1.修复docker运行无法打开页面问题 (#6)

2.支持下载DM文件
3.支持硅基流动，阿里百炼模型

app.py

@@ -7,6 +7,8 @@ from datetime import datetime
 import time
 import base64
 import os
+# 从新的配置文件导入model_options
+from model_config import model_options
 
 from stock_data import StockDataFetcher
 from ai_agents import StockAnalysisAgents
@@ -35,10 +37,7 @@ def model_selector():
     st.sidebar.markdown("---")
     st.sidebar.subheader("🤖 AI模型选择")
 
-    model_options = {
+
-        "deepseek-chat": "DeepSeek Chat (默认)",
-        "deepseek-reasoner": "DeepSeek Reasoner (推理增强)"
-    }
 
     selected_model = st.sidebar.selectbox(
         "选择AI模型",
@@ -2064,6 +2063,10 @@ def display_config_manager():
     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。")
+        st.markdown("DeepSeek:https://api.deepseek.com/v1")
+        st.markdown("硅基流动:https://api.siliconflow.cn/v1")
+        st.markdown("火山引擎:https://ark.cn-beijing.volces.com/api/v3")
+        st.markdown("阿里:https://dashscope.aliyuncs.com/compatible-mode/v1")
 
     # DeepSeek API Key
         api_key_info = config_info["DEEPSEEK_API_KEY"]

docker-compose.yml

@@ -7,7 +7,7 @@ services:
       dockerfile: Dockerfile
     container_name: agentsstock1
     ports:
-      - "8503:8501"
+      - "8503:8503"
     volumes:
       # 数据和数据库持久化 - 使用目录挂载而不是文件挂载
       - ./data:/app/data
@@ -20,7 +20,7 @@ services:
     networks:
       - agentsstock-network
     healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:8501/_stcore/health"]
+      test: ["CMD", "curl", "-f", "http://localhost:8503/_stcore/health"]
       interval: 30s
       timeout: 10s
       retries: 3

longhubang_ui.py

@@ -136,9 +136,12 @@ def display_analysis_tab():
             )
     
     with col3:
+        # 导入model_config.py中定义的model_options
+        from model_config import model_options as app_model_options
         selected_model = st.selectbox(
             "AI模型",
-            ["deepseek-chat", "deepseek-reasoner"],
+            list(app_model_options.keys()),
+            format_func=lambda x: app_model_options[x],
             help="Reasoner模型提供更强的推理能力"
         )
     
@@ -721,12 +724,12 @@ def display_visualizations(result):
 def display_pdf_export_section(result):
     """显示PDF导出功能"""
     
-    st.markdown("### 📄 导出PDF报告")
+    st.markdown("### 📄 导出报告")
     
-    col1, col2 = st.columns([3, 1])
+    col1, col2, col3 = st.columns([2, 1, 1])
     
     with col1:
-        st.info("💡 点击按钮生成并下载专业的PDF分析报告")
+        st.info("💡 点击按钮生成并下载专业分析报告")
     
     with col2:
         if st.button("📥 生成PDF", type="primary", width='stretch'):
@@ -753,6 +756,154 @@ def display_pdf_export_section(result):
                 except Exception as e:
                     st.error(f"❌ PDF生成失败: {str(e)}")
     
