oficcejo
2257 lines
84 KiB
Python
2257 lines
84 KiB
Python
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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import json
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from datetime import datetime
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import time
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import base64
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import os
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from stock_data import StockDataFetcher
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from ai_agents import StockAnalysisAgents
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from pdf_generator import display_pdf_export_section
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from database import db
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from monitor_manager import display_monitor_manager, get_monitor_summary
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from monitor_service import monitor_service
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from notification_service import notification_service
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from config_manager import config_manager
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# 页面配置
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st.set_page_config(
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page_title="复合多AI智能体股票团队分析系统",
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page_icon="📈",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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# 模型选择器
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def model_selector():
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"""模型选择器"""
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st.sidebar.markdown("---")
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st.sidebar.subheader("🤖 AI模型选择")
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model_options = {
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"deepseek-chat": "DeepSeek Chat (默认)",
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"deepseek-reasoner": "DeepSeek Reasoner (推理增强)"
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}
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selected_model = st.sidebar.selectbox(
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"选择AI模型",
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options=list(model_options.keys()),
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format_func=lambda x: model_options[x],
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help="DeepSeek Reasoner提供更强的推理能力，但响应时间可能更长"
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)
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return selected_model
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# 自定义CSS样式 - 专业版
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st.markdown("""
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<style>
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/* 全局样式 */
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.main {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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background-attachment: fixed;
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}
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.stApp {
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background: transparent;
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}
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/* 主容器 */
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.block-container {
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padding-top: 2rem;
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padding-bottom: 2rem;
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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box-shadow: 0 10px 40px rgba(0, 0, 0, 0.1);
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margin-top: 1rem;
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}
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/* 顶部导航栏 */
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.top-nav {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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padding: 1.5rem 2rem;
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border-radius: 15px;
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margin-bottom: 2rem;
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box-shadow: 0 8px 32px rgba(102, 126, 234, 0.3);
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}
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.nav-title {
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font-size: 2rem;
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font-weight: 800;
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color: white;
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text-align: center;
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margin: 0;
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text-shadow: 2px 2px 4px rgba(0,0,0,0.2);
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letter-spacing: 1px;
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}
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.nav-subtitle {
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text-align: center;
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color: rgba(255, 255, 255, 0.9);
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font-size: 0.95rem;
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margin-top: 0.5rem;
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font-weight: 300;
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}
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/* 标签页样式 */
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.stTabs [data-baseweb="tab-list"] {
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gap: 2rem;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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padding: 1rem 2rem;
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border-radius: 15px;
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box-shadow: 0 4px 15px rgba(102, 126, 234, 0.2);
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}
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.stTabs [data-baseweb="tab"] {
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height: 60px;
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background: rgba(255, 255, 255, 0.1);
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border-radius: 10px;
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color: white;
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font-weight: 600;
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font-size: 1.1rem;
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padding: 0 2rem;
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border: none;
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transition: all 0.3s ease;
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}
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.stTabs [data-baseweb="tab"]:hover {
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background: rgba(255, 255, 255, 0.2);
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transform: translateY(-2px);
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}
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.stTabs [aria-selected="true"] {
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background: white !important;
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color: #667eea !important;
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box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
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}
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/* 侧边栏美化 */
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.css-1d391kg, [data-testid="stSidebar"] {
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background: linear-gradient(180deg, #667eea 0%, #764ba2 100%);
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padding-top: 2rem;
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}
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.css-1d391kg h1, .css-1d391kg h2, .css-1d391kg h3,
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[data-testid="stSidebar"] h1, [data-testid="stSidebar"] h2, [data-testid="stSidebar"] h3 {
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color: white !important;
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}
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.css-1d391kg .stMarkdown, [data-testid="stSidebar"] .stMarkdown {
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color: rgba(255, 255, 255, 0.95) !important;
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}
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/* 分析师卡片 */
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.agent-card {
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background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
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padding: 1.5rem;
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border-radius: 15px;
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margin: 1rem 0;
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border-left: 5px solid #667eea;
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box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
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transition: transform 0.3s ease;
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}
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.agent-card:hover {
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transform: translateX(5px);
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}
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/* 决策卡片 */
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.decision-card {
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background: linear-gradient(135deg, #e8f5e9 0%, #c8e6c9 100%);
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padding: 2rem;
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border-radius: 15px;
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border: 3px solid #4caf50;
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margin: 1.5rem 0;
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box-shadow: 0 8px 30px rgba(76, 175, 80, 0.2);
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}
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/* 警告卡片 */
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.warning-card {
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background: linear-gradient(135deg, #fff3e0 0%, #ffe0b2 100%);
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padding: 1.5rem;
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border-radius: 15px;
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border-left: 5px solid #ff9800;
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box-shadow: 0 4px 15px rgba(255, 152, 0, 0.2);
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}
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/* 指标卡片 */
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.metric-card {
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background: white;
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padding: 1.5rem;
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border-radius: 12px;
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box-shadow: 0 4px 20px rgba(0, 0, 0, 0.08);
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text-align: center;
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transition: transform 0.3s ease, box-shadow 0.3s ease;
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border-top: 4px solid #667eea;
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}
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.metric-card:hover {
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transform: translateY(-5px);
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box-shadow: 0 8px 30px rgba(0, 0, 0, 0.15);
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}
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/* 按钮美化 */
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.stButton>button {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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border: none;
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border-radius: 10px;
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padding: 0.75rem 2rem;
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font-weight: 600;
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font-size: 1rem;
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transition: all 0.3s ease;
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box-shadow: 0 4px 15px rgba(102, 126, 234, 0.3);
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}
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.stButton>button:hover {
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transform: translateY(-2px);
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box-shadow: 0 6px 25px rgba(102, 126, 234, 0.4);
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}
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/* 输入框美化 */
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.stTextInput>div>div>input {
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border-radius: 10px;
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border: 2px solid #e0e0e0;
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padding: 0.75rem;
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font-size: 1rem;
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transition: border-color 0.3s ease;
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}
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.stTextInput>div>div>input:focus {
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border-color: #667eea;
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box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1);
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}
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/* 进度条美化 */
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.stProgress > div > div > div > div {
