app.py

import streamlit as st
import weave
from dotenv import load_dotenv

from guardrails_genie.guardrails import GuardrailManager
from guardrails_genie.guardrails.injection import SurveyGuardrail
from guardrails_genie.llm import OpenAIModel

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

openai_model = st.sidebar.selectbox("OpenAI LLM", ["", "gpt-4o-mini", "gpt-4o"])
chat_condition = openai_model != ""

guardrails = []

with st.sidebar.expander("Switch on Guardrails"):
    is_survey_guardrail_enabled = st.toggle("Survey Guardrail", value=True)

    if is_survey_guardrail_enabled:
        guardrails.append(SurveyGuardrail(llm_model=OpenAIModel(model_name="gpt-4o")))

guardrails_manager = GuardrailManager(guardrails=guardrails)

# Use session state to track if the chat has started
if "chat_started" not in st.session_state:
    st.session_state.chat_started = False

# Start chat when button is pressed
if st.sidebar.button("Start Chat") and chat_condition:
    st.session_state.chat_started = True

# Display chat UI if chat has started
if st.session_state.chat_started:
    st.title("Guardrails Genie")

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

    llm_model = OpenAIModel(model_name=openai_model)

    # 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})

        guardrails_response, call = guardrails_manager.guard.call(
            guardrails_manager, prompt=prompt
        )

        if guardrails_response["safe"]:
            response, call = llm_model.predict.call(
                llm_model, user_prompts=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 + f"\n\n---\n[Explore in Weave]({call.ui_url})")
            # Add assistant response to chat history
            st.session_state.messages.append({"role": "assistant", "content": response})
        else:
            st.error("Guardrails detected an issue with the prompt.")
            for alert in guardrails_response["alerts"]:
                st.error(f"{alert['guardrail_name']}: {alert['response']}")
            st.error(f"For details, explore in Weave at {call.ui_url}")