@ async def search_mobile(mobile: str = Query(..., description="Enter the mobile n
             LIMIT 1
         """
         
-        # Query execute karo
+        # Query execute karo aur result fetch karo
         result = con.execute(query, [str(mobile)]).fetchall()
         
         if not result:
@@ -35,7 +42,7 @@ async def search_mobile(mobile: str = Query(..., description="Enter the mobile n
                 "message": f"Mobile number {mobile} nahi mila."
             }
         
-        # Column names nikalne ke liye desc ka use karenge
+        # Columns names nikal kar dictionary format me data convert karo
         columns = [desc[0] for desc in con.description]
         row_dict = dict(zip(columns, result[0]))