+    with col3:
+        if st.button("📝 生成Markdown", type="secondary", width='stretch'):
+            with st.spinner("正在生成Markdown报告..."):
+                try:
+                    # 生成Markdown内容
+                    markdown_content = generate_markdown_report(result)
+                    
+                    # 提供下载
+                    st.download_button(
+                        label="📥 下载Markdown报告",
+                        data=markdown_content,
+                        file_name=f"智瞰龙虎报告_{datetime.now().strftime('%Y%m%d_%H%M%S')}.md",
+                        mime="text/markdown",
+                        width='stretch'
+                    )
+                    
+                    st.success("✅ Markdown报告生成成功！")
+                
+                except Exception as e:
+                    st.error(f"❌ Markdown生成失败: {str(e)}")
+
+
+def generate_markdown_report(result_data: dict) -> str:
+    """生成龙虎榜分析Markdown报告"""
+    
+    # 获取当前时间
+    current_time = datetime.now().strftime("%Y年%m月%d日 %H:%M:%S")
+    
+    # 标题页
+    markdown_content = f"""# 智瞰龙虎榜分析报告
+
+**AI驱动的龙虎榜多维度分析系统**
+
+---
+
+## 📊 报告概览
+
+- **生成时间**: {current_time}
+- **数据记录**: {result_data.get('data_info', {}).get('total_records', 0)} 条
+- **涉及股票**: {result_data.get('data_info', {}).get('total_stocks', 0)} 只
+- **涉及游资**: {result_data.get('data_info', {}).get('total_youzi', 0)} 个
+- **AI分析师**: 5位专业分析师团队
+- **分析模型**: DeepSeek AI Multi-Agent System
+
+> ⚠️ 本报告由AI系统基于龙虎榜公开数据自动生成，仅供参考，不构成投资建议。市场有风险，投资需谨慎。
+
+---
+
+## 📈 数据概况
+
+本次分析共涵盖 **{result_data.get('data_info', {}).get('total_records', 0)}** 条龙虎榜记录，
+涉及 **{result_data.get('data_info', {}).get('total_stocks', 0)}** 只股票和 
+**{result_data.get('data_info', {}).get('total_youzi', 0)}** 个游资席位。
+
+"""
+    
+    # 资金概况
+    summary = result_data.get('data_info', {}).get('summary', {})
+    markdown_content += f"""
+### 💰 资金概况
+
+- **总买入金额**: {summary.get('total_buy_amount', 0):,.2f} 元
+- **总卖出金额**: {summary.get('total_sell_amount', 0):,.2f} 元
+- **净流入金额**: {summary.get('total_net_inflow', 0):,.2f} 元
+
+"""
+    
+    # TOP游资
+    if summary.get('top_youzi'):
+        markdown_content += "### 🏆 活跃游资 TOP10\n\n| 排名 | 游资名称 | 净流入金额(元) |\n|------|----------|---------------|\n"
+        for idx, (name, amount) in enumerate(list(summary['top_youzi'].items())[:10], 1):
+            markdown_content += f"| {idx} | {name} | {amount:,.2f} |\n"
+        markdown_content += "\n"
+    
+    # TOP股票
+    if summary.get('top_stocks'):
+        markdown_content += "### 📈 资金净流入 TOP20 股票\n\n| 排名 | 股票代码 | 股票名称 | 净流入金额(元) |\n|------|----------|----------|---------------|\n"
+        for idx, stock in enumerate(summary['top_stocks'][:20], 1):
+            markdown_content += f"| {idx} | {stock['code']} | {stock['name']} | {stock['net_inflow']:,.2f} |\n"
+        markdown_content += "\n"
+    
+    # 热门概念
+    if summary.get('hot_concepts'):
+        markdown_content += "### 🔥 热门概念 TOP15\n\n"
+        for idx, (concept, count) in enumerate(list(summary['hot_concepts'].items())[:15], 1):
+            markdown_content += f"{idx}. {concept} ({count}次)  \n"
+        markdown_content += "\n"
+    
+    # 推荐股票
+    recommended = result_data.get('recommended_stocks', [])
+    if recommended:
+        markdown_content += f"""
+## 🎯 AI推荐股票
+
+基于5位AI分析师的综合分析，系统识别出以下 **{len(recommended)}** 只潜力股票，
+这些股票在资金流向、游资关注度、题材热度等多个维度表现突出。
+
+### 推荐股票清单
+
+| 排名 | 股票代码 | 股票名称 | 净流入金额 | 确定性 | 持有周期 |
+|------|----------|----------|------------|--------|----------|
+"""
+        for stock in recommended[:10]:
+            markdown_content += f"| {stock.get('rank', '-')} | {stock.get('code', '-')} | {stock.get('name', '-')} | {stock.get('net_inflow', 0):,.0f} | {stock.get('confidence', '-')} | {stock.get('hold_period', '-')} |\n"
+        
+        markdown_content += "\n### 推荐理由详解\n\n"
+        for stock in recommended[:5]:  # 只详细展示前5只
+            markdown_content += f"**{stock.get('rank', '-')}. {stock.get('name', '-')} ({stock.get('code', '-')})**\n\n"
+            markdown_content += f"- 推荐理由: {stock.get('reason', '暂无')}\n"
+            markdown_content += f"- 确定性: {stock.get('confidence', '-')}\n"
+            markdown_content += f"- 持有周期: {stock.get('hold_period', '-')}\n\n"
+    
+    # AI分析师报告
+    agents_analysis = result_data.get('agents_analysis', {})
+    if agents_analysis:
+        markdown_content += "## 🤖 AI分析师报告\n\n"
+        markdown_content += "本报告由5位AI专业分析师从不同维度进行分析，综合形成投资建议：\n\n"
+        markdown_content += "- **游资行为分析师** - 分析游资操作特征和意图\n"
+        markdown_content += "- **个股潜力分析师** - 挖掘次日大概率上涨的股票\n"
+        markdown_content += "- **题材追踪分析师** - 识别热点题材和轮动机会\n"
+        markdown_content += "- **风险控制专家** - 识别高风险股票和市场陷阱\n"
+        markdown_content += "- **首席策略师** - 综合研判并给出最终建议\n\n"
+        
+        agent_titles = {
+            'youzi': '游资行为分析师',
+            'stock': '个股潜力分析师',
+            'theme': '题材追踪分析师',
+            'risk': '风险控制专家',
+            'chief': '首席策略师综合研判'
+        }
+        
+        for agent_key, agent_title in agent_titles.items():
+            agent_data = agents_analysis.get(agent_key, {})
+            if agent_data:
+                markdown_content += f"### {agent_title}\n\n"
+                analysis_text = agent_data.get('analysis', '暂无分析')
+                # 处理文本中的换行
+                analysis_text = analysis_text.replace('\n', '\n\n')
+                markdown_content += f"{analysis_text}\n\n"
+    
+    markdown_content += """
+---
+
+*报告由智瞰龙虎AI系统自动生成*
+"""
+    
+    return markdown_content
+
 
 def display_history_tab():
     """显示历史报告标签页（增强版）"""

main_force_ui.py

@@ -128,9 +128,12 @@ def display_main_force_selector():
             )
 
