"""
PropBazaar — AI Real Estate Assistant
HuggingFace Spaces entry point (Gradio)
"""

import os
import sys
import gradio as gr

# Make src importable
sys.path.insert(0, os.path.dirname(__file__))

from src.database.queries import init_db
from src.rag.retriever import load_vector_store
from src.rag.chatbot import chat
from src.rag.searcher import (
    get_all_properties, get_leases_expiring, get_leases_vacant_or_pending
)

# ── Startup ──────────────────────────────────────────────────────
print("Initialising PropBazaar...")
init_db()
load_vector_store()
print("PropBazaar ready ✅")

ADMIN_USERNAME = os.environ.get("ADMIN_USERNAME", "manager")
ADMIN_PASSWORD = os.environ.get("ADMIN_PASSWORD", "propbazaar2025")
WHATSAPP_URL = "https://wa.me/919800000000"

# ── Helpers ──────────────────────────────────────────────────────
def _fmt_price(price_inr):
    if price_inr >= 10000000:
        return f"₹{price_inr/10000000:.2f} Cr"
    return f"₹{price_inr/100000:.1f} L"


# ── Chat handler ─────────────────────────────────────────────────
def customer_chat(message, history, role_state):
    if not message.strip():
        return history, history, ""

    role = role_state or "customer"
    history_fmt = [{"role": h[0], "content": h[1]} for h in history] if history else []

    result = chat(message, role=role, history=history_fmt)
    reply = result["reply"]

    history = history or []
    history.append(("user", message))
    history.append(("assistant", reply))

    # Convert to Gradio chatbot format
    gradio_history = [[u, a] for u, a in zip(
        [h[1] for h in history if h[0] == "user"],
        [h[1] for h in history if h[0] == "assistant"]
    )]

    return gradio_history, history, ""


def admin_login(username, password):
    if username == ADMIN_USERNAME and password == ADMIN_PASSWORD:
        return (
            gr.update(visible=False),
            gr.update(visible=True),
            "✅ Logged in as Manager"
        )
    return (
        gr.update(visible=True),
        gr.update(visible=False),
        "❌ Invalid credentials"
    )


def get_dashboard_data():
    """Return all properties as a dataframe for the manager dashboard."""
    import pandas as pd
    props = get_all_properties()
    if not props:
        return pd.DataFrame()
    df = pd.DataFrame(props)
    df["price_display"] = df["price_inr"].apply(_fmt_price)
    cols = ["property_id", "title", "bhk", "property_type", "area_sqft",
            "price_display", "location", "furnishing", "condition_grade", "available"]
    return df[[c for c in cols if c in df.columns]]


def get_expiring_leases(days):
    import pandas as pd
    records = get_leases_expiring(int(days))
    if not records:
        return pd.DataFrame(columns=["property_id", "title", "location",
                                      "monthly_rent", "lease_status", "lease_end",
                                      "tenant_name", "followup_person"])
    df = pd.DataFrame(records)
    return df[["property_id", "title", "location", "monthly_rent",
               "lease_status", "lease_end", "tenant_name", "followup_person"]]


def get_vacant_pending():
    import pandas as pd
    records = get_leases_vacant_or_pending()
    if not records:
        return pd.DataFrame(columns=["property_id", "title", "location",
                                      "lease_status", "lease_end",
                                      "followup_person", "notes"])
    df = pd.DataFrame(records)
    return df[["property_id", "title", "location", "lease_status",
               "lease_end", "followup_person", "notes"]]


def manager_chat_fn(message, history, chat_history_state):
    if not message.strip():
        return history, chat_history_state, ""

    history_fmt = [{"role": h[0], "content": h[1]}
                   for h in chat_history_state] if chat_history_state else []

    result = chat(message, role="manager", history=history_fmt)
    reply = result["reply"]

    chat_history_state = chat_history_state or []
    chat_history_state.append(("user", message))
    chat_history_state.append(("assistant", reply))

    gradio_history = [[u, a] for u, a in zip(
        [h[1] for h in chat_history_state if h[0] == "user"],
        [h[1] for h in chat_history_state if h[0] == "assistant"]
    )]
    return gradio_history, chat_history_state, ""


