增加智瞰龙虎板块
This commit is contained in:
oficcejo
@@ -0,0 +1,610 @@
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"""
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智瞰龙虎UI界面模块
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展示龙虎榜分析结果和推荐股票
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"""
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import streamlit as st
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import plotly.graph_objects as go
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import plotly.express as px
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import pandas as pd
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from datetime import datetime, timedelta
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import time
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import base64
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from longhubang_engine import LonghubangEngine
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from longhubang_pdf import LonghubangPDFGenerator
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def display_longhubang():
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"""显示智瞰龙虎主界面"""
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st.markdown("""
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<div class="top-nav">
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<h1 class="nav-title">🎯 智瞰龙虎 - AI驱动的龙虎榜分析</h1>
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<p class="nav-subtitle">Multi-Agent Dragon Tiger Analysis | 游资·个股·题材·风险多维分析</p>
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</div>
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""", unsafe_allow_html=True)
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st.markdown("---")
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# 功能说明
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with st.expander("💡 智瞰龙虎系统介绍", expanded=False):
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st.markdown("""
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### 🌟 系统特色
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**智瞰龙虎**是基于多AI智能体的龙虎榜深度分析系统，通过5位专业分析师的协同工作，
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为您挖掘次日大概率上涨的潜力股票。
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### 🤖 AI分析师团队
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1. **🎯 游资行为分析师**
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- 识别活跃游资及其操作风格
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- 分析游资席位的进出特征
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- 研判游资对个股的态度
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2. **📈 个股潜力分析师**
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- 从龙虎榜数据挖掘潜力股
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- 识别次日大概率上涨的股票
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- 分析资金动向和技术形态
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3. **🔥 题材追踪分析师**
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- 识别当前热点题材和概念
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- 分析题材的炒作周期
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- 预判题材的持续性
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4. **⚠️ 风险控制专家**
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- 识别高风险股票和陷阱
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- 分析游资出货信号
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- 提供风险管理建议
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5. **👔 首席策略师**
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- 综合所有分析师意见
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- 给出最终推荐股票清单
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- 提供具体操作策略
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### 📊 数据来源
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数据来自**StockAPI龙虎榜接口**，包括：
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- 游资上榜交割单历史数据
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- 股票买卖金额和净流入
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- 热门概念和题材
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- 更新时间：交易日下午5点40
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### 🎯 核心功能
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- ✅ **潜力股挖掘** - AI识别次日大概率上涨股票
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- ✅ **游资追踪** - 跟踪活跃游资的操作
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- ✅ **题材识别** - 发现热点题材和龙头股
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- ✅ **风险提示** - 识别高风险股票和陷阱
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- ✅ **历史记录** - 存储所有龙虎榜数据
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- ✅ **PDF报告** - 生成专业分析报告
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""")
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st.markdown("---")
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# 创建标签页
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tab1, tab2, tab3 = st.tabs([
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"📊 龙虎榜分析",
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"📚 历史报告",
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"📈 数据统计"
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])
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with tab1:
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display_analysis_tab()
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with tab2:
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display_history_tab()
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with tab3:
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display_statistics_tab()
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def display_analysis_tab():
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"""显示分析标签页"""
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st.subheader("🔍 龙虎榜综合分析")
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# 参数设置
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col1, col2, col3 = st.columns([2, 2, 2])
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with col1:
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analysis_mode = st.selectbox(
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"分析模式",