     # 模型选择
+    # 导入model_config.py中定义的model_options
+    from model_config import model_options as app_model_options
     model = st.selectbox(
         "选择AI模型",
-        ["deepseek-chat", "deepseek-reasoner"],
+        list(app_model_options.keys()),
+        format_func=lambda x: app_model_options[x],
         help="deepseek-chat速度快，deepseek-reasoner推理能力强"
     )
 

model_config.py

@@ -0,0 +1,24 @@
+"""
+模型配置文件
+包含所有可用的AI模型选项
+"""
+
+model_options = {
+    "deepseek-chat": "DeepSeek Chat (默认)",
+    "deepseek-reasoner": "DeepSeek Reasoner (推理增强)",
+    "qwen-plus": "qwen-plus (阿里百炼)",
+    "qwen-plus-latest": "qwen-plus-latest (阿里百炼)",
+    "qwen-flash": "qwen-flash (阿里百炼)",
+    "qwen-turbo": "qwen-turbo (阿里百炼)",
+    "qwen3-max": "qwen-max (阿里百炼)",
+    "qwen-long": "qwen-long (阿里百炼)",
+    "deepseek-ai/DeepSeek-R1-0528-Qwen3-8B": "DeepSeek-R1 免费(硅基流动)",
+    "Qwen/Qwen2.5-7B-Instruct": "Qwen 免费(硅基流动)",
+    "Pro/deepseek-ai/DeepSeek-V3.1-Terminus": "DeepSeek-V3.1-Terminus (硅基流动)",
+    "deepseek-ai/DeepSeek-R1": "DeepSeek-R1 (硅基流动)",
+    "Qwen/Qwen3-235B-A22B-Thinking-2507": "Qwen3-235B (硅基流动)",
+    "zai-org/GLM-4.6": "智谱(硅基流动)",
+    "moonshotai/Kimi-K2-Instruct-0905": "Kimi (硅基流动)",
+    "Ring-1T": "蚂蚁百灵 (硅基流动)",
+    "step3": "阶跃星辰(硅基流动)"
+}

pdf_generator.py

@@ -259,6 +259,128 @@ def create_download_link(pdf_content, filename):
     href = f'<a href="data:application/pdf;base64,{b64}" download="{filename}" style="display: inline-block; padding: 15px 30px; background-color: #e74c3c; color: white; text-decoration: none; border-radius: 8px; font-weight: bold; font-size: 16px; margin: 10px;">📄 下载PDF报告</a>'
     return href
 
