Update app.py

app.py

@@ -81,26 +81,27 @@ def verify_api_key(authorization: str = Header(...)):
     if token != TEAM_API_KEY:
         raise HTTPException(status_code=403, detail="Invalid or missing API key")
 
-def create_serverless_index(pc, index_name):
-    """Create a Pinecone serverless index using managed model dimensions."""
-    existing_indexes = [index.name for index in pc.list_indexes()]
-    
+def create_serverless_index(pinecone_client, index_name):
+    """Creates a Pinecone serverless index if it doesn't already exist."""
+    existing_indexes = [index_info.name for index_info in pinecone_client.list_indexes().indexes]
     if index_name not in existing_indexes:
-        pc.create_index(
+        print(f"🪄 Creating serverless index: {index_name}")
+        pinecone_client.create_index(
             name=index_name,
-            dimension=1024,  # multilingual-e5-large output dimension
-            metric="cosine",
+            dimension=768,  # or 384 depending on your embedding model
+            metric='cosine',
             spec={
-                "serverless": {
-                     cloud='gcp',          # ✅ Use GCP for Free Tier
-                     region='us-central1'  # ✅ Free Tier supported region
+                'serverless': {
+                    'cloud': 'gcp',             # ✅ Required for Free Tier
+                    'region': 'gcp-starter'     # ✅ Required for Free Tier
                 }
             }
         )
-        print(f"✅ Created serverless index: {index_name}")
-    
-    # Return index object
-    return pc.Index(index_name)
+        print("✅ Index created.")
+    else:
+        print(f"⚠️ Index '{index_name}' already exists.")
+    return pinecone_client.Index(index_name)
+
 
 async def embed_with_pinecone_inference(pc, texts, model="multilingual-e5-large"):
     """Use Pinecone's hosted inference model for embeddings."""