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background: linear-gradient(90deg, #667eea 0%, #764ba2 100%);
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}
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/* 成功/错误/警告/信息消息框 */
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.stSuccess, .stError, .stWarning, .stInfo {
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border-radius: 10px;
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padding: 1rem;
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box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
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}
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/* 图表容器 */
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.js-plotly-plot {
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border-radius: 15px;
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box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
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}
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/* Expander美化 */
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.streamlit-expanderHeader {
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background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
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border-radius: 10px;
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font-weight: 600;
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}
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/* 数据框美化 */
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.dataframe {
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border-radius: 10px;
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overflow: hidden;
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box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
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}
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/* 隐藏Streamlit默认元素 */
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#MainMenu {visibility: hidden;}
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footer {visibility: hidden;}
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/* 响应式设计 */
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@media (max-width: 768px) {
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.nav-title {
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font-size: 1.5rem;
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}
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.stTabs [data-baseweb="tab"] {
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font-size: 0.9rem;
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padding: 0 1rem;
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}
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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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# 顶部标题栏
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st.markdown("""
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<div class="top-nav">
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<h1 class="nav-title">📈 复合多AI智能体股票团队分析系统</h1>
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<p class="nav-subtitle">基于DeepSeek的专业量化投资分析平台 | Multi-Agent Stock Analysis System</p>
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</div>
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""", unsafe_allow_html=True)
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# 侧边栏
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with st.sidebar:
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# 快捷导航 - 移到顶部
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st.markdown("### 🔍 快捷导航")
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if st.button("📖 历史记录", use_container_width=True, key="nav_history"):
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st.session_state.show_history = True
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if 'show_monitor' in st.session_state:
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del st.session_state.show_monitor
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if st.button("📊 实时监测", use_container_width=True, key="nav_monitor"):
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st.session_state.show_monitor = True
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if 'show_history' in st.session_state:
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del st.session_state.show_history
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if st.button("🏠 返回首页", use_container_width=True, key="nav_home"):
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if 'show_history' in st.session_state:
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del st.session_state.show_history
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if 'show_monitor' in st.session_state:
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del st.session_state.show_monitor
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if 'show_config' in st.session_state:
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del st.session_state.show_config
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if st.button("⚙️ 环境配置", use_container_width=True, key="nav_config"):
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st.session_state.show_config = True
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if 'show_history' in st.session_state:
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del st.session_state.show_history
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if 'show_monitor' in st.session_state:
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del st.session_state.show_monitor
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st.markdown("---")
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# 系统配置
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st.markdown("### ⚙️ 系统配置")
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# API密钥检查
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api_key_status = check_api_key()
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if api_key_status:
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st.success("✅ API已连接")
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else:
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st.error("❌ API未配置")
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st.caption("请在.env中配置API密钥")
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st.markdown("---")
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# 模型选择器
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selected_model = model_selector()
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st.session_state.selected_model = selected_model
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st.markdown("---")
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# 系统状态面板
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st.markdown("### 📊 系统状态")
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monitor_status = "🟢 运行中" if monitor_service.running else "🔴 已停止"
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st.markdown(f"**监测服务**: {monitor_status}")
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try:
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from monitor_db import monitor_db
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stocks = monitor_db.get_monitored_stocks()
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notifications = monitor_db.get_pending_notifications()
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record_count = db.get_record_count()
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st.markdown(f"**分析记录**: {record_count}条")
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st.markdown(f"**监测股票**: {len(stocks)}只")
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st.markdown(f"**待处理**: {len(notifications)}条")
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except:
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pass
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st.markdown("---")
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# 分析参数设置
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st.markdown("### 📊 分析参数")
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period = st.selectbox(
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"数据周期",
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["1y", "6mo", "3mo", "1mo"],
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index=0,
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help="选择历史数据的时间范围"
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)
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st.markdown("---")
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# 帮助信息
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with st.expander("💡 使用帮助"):
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st.markdown("""
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**股票代码格式**
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- 🇨🇳 A股：6位数字（如600519）
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- 🇺🇸 美股：字母代码（如AAPL）
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**功能说明**
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- **智能分析**：AI团队深度分析
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- **实时监测**：价格监控与提醒
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- **历史记录**：查看分析历史
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**AI分析流程**
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1. 数据获取 → 2. 技术分析
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3. 基本面分析 → 4. 资金分析
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5. 情绪数据(ARBR) → 6. 新闻公告
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7. AI团队分析 → 8. 团队讨论 → 9. 决策
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""")
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# 检查是否显示历史记录
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if 'show_history' in st.session_state and st.session_state.show_history:
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display_history_records()
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return
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# 检查是否显示监测面板
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if 'show_monitor' in st.session_state and st.session_state.show_monitor:
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display_monitor_manager()
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return
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# 检查是否显示环境配置
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if 'show_config' in st.session_state and st.session_state.show_config:
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display_config_manager()
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return
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# 主界面
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# 添加单个/批量分析切换
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col_mode1, col_mode2 = st.columns([1, 3])
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with col_mode1:
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analysis_mode = st.radio(
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"分析模式",
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["单个分析", "批量分析"],
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horizontal=True,
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help="单个分析：分析单只股票；批量分析：同时分析多只股票"
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)
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with col_mode2:
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if analysis_mode == "批量分析":
|
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batch_mode = st.radio(
|
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"批量模式",
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["顺序分析", "多线程并行"],
|
||
horizontal=True,
|
||
help="顺序分析：按次序分析，稳定但较慢；多线程并行：同时分析多只，快速但消耗资源"
|
||
)
|
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st.session_state.batch_mode = batch_mode
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||
|
||
st.markdown("---")
|
||
|
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if analysis_mode == "单个分析":
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# 单个股票分析界面
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col1, col2, col3 = st.columns([2, 1, 1])
|
||
|
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with col1:
|
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stock_input = st.text_input(
|
||
"🔍 请输入股票代码或名称",
|
||
placeholder="例如: AAPL, 000001, 600036",
|
||
help="支持美股代码(如AAPL)和A股代码(如000001)"
|
||
)
|
||
|
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with col2:
|
||
analyze_button = st.button("🚀 开始分析", type="primary", use_container_width=True)
|
||
|
||
with col3:
|
||
if st.button("🔄 清除缓存", use_container_width=True):
|
||
st.cache_data.clear()
|
||
st.success("缓存已清除")
|
||
|
||
else:
|
||
# 批量股票分析界面
|
||
stock_input = st.text_area(
|
||
"🔍 请输入多个股票代码（每行一个或用逗号分隔）",
|
||
placeholder="例如:\n000001\n600036\n600519\n\n或者: 000001, 600036, 600519",
|
||
height=120,
|
||
help="支持多种格式：每行一个代码或用逗号分隔"
|
||
)
|
||
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||
col1, col2, col3 = st.columns(3)
|
||
with col1:
|
||
analyze_button = st.button("🚀 开始批量分析", type="primary", use_container_width=True)
|
||
with col2:
|
||
if st.button("🔄 清除缓存", use_container_width=True):
|
||
st.cache_data.clear()
|
||
st.success("缓存已清除")
|
||
with col3:
|
||
if st.button("🗑️ 清除结果", use_container_width=True):
|
||
if 'batch_analysis_results' in st.session_state:
|
||
del st.session_state.batch_analysis_results
|
||
st.success("已清除批量分析结果")
|
||
|
||
# 分析师团队选择
|
||
st.markdown("---")
|
||
st.subheader("👥 选择分析师团队")
|
||
|
||
col1, col2, col3 = st.columns(3)
|
||
|
||
with col1:
|
||
enable_technical = st.checkbox("📊 技术分析师", value=True,
|
||
help="负责技术指标分析、图表形态识别、趋势判断")
|
||
enable_fundamental = st.checkbox("💼 基本面分析师", value=True,
|
||
help="负责公司财务分析、行业研究、估值分析")
|
||
|
||
with col2:
|
||
enable_fund_flow = st.checkbox("💰 资金面分析师", value=True,
|
||
help="负责资金流向分析、主力行为研究")
|
||
enable_risk = st.checkbox("⚠️ 风险管理师", value=True,
|
||
help="负责风险识别、风险评估、风险控制策略制定")
|
||
|
||
with col3:
|
||
enable_sentiment = st.checkbox("📈 市场情绪分析师", value=False,
|
||
help="负责市场情绪研究、ARBR指标分析（仅A股）")
|
||
enable_news = st.checkbox("📰 新闻公告分析师", value=False,
|
||
help="负责新闻事件分析、公司公告解读（仅A股）")
|
||
|
||
# 显示已选择的分析师
|
||
selected_analysts = []
|
||
if enable_technical:
|
