"""
ShopAgent - Streamlit UI
Multi-modal fashion shopping assistant with conversational AI
"""

import logging
import re
import uuid
from pathlib import Path
from typing import Optional

import streamlit as st
from PIL import Image, ImageOps

from app.agents.shopping_agent import ShoppingAgent
from app.search_registry import ProductItem, SearchResult, global_registry

# Matches [SEARCH_REF:sr_xxxxxxxx] tokens embedded in AI responses.
# Case-insensitive, optional spaces around the id.
SEARCH_REF_PATTERN = re.compile(r"\[SEARCH_REF:\s*([a-zA-Z0-9_]+)\s*\]", re.IGNORECASE)

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
logger = logging.getLogger(__name__)

# Page config
st.set_page_config(
    page_title="ShopAgent",
    page_icon="👗",
    layout="centered",
    initial_sidebar_state="collapsed",
)

# Custom CSS - ChatGPT-like style
st.markdown(
    """
    <style>
    /* Show default Streamlit elements (sidebar toggle, etc.) */
    /* #MainMenu, footer, header no longer hidden */
    
    /* Body and root container */
    .main .block-container {
        padding-bottom: 180px !important;
        padding-top: 2rem;
        max-width: 900px;
        margin: 0 auto;
    }
    
    /* Fixed input container at bottom */
    .fixed-input-container {
        position: fixed;
        bottom: 0;
        left: 0;
        right: 0;
        background: white;
        border-top: 1px solid #e5e5e5;
        padding: 1rem 0;
        z-index: 1000;
        box-shadow: 0 -2px 10px rgba(0,0,0,0.05);
    }
    
    .fixed-input-container .block-container {
        max-width: 900px;
        margin: 0 auto;
        padding: 0 1rem !important;
    }
    
    /* Message bubbles */
    .message {
        margin: 1rem 0;
        padding: 1rem 1.5rem;
        border-radius: 1rem;
        animation: fadeIn 0.3s ease-in;
    }
    
    @keyframes fadeIn {
        from { opacity: 0; transform: translateY(10px); }
        to { opacity: 1; transform: translateY(0); }
    }
    
    .user-message {
        background: transparent;
        margin: 0 0 1rem 0;
        padding: 0;
        border-radius: 0;
    }
    
    .assistant-message {
        background: white;
        border: 1px solid #e5e5e5;
        margin-right: 3rem;
    }
    
    /* Product cards - simplified */
    .stImage {
        border-radius: 0px;
        overflow: hidden;
    }
    
    .stImage img {
        transition: transform 0.2s;
    }
    
    .stImage:hover img {
        transform: scale(1.05);
    }
    
    /* Scroll to bottom behavior */
    html {
        scroll-behavior: smooth;
    }
    
    /* Header */
    .app-header {
        text-align: center;
        padding: 2rem 1rem;
        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
        color: white;
        border-radius: 1rem;
        margin-bottom: 2rem;
    }
    
    .app-title {
        font-size: 2rem;
        font-weight: 700;
        margin: 0;
    }
    
    .app-subtitle {
        font-size: 1rem;
        opacity: 0.9;
        margin-top: 0.5rem;
    }
    
    /* Welcome screen */
    .welcome-container {
        text-align: center;
        padding: 4rem 2rem;
        color: #666;
    }
    
    .welcome-title {
        font-size: 2rem;
        font-weight: 600;
        color: #1a1a1a;
        margin-bottom: 1rem;
    }
    
    .welcome-features {
        display: grid;
        grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
        gap: 1.5rem;
        margin: 2rem 0;
    }
    
    .feature-card {
        background: #f7f7f8;
        padding: 1.5rem;
        border-radius: 12px;
        transition: all 0.2s;
    }
    
    .feature-card:hover {
        background: #efefef;
        transform: translateY(-2px);
    }
    
    .feature-icon {
        font-size: 2rem;
        margin-bottom: 0.5rem;
    }
    
    .feature-title {
        font-weight: 600;
        margin-bottom: 0.25rem;
    }
    
    /* Image preview */
    .image-preview {
        position: relative;
        display: inline-block;
        margin: 0.5rem 0;
    }
    
    .image-preview img {
        max-width: 200px;
        border-radius: 8px;
        border: 2px solid #e5e5e5;
    }
    
    .remove-image-btn {
        position: absolute;
        top: 5px;
        right: 5px;
        background: rgba(0,0,0,0.6);
        color: white;
        border: none;
        border-radius: 50%;
        width: 24px;
        height: 24px;
        cursor: pointer;
        font-size: 14px;
    }
    
    /* Buttons */
    .stButton>button {
        border-radius: 8px;
        border: 1px solid #e5e5e5;
        padding: 0.5rem 1rem;
        transition: all 0.2s;
    }
    
