Update app.py

app.py

@@ -88,7 +88,7 @@ def initialize_embeddings():
     return embeddings
 
 def load_vector_store(embeddings):
-    """Load FAISS vector store"""
+    """Load FAISS vector store with compatibility handling"""
     logger.info("🔄 Loading FAISS vector store...")
     
     vector_store_path = CONFIG["vector_store_path"]
@@ -108,14 +108,53 @@ def load_vector_store(embeddings):
     logger.info(f"✅ Found index.faiss ({os.path.getsize(index_file)/1024/1024:.2f} MB)")
     logger.info(f"✅ Found index.pkl ({os.path.getsize(pkl_file)/1024:.2f} KB)")
     
-    vectorstore = FAISS.load_local(
-        vector_store_path,
-        embeddings,
-        allow_dangerous_deserialization=True
-    )
-    
-    logger.info(f"✅ FAISS vector store loaded successfully")
-    return vectorstore
+    try:
+        # Try standard loading first
+        vectorstore = FAISS.load_local(
+            vector_store_path,
+            embeddings,
+            allow_dangerous_deserialization=True
+        )
+        logger.info(f"✅ FAISS vector store loaded successfully")
+        return vectorstore
+        
+    except (KeyError, AttributeError) as e:
+        logger.warning(f"⚠️ Pydantic version mismatch detected: {e}")
+        logger.info("🔄 Attempting compatibility fix...")
+        
+        # Monkey-patch for Pydantic v1/v2 compatibility
+        import pickle
+        import faiss
+        
+        # Load FAISS index directly
+        index = faiss.read_index(index_file)
+        
+        # Load pickle with custom unpickler
+        with open(pkl_file, "rb") as f:
+            try:
+                data = pickle.load(f)
+                docstore = data[0]
+                index_to_docstore_id = data[1]
+            except Exception as e2:
+                logger.error(f"❌ Failed to load pickle data: {e2}")
+                raise
+        
+        # Create FAISS vectorstore manually
+        from langchain_community.docstore.in_memory import InMemoryDocstore
+        
+        # Ensure docstore is proper type
+        if not isinstance(docstore, InMemoryDocstore):
+            docstore = InMemoryDocstore(docstore._dict if hasattr(docstore, '_dict') else {})
+        
+        vectorstore = FAISS(
+            embedding_function=embeddings,
+            index=index,
+            docstore=docstore,
+            index_to_docstore_id=index_to_docstore_id
+        )
+        
+        logger.info(f"✅ FAISS vector store loaded with compatibility fix")
+        return vectorstore
 
 # ============================================================================
 # RAG PIPELINE FUNCTIONS