||
selected_analysts.append("技术分析师")
|
||
if enable_fundamental:
|
||
selected_analysts.append("基本面分析师")
|
||
if enable_fund_flow:
|
||
selected_analysts.append("资金面分析师")
|
||
if enable_risk:
|
||
selected_analysts.append("风险管理师")
|
||
if enable_sentiment:
|
||
selected_analysts.append("市场情绪分析师")
|
||
if enable_news:
|
||
selected_analysts.append("新闻公告分析师")
|
||
|
||
if selected_analysts:
|
||
st.info(f"✅ 已选择 {len(selected_analysts)} 位分析师: {', '.join(selected_analysts)}")
|
||
else:
|
||
st.warning("⚠️ 请至少选择一位分析师")
|
||
|
||
# 保存选择到session_state
|
||
st.session_state.enable_technical = enable_technical
|
||
st.session_state.enable_fundamental = enable_fundamental
|
||
st.session_state.enable_fund_flow = enable_fund_flow
|
||
st.session_state.enable_risk = enable_risk
|
||
st.session_state.enable_sentiment = enable_sentiment
|
||
st.session_state.enable_news = enable_news
|
||
|
||
st.markdown("---")
|
||
|
||
if analyze_button and stock_input:
|
||
if not api_key_status:
|
||
st.error("❌ 请先配置 DeepSeek API Key")
|
||
return
|
||
|
||
# 检查是否至少选择了一位分析师
|
||
if not selected_analysts:
|
||
st.error("❌ 请至少选择一位分析师参与分析")
|
||
return
|
||
|
||
if analysis_mode == "单个分析":
|
||
# 单个股票分析
|
||
# 清除之前的分析结果
|
||
if 'analysis_completed' in st.session_state:
|
||
del st.session_state.analysis_completed
|
||
if 'stock_info' in st.session_state:
|
||
del st.session_state.stock_info
|
||
if 'agents_results' in st.session_state:
|
||
del st.session_state.agents_results
|
||
if 'discussion_result' in st.session_state:
|
||
del st.session_state.discussion_result
|
||
if 'final_decision' in st.session_state:
|
||
del st.session_state.final_decision
|
||
|
||
run_stock_analysis(stock_input, period)
|
||
|
||
else:
|
||
# 批量股票分析
|
||
# 解析股票代码列表
|
||
stock_list = parse_stock_list(stock_input)
|
||
|
||
if not stock_list:
|
||
st.error("❌ 请输入有效的股票代码")
|
||
return
|
||
|
||
if len(stock_list) > 20:
|
||
st.warning(f"⚠️ 检测到 {len(stock_list)} 只股票，建议一次分析不超过20只")
|
||
|
||
st.info(f"📊 准备分析 {len(stock_list)} 只股票: {', '.join(stock_list)}")
|
||
|
||
# 清除之前的批量分析结果
|
||
if 'batch_analysis_results' in st.session_state:
|
||
del st.session_state.batch_analysis_results
|
||
|
||
# 获取批量模式
|
||
batch_mode = st.session_state.get('batch_mode', '顺序分析')
|
||
|
||
# 运行批量分析
|
||
run_batch_analysis(stock_list, period, batch_mode)
|
||
|
||
# 检查是否有已完成的单个分析结果
|
||
if 'analysis_completed' in st.session_state and st.session_state.analysis_completed:
|
||
# 重新显示分析结果
|
||
stock_info = st.session_state.stock_info
|
||
agents_results = st.session_state.agents_results
|
||
discussion_result = st.session_state.discussion_result
|
||
final_decision = st.session_state.final_decision
|
||
|
||
# 重新获取股票数据用于显示图表
|
||
stock_info_current, stock_data, indicators = get_stock_data(stock_info['symbol'], period)
|
||
|
||
# 显示股票基本信息
|
||
display_stock_info(stock_info, indicators)
|
||
|
||
# 显示股票图表
|
||
if stock_data is not None:
|
||
display_stock_chart(stock_data, stock_info)
|
||
|
||
# 显示各分析师报告
|
||
display_agents_analysis(agents_results)
|
||
|
||
# 显示团队讨论
|
||
display_team_discussion(discussion_result)
|
||
|
||
# 显示最终决策
|
||
display_final_decision(final_decision, stock_info, agents_results, discussion_result)
|
||
|
||
# 检查是否有已完成的批量分析结果
|
||
elif 'batch_analysis_results' in st.session_state and st.session_state.batch_analysis_results:
|
||
display_batch_analysis_results(st.session_state.batch_analysis_results, period)
|
||
|
||
# 示例和说明
|
||
elif not stock_input:
|
||
show_example_interface()
|
||
|
||
def check_api_key():
|
||
"""检查API密钥是否配置"""
|
||
try:
|
||
import config
|
||
return bool(config.DEEPSEEK_API_KEY and config.DEEPSEEK_API_KEY.strip())
|
||
except:
|
||
return False
|
||
|
||
@st.cache_data(ttl=300) # 缓存5分钟
|
||
def get_stock_data(symbol, period):
|
||
"""获取股票数据（带缓存）"""
|
||
fetcher = StockDataFetcher()
|
||
stock_info = fetcher.get_stock_info(symbol)
|
||
stock_data = fetcher.get_stock_data(symbol, period)
|
||
|
||
if isinstance(stock_data, dict) and "error" in stock_data:
|
||
return stock_info, None, None
|
||
|
||
stock_data_with_indicators = fetcher.calculate_technical_indicators(stock_data)
|
||
indicators = fetcher.get_latest_indicators(stock_data_with_indicators)
|
||
|
||
return stock_info, stock_data_with_indicators, indicators
|
||
|
||
def parse_stock_list(stock_input):
|
||
"""解析股票代码列表
|
||
|
||
支持的格式：
|
||
- 每行一个代码
|
||
- 逗号分隔
|
||
- 空格分隔
|
||
"""
|
||
if not stock_input or not stock_input.strip():
|
||
return []
|
||
|
||
# 先按换行符分割
|
||
lines = stock_input.strip().split('\n')
|
||
|
||
# 处理每一行
|
||
stock_list = []
|
||
for line in lines:
|
||
line = line.strip()
|
||
if not line:
|
||
continue
|
||
|
||
# 检查是否包含逗号
|
||
if ',' in line:
|
||
codes = [code.strip() for code in line.split(',')]
|
||
stock_list.extend([code for code in codes if code])
|
||
# 检查是否包含空格
|
||
elif ' ' in line:
|
||
codes = [code.strip() for code in line.split()]
|
||
stock_list.extend([code for code in codes if code])
|
||
else:
|
||
stock_list.append(line)
|
||
|
||
# 去重并保持顺序
|
||
seen = set()
|
||
unique_list = []
|
||
for code in stock_list:
|
||
if code not in seen:
|
||
seen.add(code)
|
||
unique_list.append(code)
|
||
|
||
return unique_list
|
||
|
||
def analyze_single_stock_for_batch(symbol, period, enabled_analysts_config=None, selected_model='deepseek-chat'):
|
||
"""单个股票分析（用于批量分析）
|
||
|
||
Args:
|
||
symbol: 股票代码
|
||
period: 数据周期
|
||
enabled_analysts_config: 分析师配置字典
|
||
selected_model: 选择的AI模型
|
||
|
||
返回分析结果或错误信息
|
||
"""
|
||
try:
|
||
# 使用默认配置
|
||
if enabled_analysts_config is None:
|
||
enabled_analysts_config = {
|
||
'technical': True,
|
||
'fundamental': True,
|
||
'fund_flow': True,
|
||
'risk': True,
|
||
'sentiment': False,
|
||
'news': False
|
||
}
|
||
|
||
# 1. 获取股票数据
|
||
stock_info, stock_data, indicators = get_stock_data(symbol, period)
|
||
|
||
if "error" in stock_info:
|
||
return {"symbol": symbol, "error": stock_info['error'], "success": False}
|
||
|
||
if stock_data is None:
|
||
return {"symbol": symbol, "error": "无法获取股票历史数据", "success": False}
|
||
|
||
# 2. 获取财务数据
|
||
fetcher = StockDataFetcher()
|
||
financial_data = fetcher.get_financial_data(symbol)
|
||
|
||
# 获取分析师选择状态（从参数而不是session_state）
|
||
enable_fund_flow = enabled_analysts_config.get('fund_flow', True)
|
||
enable_sentiment = enabled_analysts_config.get('sentiment', False)
|
||
enable_news = enabled_analysts_config.get('news', False)
|
||
|
||
# 3. 获取资金流向数据（可选）
|
||
fund_flow_data = None
|
||
if enable_fund_flow and fetcher._is_chinese_stock(symbol):
|
||
try:
|
||
fund_flow_data = fetcher.get_fund_flow_data(symbol)
|
||
except:
|
||
pass
|
||
|
||
# 4. 获取市场情绪数据（可选）
|
||
sentiment_data = None
|
||
if enable_sentiment and fetcher._is_chinese_stock(symbol):
|
||
try:
|
||
from market_sentiment_data import MarketSentimentDataFetcher
|
||
sentiment_fetcher = MarketSentimentDataFetcher()
|
||
sentiment_data = sentiment_fetcher.get_market_sentiment_data(symbol, stock_data)
|
||
except:
|
||
pass
|
||
|
||
# 5. 获取新闻公告数据（可选）
|
||
news_announcement_data = None
|
||
if enable_news and fetcher._is_chinese_stock(symbol):
|
||
try:
|
||
from news_announcement_data import NewsAnnouncementDataFetcher
|
||
news_fetcher = NewsAnnouncementDataFetcher()
|
||
news_announcement_data = news_fetcher.get_news_and_announcements(symbol)
|
||
except:
|
||
pass
|
||
|
||
# 6. 初始化AI分析系统
|
||
agents = StockAnalysisAgents(model=selected_model)
|
||
|
||
# 使用传入的分析师配置
|
||
enabled_analysts = enabled_analysts_config
|
||
|
||
# 7. 运行多智能体分析
|
||
agents_results = agents.run_multi_agent_analysis(
|
||
stock_info, stock_data, indicators, financial_data,
|
||
fund_flow_data, sentiment_data, news_announcement_data,
|
||
enabled_analysts=enabled_analysts
|
||
)
|
||
|
||
# 8. 团队讨论
|
||
discussion_result = agents.conduct_team_discussion(agents_results, stock_info)
|
||
|
||
# 9. 最终决策
|
||
final_decision = agents.make_final_decision(discussion_result, stock_info, indicators)
|
||
|
||
# 保存到数据库
|
||
saved_to_db = False
|
||
db_error = None
|
||
try:
|
||
record_id = db.save_analysis(
|
||
symbol=stock_info.get('symbol', ''),
|
||
stock_name=stock_info.get('name', ''),
|
||
period=period,
|
||
stock_info=stock_info,
|
||
agents_results=agents_results,
|
||
discussion_result=discussion_result,
|
||
final_decision=final_decision
|
||
)
|
||
saved_to_db = True
|
||
print(f"✅ {symbol} 成功保存到数据库，记录ID: {record_id}")
|
||
except Exception as e:
|
||
db_error = str(e)
|
||
print(f"❌ {symbol} 保存到数据库失败: {db_error}")
|
||
|
||
return {
|
||
"symbol": symbol,
|
||
"success": True,
|
||
"stock_info": stock_info,
|
||
"indicators": indicators,
|
||
"agents_results": agents_results,
|
||
"discussion_result": discussion_result,
|
||
"final_decision": final_decision,
|
||
"saved_to_db": saved_to_db,
|
||
"db_error": db_error
|
||
}
|
||
|
||
except Exception as e:
|
||
return {"symbol": symbol, "error": str(e), "success": False}
|
||
|
||
def run_batch_analysis(stock_list, period, batch_mode="顺序分析"):
|
||
"""运行批量股票分析"""
|
||
import concurrent.futures
|
||
import threading
|
||
|
||
# 在开始分析前获取配置（从session_state）
|
||
enabled_analysts_config = {
|
||
'technical': st.session_state.get('enable_technical', True),
|
||
'fundamental': st.session_state.get('enable_fundamental', True),
|
||
'fund_flow': st.session_state.get('enable_fund_flow', True),
|
||
'risk': st.session_state.get('enable_risk', True),
|
||
'sentiment': st.session_state.get('enable_sentiment', False),
|
||
'news': st.session_state.get('enable_news', False)
|
||
}
|
||
selected_model = st.session_state.get('selected_model', 'deepseek-chat')
|
||
|
||
# 创建进度显示
|
||
st.subheader(f"📊 批量分析进行中 ({batch_mode})")
|
||
|
||
progress_bar = st.progress(0)
|
||
status_text = st.empty()
|
||
|
||
# 存储结果
|
||
results = []
|
||
total = len(stock_list)
|
||
|
||
if batch_mode == "多线程并行":
|
||
# 多线程并行分析
|
||
status_text.text(f"🚀 使用多线程并行分析 {total} 只股票...")
|
||
|
||
# 创建线程锁用于更新进度
|
||
lock = threading.Lock()
|
||
completed = [0] # 使用列表以便在闭包中修改
|
||
progress_status = [{}] # 存储进度状态
|
||
|
||
def analyze_with_progress(symbol):
|
||
"""包装分析函数，不在线程中访问Streamlit上下文"""
|
||
try:
|
||
result = analyze_single_stock_for_batch(symbol, period, enabled_analysts_config, selected_model)
|
||
with lock:
|
||
completed[0] += 1
|
||
progress_status[0][symbol] = result
|
||
return result
|
||
except Exception as e:
|
||
with lock:
|
||
completed[0] += 1
|
||
error_result = {"symbol": symbol, "error": str(e), "success": False}
|
||
progress_status[0][symbol] = error_result
|
||
return error_result
|
||
|
||
# 使用线程池执行，限制最大并发数为3以避免API限流
|
||
with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
|
||
future_to_symbol = {executor.submit(analyze_with_progress, symbol): symbol
|
||
for symbol in stock_list}
|
||
|
||
for future in concurrent.futures.as_completed(future_to_symbol):
|
||
symbol = future_to_symbol[future]
|
||
try:
|
||
result = future.result(timeout=300) # 5分钟超时
|
||
results.append(result)
|
||
|
||
# 在主线程中更新UI
|
||
progress = len(results) / total
|
||
progress_bar.progress(progress)
|
||
|
||
if result['success']:
|
||
status_text.text(f"✅ [{len(results)}/{total}] {symbol} 分析完成")
|
||
else:
|
||
status_text.text(f"❌ [{len(results)}/{total}] {symbol} 分析失败: {result.get('error', '未知错误')}")
|
||
|
||
except concurrent.futures.TimeoutError:
|
||
results.append({"symbol": symbol, "error": "分析超时（5分钟）", "success": False})
|
||
progress_bar.progress(len(results) / total)
|
||
status_text.text(f"⏱️ [{len(results)}/{total}] {symbol} 分析超时")
|
||
except Exception as e:
|
||
results.append({"symbol": symbol, "error": str(e), "success": False})
|
||
progress_bar.progress(len(results) / total)
|
||
status_text.text(f"❌ [{len(results)}/{total}] {symbol} 出现错误")
|
||
|
||
else:
|
||
# 顺序分析
|
||
status_text.text(f"📝 按顺序分析 {total} 只股票...")
|
||
|
||
for i, symbol in enumerate(stock_list, 1):
|
||
status_text.text(f"🔍 [{i}/{total}] 正在分析 {symbol}...")
|
||
|
||
try:
|
||
result = analyze_single_stock_for_batch(symbol, period, enabled_analysts_config, selected_model)
|
||
except Exception as e:
|
||
result = {"symbol": symbol, "error": str(e), "success": False}
|
||
|
||
results.append(result)
|
||
|
||
# 更新进度
|
||
progress = i / total
|
||
progress_bar.progress(progress)
|
||
|
||
if result['success']:
|
||
status_text.text(f"✅ [{i}/{total}] {symbol} 分析完成")
|
||
else:
|
||
status_text.text(f"❌ [{i}/{total}] {symbol} 分析失败: {result.get('error', '未知错误')}")
|
||
|
||
# 完成
|
||
progress_bar.progress(1.0)
|
||
|
||
# 统计结果
|
||
success_count = sum(1 for r in results if r['success'])
|
||
failed_count = total - success_count
|
||
saved_count = sum(1 for r in results if r.get('saved_to_db', False))
|
||
|
||
# 显示完成信息
|
||
if success_count > 0:
|
||
status_text.success(f"✅ 批量分析完成！成功 {success_count} 只，失败 {failed_count} 只，已保存 {saved_count} 只到历史记录")
|
||
|
||
# 显示保存失败的股票
|
||
save_failed = [r['symbol'] for r in results if r.get('success') and not r.get('saved_to_db', False)]
|
||
if save_failed:
|
||
st.warning(f"⚠️ 以下股票分析成功但保存失败: {', '.join(save_failed)}")
|
||
else:
|
||
status_text.error(f"❌ 批量分析完成，但所有股票都分析失败")
|
||
|
||
# 保存结果到session_state
|
||
st.session_state.batch_analysis_results = results
|
||
st.session_state.batch_analysis_mode = batch_mode
|
||
|
||
time.sleep(1)
|
||
progress_bar.empty()
|
||
|
||
# 自动显示结果
|
||
st.rerun()
|
||
|
||
def run_stock_analysis(symbol, period):
|
||
"""运行股票分析"""
|
||
|
||
# 进度条
|
||
progress_bar = st.progress(0)
|
||
status_text = st.empty()
|
||
|
||
try:
|
||
# 1. 获取股票数据
|
||
status_text.text("📈 正在获取股票数据...")
|
||
progress_bar.progress(10)
|
||
|
||
stock_info, stock_data, indicators = get_stock_data(symbol, period)
|
||
|
||
if "error" in stock_info:
|
||
st.error(f"❌ {stock_info['error']}")
|
||
return
|
||
|
||
if stock_data is None:
|
||
st.error("❌ 无法获取股票历史数据")
|
||
return
|
||
|
||
# 显示股票基本信息
|
||
display_stock_info(stock_info, indicators)
|
||
progress_bar.progress(20)
|
||
|
||
# 显示股票图表
|
||
display_stock_chart(stock_data, stock_info)
|
||
progress_bar.progress(30)
|
||
|
||
# 2. 获取财务数据
|
||
status_text.text("📊 正在获取财务数据...")
|
||
fetcher = StockDataFetcher() # 创建fetcher实例
|
||
financial_data = fetcher.get_financial_data(symbol)
|
||
progress_bar.progress(35)
|
||
|
||
# 获取分析师选择状态
|
||
enable_fund_flow = st.session_state.get('enable_fund_flow', True)
|
||
enable_sentiment = st.session_state.get('enable_sentiment', False)
|
||
enable_news = st.session_state.get('enable_news', False)
|
||
|
||
# 3. 获取资金流向数据（仅在选择了资金面分析师时）
|
||
fund_flow_data = None
|
||
if enable_fund_flow and fetcher._is_chinese_stock(symbol):
|
||
status_text.text("💰 正在获取资金流向数据（主力）...")
