mindnet/app/frontend/ui_chat.py

"""
FILE: app/frontend/ui_chat.py
DESCRIPTION: Chat-UI. Rendert Nachrichtenverlauf, Quellen-Expanders mit Feedback-Buttons und delegiert bei Bedarf an den Editor.
VERSION: 2.6.0
STATUS: Active
DEPENDENCIES: streamlit, ui_api, ui_editor
LAST_ANALYSIS: 2025-12-15
"""

import streamlit as st
from ui_api import send_chat_message, submit_feedback
from ui_editor import render_draft_editor

def render_chat_interface(top_k, explain):
    """
    Rendert das Chat-Interface.
    Zeigt Nachrichten an und behandelt User-Input.
    """
    # 1. Verlauf anzeigen
    for idx, msg in enumerate(st.session_state.messages):
        with st.chat_message(msg["role"]):
            if msg["role"] == "assistant":
                # Intent Badge
                intent = msg.get("intent", "UNKNOWN")
                st.markdown(f'<div class="intent-badge">Intent: {intent}</div>', unsafe_allow_html=True)
                
                # Debugging (optional, gut für Entwicklung)
                with st.expander("🐞 Payload", expanded=False):
                    st.json(msg)

                # Unterscheidung: Normaler Text oder Editor-Modus (Interview)
                if intent == "INTERVIEW":
                    render_draft_editor(msg)
                else:
                    st.markdown(msg["content"])
                
                # Quellen anzeigen
                if "sources" in msg and msg["sources"]:
                    for hit in msg["sources"]:
                        score = hit.get('total_score', 0)
                        # Wenn score None ist, 0.0 annehmen
                        if score is None: score = 0.0
                            
                        with st.expander(f"📄 {hit.get('note_id', '?')} ({score:.2f})"):
                            st.markdown(f"_{hit.get('source', {}).get('text', '')[:300]}..._")
                            
                            # Explanation Layer
                            if hit.get('explanation'):
                                st.caption(f"Grund: {hit['explanation']['reasons'][0]['message']}")
                            
                            # Feedback Buttons pro Source
                            def _cb(qid=msg.get("query_id"), nid=hit.get('node_id')):
                                val = st.session_state.get(f"fb_src_{qid}_{nid}")
                                if val is not None: submit_feedback(qid, nid, val+1)
                            
                            st.feedback("faces", key=f"fb_src_{msg.get('query_id')}_{hit.get('node_id')}", on_change=_cb)
                
                # Globales Feedback für die Antwort
                if "query_id" in msg:
                    qid = msg["query_id"]
                    st.feedback("stars", key=f"fb_glob_{qid}", on_change=lambda: submit_feedback(qid, "generated_answer", st.session_state[f"fb_glob_{qid}"]+1))
            else:
                # User Nachricht
                st.markdown(msg["content"])

    # 2. Input Feld
    if prompt := st.chat_input("Frage Mindnet..."):
        st.session_state.messages.append({"role": "user", "content": prompt})
        st.rerun()
        
    # 3. Antwort generieren (wenn letzte Nachricht vom User ist)
    if len(st.session_state.messages) > 0 and st.session_state.messages[-1]["role"] == "user":
        with st.chat_message("assistant"):
            with st.spinner("Thinking..."):
                resp = send_chat_message(st.session_state.messages[-1]["content"], top_k, explain)
            
            if "error" in resp:
                st.error(resp["error"])
            else:
                st.session_state.messages.append({
                    "role": "assistant",
                    "content": resp.get("answer"),
                    "intent": resp.get("intent", "FACT"),
                    "sources": resp.get("sources", []),
                    "query_id": resp.get("query_id")
                })
                st.rerun()