# components/chat.py

import streamlit as st
from langchain_core.messages import HumanMessage, AIMessage
from utils.database import verify_vector_store
from threading import Lock
from typing import Optional
import traceback
from utils.response_formatter import EnhancedResponseFormatter, display_enhanced_response


# Create a lock for QA system access
qa_lock = Lock()

def display_chat_interface():
    """Display chat interface with proper formatting."""
    if not st.session_state.get('messages'):
        st.session_state.messages = []

    # Display chat messages
    for message in st.session_state.messages:
        if isinstance(message, HumanMessage):
            with st.chat_message("user"):
                st.write(message.content)
        elif isinstance(message, AIMessage):
            with st.chat_message("assistant"):
                display_enhanced_response(message.content, message.additional_kwargs.get('sources'))

    # Chat input
    if prompt := st.chat_input("Ask about your documents..."):
        with st.chat_message("user"):
            st.write(prompt)
            st.session_state.messages.append(HumanMessage(content=prompt))

        with st.chat_message("assistant"):
            with st.spinner("Analyzing documents..."):
                response = st.session_state.qa_system.invoke({
                    "input": prompt,
                    "chat_history": st.session_state.messages
                })
                
                if response:
                    ai_message = AIMessage(
                        content=str(response),
                        additional_kwargs={'sources': response.metadata.get('sources', [])}
                    )
                    st.session_state.messages.append(ai_message)
                    display_enhanced_response(
                        str(response),
                        response.metadata.get('sources', [])
                    )

def _verify_chat_ready() -> bool:
    """Check if the chat system is properly initialized."""
    if 'qa_system' not in st.session_state or st.session_state.qa_system is None:
        st.warning("Please upload documents first to initialize the chat system.")
        return False
    return True


def _process_user_message(prompt: str):
    """Process a new user message and generate AI response."""
    try:
        with st.spinner("Analyzing..."):
            # Create and display user message
            human_message = HumanMessage(content=prompt)
            st.session_state.messages.append(human_message)
            with st.chat_message("user"):
                st.write(prompt)

            # Generate AI response with source tracking
            with qa_lock:
                response = st.session_state.qa_system.invoke({
                    "input": prompt,
                    "chat_history": st.session_state.messages
                })

            if response:
                # Extract sources from response metadata
                sources = response.metadata.get('sources', []) if hasattr(response, 'metadata') else []
                
                # Create and display AI message with enhanced formatting
                ai_message = AIMessage(
                    content=str(response),
                    additional_kwargs={'sources': sources}
                )
                st.session_state.messages.append(ai_message)
                
                with st.chat_message("assistant"):
                    display_enhanced_response(
                        str(response),
                        sources=sources
                    )
                
                st.rerun()
            else:
                st.error("No response received. Please try again.")

    except Exception as e:
        st.error(f"An error occurred while processing your message: {str(e)}")
        if st.session_state.get('debug_mode'):
            st.error(traceback.format_exc())

def _display_chat_history():
    """Display all messages in the chat history."""
    for message in st.session_state.messages:
        if isinstance(message, HumanMessage):
            with st.chat_message("user"):
                st.write(message.content)
        elif isinstance(message, AIMessage):
            with st.chat_message("assistant"):
                st.write(message.content)