|
||
try:
|
||
fund_flow_data = fetcher.get_fund_flow_data(symbol)
|
||
if fund_flow_data and fund_flow_data.get('query_success'):
|
||
st.info("✅ 成功获取主力资金流向数据")
|
||
else:
|
||
st.warning("⚠️ 未能获取主力资金流向数据，将基于技术指标进行资金面分析")
|
||
except Exception as e:
|
||
st.warning(f"⚠️ 获取资金流向数据时出错: {str(e)}")
|
||
fund_flow_data = None
|
||
elif enable_fund_flow and not fetcher._is_chinese_stock(symbol):
|
||
st.info("ℹ️ 美股暂不支持资金流向数据")
|
||
progress_bar.progress(40)
|
||
|
||
# 4. 获取市场情绪数据（仅在选择了市场情绪分析师时）
|
||
sentiment_data = None
|
||
if enable_sentiment and fetcher._is_chinese_stock(symbol):
|
||
status_text.text("📊 正在获取市场情绪数据（ARBR等指标）...")
|
||
try:
|
||
from market_sentiment_data import MarketSentimentDataFetcher
|
||
sentiment_fetcher = MarketSentimentDataFetcher()
|
||
sentiment_data = sentiment_fetcher.get_market_sentiment_data(symbol, stock_data)
|
||
if sentiment_data and sentiment_data.get('data_success'):
|
||
st.info("✅ 成功获取市场情绪数据（ARBR、换手率、涨跌停等）")
|
||
else:
|
||
st.warning("⚠️ 未能获取完整的市场情绪数据，将基于基本信息进行分析")
|
||
except Exception as e:
|
||
st.warning(f"⚠️ 获取市场情绪数据时出错: {str(e)}")
|
||
sentiment_data = None
|
||
elif enable_sentiment and not fetcher._is_chinese_stock(symbol):
|
||
st.info("ℹ️ 美股暂不支持市场情绪数据（ARBR等指标）")
|
||
progress_bar.progress(45)
|
||
|
||
# 5. 获取新闻公告数据（仅在选择了新闻公告分析师时）
|
||
news_announcement_data = None
|
||
if enable_news and fetcher._is_chinese_stock(symbol):
|
||
status_text.text("📰 正在获取新闻公告数据（问财）...")
|
||
try:
|
||
from news_announcement_data import NewsAnnouncementDataFetcher
|
||
news_fetcher = NewsAnnouncementDataFetcher()
|
||
news_announcement_data = news_fetcher.get_news_and_announcements(symbol)
|
||
if news_announcement_data and news_announcement_data.get('data_success'):
|
||
news_count = news_announcement_data.get('news_data', {}).get('count', 0) if news_announcement_data.get('news_data') else 0
|
||
announcement_count = news_announcement_data.get('announcement_data', {}).get('count', 0) if news_announcement_data.get('announcement_data') else 0
|
||
st.info(f"✅ 成功获取 {news_count} 条新闻，{announcement_count} 条公告")
|
||
else:
|
||
st.warning("⚠️ 未能获取新闻公告数据，将基于基本信息进行分析")
|
||
except Exception as e:
|
||
st.warning(f"⚠️ 获取新闻公告数据时出错: {str(e)}")
|
||
news_announcement_data = None
|
||
elif enable_news and not fetcher._is_chinese_stock(symbol):
|
||
st.info("ℹ️ 美股暂不支持新闻公告数据")
|
||
progress_bar.progress(50)
|
||
|
||
# 6. 初始化AI分析系统
|
||
status_text.text("🤖 正在初始化AI分析系统...")
|
||
# 使用选择的模型
|
||
selected_model = st.session_state.get('selected_model', 'deepseek-chat')
|
||
agents = StockAnalysisAgents(model=selected_model)
|
||
progress_bar.progress(55)
|
||
|
||
# 获取所有分析师选择状态
|
||
enable_technical = st.session_state.get('enable_technical', True)
|
||
enable_fundamental = st.session_state.get('enable_fundamental', True)
|
||
enable_risk = st.session_state.get('enable_risk', True)
|
||
|
||
# 创建分析师启用字典
|
||
enabled_analysts = {
|
||
'technical': enable_technical,
|
||
'fundamental': enable_fundamental,
|
||
'fund_flow': enable_fund_flow,
|
||
'risk': enable_risk,
|
||
'sentiment': enable_sentiment,
|
||
'news': enable_news
|
||
}
|
||
|
||
# 7. 运行多智能体分析（传入所有数据和分析师选择）
|
||
status_text.text("🔍 AI分析师团队正在分析,请耐心等待几分钟...")
|
||
agents_results = agents.run_multi_agent_analysis(
|
||
stock_info, stock_data, indicators, financial_data,
|
||
fund_flow_data, sentiment_data, news_announcement_data,
|
||
enabled_analysts=enabled_analysts
|
||
)
|
||
progress_bar.progress(75)
|
||
|
||
# 显示各分析师报告
|
||
display_agents_analysis(agents_results)
|
||
|
||
# 8. 团队讨论
|
||
status_text.text("🤝 分析团队正在讨论...")
|
||
discussion_result = agents.conduct_team_discussion(agents_results, stock_info)
|
||
progress_bar.progress(88)
|
||
|
||
# 显示团队讨论
|
||
display_team_discussion(discussion_result)
|
||
|
||
# 9. 最终决策
|
||
status_text.text("📋 正在制定最终投资决策...")
|
||
final_decision = agents.make_final_decision(discussion_result, stock_info, indicators)
|
||
progress_bar.progress(100)
|
||
|
||
# 保存分析结果到session_state
|
||
st.session_state.analysis_completed = True
|
||
st.session_state.stock_info = stock_info
|
||
st.session_state.agents_results = agents_results
|
||
st.session_state.discussion_result = discussion_result
|
||
st.session_state.final_decision = final_decision
|
||
|
||
# 保存到数据库
|
||
try:
|
||
db.save_analysis(
|
||
symbol=stock_info.get('symbol', ''),
|
||
stock_name=stock_info.get('name', ''),
|
||
period=period,
|
||
stock_info=stock_info,
|
||
agents_results=agents_results,
|
||
discussion_result=discussion_result,
|
||
final_decision=final_decision
|
||
)
|
||
st.success("✅ 分析记录已保存到数据库")
|
||
except Exception as e:
|
||
st.warning(f"⚠️ 保存到数据库时出现错误: {str(e)}")
|
||
|
||
# 显示最终决策
|
||
display_final_decision(final_decision, stock_info, agents_results, discussion_result)
|
||
|
||
status_text.text("✅ 分析完成！")
|
||
time.sleep(1)
|
||
status_text.empty()
|
||
progress_bar.empty()
|
||
|
||
except Exception as e:
|
||
st.error(f"❌ 分析过程中出现错误: {str(e)}")
|
||
progress_bar.empty()
|
||
status_text.empty()
|
||
|
||
def display_stock_info(stock_info, indicators):
|
||
"""显示股票基本信息"""
|
||
st.subheader(f"📊 {stock_info.get('name', 'N/A')} ({stock_info.get('symbol', 'N/A')})")
|
||
|
||
# 基本信息卡片
|
||
col1, col2, col3, col4, col5 = st.columns(5)
|
||
|
||
with col1:
|
||
current_price = stock_info.get('current_price', 'N/A')
|
||
st.metric("当前价格", f"{current_price}")
|
||
|
||
with col2:
|
||
change_percent = stock_info.get('change_percent', 'N/A')
|
||
if isinstance(change_percent, (int, float)):
|
||
st.metric("涨跌幅", f"{change_percent:.2f}%", f"{change_percent:.2f}%")
|
||
else:
|
||
st.metric("涨跌幅", f"{change_percent}")
|
||
|
||
with col3:
|
||
pe_ratio = stock_info.get('pe_ratio', 'N/A')
|
||
st.metric("市盈率", f"{pe_ratio}")
|
||
|
||
with col4:
|
||
pb_ratio = stock_info.get('pb_ratio', 'N/A')
|
||
st.metric("市净率", f"{pb_ratio}")
|
||
|
||
with col5:
|
||
market_cap = stock_info.get('market_cap', 'N/A')
|
||
if isinstance(market_cap, (int, float)):
|
||
market_cap_str = f"{market_cap/1e9:.2f}B" if market_cap > 1e9 else f"{market_cap/1e6:.2f}M"
|
||
st.metric("市值", market_cap_str)
|
||
else:
|
||
st.metric("市值", f"{market_cap}")
|
||
|
||
# 技术指标
|
||
if indicators and not isinstance(indicators, dict) or "error" not in indicators:
|
||
st.subheader("📈 关键技术指标")
|
||
|
||
col1, col2, col3, col4 = st.columns(4)
|
||
|
||
with col1:
|
||
rsi = indicators.get('rsi', 'N/A')
|
||
if isinstance(rsi, (int, float)):
|
||
rsi_color = "normal"
|
||
if rsi > 70:
|
||
rsi_color = "inverse"
|
||
elif rsi < 30:
|
||
rsi_color = "off"
|
||
st.metric("RSI", f"{rsi:.2f}")
|
||
else:
|
||
st.metric("RSI", f"{rsi}")
|
||
|
||
with col2:
|
||
ma20 = indicators.get('ma20', 'N/A')
|
||
if isinstance(ma20, (int, float)):
|
||
st.metric("MA20", f"{ma20:.2f}")
|
||
else:
|
||
st.metric("MA20", f"{ma20}")
|
||
|
||
with col3:
|
||
volume_ratio = indicators.get('volume_ratio', 'N/A')
|
||
if isinstance(volume_ratio, (int, float)):
|
||
st.metric("量比", f"{volume_ratio:.2f}")
|
||
else:
|
||
st.metric("量比", f"{volume_ratio}")
|
||
|
||
with col4:
|
||
macd = indicators.get('macd', 'N/A')
|
||
if isinstance(macd, (int, float)):
|
||
st.metric("MACD", f"{macd:.4f}")
|
||
else:
|
||
st.metric("MACD", f"{macd}")
|
||
|
||
def display_stock_chart(stock_data, stock_info):
|
||
"""显示股票图表"""
|
||
st.subheader("📈 股价走势图")
|
||
|
||
# 创建蜡烛图
|
||
fig = go.Figure()
|
||
|
||
# 添加蜡烛图
|
||
fig.add_trace(go.Candlestick(
|
||
x=stock_data.index,
|
||
open=stock_data['Open'],
|
||
high=stock_data['High'],
|
||
low=stock_data['Low'],
|
||
close=stock_data['Close'],
|
||
name="K线"
|
||
))
|
||
|
||
# 添加移动平均线
|
||
if 'MA5' in stock_data.columns:
|
||
fig.add_trace(go.Scatter(
|
||
x=stock_data.index,
|
||
y=stock_data['MA5'],
|
||
name="MA5",
|
||
line=dict(color='orange', width=1)
|
||
))
|
||
|
||
if 'MA20' in stock_data.columns:
|
||
fig.add_trace(go.Scatter(
|
||
x=stock_data.index,
|
||
y=stock_data['MA20'],
|
||
