650 行
28 KiB
Python
650 行
28 KiB
Python
import streamlit as st
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import numpy as np
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import sys
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import os
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# Ensure src is in path
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sys.path.append(os.path.dirname(os.path.abspath(__file__)))
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from src.models import WaterSoundData
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from src.bridges import PythonBridge
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from src.scheduler import CoreScheduler
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from src.algo_loader import load_algo_func
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st.set_page_config(page_title="水声算法全协议集成与调度平台", layout="wide")
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from src.algo_manager import AlgorithmManager
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from src.template_manager import TemplateManager
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ALGO_DB = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data/algorithms.json")
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TEMPLATE_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data/templates")
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def set_design_system():
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st.markdown("""
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<style>
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* {
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/* Keep offline-friendly font stack (Inter if installed). */
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font-family: Inter, ui-sans-serif, system-ui, -apple-system, "Segoe UI", Roboto, Helvetica, Arial, "Noto Sans", "Liberation Sans", sans-serif;
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}
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/* Sidebar Styling */
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[data-testid="stSidebar"] {
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background-image: linear-gradient(180deg, #023e8a 0%, #03045e 100%);
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color: white;
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}
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[data-testid="stSidebar"] * {
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color: white !important;
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}
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/* Metric Cards */
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[data-testid="stMetricValue"] {
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font-size: 2.5rem !important;
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font-weight: 700 !important;
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color: #00b4d8 !important;
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}
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/* Glassmorphism Containers (Approximation in Streamlit) */
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.stExpander {
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border: 1px solid rgba(255, 255, 255, 0.1) !important;
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border-radius: 12px !important;
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box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06) !important;
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background: rgba(255, 255, 255, 0.02) !important;
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}
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/* Custom Badges */
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.algo-badge {
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padding: 4px 12px;
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border-radius: 20px;
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font-size: 0.8rem;
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font-weight: 600;
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color: white;
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display: inline-block;
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margin-bottom: 10px;
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}
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.badge-python { background-color: #3776AB; }
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.badge-cpp { background-color: #7C3AED; }
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.badge-matlab { background-color: #ED8B00; }
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/* Hero Section */
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.hero {
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padding: 2rem;
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border-radius: 15px;
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background: linear-gradient(90deg, #0077b6 0%, #0096c7 100%);
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color: white;
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margin-bottom: 2rem;
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box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1);
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}
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/* Buttons */
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.stButton>button {
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border-radius: 8px !important;
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border: none !important;
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background-color: #0077b6 !important;
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color: white !important;
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transition: all 0.3s ease !important;
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}
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.stButton>button:hover {
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background-color: #00b4d8 !important;
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transform: translateY(-2px);
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box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.2);
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}
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</style>
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""", unsafe_allow_html=True)
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def main():
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set_design_system()
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st.sidebar.markdown("<h1 style='text-align: center; color: white;'>🌊 HYD-SCHED</h1>", unsafe_allow_html=True)
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st.sidebar.markdown("<p style='text-align: center; opacity: 0.8;'>海音达算法智能调度平台 v3.5</p>", unsafe_allow_html=True)
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st.sidebar.divider()
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app_mode = st.sidebar.selectbox("功能菜单",
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["首页", "算法库管理", "接口配置", "算法调度", "海试专属", "异常中心"])
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if app_mode == "首页":
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show_home()
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elif app_mode == "算法库管理":
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show_algo_library()
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elif app_mode == "接口配置":
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show_interface_config()
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elif app_mode == "算法调度":
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show_scheduling()
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elif app_mode == "海试专属":
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show_sea_trial()
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elif app_mode == "异常中心":
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show_exceptions()
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else:
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st.info(f"模块 '{app_mode}' 正在开发中...")
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# Keep sidebar spacing without relying on non-Streamlit APIs.