# ── UI ───────────────────────────────────────────────────────────
CSS = """
#header { background: linear-gradient(135deg, #1a1a2e 0%, #16213e 50%, #0f3460 100%);
          padding: 24px 32px; border-radius: 12px; margin-bottom: 16px; }
#header h1 { color: #e94560; margin: 0; font-size: 2rem; }
#header p  { color: #a8b2d8; margin: 4px 0 0; font-size: 0.95rem; }
.chatbot { border-radius: 10px; }
.send-btn { background: #e94560 !important; border: none !important; color: white !important; }
.tab-nav button { font-weight: 600; }
"""

with gr.Blocks(css=CSS, title="PropBazaar — AI Real Estate Assistant") as demo:

    # Header
    gr.HTML("""
    <div id="header">
      <h1>🏠 PropBazaar</h1>
      <p>AI-Powered Real Estate Assistant — Mumbai &amp; MMR</p>
    </div>
    """)

    role_state = gr.State("customer")
    chat_history_state = gr.State([])

    with gr.Tabs():

        # ── Tab 1: Customer Chatbot ──────────────────────────────
        with gr.Tab("🏡 Find Properties"):
            gr.Markdown("""
**Ask me anything!** Examples:
- *Show me 2BHK flats in Andheri under ₹1 crore*
- *3BHK fully furnished in Bandra between 1.5 and 2 crore*
- *Villas in Thane below 3 crore with parking*
- *What is the stamp duty in Mumbai?*
- *Do you help with home loans?*
            """)

            chatbot = gr.Chatbot(
                label="PropBazaar Assistant",
                elem_id="chatbot",
                height=420,
                show_label=False,
            )
            with gr.Row():
                msg_input = gr.Textbox(
                    placeholder="Type your query here... (e.g. '2BHK under 90 lakh in Malad')",
                    show_label=False,
                    scale=5,
                    lines=1,
                )
                send_btn = gr.Button("Send 🚀", elem_classes="send-btn", scale=1)

            with gr.Row():
                clear_btn = gr.Button("🗑️ Clear Chat", size="sm")
                wa_btn = gr.Button("📱 WhatsApp Us", size="sm", variant="secondary")

            gr.Markdown("*Powered by Groq LLaMA 3.3 · Data from PropBazaar inventory*")

            # Quick prompts
            with gr.Accordion("💡 Quick Search Examples", open=False):
                with gr.Row():
                    gr.Button("2BHK in Andheri under 1 Cr").click(
                        lambda: "Show me 2BHK flats in Andheri under 1 crore",
                        outputs=msg_input
                    )
                    gr.Button("3BHK fully furnished Bandra").click(
                        lambda: "3BHK fully furnished flat in Bandra",
                        outputs=msg_input
                    )
                    gr.Button("Stamp duty info").click(
                        lambda: "What is the stamp duty in Mumbai?",
                        outputs=msg_input
                    )
                with gr.Row():
                    gr.Button("Villa in Thane").click(
                        lambda: "Show me villas in Thane",
                        outputs=msg_input
                    )
                    gr.Button("Home loan process").click(
                        lambda: "How do I get a home loan for buying a flat?",
                        outputs=msg_input
                    )
                    gr.Button("Property registration docs").click(
                        lambda: "What documents are needed for property registration?",
                        outputs=msg_input
                    )

            def send_message(message, history, chat_hist_state):
                return customer_chat(message, chat_hist_state, "customer")

            send_btn.click(
                send_message,
                inputs=[msg_input, chatbot, chat_history_state],
                outputs=[chatbot, chat_history_state, msg_input]
            )
            msg_input.submit(
                send_message,
                inputs=[msg_input, chatbot, chat_history_state],
                outputs=[chatbot, chat_history_state, msg_input]
            )
            clear_btn.click(
                lambda: ([], [], ""),
                outputs=[chatbot, chat_history_state, msg_input]
            )
            wa_btn.click(lambda: None, js=f"() => window.open('{WHATSAPP_URL}', '_blank')")

