Upload app.py

app.py

@@ -24,12 +24,12 @@ embeddings = HuggingFaceEmbeddings(
     model_kwargs={"trust_remote_code": True, "revision": "289f532e14dbbbd5a04753fa58739e9ba766f3c7"},
 )
 
-index_path = Path("index.faiss")
+index_path = Path("models/index.faiss")
 if not index_path.exists():
     raise FileNotFoundError("FAISS index not found. Please generate it and place it in 'ipc_vector_db'.")
 
 # Load the FAISS index
-db = FAISS.load_local("AI LAW CHATBOT", embeddings, allow_dangerous_deserialization=True)
+db = FAISS.load_local("models", embeddings, allow_dangerous_deserialization=True)
 db_retriever = db.as_retriever(search_type="similarity", search_kwargs={"k": 4})
 
 # Define the prompt template for the legal chatbot