linebot_app.py

@@ -13,7 +13,6 @@ from langchain.vectorstores import Chroma
 from langchain.memory import ConversationBufferMemory
 from langchain.chains import RetrievalQA, ConversationalRetrievalChain
 from langchain.retrievers.multi_query import MultiQueryRetriever
-from langchain.prompts import PromptTemplate
 
 from flask import Flask, request, abort
 from linebot.v3 import (
@@ -45,22 +44,15 @@ log_file = open(log_file_name, "w")
 log_file.write("")
 log_file.close()
 
+
+
 # User Sessions
 user_sessions = {}
 
 # init vectorstore embedding
-qa_prompt_template = """
-Use the following pieces of context to answer the question at the end. 
-If you don't know the answer, just say that you don't know, don't try to make up an answer. 
-always add this exact keyphrase "answer_not_found" to the end of the text if you don't know the answer.
-{context}
-Question: {question}
-Helpful Answer:"""
-
 os.environ["OPENAI_API_KEY"] = srv_secrets.openai_key
 llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0)
 vectorstore = Chroma(persist_directory=srv_secrets.chroma_db_dir, embedding_function=OpenAIEmbeddings()) 
-qa_prompt = PromptTemplate.from_template(qa_prompt_template)
 
 # Setup Logging
 logging.basicConfig()
@@ -117,7 +109,7 @@ def message_text(event):
     # User Session
     # create session if none exist
     if event.source.user_id not in user_sessions.keys():
-        user_sessions[event.source.user_id] = ConversationalRetrievalChain.from_llm(llm,retriever=retriever,memory=ConversationBufferMemory(memory_key="chat_history", return_messages=True, combine_docs_chain_kwargs={"prompt": qa_prompt}))
+        user_sessions[event.source.user_id] = ConversationalRetrievalChain.from_llm(llm,retriever=retriever,memory=ConversationBufferMemory(memory_key="chat_history", return_messages=True))
     
     # unique_docs = retriever_from_llm.get_relevant_documents(query=event.message.text)
     with ApiClient(configuration) as api_client:
@@ -133,7 +125,7 @@ def message_text(event):
                 messages=[TextMessage(text=answer)]
             ))
 
-    log_file.write(", bot_answer: " + answer + "\n")
+    log_file.write("bot_answer: " + answer + "\n")
     log_file.close()
 
 #    with ApiClient(configuration) as api_client: