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| import streamlit as st | |
| import time | |
| import LlamaIndex_helper as lch | |
| from llama_index.core import Settings | |
| from llama_index.llms.openai import OpenAI | |
| st.set_page_config( | |
| page_title="Work history response generator !", page_icon=":flag-ca:") | |
| st.title("Work history response generator ! 🍁") | |
| st.header("Let's chat :star2:") | |
| DATA_PATH = "data" | |
| Settings.llm = OpenAI(temperature=0.1, model="gpt-4o") | |
| def prepare_top_agents(): | |
| file_names = lch.get_pdf_file_names(DATA_PATH) | |
| relevant_docs = lch.get_relevant_docs(file_names) | |
| agents = lch.building_document_agents(file_names=file_names, | |
| relevant_docs=relevant_docs) | |
| obj_index = lch.define_all_tools(agents=agents, file_names=file_names) | |
| top_agent = lch.create_top_agent(obj_index=obj_index) | |
| return top_agent | |
| top_agent = prepare_top_agents() | |
| YES_MESSAGE = "Hello there, thank you for trying out the app. So, how can I help you today? " | |
| if "messages" not in st.session_state.keys(): | |
| st.session_state.messages = [ | |
| {"role": "assistant", "content": YES_MESSAGE} | |
| ] | |
| for message in st.session_state.messages: # Display the prior chat messages | |
| with st.chat_message(message["role"]): | |
| st.write(message["content"]) | |
| if prompt := st.chat_input("Your question"): # Prompt for user input and save to chat history | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| st.chat_message("user").write(prompt) | |
| with st.chat_message("assistant"): | |
| with st.spinner("Thinking...please be patient"): | |
| response = top_agent.stream_chat(prompt) | |
| # st.write_stream(response.response_gen) | |
| def generate(): | |
| for text in response.response_gen: | |
| yield text | |
| time.sleep(0.05) | |
| st.write_stream(generate) | |
| message = {"role": "assistant", "content": response.response} | |
| st.session_state.messages.append(message) |