        # ── Tab 2: Manager Dashboard ─────────────────────────────
        with gr.Tab("🔐 Manager Dashboard"):

            login_section = gr.Group(visible=True)
            dashboard_section = gr.Group(visible=False)
            login_status = gr.Markdown("")

            with login_section:
                gr.Markdown("### 🔒 Manager Login")
                with gr.Row():
                    username_input = gr.Textbox(label="Username", placeholder="manager")
                    password_input = gr.Textbox(label="Password", type="password")
                login_btn = gr.Button("Login", variant="primary")

            with dashboard_section:
                gr.Markdown("### 📊 Manager Dashboard")

                with gr.Tabs():
                    with gr.Tab("🏠 All Properties"):
                        refresh_props_btn = gr.Button("🔄 Refresh", size="sm")
                        props_table = gr.Dataframe(
                            label="Property Inventory",
                            interactive=False,
                            wrap=True,
                        )
                        refresh_props_btn.click(get_dashboard_data, outputs=props_table)
                        demo.load(get_dashboard_data, outputs=props_table)

                    with gr.Tab("📅 Leases Expiring Soon"):
                        with gr.Row():
                            days_slider = gr.Slider(
                                minimum=7, maximum=90, value=30, step=7,
                                label="Show leases expiring within (days)"
                            )
                            refresh_lease_btn = gr.Button("🔄 Refresh", size="sm")
                        leases_table = gr.Dataframe(
                            label="Expiring Leases",
                            interactive=False,
                            wrap=True,
                        )
                        refresh_lease_btn.click(
                            get_expiring_leases,
                            inputs=days_slider,
                            outputs=leases_table
                        )
                        days_slider.change(
                            get_expiring_leases,
                            inputs=days_slider,
                            outputs=leases_table
                        )

                    with gr.Tab("🚨 Vacant / Pending"):
                        refresh_vacant_btn = gr.Button("🔄 Refresh", size="sm")
                        vacant_table = gr.Dataframe(
                            label="Vacant & Pending Properties",
                            interactive=False,
                            wrap=True,
                        )
                        refresh_vacant_btn.click(get_vacant_pending, outputs=vacant_table)

                    with gr.Tab("💬 Manager Chat"):
                        gr.Markdown("Ask about leases, inventory, or get AI-powered insights.")
                        mgr_chatbot = gr.Chatbot(height=350, show_label=False)
                        mgr_chat_state = gr.State([])
                        with gr.Row():
                            mgr_input = gr.Textbox(
                                placeholder="e.g. 'Show leases expiring this month' or 'List vacant properties'",
                                show_label=False, scale=5
                            )
                            mgr_send_btn = gr.Button("Send", scale=1, variant="primary")
                        mgr_clear_btn = gr.Button("🗑️ Clear", size="sm")

                        mgr_send_btn.click(
                            manager_chat_fn,
                            inputs=[mgr_input, mgr_chatbot, mgr_chat_state],
                            outputs=[mgr_chatbot, mgr_chat_state, mgr_input]
                        )
                        mgr_input.submit(
                            manager_chat_fn,
                            inputs=[mgr_input, mgr_chatbot, mgr_chat_state],
                            outputs=[mgr_chatbot, mgr_chat_state, mgr_input]
                        )
                        mgr_clear_btn.click(
                            lambda: ([], [], ""),
                            outputs=[mgr_chatbot, mgr_chat_state, mgr_input]
                        )

            login_btn.click(
                admin_login,
                inputs=[username_input, password_input],
                outputs=[login_section, dashboard_section, login_status]
            )

        # ── Tab 3: About ─────────────────────────────────────────
        with gr.Tab("ℹ️ About"):
            gr.Markdown("""
## 🏠 PropBazaar — AI Real Estate Assistant

PropBazaar is an intelligent RAG-based chatbot for a Mumbai resale real estate business.

### Features
- **🔍 Property Search** — Find flats, villas, studios by budget, BHK, location, furnishing
- **💬 FAQ Chatbot** — Answers on home loans, stamp duty, registration, RERA, documents
- **📊 Manager Dashboard** — Track lease expirations, vacant properties, portfolio
- **🔐 Secure Login** — Manager-only access to business data

### How to Set Up
1. Clone this Space
2. Add your `GROQ_API_KEY` in Space Settings → Secrets (free at console.groq.com)
3. Optionally add `GEMINI_API_KEY` for semantic FAQ search
4. Set `ADMIN_USERNAME` and `ADMIN_PASSWORD` for the manager dashboard

### Tech Stack
- **Frontend**: Gradio (HuggingFace Spaces)
- **AI**: Groq LLaMA 3.3 70B (fast, free tier available)
- **Database**: SQLite (property & lease data)
- **Search**: FAISS vector search + keyword fallback
- **Data**: CSV → SQLite on startup

---
*Built with ❤️ for Indian Real Estate businesses*
            """)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)