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st.sidebar.markdown("<div style='height: 100px;'></div>", unsafe_allow_html=True)
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st.sidebar.markdown("""
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<div style="position: fixed; bottom: 20px; width: 200px; padding: 10px; border-top: 1px solid rgba(255,255,255,0.1);">
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<p style="font-size: 0.7rem; opacity: 0.6; margin: 0;">平台状态: 🟢 已就绪</p>
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<p style="font-size: 0.7rem; opacity: 0.6; margin: 0;">环境检测: ✅ 2.0.4</p>
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</div>
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""", unsafe_allow_html=True)
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def show_home():
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st.markdown("""
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<div class="hero">
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<h1>🌊 海音达智能调度处理系统</h1>
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<p style="font-size: 1.2rem; opacity: 0.9;">
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全协议集成 · 五维实时校验 · 跨语言桥接驱动
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</p>
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<hr style="border-color: rgba(255,255,255,0.2);">
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<div style="display: flex; gap: 20px;">
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<span>✅ Python Native</span>
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<span>⚡ C++ Performance</span>
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<span>📊 MATLAB Legacy</span>
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</div>
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</div>
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""", unsafe_allow_html=True)
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# 环境诊断与建议 (Phase 5)
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from src.env_detect import get_actionable_suggestions
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suggestions = get_actionable_suggestions()
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if suggestions:
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st.error("⚠️ 检测到环境瓶颈")
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for sug in suggestions:
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with st.expander(f"🛠️ {sug['target']} - {sug['reason']}"):
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st.code(sug['fix'], language="bash")
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else:
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st.success("✨ 系统环境全量兼容 (v2.0.4)")
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col1, col2 = st.columns(2)
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with col1:
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st.subheader("🚀 核心能力")
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st.markdown("""
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- **全协议兼容**: 支持 Python/C++/MATLAB/Octave 原生算法无缝调用。
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- **工业级校验**: 5维字段、类型、空间、完整性与环境兼容性实时监测。
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- **动态资产化**: 算法元数据驱动，支持 I/O 映射模板化管理。
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""")
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with col2:
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st.subheader("⚓ 应用场景")
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st.markdown("""
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- **海试一键巡检**: 自动化质量巡检链路，实时出具测评分析报表。
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- **多源异构调度**: 将不同语言编写的声呐算法快速编排入链。
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- **异常深度追溯**: 聚合校验、执行与环境日志，一键打包现场问题。
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""")
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def show_algo_library():
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st.title("📚 算法库管理")
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from src.env_detect import collect_env_info, get_available_algo_types
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manager = AlgorithmManager(ALGO_DB)
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algos = manager.load_algorithms()
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env = collect_env_info()
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available_types = get_available_algo_types()
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# 环境状态概览
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with st.expander("🖥️ 当前环境能力", expanded=False):
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col1, col2, col3 = st.columns(3)
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col1.metric("Python", "✅ 可用")