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["指定日期", "最近N天"],
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help="选择分析特定日期还是最近几天的数据"
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)
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with col2:
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if analysis_mode == "指定日期":
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selected_date = st.date_input(
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"选择日期",
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value=datetime.now() - timedelta(days=1),
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help="选择要分析的龙虎榜日期"
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)
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else:
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days = st.number_input(
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"最近天数",
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min_value=1,
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max_value=10,
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value=1,
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help="分析最近N天的龙虎榜数据"
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)
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with col3:
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selected_model = st.selectbox(
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"AI模型",
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["deepseek-chat", "deepseek-reasoner"],
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help="Reasoner模型提供更强的推理能力"
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)
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# 分析按钮
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col1, col2, col3 = st.columns([2, 2, 2])
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with col1:
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analyze_button = st.button("🚀 开始分析", type="primary", use_container_width=True)
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with col2:
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if st.button("🔄 清除结果", use_container_width=True):
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if 'longhubang_result' in st.session_state:
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del st.session_state.longhubang_result
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st.success("已清除分析结果")
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st.rerun()
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st.markdown("---")
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# 开始分析
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if analyze_button:
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# 清除之前的结果
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if 'longhubang_result' in st.session_state:
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del st.session_state.longhubang_result
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# 准备参数
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if analysis_mode == "指定日期":
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date_str = selected_date.strftime('%Y-%m-%d')
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run_longhubang_analysis(model=selected_model, date=date_str)
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else:
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run_longhubang_analysis(model=selected_model, days=days)
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# 显示分析结果
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if 'longhubang_result' in st.session_state:
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result = st.session_state.longhubang_result
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if result.get("success"):
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display_analysis_results(result)
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else:
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st.error(f"❌ 分析失败: {result.get('error', '未知错误')}")
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def run_longhubang_analysis(model="deepseek-chat", date=None, days=1):
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"""运行龙虎榜分析"""
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# 进度显示
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progress_bar = st.progress(0)
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status_text = st.empty()
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try:
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status_text.text("🚀 初始化分析引擎...")
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progress_bar.progress(5)
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engine = LonghubangEngine(model=model)
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status_text.text("📊 正在获取龙虎榜数据...")
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progress_bar.progress(15)
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# 运行分析
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result = engine.run_comprehensive_analysis(date=date, days=days)
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progress_bar.progress(90)
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if result.get("success"):
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# 保存结果
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st.session_state.longhubang_result = result
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progress_bar.progress(100)
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status_text.text("✅ 分析完成！")
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time.sleep(1)
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status_text.empty()
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progress_bar.empty()
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# 自动刷新显示结果
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st.rerun()
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else:
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st.error(f"❌ 分析失败: {result.get('error', '未知错误')}")
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except Exception as e:
