import streamlit as st
from src.main import ConversationalResponse
import os

# Constants
ROLE_USER = "user"
ROLE_ASSISTANT = "assistant"

st.set_page_config(page_title="Chat with Git", page_icon="🦜")
st.title("Chat with Git 🤖📚")
st.markdown("by [Rohan Kataria](https://www.linkedin.com/in/imrohan/) view more at [VEW.AI](https://vew.ai/)")
st.markdown("This app allows you to chat with Git code files. You can paste link to the Git repository and ask questions about it. In the backround uses the Git Loader and ConversationalRetrival chain from langchain, Streamlit for UI.")

@st.cache_resource(ttl="1h")
def load_agent(url, branch, file_filter):
    with st.spinner('Loading Git documents...'):
        agent = ConversationalResponse(url, branch, file_filter)
    st.success("Git Loaded Successfully")
    return agent

def main():
    api_key = st.sidebar.text_input("Enter your OpenAI API Key", type="password")
    if api_key:
        os.environ["OPENAI_API_KEY"] = api_key
    else:
        st.sidebar.error("Please enter your OpenAI API Key.")
        return

    git_link = st.sidebar.text_input("Enter your Git Link")
    branch = st.sidebar.text_input("Enter your Git Branch")
    file_filter = st.sidebar.text_input("Enter the Extension of Files to Load eg. py,sql,r (no spaces)")

    if "agent" not in st.session_state:
        st.session_state["agent"] = None

    if st.sidebar.button("Load Agent"):
        if git_link and branch and file_filter:
            try:
                st.session_state["agent"] = load_agent(git_link, branch, file_filter)
                st.session_state["messages"] = [{"role": ROLE_ASSISTANT, "content": "How can I help you?"}]
            except Exception as e:
                st.sidebar.error(f"Error loading Git repository: {str(e)}")
                return

    if st.session_state["agent"]:  # Chat will only appear if the agent is loaded
        for msg in st.session_state.messages:
            st.chat_message(msg["role"]).write(msg["content"])

        user_query = st.chat_input(placeholder="Ask me anything!")

        if user_query:
            st.session_state.messages.append({"role": ROLE_USER, "content": user_query})
            st.chat_message(ROLE_USER).write(user_query)

            # Generate the response
            with st.spinner("Generating response"):
                response = st.session_state["agent"](user_query)

            # Display the response immediately
            st.chat_message(ROLE_ASSISTANT).write(response)

            # Add the response to the message history
            st.session_state.messages.append({"role": ROLE_ASSISTANT, "content": response})

if __name__ == "__main__":
    main()