+def generate_markdown_report(stock_info, agents_results, discussion_result, final_decision):
+    """生成Markdown格式的分析报告"""
+    
+    # 获取当前时间
+    current_time = datetime.now().strftime("%Y年%m月%d日 %H:%M:%S")
+    
+    markdown_content = f"""
+# AI股票分析报告
+
+**生成时间**: {current_time}
+
+---
+
+## 📊 股票基本信息
+
+| 项目 | 值 |
+|------|-----|
+| **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(PE)** | {stock_info.get('pe_ratio', 'N/A')} |
+| **市净率(PB)** | {stock_info.get('pb_ratio', 'N/A')} |
+| **市值** | {stock_info.get('market_cap', 'N/A')} |
+| **市场** | {stock_info.get('market', 'N/A')} |
+| **交易所** | {stock_info.get('exchange', 'N/A')} |
+
+---
+
+## 🔍 各分析师详细分析
+
+"""
+
+    # 添加各分析师的分析结果
+    agent_names = {
+        'technical': '📈 技术分析师',
+        'fundamental': '📊 基本面分析师',
+        'fund_flow': '💰 资金面分析师',
+        'risk_management': '⚠️ 风险管理师',
+        'market_sentiment': '📈 市场情绪分析师'
+    }
+    
+    for agent_key, agent_name in agent_names.items():
+        if agent_key in agents_results:
+            agent_result = agents_results[agent_key]
+            if isinstance(agent_result, dict):
+                analysis_text = agent_result.get('analysis', '暂无分析')
+            else:
+                analysis_text = str(agent_result)
+            
+            markdown_content += f"""
+### {agent_name}
+
+{analysis_text}
+
+---
+
+"""
+
+    # 添加团队讨论结果
+    markdown_content += f"""
+## 🤝 团队综合讨论
+
+{discussion_result}
+
+---
+
+## 📋 最终投资决策
+
+"""
+    
+    # 处理最终决策的显示
+    if isinstance(final_decision, dict) and "decision_text" not in final_decision:
+        # JSON格式的决策
+        markdown_content += f"""
+**投资评级**: {final_decision.get('rating', '未知')}
+
+**目标价位**: {final_decision.get('target_price', 'N/A')}
+
+**操作建议**: {final_decision.get('operation_advice', '暂无建议')}
+
+**进场区间**: {final_decision.get('entry_range', 'N/A')}
+
+**止盈位**: {final_decision.get('take_profit', 'N/A')}
+
+**止损位**: {final_decision.get('stop_loss', 'N/A')}
+
+**持有周期**: {final_decision.get('holding_period', 'N/A')}
+
+**仓位建议**: {final_decision.get('position_size', 'N/A')}
+
+**信心度**: {final_decision.get('confidence_level', 'N/A')}/10
+
+**风险提示**: {final_decision.get('risk_warning', '无')}
+"""
+    else:
+        # 文本格式的决策
+        decision_text = final_decision.get('decision_text', str(final_decision))
+        markdown_content += decision_text
+
+    markdown_content += """
+
+---
+
+## 📝 免责声明
+
+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。
+
+---
+
+*报告生成时间: {current_time}*
+*AI股票分析系统 v1.0*
+"""
+
+    return markdown_content
+
+def create_markdown_download_link(markdown_content, filename):
+    """创建Markdown下载链接"""
+    b64 = base64.b64encode(markdown_content.encode()).decode()
+    href = f'<a href="data:text/markdown;base64,{b64}" download="{filename}" style="display: inline-block; padding: 15px 30px; background-color: #9b59b6; color: white; text-decoration: none; border-radius: 8px; font-weight: bold; font-size: 16px; margin: 10px;">📝 下载Markdown报告</a>'
+    return href
+
 def display_pdf_export_section(stock_info, agents_results, discussion_result, final_decision):
     """显示PDF导出区域"""
     
@@ -269,8 +391,11 @@ def display_pdf_export_section(stock_info, agents_results, discussion_result, fi
     
     with col2:
         # 生成PDF报告按钮（使用股票代码作为key的一部分，确保唯一性）
-        button_key = f"pdf_btn_{stock_info.get('symbol', 'unknown')}"
+        pdf_button_key = f"pdf_btn_{stock_info.get('symbol', 'unknown')}"
-        if st.button("📄 生成并下载PDF报告", type="primary", width='content', key=button_key):
+        markdown_button_key = f"markdown_btn_{stock_info.get('symbol', 'unknown')}"
+        
+        # 生成PDF报告按钮
+        if st.button("📄 生成并下载PDF报告", type="primary", width='content', key=pdf_button_key):
             with st.spinner("正在生成PDF报告..."):
                 try:
                     # 生成PDF内容
@@ -300,3 +425,36 @@ def display_pdf_export_section(stock_info, agents_results, discussion_result, fi
                     st.error(f"❌ 生成PDF报告时出错: {str(e)}")
                     import traceback
                     st.error(f"详细错误信息: {traceback.format_exc()}")
+        
+        # 生成Markdown报告按钮
+        if st.button("📝 生成并下载Markdown报告", type="secondary", width='content', key=markdown_button_key):
+            with st.spinner("正在生成Markdown报告..."):
+                try:
+                    # 生成Markdown内容
+                    markdown_content = generate_markdown_report(stock_info, agents_results, discussion_result, final_decision)
+                    
+                    # 生成文件名
+                    stock_symbol = stock_info.get('symbol', 'unknown')
+                    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+                    filename = f"股票分析报告_{stock_symbol}_{timestamp}.md"
+                    
+                    st.success("✅ Markdown报告生成成功！")
+                    st.balloons()
+                    
+                    # 显示下载链接
+                    st.markdown("### 📄 报告下载")
+                    
+                    download_link = create_markdown_download_link(markdown_content, filename)
+                    st.markdown(f"""
+                    <div style="text-align: center; margin: 20px 0;">
+                        {download_link}
+                    </div>
+                    """, unsafe_allow_html=True)
+                    
+                    st.info("💡 提示：点击上方按钮即可下载Markdown格式的完整分析报告")
+                    
+                except Exception as e:
+                    st.error(f"❌ 生成Markdown报告时出错: {str(e)}")
+                    import traceback
+                    st.error(f"详细错误信息: {traceback.format_exc()}")
+

pdf_generator_fixed.py

@@ -133,151 +133,6 @@ def create_html_download_link(content, filename, link_text):
     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>'
     return href
 
