Update app/api/routes.py

app/api/routes.py

@@ -122,42 +122,6 @@ async def get_all_chats():
 # ---------------------------------------------------
 # ✅ Delete Chat (Qdrant + Mongo + File)
 # ---------------------------------------------------
-# @router.delete("/chat/{chat_id}")
-# async def delete_chat(chat_id: str):
-#     try:
-#         chat = conversations.find_one({"_id": ObjectId(chat_id)})
-#         if not chat:
-#             raise HTTPException(status_code=404, detail="Chat not found")
-
-#         doc_id = chat.get("doc_id")
-#         qdrant_collection = chat.get("qdrant_collection")
-
-#         # ✅ Delete embeddings from Qdrant
-#         try:
-#             qdrant_client.delete(
-#                 collection_name=qdrant_collection,
-#                 points_selector=Filter(
-#                     must=[FieldCondition(key="doc_id", match=MatchValue(value=doc_id))]
-#                 ),
-#             )
-#         except Exception as e:
-#             print(f"⚠️ Qdrant delete failed: {e}")
-
-#         # ✅ Delete uploaded file
-#         file_path = chat.get("file_path")
-#         if file_path and os.path.exists(file_path):
-#             os.remove(file_path)
-
-#         # ✅ Delete from MongoDB
-#         conversations.delete_one({"_id": ObjectId(chat_id)})
-
-#         return {"status": "success", "message": "Chat deleted successfully"}
-
-#     except Exception as e:
-#         raise HTTPException(status_code=500, detail=str(e))
-
-
-
 @router.delete("/chat/{chat_id}")
 async def delete_chat(chat_id: str):
     try:
@@ -193,7 +157,6 @@ async def delete_chat(chat_id: str):
 
 
 
-
 # ---------------------------------------------------
 # ✅ Chat Query Endpoint (Persistent Memory)
 # ---------------------------------------------------
@@ -216,16 +179,7 @@ async def query_pdf(doc_id: str = Form(...), question: str = Form(...)):
 
     # ✅ Vector Search
     question_vector = embedder.encode([question])[0].tolist()
-    # hits = qdrant.search(
-    #     collection_name=COLLECTION_NAME,
-    #     query_vector=question_vector,
-    #     query_filter=Filter(
-    #         must=[FieldCondition(key="doc_id", match=MatchValue(value=doc_id))]
-    #     ),
-    #     limit=5,
-    # )
-
-
+    
     hits = qdrant_client.query_points(
         collection_name=COLLECTION_NAME,
         query=question_vector,
@@ -262,5 +216,4 @@ async def get_conversation(doc_id: str):
     doc = conversations.find_one({"doc_id": doc_id})
     if not doc:
         return {"history": []}
-    return {"history": doc.get("history", [])}
-
+    return {"history": doc.get("history", [])}