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col2.metric("MATLAB/Octave", "✅ 可用" if "matlab" in available_types else "❌ 不可用")
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col3.metric("C++ 编译器", "✅ 可用" if "cpp" in available_types else "❌ 不可用")
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st.json(env)
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st.subheader("已注册算法")
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# 筛选器
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filter_type = st.selectbox("按类型筛选", ["全部"] + available_types)
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for algo in algos:
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algo_type = algo.get("type", "python")
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if filter_type != "全部" and algo_type != filter_type:
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continue
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# 判断是否可用
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is_available = algo_type in available_types
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status_icon = "🔵" if is_available else "⚪"
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badge_class = f"badge-{algo_type}"
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with st.expander(f"{status_icon} {algo['name']} (v{algo['version']})"):
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st.markdown(f'<div class="algo-badge {badge_class}">{algo_type.upper()}</div>', unsafe_allow_html=True)
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st.write(f"**描述**: {algo.get('description', 'N/A')}")
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if algo_type == "python":
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st.write(f"**入口**: `{algo.get('module', 'N/A')}.{algo.get('function', 'N/A')}`")
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elif algo_type == "cpp":
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st.write(f"**入口**: `{algo.get('lib_path', 'N/A')}::{algo.get('function', 'N/A')}`")
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elif algo_type == "matlab":
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st.write(f"**入口**: `{algo.get('m_path', 'N/A')}::{algo.get('function', 'N/A')}`")
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else:
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st.write(f"**入口**: `{algo.get('function', 'N/A')}`")
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st.write("**输入参数**:")
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for k, v in (algo.get("inputs") or {}).items():
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st.write(f" - `{k}`: {v.get('type', '?')} → `{v.get('field', k)}`")
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st.write("**输出参数**:")
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for k, v in (algo.get("outputs") or {}).items():
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st.write(f" - `{k}`: {v.get('type', '?')}")
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if not is_available:
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st.warning(f"⚠️ 当前环境不支持 {algo_type} 类型算法，请安装相应依赖。")
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def show_interface_config():
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st.title("🔧 接口配置")
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template_manager = TemplateManager(TEMPLATE_DIR)
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manager = AlgorithmManager(ALGO_DB)
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algos = manager.load_algorithms()
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st.subheader("创建/编辑接口模板")
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algo_names = [a["name"] for a in algos]
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selected_algo = st.selectbox("选择算法", algo_names) if algo_names else None
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if selected_algo:
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algo = manager.get_algorithm(selected_algo)
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st.write("**输入映射配置**")
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wsd_fields = ["raw_data", "sample_rate", "collect_time", "sea_env",
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"clean_data", "denoised_data", "stft_data", "feat_data",
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"final_result", "core_index", "vis_data"]
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input_mapping = {}
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for param, spec in (algo.get("inputs") or {}).items():
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default_field = (spec or {}).get("field", param)
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selected_field = st.selectbox(
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f"`{param}` 映射到",
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wsd_fields,
