changed chain and system prompt

app.py

@@ -122,7 +122,7 @@ async def main(message: cl.Message):
         memory: ConversationBufferMemory = tools['memory']
 
         # using query search for ArXiv documents and index files(on message) 
-        await cl.make_async(search_and_index)(message=message, quantity=1, embedder=embedder, index=index)
+        await cl.make_async(search_and_index)(message=message, quantity=10, embedder=embedder, index=index)
 
         text_field = "source_document"
         index = pinecone.Index(INDEX_NAME)
@@ -145,6 +145,8 @@ async def main(message: cl.Message):
     async for chunk in retrieval_augmented_qa_chain.astream({"question": f"{message.content}", "chat_history": memory.buffer_as_messages}):
         if res:= chunk.get('response'):
             await sys_message.stream_token(res.content)
+        if chunk.get("context"):
+            pprint(chunk.get("context"))
     await sys_message.send()
 
     memory.chat_memory.add_user_message(message.content)

utils/chain.py

@@ -1,7 +1,7 @@
 from operator import itemgetter
 from langchain_core.vectorstores import VectorStoreRetriever
 from langchain.schema.runnable import RunnableLambda, RunnableParallel, RunnableSequence
-from langchain.chat_models import ChatOpenAI
+from langchain.chat_models import ChatOpenAI, AzureChatOpenAI
 from langchain.prompts import PromptTemplate, ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.documents import Document
 from langchain_core.messages.ai import AIMessage
@@ -22,13 +22,17 @@ User question: {question}
 prompt = PromptTemplate.from_template(template=template)
 chat_prompt = ChatPromptTemplate.from_messages([
     ("system", """
-     You are a helpful assistant, your job is to answer the user's question using the relevant context:
+     You are a helpful assistant, your job is to answer the user's question using the relevant context in the context section and in the conversation history.
+     Make sure to relate the question to the conversation history and the context in the context section. If the question, the context and the conversation history
+     does not align please let the user know about this and ask for further clarification.
      =========
      CONTEXT: 
      {context}
      =========
+     PREVIOUS CONVERSATION HISTORY:
+     {chat_history}
      """),
-     MessagesPlaceholder(variable_name="chat_history"),
+    #  MessagesPlaceholder(variable_name="chat_history"),
      ("human", "{question}")
 ])
 
@@ -52,18 +56,19 @@ def create_chain(**kwargs) -> RunnableSequence:
     """
     
     retriever: VectorStoreRetriever = kwargs["retriever"]
-    llm:ChatOpenAI = kwargs.get("llm", None)
+    llm: AzureChatOpenAI = kwargs.get("llm", None)
     
 
     if not isinstance(retriever, VectorStoreRetriever):
         raise ValueError
-    if not isinstance(llm, ChatOpenAI):
+    if not isinstance(llm, AzureChatOpenAI):
         raise ValueError
 
     docs_chain = (itemgetter("question") | retriever).with_config(config={"run_name": "docs"})
     self_knowledge_chain = (itemgetter("question") | llm | to_doc).with_config(config={"run_name": "self knowledge"})
     response_chain = (chat_prompt | llm).with_config(config={"run_name": "response"})
     merge_docs_link = RunnableLambda(merge_docs).with_config(config={"run_name": "merge docs"})
+    
     context_chain = (
         RunnableParallel(
             {