-def generate_html_content(markdown_content):
-    """将Markdown转换为HTML"""
-    html_content = f"""
-<!DOCTYPE html>
-<html>
-<head>
-    <meta charset="UTF-8">
-    <title>AI股票分析报告</title>
-    <style>
-        body {{
-            font-family: 'Microsoft YaHei', Arial, sans-serif;
-            line-height: 1.6;
-            max-width: 800px;
-            margin: 0 auto;
-            padding: 20px;
-            background-color: #f5f5f5;
-        }}
-        .container {{
-            background-color: white;
-            padding: 30px;
-            border-radius: 10px;
-            box-shadow: 0 2px 10px rgba(0,0,0,0.1);
-        }}
-        h1 {{
-            color: #2c3e50;
-            border-bottom: 3px solid #3498db;
-            padding-bottom: 10px;
-        }}
-        h2 {{
-            color: #34495e;
-            border-left: 4px solid #3498db;
-            padding-left: 15px;
-            margin-top: 30px;
-        }}
-        h3 {{
-            color: #2980b9;
-            margin-top: 25px;
-        }}
-        table {{
-            width: 100%;
-            border-collapse: collapse;
-            margin: 20px 0;
-        }}
-        th, td {{
-            border: 1px solid #ddd;
-            padding: 12px;
-            text-align: left;
-        }}
-        th {{
-            background-color: #3498db;
-            color: white;
-        }}
-        tr:nth-child(even) {{
-            background-color: #f9f9f9;
-        }}
-        .disclaimer {{
-            background-color: #fff3cd;
-            border: 1px solid #ffeaa7;
-            border-radius: 5px;
-            padding: 15px;
-            margin-top: 30px;
-        }}
-        .footer {{
-            text-align: center;
-            margin-top: 30px;
-            color: #7f8c8d;
-            font-style: italic;
-        }}
-        hr {{
-            border: none;
-            height: 2px;
-            background-color: #ecf0f1;
-            margin: 20px 0;
-        }}
-        strong {{
-            color: #2c3e50;
-        }}
-    </style>
-</head>
-<body>
-    <div class="container">
-"""
-    
-    # 简单的Markdown到HTML转换
-    html_body = markdown_content
-    html_body = html_body.replace('\n# ', '\n<h1>').replace('\n## ', '\n<h2>').replace('\n### ', '\n<h3>')
-    html_body = html_body.replace('# ', '<h1>').replace('## ', '<h2>').replace('### ', '<h3>')
-    html_body = html_body.replace('\n---\n', '\n<hr>\n')
-    
-    # 处理粗体文本
-    html_body = re.sub(r'\*\*(.*?)\*\*', r'<strong>\1</strong>', html_body)
-    
-    # 处理表格
-    lines = html_body.split('\n')
-    in_table = False
-    processed_lines = []
-    
-    for line in lines:
-        if '|' in line and not in_table and line.strip().startswith('|'):
-            processed_lines.append('<table>')
-            in_table = True
-            cells = [cell.strip() for cell in line.split('|')[1:-1]]
-            processed_lines.append('<tr>')
-            for cell in cells:
-                processed_lines.append(f'<th>{cell}</th>')
-            processed_lines.append('</tr>')
-        elif '|' in line and in_table:
-            if '---' not in line:
-                cells = [cell.strip() for cell in line.split('|')[1:-1]]
-                processed_lines.append('<tr>')
-                for cell in cells:
-                    processed_lines.append(f'<td>{cell}</td>')
-                processed_lines.append('</tr>')
-        elif in_table and '|' not in line:
-            processed_lines.append('</table>')
-            processed_lines.append(line)
-            in_table = False
-        else:
-            processed_lines.append(line)
-    
-    if in_table:
-        processed_lines.append('</table>')
-    
-    html_body = '\n'.join(processed_lines)
-    
-    # 处理段落
-    paragraphs = html_body.split('\n\n')
-    processed_paragraphs = []
-    for para in paragraphs:
-        para = para.strip()
-        if para and not para.startswith('<') and not para.startswith('---'):
-            processed_paragraphs.append(f'<p>{para}</p>')
-        else:
-            processed_paragraphs.append(para)
-    
-    html_body = '\n'.join(processed_paragraphs)
-    
-    html_content += html_body + """
-    </div>
-</body>
-</html>
-"""
-    
-    return html_content
-
 def display_pdf_export_section(stock_info, agents_results, discussion_result, final_decision):
     """显示PDF导出区域 - 修复报告生成问题"""
     