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index=wsd_fields.index(default_field) if default_field in wsd_fields else 0,
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key=f"in_{param}"
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)
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input_mapping[param] = selected_field
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st.write("**输出映射配置**")
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output_mapping = {}
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for field, spec in (algo.get("outputs") or {}).items():
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idx = (spec or {}).get("index", 0)
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selected_field = st.selectbox(
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f"输出 `{field}` 写入",
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wsd_fields,
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index=wsd_fields.index(field) if field in wsd_fields else 0,
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key=f"out_{field}"
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)
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output_mapping[str(idx)] = selected_field
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st.write("**预处理算子（可选）**")
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preprocessing = []
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if st.checkbox("启用归一化 (normalize)"):
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preprocessing.append({"op": "normalize", "field": list(input_mapping.values())[0] if input_mapping else "raw_data", "params": {"min": 0, "max": 1}})
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if st.checkbox("启用缩放 (scale)"):
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factor = st.number_input("缩放因子", value=1.0, step=0.1)
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preprocessing.append({"op": "scale", "field": list(input_mapping.values())[0] if input_mapping else "raw_data", "params": {"factor": factor}})
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template_name = st.text_input("模板名称", value=selected_algo)
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if st.button("保存模板"):
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template_data = {
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"algorithm": selected_algo,
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"input_mapping": input_mapping,
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"output_mapping": output_mapping,
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"preprocessing": preprocessing,
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}
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template_manager.save_template(template_name, template_data)
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st.success(f"✅ 模板 '{template_name}' 已保存！")
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st.divider()
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st.subheader("已保存模板")
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templates = template_manager.list_templates()
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if templates:
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for tpl_name in templates:
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with st.expander(f"📄 {tpl_name}"):
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tpl = template_manager.load_template(tpl_name)
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st.json(tpl)
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else:
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st.info("暂无已保存模板。")
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def show_scheduling():
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st.title("⚙️ 算法链路编排与调度")
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manager = AlgorithmManager(ALGO_DB)
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available_algos = manager.load_algorithms()
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template_manager = TemplateManager(TEMPLATE_DIR)
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if 'pipeline' not in st.session_state:
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st.session_state.pipeline = []
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col1, col2 = st.columns([1, 1])
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# Visual Pipeline flow
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if st.session_state.pipeline:
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st.write("**📦 运行流水线预览**")
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flow_html = '<div style="display: flex; align-items: center; gap: 10px; overflow-x: auto; padding: 10px;">'
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for i, algo in enumerate(st.session_state.pipeline):
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algo_type = algo.get("type", "python")
