Move chain within on chat start

app.py

@@ -44,34 +44,36 @@ if not os.path.exists(vector_file):
 else:
     vector_store = FAISS.load_local(vector_file, cached_embedder, allow_dangerous_deserialization=True)
 
-prompt_template = ChatPromptTemplate.from_template(
-    "You are a movie recommendation system, for a given {query} find recommendations from {content}."
-)
-retriever = vector_store.as_retriever()
-chat_model = ChatOpenAI(model="gpt-4o", temperature=0.2, openai_api_key=openai_api_key)
-parser = StrOutputParser()
-
-runnable_chain = (
-    {"query": RunnablePassthrough(), "content": retriever}
-    | prompt_template
-    | chat_model
-    | StrOutputParser()
-)
-
 @cl.on_chat_start
 async def on_chat_start():
+    print("On Chat Start")
     await cl.Message(content="Hello, i am your movie recommender, how can i help you today?").send()
+    prompt_template = ChatPromptTemplate.from_template(
+        "You are a movie recommendation system, for a given {query} find recommendations from {content}."
+    )
+    retriever = vector_store.as_retriever()
+    chat_model = ChatOpenAI(model="gpt-4o", temperature=0.2, openai_api_key=openai_api_key)
+    parser = StrOutputParser()
+
+    runnable_chain = (
+        {"query": RunnablePassthrough(), "content": retriever}
+        | prompt_template
+        | chat_model
+        | StrOutputParser()
+    )
     cl.user_session.set("chain", runnable_chain)
 
 
 @cl.on_message
 async def main(message):
+    print("On Message Start")
     chain = cl.user_session.get("chain")
     cb = cl.AsyncLangchainCallbackHandler()
     user_input = cl.Message(content="")
     await user_input.send()
 
     async for stream in chain.astream(user_input, cb):
+        print(stream)
         await user_input.stream_token(stream)
 
     await user_input.update()