"""Module for rendering the PortIQ Portfolio AI chat dialog assistant."""

import streamlit as st
import os
import json
import pandas as pd


def on_chat_date_change():
    # Update chat_context_date to the selector's value
    st.session_state["chat_context_date"] = st.session_state["chat_context_date_selector"]
    # Clear chat history when date context changes
    st.session_state["chat_history"] = []


def on_chat_close():
    st.session_state["show_chat"] = False


def _inject_dialog_styles():
    """Injects CSS scoped exclusively to the PortIQ chat dialog via a unique marker class."""
    st.markdown(
        """
        <style>
        /* ── Force the Streamlit dialog wrapper to be centered & large ── */
        div[data-testid="stDialog"] {
            display: flex !important;
            align-items: center !important;
            justify-content: center !important;
        }

        /* ── PortIQ Chat dialog inner panel ── */
        div[data-testid="stDialog"] > div[role="dialog"] {
            position: relative !important;
            top: unset !important;
            right: unset !important;
            left: unset !important;
            transform: none !important;
            width: min(820px, 92vw) !important;
            max-height: 90vh !important;
            margin: auto !important;
            background: linear-gradient(140deg, #0D1526 0%, #081018 100%) !important;
            border: 1px solid rgba(6, 182, 212, 0.35) !important;
            border-radius: 18px !important;
            box-shadow: 0 28px 72px rgba(0, 0, 0, 0.85), 0 0 0 1px rgba(6, 182, 212, 0.08) !important;
            padding: 0 !important;
            overflow: hidden !important;
        }

        /* ── Dialog title header ── */
        div[data-testid="stDialog"] h2 {
            font-size: 1.15rem !important;
            font-weight: 700 !important;
            color: #06B6D4 !important;
            letter-spacing: -0.02em !important;
            margin: 0 !important;
        }

        /* ── Close (×) button ── */
        div[data-testid="stDialog"] button[aria-label="Close"] {
            color: #64748B !important;
            background: transparent !important;
            border: none !important;
        }
        div[data-testid="stDialog"] button[aria-label="Close"]:hover {
            color: #06B6D4 !important;
        }

        /* ── Scoped: Clear Chat button – cyan ghost style ──
           Targets only buttons inside the unique tcr-chat-dlg marker container */
        .tcr-chat-dlg .stButton > button {
            border: 1px solid rgba(6, 182, 212, 0.45) !important;
            color: #06B6D4 !important;
            background: transparent !important;
            border-radius: 7px !important;
            font-size: 0.82rem !important;
            padding: 4px 12px !important;
            transition: all 0.2s ease !important;
        }
        .tcr-chat-dlg .stButton > button:hover {
            background: rgba(6, 182, 212, 0.1) !important;
            border-color: #06B6D4 !important;
        }

        /* ── Scoped: Selectbox inside dialog ── */
        .tcr-chat-dlg [data-testid="stSelectbox"] label {
            font-size: 0.78rem !important;
            color: #94A3B8 !important;
            font-weight: 500 !important;
            text-transform: uppercase !important;
            letter-spacing: 0.05em !important;
        }

        /* ── Scoped: Divider inside dialog ── */
        .tcr-chat-dlg hr {
            border-color: rgba(6, 182, 212, 0.15) !important;
            margin: 6px 0 !important;
        }

        /* ── Scoped: Chat input bar ── */
        .tcr-chat-dlg [data-testid="stChatInput"] textarea {
            background: #0F1F35 !important;
            border: 1px solid rgba(6, 182, 212, 0.25) !important;
            border-radius: 10px !important;
            color: #E2E8F0 !important;
            font-size: 0.9rem !important;
        }
        .tcr-chat-dlg [data-testid="stChatInput"] textarea:focus {
            border-color: rgba(6, 182, 212, 0.6) !important;
            box-shadow: 0 0 0 2px rgba(6, 182, 212, 0.12) !important;
        }

        /* ── Scoped: Chat message area scrollbox ── */
        .tcr-chat-dlg [data-testid="stVerticalBlockBorderWrapper"] {
            border: 1px solid rgba(6, 182, 212, 0.12) !important;
            border-radius: 10px !important;
            background: rgba(6, 12, 24, 0.55) !important;
        }

        /* ── Scoped: assistant message bubble ── */
        .tcr-chat-dlg [data-testid="stChatMessage"] {
            background: transparent !important;
        }
        </style>
        """,
        unsafe_allow_html=True
    )


@st.dialog("💬 PortIQ Portfolio AI", width="large", on_dismiss=on_chat_close)
def render_chat_assistant(api_key):
    """Renders the interactive chat assistant modal."""
    from modules.api_caller import run_chat_assistant

    # Inject dialog-scoped styles
    _inject_dialog_styles()

    # Unique wrapper div — all scoped CSS is anchored to .tcr-chat-dlg
    st.markdown('<div class="tcr-chat-dlg">', unsafe_allow_html=True)