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badge_class = f"badge-{algo_type}"
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flow_html += f'''
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<div style="min-width: 120px; padding: 10px; border: 1px solid #0077b6; border-radius: 8px; text-align: center; background: rgba(0,119,182,0.05);">
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<div style="font-size: 0.7rem; opacity: 0.7;">STEP {i+1}</div>
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<div style="font-weight: 600; font-size: 0.9rem;">{algo["name"]}</div>
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<div class="algo-badge {badge_class}" style="margin: 5px 0 0 0; font-size: 0.6rem;">{algo_type.upper()}</div>
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</div>
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'''
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if i < len(st.session_state.pipeline) - 1:
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flow_html += '<div style="font-size: 1.5rem; color: #0077b6;">➡</div>'
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flow_html += '</div>'
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st.markdown(flow_html, unsafe_allow_html=True)
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st.divider()
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with col1:
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st.subheader("1. 链路编排")
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if 'pipeline' not in st.session_state:
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st.session_state.pipeline = []
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algo_names = sorted({a["name"] for a in available_algos}) if available_algos else []
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if not algo_names:
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st.warning("算法库为空：请先在 algorithms.json 注册算法元数据。")
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return
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selected_algo_name = st.selectbox("选择算法添加至链路", algo_names)
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if st.button("添加至链路"):
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algo_meta = manager.get_algorithm(selected_algo_name)
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st.session_state.pipeline.append(algo_meta)
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st.rerun()
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# 链路列表与移动操作
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for i, algo in enumerate(st.session_state.pipeline):
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cols = st.columns([0.6, 0.1, 0.1, 0.2])
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cols[0].write(f"{i+1}. **{algo['name']}** (v{algo['version']})")
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if cols[1].button("↑", key=f"up_{i}") and i > 0:
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st.session_state.pipeline[i], st.session_state.pipeline[i-1] = st.session_state.pipeline[i-1], st.session_state.pipeline[i]
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st.rerun()
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if cols[2].button("↓", key=f"down_{i}") and i < len(st.session_state.pipeline) - 1:
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st.session_state.pipeline[i], st.session_state.pipeline[i+1] = st.session_state.pipeline[i+1], st.session_state.pipeline[i]
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st.rerun()
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if cols[3].button("移除", key=f"rm_{i}"):
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st.session_state.pipeline.pop(i)
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st.rerun()
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with col2:
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st.subheader("2. 数据与校验")
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sample_rate = st.number_input("采样率 (Hz)", min_value=1.0, value=1000.0, step=100.0)
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uploaded_file = st.file_uploader("上传待处理数据 (.npy)", type=["npy"])
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auto_apply_template = st.checkbox("自动应用同名接口模板（若存在）", value=True)
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if uploaded_file and st.session_state.pipeline:
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data = np.load(uploaded_file)
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wsd = WaterSoundData(
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raw_data=data,
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sample_rate=float(sample_rate),
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sample_rate_unit="Hz",
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channel_layout="time_first",
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coordinate_system="WGS84",
