wsx180808
239 lines
8.6 KiB
Python
239 lines
8.6 KiB
Python
import os
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import tempfile
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import base64
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import re
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from datetime import datetime
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import streamlit as st
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def generate_markdown_report(stock_info, agents_results, discussion_result, final_decision):
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"""生成Markdown格式的分析报告"""
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# 获取当前时间
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current_time = datetime.now().strftime("%Y年%m月%d日 %H:%M:%S")
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markdown_content = f"""
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# AI股票分析报告
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**生成时间**: {current_time}
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---
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## 📊 股票基本信息
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| 项目 | 值 |
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|------|-----|
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| **股票代码** | {stock_info.get('symbol', 'N/A')} |
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| **股票名称** | {stock_info.get('name', 'N/A')} |
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| **当前价格** | {stock_info.get('current_price', 'N/A')} |
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| **涨跌幅** | {stock_info.get('change_percent', 'N/A')}% |
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| **市盈率(PE)** | {stock_info.get('pe_ratio', 'N/A')} |
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| **市净率(PB)** | {stock_info.get('pb_ratio', 'N/A')} |
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| **市值** | {stock_info.get('market_cap', 'N/A')} |
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| **市场** | {stock_info.get('market', 'N/A')} |
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| **交易所** | {stock_info.get('exchange', 'N/A')} |
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---
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## 🔍 各分析师详细分析
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"""
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# 添加各分析师的分析结果
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agent_names = {
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'technical': '📈 技术分析师',
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'fundamental': '📊 基本面分析师',
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'fund_flow': '💰 资金面分析师',
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'risk_management': '⚠️ 风险管理师',
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'market_sentiment': '📈 市场情绪分析师'
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}
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for agent_key, agent_name in agent_names.items():
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if agent_key in agents_results:
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agent_result = agents_results[agent_key]
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if isinstance(agent_result, dict):
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analysis_text = agent_result.get('analysis', '暂无分析')
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else:
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analysis_text = str(agent_result)
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markdown_content += f"""
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### {agent_name}
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{analysis_text}
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---
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"""
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# 添加团队讨论结果
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markdown_content += f"""
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## 🤝 团队综合讨论
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{discussion_result}
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---
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## 📋 最终投资决策
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"""
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# 处理最终决策的显示
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if isinstance(final_decision, dict) and "decision_text" not in final_decision:
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# JSON格式的决策
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markdown_content += f"""
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**投资评级**: {final_decision.get('rating', '未知')}
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**目标价位**: {final_decision.get('target_price', 'N/A')}
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**操作建议**: {final_decision.get('operation_advice', '暂无建议')}
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**进场区间**: {final_decision.get('entry_range', 'N/A')}
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**止盈位**: {final_decision.get('take_profit', 'N/A')}
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**止损位**: {final_decision.get('stop_loss', 'N/A')}
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**持有周期**: {final_decision.get('holding_period', 'N/A')}
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**仓位建议**: {final_decision.get('position_size', 'N/A')}
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**信心度**: {final_decision.get('confidence_level', 'N/A')}/10
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**风险提示**: {final_decision.get('risk_warning', '无')}
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"""
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else:
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# 文本格式的决策
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decision_text = final_decision.get('decision_text', str(final_decision))
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markdown_content += decision_text
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markdown_content += """
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---
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## 📝 免责声明
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本报告由AI系统生成，仅供参考，不构成投资建议。投资有风险，入市需谨慎。请在做出投资决策前咨询专业的投资顾问。
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---
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*报告生成时间: {current_time}*
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*AI股票分析系统 v1.0*
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"""
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return markdown_content
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def create_download_link(content, filename, link_text):
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"""创建下载链接"""
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b64 = base64.b64encode(content.encode()).decode()
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href = f'<a href="data:text/markdown;base64,{b64}" download="{filename}" style="display: inline-block; padding: 10px 20px; background-color: #4CAF50; color: white; text-decoration: none; border-radius: 5px; margin: 5px;">{link_text}</a>'
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return href
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def create_html_download_link(content, filename, link_text):
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"""创建HTML下载链接"""
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b64 = base64.b64encode(content.encode('utf-8')).decode()
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href = f'<a href="data:text/html;base64,{b64}" download="{filename}" style="display: inline-block; padding: 10px 20px; background-color: #2196F3; color: white; text-decoration: none; border-radius: 5px; margin: 5px;">{link_text}</a>'
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return href
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def display_pdf_export_section(stock_info, agents_results, discussion_result, final_decision):
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"""显示PDF导出区域 - 修复报告生成问题"""
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st.markdown("---")
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st.markdown("## 📄 导出分析报告")
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col1, col2, col3 = st.columns([1, 2, 1])
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with col2:
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# 生成报告按钮
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import uuid
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import time
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pdf_button_key = f"generate_report_btn_{int(time.time())}_{uuid.uuid4().hex[:8]}"
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markdown_button_key = f"generate_markdown_btn_{int(time.time())}_{uuid.uuid4().hex[:8]}"
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# 生成PDF和HTML报告按钮
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if st.button("📊 生成并下载报告(PDF/HTML)", type="primary", width='content', key=pdf_button_key):
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with st.spinner("正在生成报告..."):
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try:
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# 生成Markdown内容
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markdown_content = generate_markdown_report(stock_info, agents_results, discussion_result, final_decision)
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# 生成HTML内容
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html_content = generate_html_content(markdown_content)
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# 生成文件名
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stock_symbol = stock_info.get('symbol', 'unknown')
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"股票分析报告_{stock_symbol}_{timestamp}"
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st.success("✅ 报告生成成功！")
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st.balloons()
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# 立即显示下载链接
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st.markdown("### 📄 报告下载")
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# 创建下载链接
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md_link = create_download_link(
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markdown_content,
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f"{filename}.md",
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"📝 下载Markdown报告"
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)
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html_link = create_html_download_link(
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html_content,
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f"{filename}.html",
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"🌐 下载HTML报告"
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)
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# 显示下载链接
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st.markdown(f"""
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<div style="text-align: center; margin: 20px 0;">
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{md_link}
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{html_link}
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</div>
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""", unsafe_allow_html=True)
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st.info("💡 提示：点击上方按钮即可下载对应格式的报告文件")
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except Exception as e:
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st.error(f"❌ 生成报告时出错: {str(e)}")
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import traceback
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st.error(f"详细错误信息: {traceback.format_exc()}")
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# 单独生成Markdown报告按钮
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if st.button("📝 生成并下载Markdown报告", type="secondary", width='content', key=markdown_button_key):
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with st.spinner("正在生成Markdown报告..."):
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try:
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# 生成Markdown内容
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markdown_content = generate_markdown_report(stock_info, agents_results, discussion_result, final_decision)
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# 生成文件名
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stock_symbol = stock_info.get('symbol', 'unknown')
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"股票分析报告_{stock_symbol}_{timestamp}.md"
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st.success("✅ Markdown报告生成成功！")
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st.balloons()
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# 显示下载链接
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st.markdown("### 📄 报告下载")
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# 创建下载链接
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md_link = create_download_link(
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markdown_content,
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filename,
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"📝 下载Markdown报告"
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)
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# 显示下载链接
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st.markdown(f"""
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<div style="text-align: center; margin: 20px 0;">
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{md_link}
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</div>
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""", unsafe_allow_html=True)
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st.info("💡 提示：点击上方按钮即可下载Markdown格式的报告文件")
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except Exception as e:
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st.error(f"❌ 生成Markdown报告时出错: {str(e)}")
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import traceback
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st.error(f"详细错误信息: {traceback.format_exc()}")
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