chat.py

import streamlit as st
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.llms.openai import OpenAI
from llama_index.embeddings.openai import OpenAIEmbedding
from llama_index.core import Settings

from traceloop.sdk import Traceloop

Traceloop.init()

Settings.llm = OpenAI(model="gpt-3.5-turbo")
Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small")


st.set_page_config(
    page_title="LlamaIndex + OpenLLMetry demo",
    page_icon="🦙",
    layout="centered",
    initial_sidebar_state="auto",
    menu_items=None,
)
st.title("Chat App with LlamaIndex and OpenLLMetry")
st.info("Ask me a question about Paul Graham's essays!")

if "messages" not in st.session_state.keys():  # Initialize the chat messages history
    st.session_state.messages = [
        {
            "role": "assistant",
            "content": "Ask me a question about Paul Graham's essays!",
        }
    ]


@st.cache_resource(show_spinner=False)
def load_data():
    with st.spinner(text="Loading and indexing Paul Grahm's blog post."):
        reader = SimpleDirectoryReader(input_dir="./data")
        docs = reader.load_data()
        index = VectorStoreIndex.from_documents(docs)
        return index


index = load_data()

if "chat_engine" not in st.session_state.keys():  # Initialize the chat engine
    st.session_state.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 = st.session_state.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