@@ -290,8 +145,11 @@ def display_pdf_export_section(stock_info, agents_results, discussion_result, fi
         # 生成报告按钮
         import uuid
         import time
-        button_key = f"generate_report_btn_{int(time.time())}_{uuid.uuid4().hex[:8]}"
+        pdf_button_key = f"generate_report_btn_{int(time.time())}_{uuid.uuid4().hex[:8]}"
-        if st.button("📊 生成并下载报告", type="primary", width='content', key=button_key):
+        markdown_button_key = f"generate_markdown_btn_{int(time.time())}_{uuid.uuid4().hex[:8]}"
+        
+        # 生成PDF和HTML报告按钮
+        if st.button("📊 生成并下载报告(PDF/HTML)", type="primary", width='content', key=pdf_button_key):
             with st.spinner("正在生成报告..."):
                 try:
                     # 生成Markdown内容
@@ -338,3 +196,43 @@ def display_pdf_export_section(stock_info, agents_results, discussion_result, fi
                     st.error(f"❌ 生成报告时出错: {str(e)}")
                     import traceback
                     st.error(f"详细错误信息: {traceback.format_exc()}")
+        
+        # 单独生成Markdown报告按钮
+        if st.button("📝 生成并下载Markdown报告", type="secondary", width='content', key=markdown_button_key):
+            with st.spinner("正在生成Markdown报告..."):
+                try:
+                    # 生成Markdown内容
+                    markdown_content = generate_markdown_report(stock_info, agents_results, discussion_result, final_decision)
+                    
+                    # 生成文件名
+                    stock_symbol = stock_info.get('symbol', 'unknown')
+                    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+                    filename = f"股票分析报告_{stock_symbol}_{timestamp}.md"
+                    
+                    st.success("✅ Markdown报告生成成功！")
+                    st.balloons()
+                    
+                    # 显示下载链接
+                    st.markdown("### 📄 报告下载")
+                    
+                    # 创建下载链接
+                    md_link = create_download_link(
+                        markdown_content, 
+                        filename, 
+                        "📝 下载Markdown报告"
+                    )
+                    
+                    # 显示下载链接
+                    st.markdown(f"""
+                    <div style="text-align: center; margin: 20px 0;">
+                        {md_link}
+                    </div>
+                    """, unsafe_allow_html=True)
+                    
+                    st.info("💡 提示：点击上方按钮即可下载Markdown格式的报告文件")
+                    
+                except Exception as e:
+                    st.error(f"❌ 生成Markdown报告时出错: {str(e)}")
+                    import traceback
+                    st.error(f"详细错误信息: {traceback.format_exc()}")
+

pdf_generator_pandoc.py

@@ -267,13 +267,48 @@ def display_pdf_export_section(stock_info, agents_results, discussion_result, fi
     col1, col2, col3 = st.columns([1, 2, 1])
     
     with col2:
-        if st.button("📊 生成并下载报告", type="primary", width='content', key="generate_report_btn"):
+        pdf_button_key = "generate_report_btn"
+        markdown_button_key = "generate_markdown_btn"
+        
+        # 生成PDF报告按钮
+        if st.button("📊 生成并下载报告(PDF/HTML)", type="primary", width='content', key=pdf_button_key):
             st.session_state.show_download_links = True
             with st.spinner("正在生成报告..."):
                 success = generate_pdf_report(stock_info, agents_results, discussion_result, final_decision)
                 if success:
                     st.balloons()
         
+        # 生成Markdown报告按钮
+        if st.button("📝 生成并下载Markdown报告", type="secondary", width='content', key=markdown_button_key):
+            with st.spinner("正在生成Markdown报告..."):
+                try:
+                    # 生成Markdown内容
+                    markdown_content = generate_markdown_report(stock_info, agents_results, discussion_result, final_decision)
+                    
+                    # 生成文件名
+                    stock_symbol = stock_info.get('symbol', 'unknown')
+                    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+                    filename = f"股票分析报告_{stock_symbol}_{timestamp}.md"
+                    
+                    st.success("✅ Markdown报告生成成功！")
+                    st.balloons()
+                    
+                    # 显示下载链接
+                    st.markdown("### 📄 报告下载")
+                    
+                    # Markdown下载链接
+                    md_download_link = create_download_link(
+                        markdown_content, 
+                        filename, 
+                        "📝 下载Markdown报告"
+                    )
+                    st.markdown(md_download_link, unsafe_allow_html=True)
+                    
+                    st.info("💡 提示：点击上方按钮即可下载Markdown格式的报告文件")
+                    
+                except Exception as e:
+                    st.error(f"❌ 生成Markdown报告时出错: {str(e)}")
+    
     # 如果已经生成了报告，显示下载链接
     if st.session_state.show_download_links:
         generate_pdf_report(stock_info, agents_results, discussion_result, final_decision)

sector_strategy_ui.py

@@ -116,9 +116,12 @@ def display_analysis_tab():
     col1, col2, col3 = st.columns([2, 2, 2])
     
     with col1:
+        # 导入model_config.py中定义的model_options
+        from model_config import model_options as app_model_options
         selected_model = st.selectbox(
-            "选择AI模型",
+            "AI模型",
-            ["deepseek-chat", "deepseek-reasoner"],
+            list(app_model_options.keys()),
+            format_func=lambda x: app_model_options[x],
             help="Reasoner模型提供更强的推理能力"
         )
     
@@ -774,10 +777,10 @@ def display_pdf_export_section(result):
     """显示PDF导出部分"""
     st.subheader("📄 导出报告")
     
