app.py

import streamlit as st
from llama_index import VectorStoreIndex, ServiceContext
from llama_index.llms import OpenAI
import openai
from llama_index import SimpleDirectoryReader


# Setup OpenAI key and initialize message history
openai.api_key = st.secrets.openai_key
st.header("Chat with the Streamlit docs 💬 📚")

if "messages" not in st.session_state.keys(): # Initialize the chat message history
    st.session_state.messages = [
        {"role": "assistant", "content": "Ask me a question about Streamlit's open-source Python library!"}
    ]


@st.cache_resource(show_spinner=False)
def load_data():
    with st.spinner(text="Loading and indexing the Streamlit docs – hang tight! This should take 1-2 minutes."):
        reader = SimpleDirectoryReader(input_dir="./data", recursive=True)
        docs = reader.load_data()
        service_context = ServiceContext.from_defaults(llm=OpenAI(model="gpt-3.5-turbo", temperature=0.5, system_prompt="You are an expert on the Streamlit Python library and your job is to answer technical questions. Assume that all questions are related to the Streamlit Python library. Keep your answers technical and based on facts – do not hallucinate features."))
        index = VectorStoreIndex.from_documents(docs, service_context=service_context)
        return index


def main():
    index = load_data()

    chat_engine = index.as_chat_engine(chat_mode="condense_question", verbose=True)

    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})

    for message in st.session_state.messages: # Display the prior chat messages
        with st.chat_message(message["role"]):
            st.write(message["content"])

    # If last message is not from assistant, generate a new response
    if st.session_state.messages[-1]["role"] != "assistant":
        with st.chat_message("assistant"):
            with st.spinner("Thinking..."):
                response = chat_engine.chat(prompt)
                st.write(response.response)
                message = {"role": "assistant", "content": response.response}
                st.session_state.messages.append(message) # Add response to message history


if __name__ == "__main__":
    main()