Update app.py

app.py

@@ -8,10 +8,10 @@ import numpy as np
 import datetime
 
 from langchain.chains import RetrievalQA
-from langchain.llms import OpenAI
 from langchain.schema import Document
 from langchain_core.retrievers import BaseRetriever
 from pydantic import Field
+from langchain_openai import ChatOpenAI  # FIXED: Use ChatOpenAI for chat models
 
 # --- CONFIG ---
 DB_PATH = "json_vector.db"
@@ -52,7 +52,7 @@ def flatten_json_obj(obj, parent_key="", sep="."):
         items[parent_key] = obj
     return items
 
-# --- Embedding function (updated for openai>=1.0.0) ---
+# --- Embedding function (openai>=1.0.0 style) ---
 def get_embedding(text):
     client = openai.OpenAI(api_key=OPENAI_API_KEY)
     response = client.embeddings.create(input=[text], model=EMBEDDING_MODEL)
@@ -154,7 +154,7 @@ class SQLiteVectorRetriever(BaseRetriever):
     def _get_relevant_documents(self, query, run_manager=None, **kwargs):
         return query_vector_db(query, self.top_k)
 
-llm = OpenAI(model="gpt-4.1", openai_api_key=OPENAI_API_KEY, temperature=0)
+llm = ChatOpenAI(model="gpt-4.1", openai_api_key=OPENAI_API_KEY, temperature=0)  # FIXED: use ChatOpenAI!
 retriever = SQLiteVectorRetriever(top_k=5)
 qa_chain = RetrievalQA.from_chain_type(
     llm=llm,