-    col1, col2, col3 = st.columns([2, 1, 1])
+    col1, col2, col3, col4 = st.columns([2, 1, 1, 1])
     
     with col1:
-        st.write("将分析报告导出为PDF文件，方便保存和分享")
+        st.write("将分析报告导出为PDF或Markdown文件，方便保存和分享")
     
     with col2:
         if st.button("📥 生成PDF报告", type="primary", width='content'):
@@ -802,6 +805,23 @@ def display_pdf_export_section(result):
                     st.error(f"❌ PDF生成失败: {str(e)}")
     
     with col3:
+        if st.button("📝 生成Markdown", type="secondary", width='content'):
+            with st.spinner("正在生成Markdown报告..."):
+                try:
+                    # 生成Markdown内容
+                    markdown_content = generate_sector_markdown_report(result)
+                    
+                    # 保存到session_state
+                    st.session_state.sector_markdown_data = markdown_content
+                    st.session_state.sector_markdown_filename = f"智策报告_{result.get('timestamp', datetime.now().strftime('%Y%m%d_%H%M%S')).replace(':', '').replace(' ', '_')}.md"
+                    
+                    st.success("✅ Markdown报告生成成功！")
+                    st.rerun()
+                    
+                except Exception as e:
+                    st.error(f"❌ Markdown生成失败: {str(e)}")
+    
+    with col4:
         # 如果已经生成了PDF，显示下载按钮
         if 'sector_pdf_data' in st.session_state:
             st.download_button(
@@ -812,6 +832,197 @@ def display_pdf_export_section(result):
                         width='content'
                     )
         
