added on_chat_start

app.py

@@ -79,47 +79,63 @@ recursive_index_faiss = VectorStoreIndex(nodes=base_nodes+objects, storage_conte
 # We'll need to do a couple steps:
 # 1. Initalize our reranker using `FlagEmbeddingReranker` powered by the `BAAI/bge-reranker-large`.
 # 2. Set up our recursive query engine!
-
 reranker = FlagEmbeddingReranker(
     top_n=5,
     model="BAAI/bge-reranker-large",
 )
 
-# recursive_query_engine = recursive_index_faiss.as_query_engine(
-#     similarity_top_k=5,
-#     node_postprocessors=[reranker],
-#     verbose=True
-# )
-
 
-# ChatOpenAI Templates
-system_template = """Use the following pieces of context to answer the user's question.
-If you don't know the answer, say that you don't know, do not try to make up an answer. 
-ALWAYS return a "SOURCES" part in your answer.
-The "SOURCES" part should be a reference to the source inside the document from which you got your answer.
-You are a helpful assistant who always speaks in a pleasant tone! """
+def resursive_fn(reranker):
+    recursive_query_engine = recursive_index_faiss.as_query_engine(
+        similarity_top_k=5,
+        node_postprocessors=[reranker],
+        verbose=True
+    )
 
-user_template = """ Think through your response step by step."""
+    return recursive_query_engine
 
-#user_query = "Who are the E-VP, Operations - and how old are they?"
-# prompt=system_template + user_query + user_template
+recursive_fn_val = resursive_fn(reranker)
 
-async def recursive_fn_call(reranker, system_template, user_template, user_query=None):
-    recursive_query_engine = recursive_index_faiss.as_query_engine(
-    similarity_top_k=5,
-    node_postprocessors=[reranker],
-    verbose=True
-    )
-    response = recursive_query_engine.query(system_template + user_query + user_template)
-    return response
+@cl.on_chat_start 
+async def start_chat():
+    print("A new chat session has started!") 
+    
+    
+    
+    
+    # ChatOpenAI Templates
+    system_template = """Use the following pieces of context to answer the user's question.
+    If you don't know the answer, say that you don't know, do not try to make up an answer. 
+    ALWAYS return a "SOURCES" part in your answer.
+    The "SOURCES" part should be a reference to the source inside the document from which you got your answer.
+    You are a helpful assistant who always speaks in a pleasant tone! """
+    
+    user_template = """ Think through your response step by step."""
+    
+    #user_query = "Who are the E-VP, Operations - and how old are they?"
+    
+    cl.user_session.set("recursive_query_engine", recursive_fn_val)
+    
 
 @cl.on_message  # marks a function that should be run each time the chatbot receives a message from a user
 async def main(message: cl.Message):
     settings = cl.user_session.get("settings")
-
-    user_query = message.content
     
-    response = await recursive_fn_call(reranker, system_template, user_template, user_query=user_query)
+    user_query = message.content
+    print("inside on_message - user_query: ",user_query)
+    prompt=system_template + user_query + user_template
+
+    recursive_query_engine = cl.user_session.get("recursive_query_engine")
+    print("inside on_message - recursive_query_engine: ",recursive_query_engine)
+
+    response = await recursive_query_engine.query(prompt)
+
+    print("inside on_message - response: ",response)
+
     str_resp ="{}".format(response)
+    
+    # response = await recursive_fn_call(recursive_query_engine, system_template, user_template, user_query=user_query)
     msg = cl.Message(content= str_resp)
+    print("inside on_message - after msg: ",msg)
+
     await msg.send()