Update app.py

app.py

@@ -41,8 +41,8 @@ def get_text_chunks(text):
 
 
 def get_vectorstore(text_chunks):
-    # embeddings = OpenAIEmbeddings()
-    embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
+    embeddings = OpenAIEmbeddings()
+    # embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-xl")
     # embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/paraphrase-multilingual-mpnet-base-v2")
     vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
 
@@ -50,25 +50,25 @@ def get_vectorstore(text_chunks):
 
 
 def get_conversation_chain(vectorstore, model_name):
-    llm = LlamaCpp(model_path=model_name,
-                   temperature=0.1,
-                   top_k=30,
-                   top_p=0.9,
-                   streaming=True,
-                   n_ctx=2048,
-                   n_parts=1,
-                   echo=True
-                   )
-
-    # llm = ChatOpenAI()
+    #llm = LlamaCpp(model_path=model_name,
+    #               temperature=0.1,
+    #               top_k=30,
+    #               top_p=0.9,
+    #               streaming=True,
+    #               n_ctx=2048,
+    #               n_parts=1,
+    #               echo=True
+    #               )
+
+    llm = ChatOpenAI()
     
-    memory = ConversationBufferMemory(memory_key='chat_history', input_key='question', output_key='answer', return_messages=True)
+    memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
     
     conversation_chain = ConversationalRetrievalChain.from_llm(llm=llm,
                                                                # condense_question_prompt=CONDENSE_QUESTION_PROMPT,
                                                                retriever=vectorstore.as_retriever(),
                                                                memory=memory,
-                                                               return_source_documents=True
+                                                               #return_source_documents=True
                                                                )
 
     return conversation_chain
@@ -79,15 +79,15 @@ def handle_userinput(user_question):
 
     st.session_state.chat_history = response['chat_history']
 
-    st.session_state.retrieved_text = response['source_documents'][0]
+    #st.session_state.retrieved_text = response['source_documents'][0]
 
-    for i, (message, text) in enumerate(zip(st.session_state.chat_history, st.session_state.retrieved_text)):
+    for i, message in enumerate(st.session_state.chat_history):
         if i % 2 == 0:
             st.write(user_template.replace(
-                "{{MSG}}", message.content, text.content), unsafe_allow_html=True)
+                "{{MSG}}", message.content), unsafe_allow_html=True)
         else:
             st.write(bot_template.replace(
-                "{{MSG}}", message.content, text.content), unsafe_allow_html=True)
+                "{{MSG}}", message.content), unsafe_allow_html=True)