增强风险管理师分析功能
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oficcejo
@@ -636,9 +636,21 @@ def main():
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st.info(f"📊 准备分析 {len(stock_list)} 只股票: {', '.join(stock_list)}")
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# 清除之前的批量分析结果
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# 清除之前的分析结果（包括单个和批量）
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if 'batch_analysis_results' in st.session_state:
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del st.session_state.batch_analysis_results
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if 'analysis_completed' in st.session_state:
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del st.session_state.analysis_completed
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if 'stock_info' in st.session_state:
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del st.session_state.stock_info
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if 'agents_results' in st.session_state:
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del st.session_state.agents_results
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if 'discussion_result' in st.session_state:
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del st.session_state.discussion_result
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if 'final_decision' in st.session_state:
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del st.session_state.final_decision
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if 'just_completed' in st.session_state:
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del st.session_state.just_completed
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# 获取批量模式
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batch_mode = st.session_state.get('batch_mode', '顺序分析')
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@@ -646,8 +658,12 @@ def main():
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# 运行批量分析
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run_batch_analysis(stock_list, period, batch_mode)
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# 检查是否有已完成的批量分析结果（优先显示批量结果）
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if 'batch_analysis_results' in st.session_state and st.session_state.batch_analysis_results:
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display_batch_analysis_results(st.session_state.batch_analysis_results, period)
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# 检查是否有已完成的单个分析结果（但不是刚刚完成的，避免重复显示）
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if 'analysis_completed' in st.session_state and st.session_state.analysis_completed:
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elif 'analysis_completed' in st.session_state and st.session_state.analysis_completed:
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# 如果是刚刚完成的分析，清除标志，避免重复显示
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if st.session_state.get('just_completed', False):
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st.session_state.just_completed = False
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@@ -677,10 +693,6 @@ def main():
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# 显示最终决策
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display_final_decision(final_decision, stock_info, agents_results, discussion_result)
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# 检查是否有已完成的批量分析结果
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elif 'batch_analysis_results' in st.session_state and st.session_state.batch_analysis_results:
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display_batch_analysis_results(st.session_state.batch_analysis_results, period)
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# 示例和说明
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elif not stock_input:
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show_example_interface()
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@@ -832,6 +844,15 @@ def analyze_single_stock_for_batch(symbol, period, enabled_analysts_config=None,
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except:
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pass
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# 5.5 获取风险数据（限售解禁、大股东减持、重要事件，可选）
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risk_data = None
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enable_risk = enabled_analysts_config.get('risk', True)
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if enable_risk and fetcher._is_chinese_stock(symbol):
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try:
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risk_data = fetcher.get_risk_data(symbol)
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except:
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pass
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# 6. 初始化AI分析系统
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agents = StockAnalysisAgents(model=selected_model)
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@@ -841,7 +862,7 @@ def analyze_single_stock_for_batch(symbol, period, enabled_analysts_config=None,
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# 7. 运行多智能体分析
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agents_results = agents.run_multi_agent_analysis(
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stock_info, stock_data, indicators, financial_data,
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fund_flow_data, sentiment_data, news_data, quarterly_data,
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fund_flow_data, sentiment_data, news_data, quarterly_data, risk_data,
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enabled_analysts=enabled_analysts_config
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)
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@@ -1137,6 +1158,36 @@ def run_stock_analysis(symbol, period):
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news_data = None
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elif enable_news and not fetcher._is_chinese_stock(symbol):
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st.info("ℹ️ 美股暂不支持新闻数据")
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progress_bar.progress(45)
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# 5.5 获取风险数据（仅在选择了风险管理师时，使用问财数据源）
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enable_risk = st.session_state.get('enable_risk', True)
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risk_data = None
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if enable_risk and fetcher._is_chinese_stock(symbol):
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status_text.text("⚠️ 正在获取风险数据（限售解禁、大股东减持、重要事件）...")
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try:
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risk_data = fetcher.get_risk_data(symbol)
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if risk_data and risk_data.get('data_success'):
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# 统计获取到的风险数据类型
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risk_types = []
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if risk_data.get('lifting_ban') and risk_data['lifting_ban'].get('has_data'):
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risk_types.append("限售解禁")
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if risk_data.get('shareholder_reduction') and risk_data['shareholder_reduction'].get('has_data'):
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risk_types.append("大股东减持")
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if risk_data.get('important_events') and risk_data['important_events'].get('has_data'):
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risk_types.append("重要事件")
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if risk_types:
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st.info(f"✅ 成功获取风险数据：{', '.join(risk_types)}")
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else:
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st.info("ℹ️ 暂无风险相关数据")
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else:
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st.info("ℹ️ 暂无风险相关数据，将基于基本信息进行风险分析")
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except Exception as e:
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st.warning(f"⚠️ 获取风险数据时出错: {str(e)}")
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risk_data = None
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elif enable_risk and not fetcher._is_chinese_stock(symbol):
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st.info("ℹ️ 美股暂不支持风险数据（限售解禁、大股东减持等）")
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progress_bar.progress(50)
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# 6. 初始化AI分析系统
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@@ -1165,7 +1216,7 @@ def run_stock_analysis(symbol, period):
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status_text.text("🔍 AI分析师团队正在分析,请耐心等待几分钟...")
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agents_results = agents.run_multi_agent_analysis(
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stock_info, stock_data, indicators, financial_data,
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fund_flow_data, sentiment_data, news_data, quarterly_data,
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fund_flow_data, sentiment_data, news_data, quarterly_data, risk_data,
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enabled_analysts=enabled_analysts
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)
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progress_bar.progress(75)
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@@ -2504,22 +2555,16 @@ def display_comparison_table(results):
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df = pd.DataFrame(comparison_data)
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# 应用样式
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def highlight_rating(val):
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if val == '买入' or val == '强烈买入':
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return 'background-color: #c8e6c9; color: #2e7d32;'
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elif val == '持有':
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return 'background-color: #fff9c4; color: #f57f17;'
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elif val == '卖出' or val == '强烈卖出':
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return 'background-color: #ffcdd2; color: #c62828;'
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return ''
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# 显示表格
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# 显示表格（不使用样式，避免matplotlib导入问题）
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st.dataframe(
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df.style.applymap(highlight_rating, subset=['投资评级']),
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df,
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use_container_width=True,
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height=400
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)
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# 添加评级说明
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st.caption("💡 投资评级说明：强烈买入 > 买入 > 持有 > 卖出 > 强烈卖出")
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# 添加筛选功能
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st.markdown("---")
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st.subheader("🔍 快速筛选")
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