+        # 如果已经生成了Markdown，显示下载按钮
+        if 'sector_markdown_data' in st.session_state:
+            st.download_button(
+                        label="💾 下载Markdown",
+                        data=st.session_state.sector_markdown_data,
+                        file_name=st.session_state.sector_markdown_filename,
+                        mime="text/markdown",
+                        width='content'
+                    )
+
+
+def generate_sector_markdown_report(result_data: dict) -> str:
+    """生成智策分析Markdown报告"""
+    
+    # 获取当前时间
+    current_time = datetime.now().strftime("%Y年%m月%d日 %H:%M:%S")
+    
+    # 标题页
+    markdown_content = f"""# 智策板块策略分析报告
+
+**AI驱动的多维度板块投资决策支持系统**
+
+---
+
+## 📊 报告信息
+
+- **生成时间**: {current_time}
+- **分析周期**: 当日市场数据
+- **AI模型**: DeepSeek Multi-Agent System
+- **分析维度**: 宏观·板块·资金·情绪
+
+> ⚠️ 本报告由AI系统自动生成，仅供参考，不构成投资建议。投资有风险，决策需谨慎。
+
+---
+
+## 📈 市场概况
+
+本报告基于{result_data.get('timestamp', 'N/A')}的实时市场数据，
+通过四位AI智能体的多维度分析，为您提供板块投资策略建议。
+
+### 分析师团队:
+
+- **宏观策略师** - 分析宏观经济、政策导向、新闻事件
+- **板块诊断师** - 分析板块走势、估值水平、轮动特征
+- **资金流向分析师** - 分析主力资金、北向资金流向
+- **市场情绪解码员** - 分析市场情绪、热度、赚钱效应
+
+"""
+    
+    # 核心预测
+    predictions = result_data.get('final_predictions', {})
+    
+    if predictions.get('prediction_text'):
+        # 文本格式预测
+        markdown_content += f"""
+## 🎯 核心预测
+
+{predictions.get('prediction_text', '')}
+
+"""
+    else:
+        # JSON格式预测
+        markdown_content += "## 🎯 核心预测\n\n"
+        
+        # 1. 板块多空预测
+        long_short = predictions.get('long_short', {})
+        bullish = long_short.get('bullish', [])
+        bearish = long_short.get('bearish', [])
+        
+        markdown_content += "### 📊 板块多空预测\n\n"
+        
+        if bullish:
+            markdown_content += "#### 🟢 看多板块\n\n"
+            for idx, item in enumerate(bullish, 1):
+                markdown_content += f"{idx}. **{item.get('sector', 'N/A')}** (信心度: {item.get('confidence', 0)}/10)\n"
+                markdown_content += f"   - 理由: {item.get('reason', 'N/A')}\n"
+                markdown_content += f"   - 风险: {item.get('risk', 'N/A')}\n\n"
+        
+        if bearish:
+            markdown_content += "#### 🔴 看空板块\n\n"
+            for idx, item in enumerate(bearish, 1):
+                markdown_content += f"{idx}. **{item.get('sector', 'N/A')}** (信心度: {item.get('confidence', 0)}/10)\n"
+                markdown_content += f"   - 理由: {item.get('reason', 'N/A')}\n"
+                markdown_content += f"   - 风险: {item.get('risk', 'N/A')}\n\n"
+        
+        # 2. 板块轮动预测
+        rotation = predictions.get('rotation', {})
+        current_strong = rotation.get('current_strong', [])
+        potential = rotation.get('potential', [])
+        declining = rotation.get('declining', [])
+        
+        markdown_content += "### 🔄 板块轮动预测\n\n"
+        
+        if current_strong:
+            markdown_content += "#### 💪 当前强势板块\n\n"
+            for item in current_strong:
+                markdown_content += f"- **{item.get('sector', 'N/A')}**\n"
+                markdown_content += f"  - 轮动逻辑: {item.get('logic', 'N/A')}\n"
+                markdown_content += f"  - 时间窗口: {item.get('time_window', 'N/A')}\n"
+                markdown_content += f"  - 操作建议: {item.get('advice', 'N/A')}\n\n"
+        
+        if potential:
+            markdown_content += "#### 🌱 潜力接力板块\n\n"
+            for item in potential:
+                markdown_content += f"- **{item.get('sector', 'N/A')}**\n"
+                markdown_content += f"  - 轮动逻辑: {item.get('logic', 'N/A')}\n"
+                markdown_content += f"  - 时间窗口: {item.get('time_window', 'N/A')}\n"
+                markdown_content += f"  - 操作建议: {item.get('advice', 'N/A')}\n\n"
+        
+        if declining:
+            markdown_content += "#### 📉 衰退板块\n\n"
+            for item in declining:
+                markdown_content += f"- **{item.get('sector', 'N/A')}**\n"
+                markdown_content += f"  - 轮动逻辑: {item.get('logic', 'N/A')}\n"
+                markdown_content += f"  - 时间窗口: {item.get('time_window', 'N/A')}\n"
+                markdown_content += f"  - 操作建议: {item.get('advice', 'N/A')}\n\n"
+        
+        # 3. 板块热度排行
+        heat = predictions.get('heat', {})
+        hottest = heat.get('hottest', [])
+        heating = heat.get('heating', [])
+        cooling = heat.get('cooling', [])
+        
+        markdown_content += "### 🔥 板块热度排行\n\n"
+        
+        if hottest:
+            markdown_content += "#### 最热板块\n\n| 排名 | 板块 | 热度评分 | 趋势 | 持续性 |\n|------|------|----------|------|--------|\n"
+            for idx, item in enumerate(hottest[:10], 1):
+                markdown_content += f"| {idx} | {item.get('sector', 'N/A')} | {item.get('score', 0)} | {item.get('trend', 'N/A')} | {item.get('sustainability', 'N/A')} |\n"
+            markdown_content += "\n"
+        
+        if heating:
+            markdown_content += "#### 升温板块\n\n"
+            for idx, item in enumerate(heating[:5], 1):
+                markdown_content += f"{idx}. {item.get('sector', 'N/A')} (评分: {item.get('score', 0)})\n"
+            markdown_content += "\n"
+        
+        if cooling:
+            markdown_content += "#### 降温板块\n\n"
+            for idx, item in enumerate(cooling[:5], 1):
+                markdown_content += f"{idx}. {item.get('sector', 'N/A')} (评分: {item.get('score', 0)})\n"
+            markdown_content += "\n"
+        
+        # 4. 策略总结
+        summary = predictions.get('summary', {})
+        if summary:
+            markdown_content += "### 📝 策略总结\n\n"
+            
+            if summary.get('market_view'):
+                markdown_content += f"**市场观点:** {summary.get('market_view', '')}\n\n"
+            
+            if summary.get('key_opportunity'):
+                markdown_content += f"**核心机会:** {summary.get('key_opportunity', '')}\n\n"
+            
+            if summary.get('major_risk'):
+                markdown_content += f"**主要风险:** {summary.get('major_risk', '')}\n\n"
+            
+            if summary.get('strategy'):
+                markdown_content += f"**整体策略:** {summary.get('strategy', '')}\n\n"
+    
+    # AI智能体分析
+    agents_analysis = result_data.get('agents_analysis', {})
+    if agents_analysis:
+        markdown_content += "## 🤖 AI智能体分析\n\n"
+        
+        for key, agent_data in agents_analysis.items():
+            agent_name = agent_data.get('agent_name', '未知分析师')
+            agent_role = agent_data.get('agent_role', '')
+            focus_areas = ', '.join(agent_data.get('focus_areas', []))
+            analysis = agent_data.get('analysis', '')
+            
+            markdown_content += f"### {agent_name}\n\n"
+            markdown_content += f"- **职责**: {agent_role}\n"
+            markdown_content += f"- **关注领域**: {focus_areas}\n\n"
+            markdown_content += f"{analysis}\n\n"
+            markdown_content += "---\n\n"
+    
+    # 综合研判
+    comprehensive_report = result_data.get('comprehensive_report', '')
+    if comprehensive_report:
+        markdown_content += "## 📊 综合研判\n\n"
+        markdown_content += f"{comprehensive_report}\n\n"
+    
+    markdown_content += """
+---
+
+*报告由智策AI系统自动生成*
+"""
+    
+    return markdown_content
+
 
 def display_scheduler_settings():
     """显示定时任务设置"""