    # Auto-scroll helper: fires on mount via a hidden <img onload>
    st.markdown(
        """
        <img src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7"
             onload="
                (function() {
                    function scrollTcrChat() {
                        var dlg = document.querySelector('div[data-testid=\\'stDialog\\']');
                        if (!dlg) return;
                        var divs = dlg.querySelectorAll('div');
                        divs.forEach(function(d) {
                            var cs = window.getComputedStyle(d);
                            if ((cs.overflowY==='auto'||cs.overflowY==='scroll') && d.scrollHeight > d.clientHeight) {
                                d.scrollTop = d.scrollHeight;
                            }
                        });
                    }
                    [0, 80, 200, 450, 900].forEach(function(t){ setTimeout(scrollTcrChat, t); });
                })()
             " style="display:none;"/>
        """,
        unsafe_allow_html=True
    )

    # ── 1. Context Date Selection ──────────────────────────────────────────────
    using_db = False
    history_dates = []
    try:
        from modules.db import get_available_briefing_dates, get_briefing_from_db
        history_dates = get_available_briefing_dates()
        using_db = True
    except Exception as e:
        print(f"[chat] DB dates fetch failed, falling back to files: {e}")

    if not using_db:
        hist_dir = "history"
        if os.path.exists(hist_dir):
            history_files = sorted(
                [f for f in os.listdir(hist_dir) if f.endswith(".json") and f != "performance_cache.json"], reverse=True
            )
            history_dates = [f.replace(".json", "") for f in history_files]

    available_dates = []
    if "report_data" in st.session_state:
        available_dates.append("Today")
    available_dates.extend(history_dates)

    if not available_dates:
        st.info("No briefing data available. Please upload portfolio data first.")
        st.markdown('</div>', unsafe_allow_html=True)
        return

    current_selected = st.session_state.get("chat_context_date", "Today")
    if current_selected not in available_dates:
        current_selected = available_dates[0]
        st.session_state["chat_context_date"] = current_selected

    st.selectbox(
        "Briefing Date Context",
        available_dates,
        index=available_dates.index(current_selected),
        key="chat_context_date_selector",
        on_change=on_chat_date_change,
        label_visibility="visible"
    )

    selected_date = st.session_state.get("chat_context_date", "Today")

    # ── Load data for selected date ────────────────────────────────────────────
    active_report_data = None
    active_portfolio_df = None

    if selected_date == "Today":
        active_report_data = st.session_state.get("report_data")
        active_portfolio_df = st.session_state.get("df_original")
    else:
        if using_db:
            try:
                active_report_data = get_briefing_from_db(selected_date)
                if active_report_data:
                    active_portfolio_df = pd.DataFrame(active_report_data.get("_portfolio_snapshot", []))
            except Exception as e:
                st.error(f"Error loading {selected_date} from DB: {e}")
        else:
            try:
                with open(os.path.join("history", f"{selected_date}.json"), "r", encoding="utf-8") as fp:
                    active_report_data = json.load(fp)
                active_portfolio_df = pd.DataFrame(active_report_data.get("_portfolio_snapshot", []))
            except Exception as e:
                st.error(f"Error loading {selected_date} from file: {e}")

    # ── 2. Actions row ─────────────────────────────────────────────────────────
    col_clear, col_status = st.columns([4, 6])
    with col_clear:
        if st.button("🗑️ Clear Chat", key="btn_clear_chat_history", use_container_width=True):
            st.session_state["chat_history"] = []
            st.rerun()
    with col_status:
        if active_report_data:
            st.markdown(
                f"<p style='text-align:right;font-size:0.75rem;color:#10B981;margin-top:8px;'>"
                f"🟢 Context Loaded ({selected_date})</p>",
                unsafe_allow_html=True
            )
        else:
            st.markdown(
                "<p style='text-align:right;font-size:0.75rem;color:#EF4444;margin-top:8px;'>"
                "🔴 No Data Loaded</p>",
                unsafe_allow_html=True
            )

    st.divider()

    # ── 3. Scrollable Chat History ─────────────────────────────────────────────
    if "chat_history" not in st.session_state:
        st.session_state["chat_history"] = []

    chat_container = st.container(height=420)
    with chat_container:
        if not st.session_state["chat_history"]:
            st.chat_message("assistant").write(
                f"Hi Ram! 👋 I'm PortIQ. Ask me anything about your briefing and stock decisions for **{selected_date}**."
            )
        for msg in st.session_state["chat_history"]:
            st.chat_message(msg["role"]).write(msg["content"])

    # ── 4. Chat Input ──────────────────────────────────────────────────────────
    user_query = st.chat_input("Ask PortIQ AI...", key="chat_input_query")
    if user_query:
        st.session_state["chat_history"].append({"role": "user", "content": user_query})
        with chat_container:
            st.chat_message("user").write(user_query)

        with chat_container:
            with st.spinner("PortIQ is analyzing..."):
                response = run_chat_assistant(
                    query=user_query,
                    chat_history=st.session_state["chat_history"][:-1],
                    active_date=selected_date,
                    active_report_data=active_report_data,
                    active_portfolio_df=active_portfolio_df,
                    api_key=api_key
                )
                st.chat_message("assistant").write(response)

        st.session_state["chat_history"].append({"role": "assistant", "content": response})
        st.rerun()

    st.markdown('</div>', unsafe_allow_html=True)