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collect_time=datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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)
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# 自动映射 (Phase 2 简化版：直接使用元数据中的映射)
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scheduler = CoreScheduler()
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bridges = []
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for algo in st.session_state.pipeline:
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tpl = None
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if auto_apply_template:
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try:
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tpl = template_manager.load_template(algo["name"])
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except FileNotFoundError:
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tpl = None
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if tpl:
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in_map = tpl.get("input_mapping") or {}
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out_map = tpl.get("output_mapping") or {}
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preprocessing = tpl.get("preprocessing") or []
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else:
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in_map = {
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param: (spec or {}).get("field") or param
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for param, spec in (algo.get("inputs") or {}).items()
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}
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out_map = {
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str((spec or {}).get("index", 0)): field
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for field, spec in (algo.get("outputs") or {}).items()
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}
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preprocessing = []
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from src.bridges import PythonBridge, CppBridge
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algo_type = algo.get("type", "python")
|
|
|
|
if algo_type == "python":
|
|
try:
|
|
algo_func = load_algo_func(algo.get("module", ""), algo.get("function", ""))
|
|
except Exception as e:
|
|
st.error(f"算法加载失败：{algo.get('name', '<unknown>')} - {e}")
|
|
st.stop()
|
|
bridge = PythonBridge(
|
|
algo["name"],
|
|
algo_func,
|
|
in_map,
|
|
out_map,
|
|
preprocessing=preprocessing,
|
|
requirements=algo.get("inputs") or {},
|
|
output_specs=algo.get("outputs") or {},
|
|
algo_type=algo_type,
|
|
)
|
|
elif algo_type == "cpp":
|
|
bridge = CppBridge(
|
|
algo["name"],
|
|
algo.get("lib_path", ""),
|
|
algo.get("function", ""),
|
|
in_map,
|
|
out_map,
|
|
preprocessing=preprocessing,
|
|
requirements=algo.get("inputs") or {}, # 包含 argtypes/restype 如果在 JSON 中定义
|
|
output_specs=algo.get("outputs") or {},
|
|
)
|
|
elif algo_type == "matlab":
|
|
from src.bridges import MatlabBridge
|
|
bridge = MatlabBridge(
|
|
algo["name"],
|
|
algo.get("m_path", ""),
|
|
algo.get("function", ""),
|
|
in_map,
|
|
out_map,
|
|
preprocessing=preprocessing,
|
|
requirements=algo.get("inputs") or {},
|
|
output_specs=algo.get("outputs") or {},
|
|
)
|
|
else:
|
|
st.warning(f"暂不支持的算法类型: {algo_type}")
|
|
continue
|
|
|
|
bridges.append(bridge)
|
|
|
|
scheduler.set_flow(bridges)
|
|
|
|
if st.button("🔍 链路全局校验"):
|
|
issues = scheduler.validate_flow(wsd)
|
|
st.session_state.last_validation_issues = issues
|
|
if not issues:
|
|
st.success("✅ 校验通过：所有字段、类型与维度匹配。")
|
|
else:
|
|
for issue in issues:
|
|
st.error(f"❌ {issue['algo']}: {issue['message']}")
|
|
st.info(issue['suggestion'])
|
|
|
|
if st.button("🚀 一键执行调度"):
|
|
issues = scheduler.validate_flow(wsd)
|
|
st.session_state.last_validation_issues = issues
|
|
if issues:
|
|
st.error("⚠️ 校验未通过：已拦截执行，请先修复问题。")
|
|
for issue in issues:
|
|
st.error(f"❌ {issue['algo']}: {issue['message']}")
|
|
st.info(issue['suggestion'])
|
|
st.stop()
|
|
|
|
with st.spinner("流水线执行中..."):
|
|
result_wsd = scheduler.execute(wsd)
|
|
st.session_state.last_run = {
|
|
"status": result_wsd.status,
|
|
"error_info": result_wsd.error_info,
|
|
"log": result_wsd.log,
|
|
}
|
|
|
|
if result_wsd.status == "finished":
|
|
st.success("🎉 执行成功")
|
|
else:
|
|
st.error(f"⚠️ 执行中断: {result_wsd.error_info}")
|
|
|
|
with st.expander("实时执行日志"):
|
|
st.table(result_wsd.log)
|
|
|
|
def show_sea_trial():
|
|
st.title("⛴️ 海试专属一键检测")
|
|
st.info("内置『一键质量检测』模板：去直流 -> 带通滤波 -> 质量巡检 -> SNR估计")
|
|
|
|
sample_rate = st.number_input("采样率 (Hz)", min_value=1.0, value=1000.0, step=100.0)
|
|
uploaded_file = st.file_uploader("上传海试原始数据 (.npy)", type=["npy"])
|
|
|
|
if uploaded_file:
|
|
data = np.load(uploaded_file)
|
|
wsd = WaterSoundData(
|
|
raw_data=data,
|
|