    .stButton>button:hover {
        background: #f0f0f0;
        border-color: #d0d0d0;
    }
    
    /* Hide upload button label */
    .uploadedFile {
        display: none;
    }
    </style>
    """,
    unsafe_allow_html=True,
)


# Initialize session state
def initialize_session():
    """Initialize session state variables"""
    if "session_id" not in st.session_state:
        st.session_state.session_id = str(uuid.uuid4())

    if "shopping_agent" not in st.session_state:
        st.session_state.shopping_agent = ShoppingAgent(
            session_id=st.session_state.session_id
        )

    if "messages" not in st.session_state:
        st.session_state.messages = []

    if "uploaded_image" not in st.session_state:
        st.session_state.uploaded_image = None

    if "show_image_upload" not in st.session_state:
        st.session_state.show_image_upload = False

    # Debug panel toggle (default True so 显示调试过程 is checked by default)
    if "show_debug" not in st.session_state:
        st.session_state.show_debug = True


def save_uploaded_image(uploaded_file) -> Optional[str]:
    """Save uploaded image to temp directory"""
    if uploaded_file is None:
        return None

    try:
        temp_dir = Path("temp_uploads")
        temp_dir.mkdir(exist_ok=True)

        image_path = temp_dir / f"{st.session_state.session_id}_{uploaded_file.name}"
        with open(image_path, "wb") as f:
            f.write(uploaded_file.getbuffer())

        logger.info(f"Saved uploaded image to {image_path}")
        return str(image_path)

    except Exception as e:
        logger.error(f"Error saving uploaded image: {e}")
        st.error(f"Failed to save image: {str(e)}")
        return None


def _load_product_image(product: ProductItem) -> Optional[Image.Image]:
    """Try to load a product image: image_url from API (normalized when stored) → local data/images → None."""
    if product.image_url:
        try:
            import requests
            resp = requests.get(product.image_url, timeout=10)
            if resp.status_code == 200:
                import io
                return Image.open(io.BytesIO(resp.content))
        except Exception as e:
            logger.debug(f"Remote image fetch failed for {product.spu_id}: {e}")

    local = Path(f"data/images/{product.spu_id}.jpg")
    if local.exists():
        try:
            return Image.open(local)
        except Exception as e:
            logger.debug(f"Local image load failed {local}: {e}")
    return None


def display_product_card_from_item(product: ProductItem) -> None:
    """Render a single product card from a ProductItem (registry entry)."""
    img = _load_product_image(product)

    if img:
        target = (220, 220)
        try:
            img = ImageOps.fit(img, target, method=Image.Resampling.LANCZOS)
        except AttributeError:
            img = ImageOps.fit(img, target, method=Image.LANCZOS)
        st.image(img, width="stretch")
    else:
        st.markdown(
            '<div style="height:120px;background:#f5f5f5;border-radius:6px;'
            'display:flex;align-items:center;justify-content:center;'
            'color:#bbb;font-size:2rem;">🛍️</div>',
            unsafe_allow_html=True,
        )

    title = product.title or "未知商品"
    st.markdown(f"**{title[:40]}**" + ("…" if len(title) > 40 else ""))

    if product.price is not None:
        st.caption(f"¥{product.price:.2f}")

    label_style = "⭐" if product.match_label == "完美匹配" else "✦"
    st.caption(f"{label_style} {product.match_label}")


def render_search_result_block(result: SearchResult) -> None:
    """
    Render a full search result block in place of a [SEARCH_REF:xxx] token.

    Shows:
    - A styled header with query text + quality verdict + match counts
    - A grid of product cards (perfect matches first, then partial; max 6)
    """
    verdict_icon = {"优质": "✅", "一般": "〰️", "较差": "⚠️"}.get(result.quality_verdict, "🔍")
    header_html = (
        f'<div style="border:1px solid #e0e0e0;border-radius:8px;padding:10px 14px;'
        f'margin:8px 0 4px 0;background:#fafafa;">'
        f'<span style="font-size:0.8rem;color:#555;">'
        f'🔍 <b>{result.query}</b>'
        f'&nbsp;&nbsp;{verdict_icon} {result.quality_verdict}'
        f'&nbsp;·&nbsp;完美匹配&nbsp;{result.perfect_count}&nbsp;件'
        f'&nbsp;·&nbsp;相关&nbsp;{result.partial_count}&nbsp;件'
        f'</span></div>'
    )
    st.markdown(header_html, unsafe_allow_html=True)

    # Perfect matches first, fall back to partials if none
    perfect = [p for p in result.products if p.match_label == "完美匹配"]
    partial = [p for p in result.products if p.match_label == "部分匹配"]
    to_show = (perfect + partial)[:6] if perfect else partial[:6]

    if not to_show:
        st.caption("（本次搜索未找到可展示的商品）")
        return

    cols = st.columns(min(len(to_show), 3))
    for i, product in enumerate(to_show):
        with cols[i % 3]:
            display_product_card_from_item(product)


def render_message_with_refs(content: str, session_id: str) -> None:
    """
    Render an assistant message that may contain [SEARCH_REF:xxx] tokens.