name="MA20",
|
||
line=dict(color='blue', width=1)
|
||
))
|
||
|
||
if 'MA60' in stock_data.columns:
|
||
fig.add_trace(go.Scatter(
|
||
x=stock_data.index,
|
||
y=stock_data['MA60'],
|
||
name="MA60",
|
||
line=dict(color='purple', width=1)
|
||
))
|
||
|
||
# 布林带
|
||
if 'BB_upper' in stock_data.columns and 'BB_lower' in stock_data.columns:
|
||
fig.add_trace(go.Scatter(
|
||
x=stock_data.index,
|
||
y=stock_data['BB_upper'],
|
||
name="布林上轨",
|
||
line=dict(color='red', width=1, dash='dash')
|
||
))
|
||
fig.add_trace(go.Scatter(
|
||
x=stock_data.index,
|
||
y=stock_data['BB_lower'],
|
||
name="布林下轨",
|
||
line=dict(color='green', width=1, dash='dash'),
|
||
fill='tonexty',
|
||
fillcolor='rgba(0,100,80,0.1)'
|
||
))
|
||
|
||
fig.update_layout(
|
||
title=f"{stock_info.get('name', 'N/A')} 股价走势",
|
||
xaxis_title="日期",
|
||
yaxis_title="价格",
|
||
height=500,
|
||
showlegend=True
|
||
)
|
||
|
||
# 生成唯一的key
|
||
chart_key = f"main_stock_chart_{stock_info.get('symbol', 'unknown')}_{int(time.time())}"
|
||
st.plotly_chart(fig, use_container_width=True, key=chart_key)
|
||
|
||
# 成交量图
|
||
if 'Volume' in stock_data.columns:
|
||
fig_volume = go.Figure()
|
||
fig_volume.add_trace(go.Bar(
|
||
x=stock_data.index,
|
||
y=stock_data['Volume'],
|
||
name="成交量",
|
||
marker_color='lightblue'
|
||
))
|
||
|
||
fig_volume.update_layout(
|
||
title="成交量",
|
||
xaxis_title="日期",
|
||
yaxis_title="成交量",
|
||
height=200
|
||
)
|
||
|
||
# 生成唯一的key
|
||
volume_key = f"volume_chart_{stock_info.get('symbol', 'unknown')}_{int(time.time())}"
|
||
st.plotly_chart(fig_volume, use_container_width=True, key=volume_key)
|
||
|
||
def display_agents_analysis(agents_results):
|
||
"""显示各分析师报告"""
|
||
st.subheader("🤖 AI分析师团队报告")
|
||
|
||
# 创建标签页
|
||
tab_names = []
|
||
tab_contents = []
|
||
|
||
for agent_key, agent_result in agents_results.items():
|
||
agent_name = agent_result.get('agent_name', '未知分析师')
|
||
tab_names.append(agent_name)
|
||
tab_contents.append(agent_result)
|
||
|
||
tabs = st.tabs(tab_names)
|
||
|
||
for i, tab in enumerate(tabs):
|
||
with tab:
|
||
agent_result = tab_contents[i]
|
||
|
||
# 分析师信息
|
||
st.markdown(f"""
|
||
<div class="agent-card">
|
||
<h4>👨💼 {agent_result.get('agent_name', '未知')}</h4>
|
||
<p><strong>职责：</strong>{agent_result.get('agent_role', '未知')}</p>
|
||
<p><strong>关注领域：</strong>{', '.join(agent_result.get('focus_areas', []))}</p>
|
||
<p><strong>分析时间：</strong>{agent_result.get('timestamp', '未知')}</p>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
# 分析报告
|
||
st.markdown("**📄 分析报告:**")
|
||
st.write(agent_result.get('analysis', '暂无分析'))
|
||
|
||
def display_team_discussion(discussion_result):
|
||
"""显示团队讨论"""
|
||
st.subheader("🤝 分析团队讨论")
|
||
|
||
st.markdown("""
|
||
<div class="agent-card">
|
||
<h4>💭 团队综合讨论</h4>
|
||
<p>各位分析师正在就该股票进行深入讨论，整合不同维度的分析观点...</p>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
st.write(discussion_result)
|
||
|
||
def display_final_decision(final_decision, stock_info, agents_results=None, discussion_result=None):
|
||
"""显示最终投资决策"""
|
||
st.subheader("📋 最终投资决策")
|
||
|
||
if isinstance(final_decision, dict) and "decision_text" not in final_decision:
|
||
# JSON格式的决策
|
||
col1, col2 = st.columns([1, 2])
|
||
|
||
with col1:
|
||
# 投资评级
|
||
rating = final_decision.get('rating', '未知')
|
||
rating_color = {"买入": "🟢", "持有": "🟡", "卖出": "🔴"}.get(rating, "⚪")
|
||
|
||
st.markdown(f"""
|
||
<div class="decision-card">
|
||
<h3 style="text-align: center;">{rating_color} {rating}</h3>
|
||
<h4 style="text-align: center;">投资评级</h4>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
# 关键指标
|
||
confidence = final_decision.get('confidence_level', 'N/A')
|
||
st.metric("信心度", f"{confidence}/10")
|
||
|
||
target_price = final_decision.get('target_price', 'N/A')
|
||
st.metric("目标价格", f"{target_price}")
|
||
|
||
position_size = final_decision.get('position_size', 'N/A')
|
||
st.metric("建议仓位", f"{position_size}")
|
||
|
||
with col2:
|
||
# 详细建议
|
||
st.markdown("**🎯 操作建议:**")
|
||
st.write(final_decision.get('operation_advice', '暂无建议'))
|
||
|
||
st.markdown("**📍 关键位置:**")
|
||
col2_1, col2_2 = st.columns(2)
|
||
|
||
with col2_1:
|
||
st.write(f"**进场区间:** {final_decision.get('entry_range', 'N/A')}")
|
||
st.write(f"**止盈位:** {final_decision.get('take_profit', 'N/A')}")
|
||
|
||
with col2_2:
|
||
st.write(f"**止损位:** {final_decision.get('stop_loss', 'N/A')}")
|
||
st.write(f"**持有周期:** {final_decision.get('holding_period', 'N/A')}")
|
||
|
||
# 风险提示
|
||
risk_warning = final_decision.get('risk_warning', '')
|
||
if risk_warning:
|
||
st.markdown(f"""
|
||
<div class="warning-card">
|
||
<h4>⚠️ 风险提示</h4>
|
||
<p>{risk_warning}</p>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
else:
|
||
# 文本格式的决策
|
||
decision_text = final_decision.get('decision_text', str(final_decision))
|
||
st.write(decision_text)
|
||
|
||
# 添加PDF导出功能
|
||
st.markdown("---")
|
||
if agents_results and discussion_result:
|
||
display_pdf_export_section(stock_info, agents_results, discussion_result, final_decision)
|
||
else:
|
||
st.warning("⚠️ PDF导出功能需要完整的分析数据")
|
||
|
||
def show_example_interface():
|
||
"""显示示例界面"""
|
||
st.subheader("💡 使用说明")
|
||
|
||
col1, col2 = st.columns(2)
|
||
|
||
with col1:
|
||
st.markdown("""
|
||
### 🚀 如何使用
|
||
1. **输入股票代码**：支持美股(如AAPL、MSFT)和A股(如000001、600036)
|
||
2. **点击开始分析**：系统将启动AI分析师团队
|
||
3. **查看分析报告**：5位专业分析师将从不同角度分析
|
||
4. **获得投资建议**：获得最终的投资评级和操作建议
|
||
|
||
### 📊 分析维度
|
||
- **技术面**：趋势、指标、支撑阻力
|
||
- **基本面**：财务、估值、行业分析
|
||
- **资金面**：资金流向、主力行为
|
||
- **风险管理**：风险识别与控制
|
||
- **市场情绪**：情绪指标、热点分析
|
||
""")
|
||
|
||
with col2:
|
||
st.markdown("""
|
||
### 📈 示例股票代码
|
||
|
||
**美股热门**
|
||
- AAPL (苹果)
|
||
- MSFT (微软)
|
||
- GOOGL (谷歌)
|
||
- TSLA (特斯拉)
|
||
- NVDA (英伟达)
|
||
|
||
**A股热门**
|
||
- 000001 (平安银行)
|
||
- 600036 (招商银行)
|
||
- 000002 (万科A)
|
||
- 600519 (贵州茅台)
|
||
- 000858 (五粮液)
|
||
""")
|
||
|
||
st.info("💡 提示：首次运行需要配置DeepSeek API Key，请在.env中设置DEEPSEEK_API_KEY")
|
||
|
||
def display_history_records():
|
||
"""显示历史分析记录"""
|
||
st.subheader("📚 历史分析记录")
|
||
|
||
# 获取所有记录
|
||
records = db.get_all_records()
|
||
|
||
if not records:
|
||
st.info("📭 暂无历史分析记录")
|
||
return
|
||
|
||
st.write(f"📊 共找到 {len(records)} 条分析记录")
|
||
|
||
# 搜索和筛选
|
||
col1, col2 = st.columns([3, 1])
|
||
with col1:
|
||
search_term = st.text_input("🔍 搜索股票代码或名称", placeholder="输入股票代码或名称进行搜索")
|
||
with col2:
|
||
st.write("")
|
||
st.write("")
|
||
if st.button("🔄 刷新列表"):
|
||
st.rerun()
|
||
|
||
# 筛选记录
|
||
filtered_records = records
|
||
if search_term:
|
||
filtered_records = [
|
||
record for record in records
|
||
if search_term.lower() in record['symbol'].lower() or
|
||
search_term.lower() in record['stock_name'].lower()
|
||
]
|
||
|
||
if not filtered_records:
|
||
st.warning("🔍 未找到匹配的记录")
|
||
return
|
||
|
||
# 显示记录列表
|
||
for record in filtered_records:
|
||
# 根据评级设置颜色和图标
|
||
rating = record.get('rating', '未知')
|
||
rating_color = {
|
||
"买入": "🟢",
|
||
"持有": "🟡",
|
||
"卖出": "🔴",
|
||
"强烈买入": "🟢",
|
||
"强烈卖出": "🔴"
|
||
}.get(rating, "⚪")
|
||
|
||
with st.expander(f"{rating_color} {record['stock_name']} ({record['symbol']}) - {record['analysis_date']}"):
|
||
col1, col2, col3, col4 = st.columns([2, 2, 1, 1])
|
||
|
||
with col1:
|
||
st.write(f"**股票代码:** {record['symbol']}")
|
||
st.write(f"**股票名称:** {record['stock_name']}")
|
||
|
||
with col2:
|
||
st.write(f"**分析时间:** {record['analysis_date']}")
|
||
st.write(f"**数据周期:** {record['period']}")
|
||
st.write(f"**投资评级:** **{rating}**")
|
||
|
||
with col3:
|
||
if st.button("👀 查看详情", key=f"view_{record['id']}"):
|
||
st.session_state.viewing_record_id = record['id']
|
||
|
||
with col4:
|
||
if st.button("➕ 监测", key=f"add_monitor_{record['id']}"):
|
||
st.session_state.add_to_monitor_id = record['id']
|
||
st.session_state.viewing_record_id = record['id']
|
||
|
||
# 删除按钮（新增一行）
|
||
col5, _, _, _ = st.columns(4)
|