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st.error(f"❌ 分析过程出错: {str(e)}")
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import traceback
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st.code(traceback.format_exc())
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finally:
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progress_bar.empty()
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status_text.empty()
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def display_analysis_results(result):
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"""显示分析结果"""
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st.success("✅ 龙虎榜分析完成！")
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st.info(f"📅 分析时间: {result.get('timestamp', 'N/A')}")
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# 数据概况
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data_info = result.get('data_info', {})
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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st.metric("龙虎榜记录", f"{data_info.get('total_records', 0)} 条")
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with col2:
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st.metric("涉及股票", f"{data_info.get('total_stocks', 0)} 只")
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with col3:
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st.metric("涉及游资", f"{data_info.get('total_youzi', 0)} 个")
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with col4:
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recommended = result.get('recommended_stocks', [])
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st.metric("推荐股票", f"{len(recommended)} 只", delta="AI筛选")
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# PDF导出功能
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display_pdf_export_section(result)
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st.markdown("---")
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# 创建子标签页
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tab1, tab2, tab3, tab4 = st.tabs([
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"🎯 推荐股票",
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"🤖 AI分析师报告",
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"📊 数据详情",
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"📈 可视化图表"
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])
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with tab1:
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display_recommended_stocks(result)
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with tab2:
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display_agents_reports(result)
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with tab3:
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display_data_details(result)
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with tab4:
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display_visualizations(result)
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def display_recommended_stocks(result):
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"""显示推荐股票"""
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st.subheader("🎯 AI推荐股票")
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recommended = result.get('recommended_stocks', [])
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if not recommended:
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st.warning("暂无推荐股票")
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return
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st.info(f"💡 基于5位AI分析师的综合分析，系统识别出以下 **{len(recommended)}** 只潜力股票")
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# 创建DataFrame
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df_recommended = pd.DataFrame(recommended)
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# 显示表格
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st.dataframe(
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df_recommended,
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column_config={
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"rank": st.column_config.NumberColumn("排名", format="%d"),
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"code": st.column_config.TextColumn("股票代码"),
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"name": st.column_config.TextColumn("股票名称"),
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"net_inflow": st.column_config.NumberColumn("净流入金额", format="%.2f"),
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"confidence": st.column_config.TextColumn("确定性"),
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"hold_period": st.column_config.TextColumn("持有周期"),
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"reason": st.column_config.TextColumn("推荐理由")
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},
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hide_index=True,
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use_container_width=True
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)
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# 详细推荐理由
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st.markdown("### 📝 详细推荐理由")
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for stock in recommended[:5]: # 只显示前5只
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with st.expander(f"**{stock.get('rank', '-')}. {stock.get('name', '-')} ({stock.get('code', '-')})**"):
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col1, col2 = st.columns([2, 1])
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with col1:
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st.markdown(f"**推荐理由:** {stock.get('reason', '暂无')}")
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st.markdown(f"**净流入:** {stock.get('net_inflow', 0):,.2f} 元")
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with col2:
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st.markdown(f"**确定性:** {stock.get('confidence', '-')}")
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st.markdown(f"**持有周期:** {stock.get('hold_period', '-')}")
