# -*- coding: utf-8 -*-
"""
🕸️ 供应链知识图谱页面
交互式图谱展示 + 供应链风险传染路径 + 实体清单命中标记
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

import streamlit as st
import streamlit.components.v1 as components

from collectors.financial_collector import get_all_companies
from knowledge_graph.graph_builder import build_graph, get_graph_stats
from knowledge_graph.contagion_analyzer import analyze_contagion
from knowledge_graph.graph_visualizer import (
    generate_interactive_graph,
    get_subgraph_for_company,
)

st.set_page_config(page_title="供应链知识图谱", page_icon="🕸️", layout="wide")

st.markdown("# 🕸️ 供应链风险传染知识图谱")
st.markdown("可视化科创企业供应链网络，识别风险传染路径和关键断裂节点。")

# 构建图谱
@st.cache_resource
def get_graph():
    return build_graph()

G = get_graph()
stats = get_graph_stats(G)

# ============================================================
# 图谱统计
# ============================================================
col1, col2, col3, col4 = st.columns(4)
with col1:
    st.metric("📌 总节点数", stats["total_nodes"])
with col2:
    st.metric("🔗 总边数", stats["total_edges"])
with col3:
    st.metric("⛔ 受制裁节点", stats["sanctioned_nodes"])
with col4:
    st.metric("🔀 图密度", f"{stats['density']:.4f}")

# 节点类型分布
with st.expander("📊 节点类型分布"):
    for ntype, count in stats["node_types"].items():
        st.markdown(f"- **{ntype}**: {count} 个")

st.markdown("---")

# ============================================================
# 图谱视图选择
# ============================================================
view_mode = st.radio(
    "🔍 视图模式",
    ["全局图谱", "企业中心视图（推荐）"],
    horizontal=True,
)

from utils.session_helper import render_company_selector, render_sidebar_global_company_selector

with st.sidebar:
    render_sidebar_global_company_selector()
    st.markdown("---")

if view_mode == "企业中心视图（推荐）":
    target_company = render_company_selector("🏢 选择中心企业", key_suffix="graph_page")
    selected_company = target_company["short_name"] if target_company else "寒武纪"

    depth = st.slider("穿透深度", 1, 3, 2)

    # 提取子图
    subgraph = get_subgraph_for_company(G, selected_company, depth=depth)

    if subgraph.number_of_nodes() > 0:
        html_content = generate_interactive_graph(
            subgraph,
            highlight_company=selected_company,
            height="550px",
        )
        components.html(html_content, height=600, scrolling=True)

        # ============================================================
        # 供应链风险传染分析
        # ============================================================
        st.markdown("---")
        st.markdown(f"### ⚠️ {selected_company} 供应链风险传染分析")

        contagion = analyze_contagion(G, selected_company)

        # 风险评分
        supply_risk_score = contagion.get("risk_score", 0)
        if supply_risk_score >= 60:
            st.error(f"🔴 供应链风险评分: **{supply_risk_score}/100** — 供应链断裂风险极高")
        elif supply_risk_score >= 30:
            st.warning(f"🟡 供应链风险评分: **{supply_risk_score}/100** — 存在一定供应链风险")
        else:
            st.success(f"🟢 供应链风险评分: **{supply_risk_score}/100** — 供应链风险可控")

        # 直接风险
        if contagion.get("direct_risks"):
            st.markdown("#### 🔴 直接风险（一度关联）")
            for risk in contagion["direct_risks"]:
                icon = "⛔" if risk.get("status") == "受限" else "⚠️"
                st.markdown(
                    f"- {icon} **{risk['entity']}** ({risk['node_type']}) — "
                    f"{risk['relation']} — 状态: {risk.get('status', '未知')} "
                    f"{'🔑 关键供应' if risk.get('is_critical') else ''}"
                )

        # 间接风险
        if contagion.get("indirect_risks"):
            st.markdown("#### 🟡 间接风险（二度及以上关联）")
            for risk in contagion["indirect_risks"]:
                st.markdown(
                    f"- ⚠️ **{risk['entity']}** (距离: {risk['distance']}层) — {risk['relation']}"
                )

        # 传染路径
        if contagion.get("contagion_paths"):
            st.markdown("#### 🔗 风险传染路径")
            for path in contagion["contagion_paths"]:
                severity_icon = "🔴" if path["severity"] == "高" else "🟡"
                st.markdown(f"- {severity_icon} `{path['path_str']}` (长度: {path['length']})")

        # 关键断裂节点
        if contagion.get("critical_nodes"):
            st.markdown("#### 🔑 关键断裂节点")
            for node in contagion["critical_nodes"]:
                alt_info = f"✅ 有{node['alternative_count']}个替代" if node["has_alternative"] else "❌ 无替代方案"
                st.markdown(
                    f"- **{node['node']}** — {node['relation']} — "
                    f"状态: {node['status']} — {alt_info}"
                )
    else:
        st.warning(f"未找到 {selected_company} 的相关图谱数据")

else:
    # 全局视图
    st.info("💡 全局图谱节点较多，加载可能需要几秒钟。推荐使用“企业中心视图”获得更好的体验。")
    html_content = generate_interactive_graph(G, height="650px")
    components.html(html_content, height=700, scrolling=True)

# ============================================================
# 图例
# ============================================================
st.markdown("---")
st.markdown("#### 🎨 图例说明")
col_l1, col_l2, col_l3 = st.columns(3)
with col_l1:
    st.markdown("""
    **节点颜色**
    - 🟢 绿色: 科创企业 (正常)
    - 🟡 金色: 选中的中心企业
    - 🟠 橙色: 供应商
    - 🟣 紫色: 客户
    - 🔵 蓝色: 核心人员
    - 🔴 红色: 受制裁实体
    """)
with col_l2:
    st.markdown("""
    **边类型**
    - 实线: 正常关系
    - 红色虚线: 受限关系
    - 黄色粗线: 关键供应关系
    """)
with col_l3:
    st.markdown("""
    **交互操作**
    - 鼠标悬浮: 查看节点详情
    - 拖拽: 移动节点
    - 滚轮: 缩放图谱
    - 双击: 聚焦节点
    """)