||
with col5:
|
||
if st.button("🗑️ 删除", key=f"delete_{record['id']}"):
|
||
if db.delete_record(record['id']):
|
||
st.success("✅ 记录已删除")
|
||
st.rerun()
|
||
else:
|
||
st.error("❌ 删除失败")
|
||
|
||
# 查看详细记录
|
||
if 'viewing_record_id' in st.session_state:
|
||
display_record_detail(st.session_state.viewing_record_id)
|
||
|
||
def display_add_to_monitor_dialog(record):
|
||
"""显示加入监测的对话框"""
|
||
st.markdown("---")
|
||
st.subheader("➕ 加入监测")
|
||
|
||
final_decision = record['final_decision']
|
||
|
||
# 从final_decision中提取关键数据
|
||
if isinstance(final_decision, dict):
|
||
# 解析进场区间
|
||
entry_range_str = final_decision.get('entry_range', 'N/A')
|
||
entry_min = 0.0
|
||
entry_max = 0.0
|
||
|
||
# 尝试解析进场区间字符串，支持多种格式
|
||
if entry_range_str and entry_range_str != 'N/A':
|
||
try:
|
||
import re
|
||
# 移除常见的前缀和单位
|
||
clean_str = str(entry_range_str).replace('¥', '').replace('元', '').replace('$', '')
|
||
# 使用正则表达式提取数字
|
||
# 支持格式：10.5-12.0, 10.5 - 12.0, 10.5~12.0, 10.5至12.0 等
|
||
numbers = re.findall(r'\d+\.?\d*', clean_str)
|
||
if len(numbers) >= 2:
|
||
entry_min = float(numbers[0])
|
||
entry_max = float(numbers[1])
|
||
except:
|
||
# 如果解析失败，尝试用分隔符split
|
||
try:
|
||
clean_str = str(entry_range_str).replace('¥', '').replace('元', '').replace('$', '')
|
||
# 尝试多种分隔符
|
||
for sep in ['-', '~', '至', '到']:
|
||
if sep in clean_str:
|
||
parts = clean_str.split(sep)
|
||
if len(parts) == 2:
|
||
entry_min = float(parts[0].strip())
|
||
entry_max = float(parts[1].strip())
|
||
break
|
||
except:
|
||
pass
|
||
|
||
# 提取止盈和止损
|
||
take_profit_str = final_decision.get('take_profit', 'N/A')
|
||
stop_loss_str = final_decision.get('stop_loss', 'N/A')
|
||
|
||
take_profit = 0.0
|
||
stop_loss = 0.0
|
||
|
||
# 解析止盈位
|
||
if take_profit_str and take_profit_str != 'N/A':
|
||
try:
|
||
import re
|
||
# 移除单位和符号
|
||
clean_str = str(take_profit_str).replace('¥', '').replace('元', '').replace('$', '').strip()
|
||
# 提取第一个数字
|
||
numbers = re.findall(r'\d+\.?\d*', clean_str)
|
||
if numbers:
|
||
take_profit = float(numbers[0])
|
||
except:
|
||
pass
|
||
|
||
# 解析止损位
|
||
if stop_loss_str and stop_loss_str != 'N/A':
|
||
try:
|
||
import re
|
||
# 移除单位和符号
|
||
clean_str = str(stop_loss_str).replace('¥', '').replace('元', '').replace('$', '').strip()
|
||
# 提取第一个数字
|
||
numbers = re.findall(r'\d+\.?\d*', clean_str)
|
||
if numbers:
|
||
stop_loss = float(numbers[0])
|
||
except:
|
||
pass
|
||
|
||
# 获取评级
|
||
rating = final_decision.get('rating', '买入')
|
||
|
||
# 检查是否已经在监测列表中
|
||
from monitor_db import monitor_db
|
||
existing_stocks = monitor_db.get_monitored_stocks()
|
||
is_duplicate = any(stock['symbol'] == record['symbol'] for stock in existing_stocks)
|
||
|
||
if is_duplicate:
|
||
st.warning(f"⚠️ {record['symbol']} 已经在监测列表中。继续添加将创建重复监测项。")
|
||
|
||
st.info(f"""
|
||
**从分析结果中提取的数据：**
|
||
- 进场区间: {entry_min} - {entry_max}
|
||
- 止盈位: {take_profit if take_profit > 0 else '未设置'}
|
||
- 止损位: {stop_loss if stop_loss > 0 else '未设置'}
|
||
- 投资评级: {rating}
|
||
""")
|
||
|
||
# 显示表单供用户确认或修改
|
||
with st.form(key=f"monitor_form_{record['id']}"):
|
||
st.markdown("**请确认或修改监测参数：**")
|
||
|
||
col1, col2 = st.columns([1, 1])
|
||
|
||
with col1:
|
||
st.subheader("🎯 关键位置")
|
||
new_entry_min = st.number_input("进场区间最低价", value=float(entry_min), step=0.01, format="%.2f")
|
||
new_entry_max = st.number_input("进场区间最高价", value=float(entry_max), step=0.01, format="%.2f")
|
||
new_take_profit = st.number_input("止盈价位", value=float(take_profit), step=0.01, format="%.2f")
|
||
new_stop_loss = st.number_input("止损价位", value=float(stop_loss), step=0.01, format="%.2f")
|
||
|
||
with col2:
|
||
st.subheader("⚙️ 监测设置")
|
||
check_interval = st.slider("监测间隔(分钟)", 5, 120, 30)
|
||
notification_enabled = st.checkbox("启用通知", value=True)
|
||
new_rating = st.selectbox("投资评级", ["买入", "持有", "卖出"],
|
||
index=["买入", "持有", "卖出"].index(rating) if rating in ["买入", "持有", "卖出"] else 0)
|
||
|
||
col_a, col_b, col_c = st.columns(3)
|
||
|
||
with col_a:
|
||
submit = st.form_submit_button("✅ 确认加入监测", type="primary", use_container_width=True)
|
||
|
||
with col_b:
|
||
cancel = st.form_submit_button("❌ 取消", use_container_width=True)
|
||
|
||
if submit:
|
||
if new_entry_min > 0 and new_entry_max > 0 and new_entry_max > new_entry_min:
|
||
try:
|
||
# 添加到监测数据库
|
||
entry_range = {"min": new_entry_min, "max": new_entry_max}
|
||
|
||
stock_id = monitor_db.add_monitored_stock(
|
||
symbol=record['symbol'],
|
||
name=record['stock_name'],
|
||
rating=new_rating,
|
||
entry_range=entry_range,
|
||
take_profit=new_take_profit if new_take_profit > 0 else None,
|
||
stop_loss=new_stop_loss if new_stop_loss > 0 else None,
|
||
check_interval=check_interval,
|
||
notification_enabled=notification_enabled
|
||
)
|
||
|
||
st.success(f"✅ 已成功将 {record['symbol']} 加入监测列表！")
|
||
st.balloons()
|
||
|
||
# 立即更新一次价格
|
||
from monitor_service import monitor_service
|
||
monitor_service.manual_update_stock(stock_id)
|
||
|
||
# 清理session state并跳转到监测页面
|
||
if 'add_to_monitor_id' in st.session_state:
|
||
del st.session_state.add_to_monitor_id
|
||
if 'viewing_record_id' in st.session_state:
|
||
del st.session_state.viewing_record_id
|
||
if 'show_history' in st.session_state:
|
||
del st.session_state.show_history
|
||
|
||
# 设置跳转到监测页面
|
||
st.session_state.show_monitor = True
|
||
st.session_state.monitor_jump_highlight = record['symbol'] # 标记要高亮显示的股票
|
||
|
||
time.sleep(1.5)
|
||
st.rerun()
|
||
|
||
except Exception as e:
|
||
st.error(f"❌ 加入监测失败: {str(e)}")
|
||
else:
|
||
st.error("❌ 请输入有效的进场区间（最低价应小于最高价，且都大于0）")
|
||
|
||
if cancel:
|
||
if 'add_to_monitor_id' in st.session_state:
|
||
del st.session_state.add_to_monitor_id
|
||
st.rerun()
|
||
else:
|
||
st.warning("⚠️ 无法从分析结果中提取关键数据")
|
||
if st.button("❌ 取消"):
|
||
if 'add_to_monitor_id' in st.session_state:
|
||
del st.session_state.add_to_monitor_id
|
||
st.rerun()
|
||
|
||
def display_record_detail(record_id):
|
||
"""显示单条记录的详细信息"""
|
||
st.markdown("---")
|
||
st.subheader("📋 详细分析记录")
|
||
|
||
record = db.get_record_by_id(record_id)
|
||
if not record:
|
||
st.error("❌ 记录不存在")
|
||
return
|
||
|
||
# 基本信息
|
||
col1, col2, col3 = st.columns(3)
|
||
with col1:
|
||
st.metric("股票代码", record['symbol'])
|
||
with col2:
|
||
st.metric("股票名称", record['stock_name'])
|
||
with col3:
|
||
st.metric("分析时间", record['analysis_date'])
|
||
|
||
# 股票基本信息
|
||
st.subheader("📊 股票基本信息")
|
||
stock_info = record['stock_info']
|
||
if stock_info:
|
||
col1, col2, col3, col4, col5 = st.columns(5)
|
||
|
||
with col1:
|
||
current_price = stock_info.get('current_price', 'N/A')
|
||
st.metric("当前价格", f"{current_price}")
|
||
|
||
with col2:
|
||
change_percent = stock_info.get('change_percent', 'N/A')
|
||
if isinstance(change_percent, (int, float)):
|
||
st.metric("涨跌幅", f"{change_percent:.2f}%", f"{change_percent:.2f}%")
|
||
else:
|
||
st.metric("涨跌幅", f"{change_percent}")
|
||
|
||
with col3:
|
||
pe_ratio = stock_info.get('pe_ratio', 'N/A')
|
||
st.metric("市盈率", f"{pe_ratio}")
|
||
|
||
with col4:
|
||
pb_ratio = stock_info.get('pb_ratio', 'N/A')
|
||
st.metric("市净率", f"{pb_ratio}")
|
||
|
||
with col5:
|
||
market_cap = stock_info.get('market_cap', 'N/A')
|
||
if isinstance(market_cap, (int, float)):
|
||
market_cap_str = f"{market_cap/1e9:.2f}B" if market_cap > 1e9 else f"{market_cap/1e6:.2f}M"
|
||
st.metric("市值", market_cap_str)
|
||
else:
|
||
st.metric("市值", f"{market_cap}")
|
||
|
||
# 各分析师报告
|
||
st.subheader("🤖 AI分析师团队报告")
|
||
agents_results = record['agents_results']
|
||
if agents_results:
|
||
tab_names = []
|
||
tab_contents = []
|
||
|
||
for agent_key, agent_result in agents_results.items():
|
||
agent_name = agent_result.get('agent_name', '未知分析师')
|
||
tab_names.append(agent_name)
|
||
tab_contents.append(agent_result)
|
||
|
||
tabs = st.tabs(tab_names)
|
||
|
||
for i, tab in enumerate(tabs):
|
||
with tab:
|
||
agent_result = tab_contents[i]
