app.py

import streamlit as st
import weave
from dotenv import load_dotenv

from guardrails_genie.llm import OpenAIModel

load_dotenv()
weave.init(project_name="guardrails-genie")

st.title("Echo Bot")

# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = []

llm_model = OpenAIModel(model_name="gpt-4o-mini")

# Display chat messages from history on app rerun
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# React to user input
if prompt := st.chat_input("What is up?"):
    # Display user message in chat message container
    st.chat_message("user").markdown(prompt)
    # Add user message to chat history
    st.session_state.messages.append({"role": "user", "content": prompt})

    response = llm_model.predict(prompt, messages=st.session_state.messages)
    response = response.choices[0].message.content
    # Display assistant response in chat message container
    with st.chat_message("assistant"):
        st.markdown(response)
    # Add assistant response to chat history
    st.session_state.messages.append({"role": "assistant", "content": response})