    Text segments are rendered as markdown.
    [SEARCH_REF:xxx] tokens are replaced with full product card blocks
    loaded from the global registry.
    """
    # re.split with a capture group alternates: [text, ref_id, text, ref_id, ...]
    parts = SEARCH_REF_PATTERN.split(content)

    for i, segment in enumerate(parts):
        if i % 2 == 0:
            # Text segment
            text = segment.strip()
            if text:
                st.markdown(text)
        else:
            # ref_id segment
            ref_id = segment.strip()
            result = global_registry.get(session_id, ref_id)
            if result:
                render_search_result_block(result)
            else:
                # ref not found (e.g. old session after restart)
                st.caption(f"[搜索结果 {ref_id} 不可用]")


def display_message(message: dict):
    """Display a chat message"""
    role = message["role"]
    content = message["content"]
    image_path = message.get("image_path")
    tool_calls = message.get("tool_calls", [])
    debug_steps = message.get("debug_steps", [])

    if role == "user":
        st.markdown('<div class="message user-message">', unsafe_allow_html=True)

        if image_path and Path(image_path).exists():
            try:
                img = Image.open(image_path)
                st.image(img, width=200)
            except Exception:
                logger.warning(f"Failed to load user uploaded image: {image_path}")

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

    else:  # assistant
        # Tool call breadcrumb
        if tool_calls:
            tool_names = [tc["name"] for tc in tool_calls]
            st.caption(" → ".join(tool_names))
            st.markdown("")

        # Debug panel
        if debug_steps and st.session_state.get("show_debug"):
            with st.expander("思考 & 工具调用详细过程", expanded=False):
                for idx, step in enumerate(debug_steps, 1):
                    node = step.get("node", "unknown")
                    st.markdown(f"**Step {idx} – {node}**")

                    if node == "agent":
                        msgs = step.get("messages", [])
                        if msgs:
                            st.markdown("**Agent Messages**")
                            for m in msgs:
                                st.markdown(f"- `{m.get('type', 'assistant')}`: {m.get('content', '')}")

                        tcs = step.get("tool_calls", [])
                        if tcs:
                            st.markdown("**Planned Tool Calls**")
                            for j, tc in enumerate(tcs, 1):
                                st.markdown(f"- **{j}. {tc.get('name')}**")
                                st.code(tc.get("args", {}), language="json")

                    elif node == "tools":
                        results = step.get("results", [])
                        if results:
                            st.markdown("**Tool Results**")
                            for j, r in enumerate(results, 1):
                                st.markdown(f"- **Result {j}:**")
                                st.code(r.get("content", ""), language="text")

                    st.markdown("---")

        # Render message: expand [SEARCH_REF:xxx] tokens into product card blocks
        session_id = st.session_state.get("session_id", "")
        render_message_with_refs(content, session_id)

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


def display_welcome():
    """Display welcome screen"""

    col1, col2, col3, col4 = st.columns(4)

    with col1:
        st.markdown(
            """
            <div class="feature-card">
                <div class="feature-icon">💗</div>
                <div class="feature-title">懂你</div>
                <div>能记住你的偏好，给你推荐适合的</div>
            </div>
            """,
            unsafe_allow_html=True,
        )

    with col2:
        st.markdown(
            """
            <div class="feature-card">
                <div class="feature-icon">🛍️</div>
                <div class="feature-title">懂商品</div>
                <div>深度理解店铺内所有商品，智能匹配你的需求</div>
            </div>
            """,
            unsafe_allow_html=True,
        )

    with col3:
        st.markdown(
            """
            <div class="feature-card">
                <div class="feature-icon">💭</div>
                <div class="feature-title">贴心</div>
                <div>任意聊</div>
            </div>
            """,
            unsafe_allow_html=True,
        )

    with col4:
        st.markdown(
            """
            <div class="feature-card">
                <div class="feature-icon">👗</div>
                <div class="feature-title">懂时尚</div>
                <div>穿搭顾问 + 轻松对比</div>
            </div>
            """,
            unsafe_allow_html=True,
        )

    st.markdown("<br><br>", unsafe_allow_html=True)


def main():
    """Main Streamlit app"""
    initialize_session()

    # Header
    st.markdown(
        """
        <div class="app-header">
            <div class="app-title">👗 ShopAgent</div>
            <div class="app-subtitle">AI Fashion Shopping Assistant</div>
        </div>
        """,
        unsafe_allow_html=True,
    )