|
||
|
||
st.markdown(f"""
|
||
<div class="agent-card">
|
||
<h4>👨💼 {agent_result.get('agent_name', '未知')}</h4>
|
||
<p><strong>职责：</strong>{agent_result.get('agent_role', '未知')}</p>
|
||
<p><strong>关注领域：</strong>{', '.join(agent_result.get('focus_areas', []))}</p>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
st.markdown("**📄 分析报告:**")
|
||
st.write(agent_result.get('analysis', '暂无分析'))
|
||
|
||
# 团队讨论
|
||
st.subheader("🤝 分析团队讨论")
|
||
discussion_result = record['discussion_result']
|
||
if discussion_result:
|
||
st.markdown("""
|
||
<div class="agent-card">
|
||
<h4>💭 团队综合讨论</h4>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
st.write(discussion_result)
|
||
|
||
# 最终决策
|
||
st.subheader("📋 最终投资决策")
|
||
final_decision = record['final_decision']
|
||
if final_decision:
|
||
if isinstance(final_decision, dict) and "decision_text" not in final_decision:
|
||
col1, col2 = st.columns([1, 2])
|
||
|
||
with col1:
|
||
rating = final_decision.get('rating', '未知')
|
||
rating_color = {"买入": "🟢", "持有": "🟡", "卖出": "🔴"}.get(rating, "⚪")
|
||
|
||
st.markdown(f"""
|
||
<div class="decision-card">
|
||
<h3 style="text-align: center;">{rating_color} {rating}</h3>
|
||
<h4 style="text-align: center;">投资评级</h4>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
confidence = final_decision.get('confidence_level', 'N/A')
|
||
st.metric("信心度", f"{confidence}/10")
|
||
|
||
target_price = final_decision.get('target_price', 'N/A')
|
||
st.metric("目标价格", f"{target_price}")
|
||
|
||
position_size = final_decision.get('position_size', 'N/A')
|
||
st.metric("建议仓位", f"{position_size}")
|
||
|
||
with col2:
|
||
st.markdown("**🎯 操作建议:**")
|
||
st.write(final_decision.get('operation_advice', '暂无建议'))
|
||
|
||
st.markdown("**📍 关键位置:**")
|
||
col2_1, col2_2 = st.columns(2)
|
||
|
||
with col2_1:
|
||
st.write(f"**进场区间:** {final_decision.get('entry_range', 'N/A')}")
|
||
st.write(f"**止盈位:** {final_decision.get('take_profit', 'N/A')}")
|
||
|
||
with col2_2:
|
||
st.write(f"**止损位:** {final_decision.get('stop_loss', 'N/A')}")
|
||
st.write(f"**持有周期:** {final_decision.get('holding_period', 'N/A')}")
|
||
else:
|
||
decision_text = final_decision.get('decision_text', str(final_decision))
|
||
st.write(decision_text)
|
||
|
||
# 加入监测功能
|
||
st.markdown("---")
|
||
st.subheader("🎯 操作")
|
||
|
||
# 检查是否需要显示加入监测的对话框
|
||
if 'add_to_monitor_id' in st.session_state and st.session_state.add_to_monitor_id == record_id:
|
||
display_add_to_monitor_dialog(record)
|
||
else:
|
||
# 只有在不显示对话框时才显示按钮
|
||
col1, col2 = st.columns([1, 3])
|
||
|
||
with col1:
|
||
if st.button("➕ 加入监测", type="primary", use_container_width=True):
|
||
st.session_state.add_to_monitor_id = record_id
|
||
st.rerun()
|
||
|
||
# 返回按钮
|
||
st.markdown("---")
|
||
if st.button("⬅️ 返回历史记录列表"):
|
||
if 'viewing_record_id' in st.session_state:
|
||
del st.session_state.viewing_record_id
|
||
if 'add_to_monitor_id' in st.session_state:
|
||
del st.session_state.add_to_monitor_id
|
||
st.rerun()
|
||
|
||
def display_config_manager():
|
||
"""显示环境配置管理界面"""
|
||
st.subheader("⚙️ 环境配置管理")
|
||
|
||
st.markdown("""
|
||
<div class="agent-card">
|
||
<p>在这里可以配置系统的环境变量，包括API密钥、数据源配置、量化交易配置等。</p>
|
||
<p><strong>注意：</strong>配置修改后需要重启应用才能生效。</p>
|
||
</div>
|
||
""", unsafe_allow_html=True)
|
||
|
||
# 获取当前配置
|
||
config_info = config_manager.get_config_info()
|
||
|
||
# 创建标签页
|
||
tab1, tab2, tab3 = st.tabs(["📝 基本配置", "📊 数据源配置", "🤖 量化交易配置"])
|
||
|
||
# 使用session_state保存临时配置
|
||
if 'temp_config' not in st.session_state:
|
||
st.session_state.temp_config = {key: info["value"] for key, info in config_info.items()}
|
||
|
||
with tab1:
|
||
st.markdown("### DeepSeek API配置")
|
||
st.markdown("DeepSeek是系统的核心AI引擎，必须配置才能使用分析功能。")
|
||
|
||
# DeepSeek API Key
|
||
api_key_info = config_info["DEEPSEEK_API_KEY"]
|
||
current_api_key = st.session_state.temp_config.get("DEEPSEEK_API_KEY", "")
|
||
|
||
new_api_key = st.text_input(
|
||
f"🔑 {api_key_info['description']} {'*' if api_key_info['required'] else ''}",
|
||
value=current_api_key,
|
||
type="password",
|
||
help="从 https://platform.deepseek.com 获取API密钥",
|
||
key="input_deepseek_api_key"
|
||
)
|
||
st.session_state.temp_config["DEEPSEEK_API_KEY"] = new_api_key
|
||
|
||
# 显示当前状态
|
||
if new_api_key:
|
||
masked_key = new_api_key[:8] + "*" * (len(new_api_key) - 12) + new_api_key[-4:] if len(new_api_key) > 12 else "***"
|
||
st.success(f"✅ API密钥已设置: {masked_key}")
|
||
else:
|
||
st.warning("⚠️ 未设置API密钥，系统无法使用AI分析功能")
|
||
|
||
st.markdown("---")
|
||
|
||
# DeepSeek Base URL
|
||
base_url_info = config_info["DEEPSEEK_BASE_URL"]
|
||
current_base_url = st.session_state.temp_config.get("DEEPSEEK_BASE_URL", "")
|
||
|
||
new_base_url = st.text_input(
|
||
f"🌐 {base_url_info['description']}",
|
||
value=current_base_url,
|
||
help="一般无需修改，保持默认即可",
|
||
key="input_deepseek_base_url"
|
||
)
|
||
st.session_state.temp_config["DEEPSEEK_BASE_URL"] = new_base_url
|
||
|
||
st.info("💡 如何获取DeepSeek API密钥？\n\n1. 访问 https://platform.deepseek.com\n2. 注册/登录账号\n3. 进入API密钥管理页面\n4. 创建新的API密钥\n5. 复制密钥并粘贴到上方输入框")
|
||
|
||
with tab2:
|
||
st.markdown("### Tushare数据接口（可选）")
|
||
st.markdown("Tushare提供更丰富的A股财务数据，配置后可以获取更详细的财务分析。")
|
||
|
||
tushare_info = config_info["TUSHARE_TOKEN"]
|
||
current_tushare = st.session_state.temp_config.get("TUSHARE_TOKEN", "")
|
||
|
||
new_tushare = st.text_input(
|
||
f"🎫 {tushare_info['description']}",
|
||
value=current_tushare,
|
||
type="password",
|
||
help="从 https://tushare.pro 获取Token",
|
||
key="input_tushare_token"
|
||
)
|
||
st.session_state.temp_config["TUSHARE_TOKEN"] = new_tushare
|
||
|
||
if new_tushare:
|
||
st.success("✅ Tushare Token已设置")
|
||
else:
|
||
st.info("ℹ️ 未设置Tushare Token，系统将使用其他数据源")
|
||
|
||
st.info("💡 如何获取Tushare Token？\n\n1. 访问 https://tushare.pro\n2. 注册账号\n3. 进入个人中心\n4. 获取Token\n5. 复制并粘贴到上方输入框")
|
||
|
||
with tab3:
|
||
st.markdown("### MiniQMT量化交易配置（可选）")
|
||
st.markdown("配置后可以使用量化交易功能，自动执行交易策略。")
|
||
|
||
# 启用开关
|
||
miniqmt_enabled_info = config_info["MINIQMT_ENABLED"]
|
||
current_enabled = st.session_state.temp_config.get("MINIQMT_ENABLED", "false") == "true"
|
||
|
||
new_enabled = st.checkbox(
|
||
"启用MiniQMT量化交易",
|
||
value=current_enabled,
|
||
help="开启后可以使用量化交易功能",
|
||
key="input_miniqmt_enabled"
|
||
)
|
||
st.session_state.temp_config["MINIQMT_ENABLED"] = "true" if new_enabled else "false"
|
||
|
||
# 其他配置
|
||
col1, col2 = st.columns(2)
|
||
|
||
with col1:
|
||
account_id_info = config_info["MINIQMT_ACCOUNT_ID"]
|
||
current_account_id = st.session_state.temp_config.get("MINIQMT_ACCOUNT_ID", "")
|
||
|
||
new_account_id = st.text_input(
|
||
f"🆔 {account_id_info['description']}",
|
||
value=current_account_id,
|
||
disabled=not new_enabled,
|
||
key="input_miniqmt_account_id"
|
||
)
|
||
st.session_state.temp_config["MINIQMT_ACCOUNT_ID"] = new_account_id
|
||
|
||
host_info = config_info["MINIQMT_HOST"]
|
||
current_host = st.session_state.temp_config.get("MINIQMT_HOST", "")
|
||
|
||
new_host = st.text_input(
|
||
f"🖥️ {host_info['description']}",
|
||
value=current_host,
|
||
disabled=not new_enabled,
|
||
key="input_miniqmt_host"
|
||
)
|
||
st.session_state.temp_config["MINIQMT_HOST"] = new_host
|
||
|
||
with col2:
|
||
port_info = config_info["MINIQMT_PORT"]
|
||
current_port = st.session_state.temp_config.get("MINIQMT_PORT", "")
|
||
|
||
new_port = st.text_input(
|
||
f"🔌 {port_info['description']}",
|
||
value=current_port,
|
||
disabled=not new_enabled,
|
||
key="input_miniqmt_port"
|
||
)
|
||
st.session_state.temp_config["MINIQMT_PORT"] = new_port
|
||
|
||
if new_enabled:
|
||
st.success("✅ MiniQMT已启用")
|
||
else:
|
||
st.info("ℹ️ MiniQMT未启用")
|
||
|
||
st.warning("⚠️ 警告：量化交易涉及真实资金操作，请谨慎配置和使用！")
|
||
|
||
# 操作按钮
|
||
st.markdown("---")
|
||
col1, col2, col3, col4 = st.columns([1, 1, 1, 2])
|
||
|
||
with col1:
|
||
if st.button("💾 保存配置", type="primary", use_container_width=True):
