Update app.py

app.py

@@ -8,7 +8,6 @@ from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import FAISS
 from langchain.vectorstores import Chroma
 from langchain.chains import ConversationalRetrievalChain
-from langchain.memory import ConversationBufferMemory
 import gradio as gr
 import openai
 from langchain import PromptTemplate, OpenAI, LLMChain
@@ -126,15 +125,12 @@ class Chatbot:
             str: The answer to the question.
         """
 
-        chat_history = []
         # Retrieve the knowledge base from the state dictionary
         knowledge_base = state["knowledge_base"]
         retriever = knowledge_base.as_retriever()
-        chat_history.append(question)
         qa = ConversationalRetrievalChain.from_llm(
-            llm=OpenAI(temperature=0),
+            llm=OpenAI(temperature=0.5),
             retriever=retriever,
-            memory=ConversationBufferMemory(memory_key="chat_history",return_messages=True),
             return_source_documents=False)
         # Set the question for which we want to find the answer
         res = []
@@ -149,7 +145,6 @@ class Chatbot:
         result = qa({"question": query, "chat_history": chat_history})
         # Perform a similarity search on the knowledge base to retrieve relevant documents
         response = result["answer"]
-        chat_history.append(response)
         # Return the response as the answer to the question
         history[-1][1] = response
         return history