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def display_agents_reports(result):
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"""显示AI分析师报告"""
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st.subheader("🤖 AI分析师团队报告")
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agents_analysis = result.get('agents_analysis', {})
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if not agents_analysis:
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st.warning("暂无分析报告")
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return
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# 各分析师报告
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agent_info = {
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'youzi': {'title': '🎯 游资行为分析师', 'icon': '🎯'},
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'stock': {'title': '📈 个股潜力分析师', 'icon': '📈'},
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'theme': {'title': '🔥 题材追踪分析师', 'icon': '🔥'},
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'risk': {'title': '⚠️ 风险控制专家', 'icon': '⚠️'},
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'chief': {'title': '👔 首席策略师综合研判', 'icon': '👔'}
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}
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for agent_key, info in agent_info.items():
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agent_data = agents_analysis.get(agent_key, {})
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if agent_data:
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with st.expander(f"{info['icon']} {info['title']}", expanded=(agent_key == 'chief')):
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analysis = agent_data.get('analysis', '暂无分析')
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st.markdown(analysis)
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st.markdown(f"*{agent_data.get('agent_role', '')}*")
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st.caption(f"分析时间: {agent_data.get('timestamp', 'N/A')}")
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def display_data_details(result):
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"""显示数据详情"""
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st.subheader("📊 龙虎榜数据详情")
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data_info = result.get('data_info', {})
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summary = data_info.get('summary', {})
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# TOP游资
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if summary.get('top_youzi'):
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st.markdown("### 🏆 活跃游资 TOP10")
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youzi_data = [
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{'排名': idx, '游资名称': name, '净流入金额': amount}
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for idx, (name, amount) in enumerate(list(summary['top_youzi'].items())[:10], 1)
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]
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df_youzi = pd.DataFrame(youzi_data)
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st.dataframe(
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df_youzi,
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column_config={
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"排名": st.column_config.NumberColumn("排名", format="%d"),
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"游资名称": st.column_config.TextColumn("游资名称"),
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"净流入金额": st.column_config.NumberColumn("净流入金额(元)", format="%.2f")
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},
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hide_index=True,
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use_container_width=True
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)
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# TOP股票
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if summary.get('top_stocks'):
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st.markdown("### 📈 资金净流入 TOP20 股票")
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df_stocks = pd.DataFrame(summary['top_stocks'][:20])
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st.dataframe(
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df_stocks,
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column_config={
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"code": st.column_config.TextColumn("股票代码"),
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"name": st.column_config.TextColumn("股票名称"),
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"net_inflow": st.column_config.NumberColumn("净流入金额(元)", format="%.2f")
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},
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hide_index=True,
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use_container_width=True
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)
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# 热门概念
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if summary.get('hot_concepts'):
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st.markdown("### 🔥 热门概念 TOP20")
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concepts_data = [
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{'排名': idx, '概念名称': concept, '出现次数': count}
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for idx, (concept, count) in enumerate(list(summary['hot_concepts'].items())[:20], 1)
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]
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df_concepts = pd.DataFrame(concepts_data)
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st.dataframe(
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df_concepts,
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column_config={
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"排名": st.column_config.NumberColumn("排名", format="%d"),
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"概念名称": st.column_config.TextColumn("概念名称"),