|
||
# 验证配置
|
||
is_valid, message = config_manager.validate_config(st.session_state.temp_config)
|
||
|
||
if is_valid:
|
||
# 保存配置
|
||
if config_manager.write_env(st.session_state.temp_config):
|
||
st.success("✅ 配置已保存到 .env 文件")
|
||
st.info("ℹ️ 请重启应用使配置生效")
|
||
|
||
# 尝试重新加载配置
|
||
try:
|
||
config_manager.reload_config()
|
||
st.success("✅ 配置已重新加载")
|
||
except Exception as e:
|
||
st.warning(f"⚠️ 配置重新加载失败: {e}")
|
||
|
||
time.sleep(2)
|
||
st.rerun()
|
||
else:
|
||
st.error("❌ 保存配置失败")
|
||
else:
|
||
st.error(f"❌ 配置验证失败: {message}")
|
||
|
||
with col2:
|
||
if st.button("🔄 重置", use_container_width=True):
|
||
# 重置为当前文件中的值
|
||
st.session_state.temp_config = {key: info["value"] for key, info in config_info.items()}
|
||
st.success("✅ 已重置为当前配置")
|
||
st.rerun()
|
||
|
||
with col3:
|
||
if st.button("⬅️ 返回", use_container_width=True):
|
||
if 'show_config' in st.session_state:
|
||
del st.session_state.show_config
|
||
if 'temp_config' in st.session_state:
|
||
del st.session_state.temp_config
|
||
st.rerun()
|
||
|
||
# 显示当前.env文件内容
|
||
st.markdown("---")
|
||
with st.expander("📄 查看当前 .env 文件内容"):
|
||
current_config = config_manager.read_env()
|
||
|
||
st.code(f"""# AI股票分析系统环境配置
|
||
# 由系统自动生成和管理
|
||
|
||
# ========== DeepSeek API配置 ==========
|
||
DEEPSEEK_API_KEY="{current_config.get('DEEPSEEK_API_KEY', '')}"
|
||
DEEPSEEK_BASE_URL="{current_config.get('DEEPSEEK_BASE_URL', '')}"
|
||
|
||
# ========== Tushare数据接口（可选）==========
|
||
TUSHARE_TOKEN="{current_config.get('TUSHARE_TOKEN', '')}"
|
||
|
||
# ========== MiniQMT量化交易配置（可选）==========
|
||
MINIQMT_ENABLED="{current_config.get('MINIQMT_ENABLED', 'false')}"
|
||
MINIQMT_ACCOUNT_ID="{current_config.get('MINIQMT_ACCOUNT_ID', '')}"
|
||
MINIQMT_HOST="{current_config.get('MINIQMT_HOST', '127.0.0.1')}"
|
||
MINIQMT_PORT="{current_config.get('MINIQMT_PORT', '58610')}"
|
||
""", language="bash")
|
||
|
||
def display_batch_analysis_results(results, period):
|
||
"""显示批量分析结果（对比视图）"""
|
||
|
||
st.subheader("📊 批量分析结果对比")
|
||
|
||
# 统计信息
|
||
total = len(results)
|
||
success_results = [r for r in results if r['success']]
|
||
failed_results = [r for r in results if not r['success']]
|
||
saved_count = sum(1 for r in results if r.get('saved_to_db', False))
|
||
|
||
# 显示统计
|
||
col1, col2, col3, col4 = st.columns(4)
|
||
with col1:
|
||
st.metric("总数", total)
|
||
with col2:
|
||
st.metric("成功", len(success_results), delta=None, delta_color="normal")
|
||
with col3:
|
||
st.metric("失败", len(failed_results), delta=None, delta_color="inverse")
|
||
with col4:
|
||
st.metric("已保存", saved_count, delta=None, delta_color="normal")
|
||
|
||
# 提示信息
|
||
if saved_count > 0:
|
||
st.info(f"💾 已有 {saved_count} 只股票的分析结果保存到历史记录，可在侧边栏点击「📖 历史记录」查看")
|
||
|
||
st.markdown("---")
|
||
|
||
# 失败的股票列表
|
||
if failed_results:
|
||
with st.expander(f"❌ 查看失败的 {len(failed_results)} 只股票", expanded=False):
|
||
for result in failed_results:
|
||
st.error(f"**{result['symbol']}**: {result.get('error', '未知错误')}")
|
||
|
||
# 保存失败的股票列表
|
||
save_failed_results = [r for r in success_results if not r.get('saved_to_db', False)]
|
||
if save_failed_results:
|
||
with st.expander(f"⚠️ 查看分析成功但保存失败的 {len(save_failed_results)} 只股票", expanded=False):
|
||
for result in save_failed_results:
|
||
db_error = result.get('db_error', '未知错误')
|
||
st.warning(f"**{result['symbol']} - {result['stock_info'].get('name', 'N/A')}**: {db_error}")
|
||
|
||
# 成功的股票分析结果
|
||
if not success_results:
|
||
st.warning("⚠️ 没有成功分析的股票")
|
||
return
|
||
|
||
# 创建对比视图选项
|
||
view_mode = st.radio(
|
||
"显示模式",
|
||
["对比表格", "详细卡片"],
|
||
horizontal=True,
|
||
help="对比表格：横向对比多只股票；详细卡片：逐个查看详细分析"
|
||
)
|
||
|
||
if view_mode == "对比表格":
|
||
# 表格对比视图
|
||
display_comparison_table(success_results)
|
||
else:
|
||
# 详细卡片视图
|
||
display_detailed_cards(success_results, period)
|
||
|
||
def display_comparison_table(results):
|
||
"""显示对比表格"""
|
||
import pandas as pd
|
||
|
||
st.subheader("📋 股票对比表格")
|
||
|
||
# 构建对比数据
|
||
comparison_data = []
|
||
for result in results:
|
||
stock_info = result['stock_info']
|
||
indicators = result.get('indicators', {})
|
||
final_decision = result['final_decision']
|
||
|
||
# 解析评级
|
||
if isinstance(final_decision, dict):
|
||
rating = final_decision.get('rating', 'N/A')
|
||
confidence = final_decision.get('confidence_level', 'N/A')
|
||
target_price = final_decision.get('target_price', 'N/A')
|
||
else:
|
||
rating = 'N/A'
|
||
confidence = 'N/A'
|
||
target_price = 'N/A'
|
||
|
||
row = {
|
||
'股票代码': stock_info.get('symbol', 'N/A'),
|
||
'股票名称': stock_info.get('name', 'N/A'),
|
||
'当前价格': stock_info.get('current_price', 'N/A'),
|
||
'涨跌幅(%)': stock_info.get('change_percent', 'N/A'),
|
||
'市盈率': stock_info.get('pe_ratio', 'N/A'),
|
||
'市净率': stock_info.get('pb_ratio', 'N/A'),
|
||
'RSI': indicators.get('rsi', 'N/A'),
|
||
'MACD': indicators.get('macd', 'N/A'),
|
||
'投资评级': rating,
|
||
'信心度': confidence,
|
||
'目标价格': target_price
|
||
}
|
||
comparison_data.append(row)
|
||
|
||
# 创建DataFrame
|
||
df = pd.DataFrame(comparison_data)
|
||
|
||
# 应用样式
|
||
def highlight_rating(val):
|
||
if val == '买入' or val == '强烈买入':
|
||
return 'background-color: #c8e6c9; color: #2e7d32;'
|
||
elif val == '持有':
|
||
return 'background-color: #fff9c4; color: #f57f17;'
|
||
elif val == '卖出' or val == '强烈卖出':
|
||
return 'background-color: #ffcdd2; color: #c62828;'
|
||
return ''
|
||
|
||
# 显示表格
|
||
st.dataframe(
|
||
df.style.applymap(highlight_rating, subset=['投资评级']),
|
||
use_container_width=True,
|
||
height=400
|
||
)
|
||
|
||
# 添加筛选功能
|
||
st.markdown("---")
|
||
st.subheader("🔍 快速筛选")
|
||
|
||
col1, col2 = st.columns(2)
|
||
with col1:
|
||
rating_filter = st.multiselect(
|
||
"按评级筛选",
|
||
options=df['投资评级'].unique().tolist(),
|
||
default=df['投资评级'].unique().tolist()
|
||
)
|
||
|
||
with col2:
|
||
# 按涨跌幅排序
|
||
sort_by = st.selectbox(
|
||
"排序方式",
|
||
["默认", "涨跌幅降序", "涨跌幅升序", "信心度降序", "RSI降序"]
|
||
)
|
||
|
||
# 应用筛选
|
||
filtered_df = df[df['投资评级'].isin(rating_filter)]
|
||
|
||
# 应用排序
|
||
if sort_by == "涨跌幅降序":
|
||
filtered_df = filtered_df.sort_values('涨跌幅(%)', ascending=False)
|
||
elif sort_by == "涨跌幅升序":
|
||
filtered_df = filtered_df.sort_values('涨跌幅(%)', ascending=True)
|
||
elif sort_by == "信心度降序":
|
||
filtered_df = filtered_df.sort_values('信心度', ascending=False)
|
||
elif sort_by == "RSI降序":
|
||
filtered_df = filtered_df.sort_values('RSI', ascending=False)
|
||
|
||
if not filtered_df.empty:
|
||
st.dataframe(filtered_df, use_container_width=True)
|
||
else:
|
||
st.info("没有符合条件的股票")
|
||
|
||
def display_detailed_cards(results, period):
|
||
"""显示详细卡片视图"""
|
||
|
||
st.subheader("📇 详细分析卡片")
|
||
|
||
# 选择要查看的股票
|
||
stock_options = [f"{r['stock_info']['symbol']} - {r['stock_info']['name']}" for r in results]
|
||
selected_stock = st.selectbox("选择股票", options=stock_options)
|
||
|
||
# 找到对应的结果
|
||
selected_index = stock_options.index(selected_stock)
|
||
result = results[selected_index]
|
||
|
||
# 显示详细分析
|
||
stock_info = result['stock_info']
|
||
indicators = result['indicators']
|
||
agents_results = result['agents_results']
|
||
discussion_result = result['discussion_result']
|
||
final_decision = result['final_decision']
|
||
|
||
# 获取股票数据用于显示图表
|
||
try:
|
||
stock_info_current, stock_data, _ = get_stock_data(stock_info['symbol'], period)
|
||
|
||
# 显示股票基本信息
|
||
display_stock_info(stock_info, indicators)
|
||
|
||
# 显示股票图表
|
||
if stock_data is not None:
|
||
display_stock_chart(stock_data, stock_info)
|
||
|
||
# 显示各分析师报告
|
||
display_agents_analysis(agents_results)
|
||
|
||
# 显示团队讨论
|
||
display_team_discussion(discussion_result)
|
||
|
||
# 显示最终决策
|
||
display_final_decision(final_decision, stock_info, agents_results, discussion_result)
|
||
|
||
except Exception as e:
|
||
st.error(f"显示详细信息时出错: {str(e)}")
|
||
|
||
if __name__ == "__main__":
|
||
main() |