sample_rate=float(sample_rate),
|
|
sample_rate_unit="Hz",
|
|
channel_layout="time_first",
|
|
coordinate_system="WGS84",
|
|
collect_time=datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
|
)
|
|
|
|
# 预设模板执行
|
|
if st.button("开始一键巡检"):
|
|
# 这里的逻辑可以抽象为从 TemplateManager 加载一个名叫 "sea_trial_default" 的模板
|
|
# 这里硬编码模拟一镜到底
|
|
try:
|
|
# 1. 加载函数
|
|
from src.sample_algorithms import dc_removal_and_bandpass, quality_check, snr_estimation
|
|
|
|
# 2. 构造链路
|
|
b1 = PythonBridge("去直流+带通", dc_removal_and_bandpass,
|
|
{"raw_data": "raw_data", "fs": "sample_rate"}, {"0": "clean_data"})
|
|
b2 = PythonBridge("质量巡检", quality_check,
|
|
{"raw_data": "raw_data"}, {"0": "core_index"})
|
|
b3 = PythonBridge("SNR估计", snr_estimation,
|
|
{"raw_data": "clean_data"}, {"0": "snr_value"})
|
|
|
|
scheduler = CoreScheduler()
|
|
scheduler.set_flow([b1, b2, b3])
|
|
|
|
with st.spinner("正在巡检中..."):
|
|
result = scheduler.execute(wsd)
|
|
st.session_state.last_run = {
|
|
"status": result.status,
|
|
"error_info": result.error_info,
|
|
"log": result.log,
|
|
}
|
|
|
|
if result.status == "finished":
|
|
st.success("✅ 巡检完成")
|
|
|
|
# 展示简报 (使用更高级的展示方式)
|
|
snr_value = getattr(result, "snr_value", None)
|
|
|
|
st.markdown("""
|
|
<div style="background: rgba(0,119,182,0.05); padding: 20px; border-radius: 12px; border: 1px solid rgba(0,119,182,0.2); margin-bottom: 20px;">
|
|
<h3 style="margin-top: 0; color: #0077b6;">📊 巡检简报</h3>
|
|
</div>
|
|
""", unsafe_allow_html=True)
|
|
|
|
c1, c2, c3 = st.columns(3)
|
|
with c1:
|
|
snr_str = f"{snr_value:.2f} dB" if isinstance(snr_value, (int, float)) and np.isfinite(snr_value) else "N/A"
|
|
st.metric("信噪比 (SNR)", snr_str)
|
|
with c2:
|
|
st.metric("最大幅值 (Peak)", f"{result.core_index.get('max_abs_val',0):.2f}")
|
|
with c3:
|
|
st.metric("质量评估分", f"{result.core_index.get('quality_score',0):.1f}")
|
|
|
|
# 导出报告
|
|
import csv
|
|
import io
|
|
timestamp = result.log[0].get("timestamp") if result.log else ""
|
|
row = {
|
|
"timestamp": timestamp,
|
|
"sample_rate_hz": float(sample_rate),
|
|
"snr_db": snr_value,
|
|
"saturation": result.core_index.get("saturation"),
|
|
"dropouts": result.core_index.get("dropouts"),
|
|
"max_abs_val": result.core_index.get("max_abs_val"),
|
|
"quality_score": result.core_index.get("quality_score"),
|
|
}
|
|
output = io.StringIO()
|
|
writer = csv.DictWriter(output, fieldnames=list(row.keys()))
|
|
writer.writeheader()
|
|
writer.writerow(row)
|
|
st.download_button("下载 CSV 报告", output.getvalue(), "sea_trial_report.csv", "text/csv")
|
|
else:
|
|
st.error(f"巡检中断：{result.error_info}")
|
|
except Exception as e:
|
|
st.error(f"系统错误：{e}")
|
|
|
|
def show_exceptions():
|
|
st.markdown("""
|
|
<div style="background: rgba(255,107,107,0.1); padding: 1.5rem; border-left: 5px solid #ff6b6b; border-radius: 8px; margin-bottom: 2rem;">
|
|
<h2 style="margin:0; color: #ff6b6b;">🚑 异常中心 (Exception Hub)</h2>
|
|
<p style="margin:0; opacity: 0.8;">聚合全链路校验与执行错误，支持一键导出排障包。</p>
|
|
</div>
|
|
""", unsafe_allow_html=True)
|
|
|
|
issues = st.session_state.get("last_validation_issues")
|
|
last_run = st.session_state.get("last_run")
|
|
|
|
if issues is None and last_run is None:
|
|
st.info("💡 暂无异常记录。所有组件目前运行平稳。")
|
|
return
|
|
|
|
col1, col2 = st.columns(2)
|
|
|
|
with col1:
|
|
st.subheader("🛡️ 静态校验追踪")
|
|
if issues is not None:
|
|
if not issues:
|
|
st.success("✅ 链路校验完美 (Zero Issues)")
|
|
else:
|
|
for issue in issues:
|
|
with st.container():
|
|
st.markdown(f"""
|
|
<div style="padding: 10px; border: 1px solid rgba(255,107,107,0.3); border-radius: 8px; margin-bottom: 10px;">
|
|
<strong style="color: #ff6b6b;">❌ {issue.get('algo', 'Global')}</strong><br/>
|
|
<span style="font-size: 0.9rem;">{issue.get('message', '')}</span>
|
|
<div style="background: rgba(0,0,0,0.05); padding: 5px; margin-top: 5px; font-size: 0.8rem; border-radius: 4px;">
|
|
💡 修复建议: {issue.get('suggestion', '')}
|
|
</div>
|
|
</div>
|
|
""", unsafe_allow_html=True)
|
|
|
|
with col2:
|
|
st.subheader("⚙️ 动态执行追踪")
|
|
if last_run is not None:
|
|
status = last_run.get('status')
|
|
color = "#51cf66" if status == "finished" else "#ff6b6b"
|
|
st.markdown(f'状态: <span style="color: {color}; font-weight: bold;">{status.upper()}</span>', unsafe_allow_html=True)
|
|
|
|
if last_run.get("error_info"):
|
|
st.error(f"运行时拦截: {last_run.get('error_info')}")
|
|
|
|
with st.expander("📝 详细追踪日志"):
|
|
st.table(last_run.get("log") or [])
|
|
|
|
st.divider()
|
|
c1, c2 = st.columns(2)
|
|
with c1:
|
|
with st.expander("🖥️ 环境自检快照"):
|
|
from src.env_detect import collect_env_info
|
|
st.json(collect_env_info())
|
|
with c2:
|
|
st.write("📦 **故障包存档**")
|
|
import json
|
|
payload = {
|
|
"validation_issues": issues,
|
|
"last_run": last_run,
|
|
}
|
|
st.download_button(
|
|
"下载排障 JSON 包",
|
|
json.dumps(payload, ensure_ascii=False, indent=2),
|
|
file_name="issue_bundle.json",
|
|
mime="application/json",
|
|
use_container_width=True
|
|
)
|
|
|
|
if __name__ == "__main__":
|
|
main()
|