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"出现次数": st.column_config.NumberColumn("出现次数", format="%d")
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},
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hide_index=True,
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use_container_width=True
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)
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def display_visualizations(result):
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"""显示可视化图表"""
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st.subheader("📈 数据可视化")
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data_info = result.get('data_info', {})
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summary = data_info.get('summary', {})
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# 资金流向图表
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if summary.get('top_stocks'):
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st.markdown("### 💰 TOP20 股票资金净流入")
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stocks = summary['top_stocks'][:20]
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df_chart = pd.DataFrame(stocks)
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fig = px.bar(
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df_chart,
|
||||
x='name',
|
||||
y='net_inflow',
|
||||
title='TOP20 股票资金净流入金额',
|
||||
labels={'name': '股票名称', 'net_inflow': '净流入金额(元)'}
|
||||
)
|
||||
fig.update_layout(xaxis_tickangle=-45)
|
||||
st.plotly_chart(fig, use_container_width=True)
|
||||
|
||||
# 热门概念图表
|
||||
if summary.get('hot_concepts'):
|
||||
st.markdown("### 🔥 热门概念分布")
|
||||
|
||||
concepts = list(summary['hot_concepts'].items())[:15]
|
||||
df_concepts = pd.DataFrame(concepts, columns=['概念', '次数'])
|
||||
|
||||
fig = px.pie(
|
||||
df_concepts,
|
||||
values='次数',
|
||||
names='概念',
|
||||
title='热门概念出现次数分布'
|
||||
)
|
||||
st.plotly_chart(fig, use_container_width=True)
|
||||
|
||||
|
||||
def display_pdf_export_section(result):
|
||||
"""显示PDF导出功能"""
|
||||
|
||||
st.markdown("### 📄 导出PDF报告")
|
||||
|
||||
col1, col2 = st.columns([3, 1])
|
||||
|
||||
with col1:
|
||||
st.info("💡 点击按钮生成并下载专业的PDF分析报告")
|
||||
|
||||
with col2:
|
||||
if st.button("📥 生成PDF", type="primary", use_container_width=True):
|
||||
with st.spinner("正在生成PDF报告..."):
|
||||
try:
|
||||
generator = LonghubangPDFGenerator()
|
||||
pdf_path = generator.generate_pdf(result)
|
||||
|
||||
# 读取PDF文件
|
||||
with open(pdf_path, "rb") as f:
|
||||
pdf_bytes = f.read()
|
||||
|
||||
# 提供下载
|
||||
st.download_button(
|
||||
label="📥 下载PDF报告",
|
||||
data=pdf_bytes,
|
||||
file_name=f"智瞰龙虎报告_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf",
|
||||
mime="application/pdf",
|
||||
use_container_width=True
|
||||
)
|
||||
|
||||
st.success("✅ PDF报告生成成功！")
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"❌ PDF生成失败: {str(e)}")
|
||||
|
||||
|
||||
def display_history_tab():
|
||||
"""显示历史报告标签页"""
|
||||
|
||||
st.subheader("📚 历史分析报告")
|
||||
|
||||
try:
|
||||
engine = LonghubangEngine()
|
||||
reports_df = engine.get_historical_reports(limit=20)
|
||||
|
||||
if reports_df.empty:
|
||||
st.info("暂无历史报告")
|
||||
return
|
||||
|
||||
st.dataframe(
|
||||
reports_df,
|
||||
column_config={
|
||||
"id": st.column_config.NumberColumn("ID", format="%d"),
|
||||
"analysis_date": st.column_config.TextColumn("分析时间"),
|
||||
"data_date_range": st.column_config.TextColumn("数据日期范围"),
|
||||
"summary": st.column_config.TextColumn("摘要")
|
||||
},
|
||||
hide_index=True,
|
||||
use_container_width=True
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"❌ 加载历史报告失败: {str(e)}")
|
||||
|
||||
|
||||
def display_statistics_tab():
|
||||
"""显示数据统计标签页"""
|
||||
|
||||
st.subheader("📈 数据统计")
|
||||
|
||||
try:
|
||||
engine = LonghubangEngine()
|
||||
stats = engine.get_statistics()
|
||||
|
||||
# 基本统计
|
||||
col1, col2, col3, col4 = st.columns(4)
|
||||
|
||||
with col1:
|
||||
st.metric("总记录数", f"{stats.get('total_records', 0):,}")
|
||||
|
||||
with col2:
|
||||
st.metric("股票总数", f"{stats.get('total_stocks', 0):,}")
|
||||
|
||||
with col3:
|
||||
st.metric("游资总数", f"{stats.get('total_youzi', 0):,}")
|
||||
|
||||
with col4:
|
||||
st.metric("分析报告", f"{stats.get('total_reports', 0):,}")
|
||||
|
||||
# 日期范围
|
||||
date_range = stats.get('date_range', {})
|
||||
if date_range:
|
||||
st.info(f"📅 数据日期范围: {date_range.get('start', 'N/A')} 至 {date_range.get('end', 'N/A')}")
|
||||
|
||||
st.markdown("---")
|
||||
|
||||
# 活跃游资排名
|
||||
st.markdown("### 🏆 历史活跃游资排名 (近30天)")
|
||||
|
||||
end_date = datetime.now().strftime('%Y-%m-%d')
|
||||
start_date = (datetime.now() - timedelta(days=30)).strftime('%Y-%m-%d')
|
||||
|
||||
top_youzi_df = engine.get_top_youzi(start_date, end_date, limit=20)
|
||||
|
||||
if not top_youzi_df.empty:
|
||||
st.dataframe(
|
||||
top_youzi_df,
|
||||
column_config={
|
||||
"youzi_name": st.column_config.TextColumn("游资名称"),
|
||||
"trade_count": st.column_config.NumberColumn("交易次数", format="%d"),
|
||||
"total_net_inflow": st.column_config.NumberColumn("总净流入(元)", format="%.2f")
|
||||
},
|
||||
hide_index=True,
|
||||
use_container_width=True
|
||||
)
|
||||
|
||||
st.markdown("---")
|
||||
|
||||
# 热门股票排名
|
||||
st.markdown("### 📈 历史热门股票排名 (近30天)")
|
||||
|
||||
top_stocks_df = engine.get_top_stocks(start_date, end_date, limit=20)
|
||||
|
||||
if not top_stocks_df.empty:
|
||||
st.dataframe(
|
||||
top_stocks_df,
|
||||
column_config={
|
||||
"stock_code": st.column_config.TextColumn("股票代码"),
|
||||
"stock_name": st.column_config.TextColumn("股票名称"),
|
||||
"youzi_count": st.column_config.NumberColumn("游资数量", format="%d"),
|
||||
"total_net_inflow": st.column_config.NumberColumn("总净流入(元)", format="%.2f")
|
||||
},
|
||||
hide_index=True,
|
||||
use_container_width=True
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
st.error(f"❌ 加载统计数据失败: {str(e)}")
|
||||
|
||||
|
||||
# 测试函数
|
||||
if __name__ == "__main__":
|
||||
st.set_page_config(
|
||||
page_title="智瞰龙虎",
|
||||
page_icon="🎯",
|
||||
layout="wide"
|
||||
)
|
||||
|
||||
display_longhubang()
|
||||
|
||||
Reference in New Issue
Block a user