    # Sidebar (collapsed by default, but accessible)
    with st.sidebar:
        st.markdown("### ⚙️ Settings")

        if st.button("🗑️ Clear Chat", width="stretch"):
            if "shopping_agent" in st.session_state:
                st.session_state.shopping_agent.clear_history()
            # Clear search result registry for this session
            session_id = st.session_state.get("session_id", "")
            if session_id:
                global_registry.clear_session(session_id)
            st.session_state.messages = []
            st.session_state.uploaded_image = None
            st.rerun()

        # Debug toggle
        st.markdown("---")
        st.checkbox(
            "显示调试过程 (debug)",
            key="show_debug",
            value=True,
            help="展开后可查看中间思考过程及工具调用详情",
        )

        st.markdown("---")
        st.caption(f"Session: `{st.session_state.session_id[:8]}...`")

    # Chat messages container
    messages_container = st.container()

    with messages_container:
        if not st.session_state.messages:
            display_welcome()
        else:
            for message in st.session_state.messages:
                display_message(message)

    # Fixed input area at bottom (using container to simulate fixed position)
    st.markdown('<div class="fixed-input-container">', unsafe_allow_html=True)

    input_container = st.container()

    with input_container:
        # Image upload area (shown when + is clicked)
        if st.session_state.show_image_upload:
            uploaded_file = st.file_uploader(
                "Choose an image",
                type=["jpg", "jpeg", "png"],
                key="file_uploader",
            )

            if uploaded_file:
                st.session_state.uploaded_image = uploaded_file
                # Show preview
                col1, col2 = st.columns([1, 4])
                with col1:
                    img = Image.open(uploaded_file)
                    st.image(img, width=100)
                with col2:
                    if st.button("❌ Remove"):
                        st.session_state.uploaded_image = None
                        st.session_state.show_image_upload = False
                        st.rerun()

        # Input row
        col1, col2 = st.columns([1, 12])

        with col1:
            # Image upload toggle button
            if st.button("➕", help="Add image", width="stretch"):
                st.session_state.show_image_upload = (
                    not st.session_state.show_image_upload
                )
                st.rerun()

        with col2:
            # Text input
            user_query = st.chat_input(
                "Ask about fashion products...",
                key="chat_input",
            )

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

    # Process user input
    if user_query:
        # Ensure shopping agent is initialized
        if "shopping_agent" not in st.session_state:
            st.error("Session not initialized. Please refresh the page.")
            st.stop()

        # Save uploaded image if present, or get from recent history
        image_path = None
        if st.session_state.uploaded_image:
            # User explicitly uploaded an image for this query
            image_path = save_uploaded_image(st.session_state.uploaded_image)
        else:
            # Check if query refers to a previous image
            query_lower = user_query.lower()
            if any(
                ref in query_lower
                for ref in [
                    "this",
                    "that",
                    "the image",
                    "the shirt",
                    "the product",
                    "it",
                ]
            ):
                # Find the most recent message with an image
                for msg in reversed(st.session_state.messages):
                    if msg.get("role") == "user" and msg.get("image_path"):
                        image_path = msg["image_path"]
                        logger.info(f"Using image from previous message: {image_path}")
                        break

        # Add user message
        st.session_state.messages.append(
            {
                "role": "user",
                "content": user_query,
                "image_path": image_path,
            }
        )

        # Display user message immediately
        with messages_container:
            display_message(st.session_state.messages[-1])

        # Process with shopping agent
        try:
            shopping_agent = st.session_state.shopping_agent
            
            # Handle greetings without invoking the agent
            query_lower = user_query.lower().strip()
            # Process with agent
            result = shopping_agent.chat(
                query=user_query,
                image_path=image_path,
            )
            response = result["response"]
            tool_calls = result.get("tool_calls", [])
            debug_steps = result.get("debug_steps", [])

            # Add assistant message
            st.session_state.messages.append(
                {
                    "role": "assistant",
                    "content": response,
                    "tool_calls": tool_calls,
                    "debug_steps": debug_steps,
                }
            )

            # Clear uploaded image and hide upload area after sending
            st.session_state.uploaded_image = None
            st.session_state.show_image_upload = False

            # Auto-scroll to bottom with JavaScript
            st.markdown(
                """
                <script>
                window.scrollTo(0, document.body.scrollHeight);
                </script>
                """,
                unsafe_allow_html=True,
            )

        except Exception as e:
            logger.error(f"Error processing query: {e}", exc_info=True)
            error_msg = f"I apologize, I encountered an error: {str(e)}"

            st.session_state.messages.append(
                {
                    "role": "assistant",
                    "content": error_msg,
                }
            )

        # Rerun to update UI
        st.rerun()


if __name__ == "__main__":
    main()