ci(workflow): 添加上游仓库同步的GitHub Actions工作流

.github/workflows/sync.yml

@@ -0,0 +1,49 @@
+name: Upstream Sync
+
+on:
+  schedule:
+    - cron: "0 */6 * * *"
+  workflow_dispatch:
+
+permissions:
+  contents: write
+  actions: write
+
+jobs:
+  sync_latest_from_upstream:
+    name: Sync latest commits from upstream repo
+    runs-on: ubuntu-latest
+    if: ${{ github.event.repository.fork }}
+
+    steps:
+      # Step 1: run a standard checkout action
+      - name: Checkout target repo
+        uses: actions/checkout@v4
+
+      # Step 2: run the sync action
+      - name: Sync upstream changes
+        id: sync
+        uses: aormsby/Fork-Sync-With-Upstream-action@v3.4.1
+        with:
+          upstream_sync_repo: HuaYaoAI/FinGenius
+          upstream_sync_branch: main
+          target_sync_branch: main
+          target_repo_token: ${{ secrets.GITHUB_TOKEN }}
+          upstream_pull_args: '--allow-unrelated-histories --strategy=ours'
+          git_log_format_option: '--oneline'
+          git_push_args: '--no-verify'
+          git_commit_args: '--no-verify'
+
+      - name: Sync check
+        if: failure()
+        run: |
+          echo "[Error] Due to a change in the workflow file of the upstream repository, GitHub has automatically suspended the scheduled automatic update. You need to manually sync your fork."
+          exit 1
+
+      - name: Delete workflow runs
+        uses: Mattraks/delete-workflow-runs@main
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          repository: ${{ github.repository }}
+          retain_days: 0
+          keep_minimum_runs: 2

.gitignore

@@ -197,3 +197,6 @@ cython_debug/
 
 # node
 node_modules
+
+report/
+logs/

README.md

@@ -69,7 +69,7 @@
 
 欢迎对AI金融极致热爱的你
 
-携手完善FinGenius，共同探索金融智能分析的技术前沿边界！🌟
+携手完善[FinGenius](https://fingenius.cn)，共同探索金融智能分析的技术前沿边界！🌟
 
 
 ## 安装指南

src/agent/sentiment.py

@@ -68,43 +68,52 @@ async def analyze(self, stock_code: str, **kwargs) -> Dict:
 
             # 1. 强制执行新闻搜索
             try:
-                news_result = await self.tool_call("web_search", {
-                    "query": f"{stock_code} 股票 最新消息 舆情",
-                    "max_results": 10
-                })
-                if news_result and news_result.success:
-                    analysis_tasks.append(("news_search", news_result.data))
+                news_result = await self.available_tools.execute(
+                    name="web_search", 
+                    tool_input={
+                        "query": f"{stock_code} 股票 最新消息 舆情",
+                        "max_results": 10
+                    }
+                )
+                if news_result and not news_result.error:
+                    analysis_tasks.append(("news_search", news_result.output))
                     logger.info(f"新闻搜索成功: {stock_code}")
                 else:
-                    logger.warning(f"新闻搜索失败: {stock_code}")
+                    logger.warning(f"新闻搜索失败: {stock_code}, {news_result.error if news_result else 'Unknown error'}")
             except Exception as e:
                 logger.error(f"新闻搜索异常: {stock_code}, {str(e)}")
 
             # 2. 强制执行社交媒体分析
             try:
-                social_result = await self.tool_call("web_search", {
-                    "query": f"{stock_code} 股吧 讨论 情绪",
-                    "max_results": 5
-                })
-                if social_result and social_result.success:
-                    analysis_tasks.append(("social_media", social_result.data))
+                social_result = await self.available_tools.execute(
+                    name="web_search", 
+                    tool_input={
+                        "query": f"{stock_code} 股吧 讨论 情绪",
+                        "max_results": 5
+                    }
+                )
+                if social_result and not social_result.error:
+                    analysis_tasks.append(("social_media", social_result.output))
                     logger.info(f"社交媒体分析成功: {stock_code}")
                 else:
-                    logger.warning(f"社交媒体分析失败: {stock_code}")
+                    logger.warning(f"社交媒体分析失败: {stock_code}, {social_result.error if social_result else 'Unknown error'}")
             except Exception as e:
                 logger.error(f"社交媒体分析异常: {stock_code}, {str(e)}")
 
             # 3. 强制执行舆情分析工具
             try:
-                sentiment_result = await self.tool_call("sentiment_analysis", {
-                    "stock_code": stock_code,
-                    "analysis_type": "comprehensive"
-                })
-                if sentiment_result and sentiment_result.success:
-                    analysis_tasks.append(("sentiment_analysis", sentiment_result.data))
+                sentiment_result = await self.available_tools.execute(
+                    name="sentiment_analysis", 
+                    tool_input={
+                        "stock_code": stock_code,
+                        "analysis_type": "comprehensive"
+                    }
+                )
+                if sentiment_result and not sentiment_result.error:
+                    analysis_tasks.append(("sentiment_analysis", sentiment_result.output))
                     logger.info(f"舆情分析工具成功: {stock_code}")
                 else:
-                    logger.warning(f"舆情分析工具失败: {stock_code}")
+                    logger.warning(f"舆情分析工具失败: {stock_code}, {sentiment_result.error if sentiment_result else 'Unknown error'}")
             except Exception as e:
                 logger.error(f"舆情分析工具异常: {stock_code}, {str(e)}")
 

src/mcp/risk_control_server.py

@@ -1,16 +1,18 @@
 from src.mcp.server import MCPServer
 from src.tool import Terminate
-from src.tool.risk_control import RiskControlTool
+from src.tool.sentiment import SentimentTool
+from src.tool.web_search import WebSearch
 
 
-class RiskControlServer(MCPServer):
-    def __init__(self, name: str = "RiskControlServer"):
+class SentimentServer(MCPServer):
+    def __init__(self, name: str = "SentimentServer"):
         super().__init__(name)
 
     def _initialize_standard_tools(self) -> None:
         self.tools.update(
             {
-                "risk_control_tool": RiskControlTool(),
+                "sentiment_tool": SentimentTool(),
+                "web_search": WebSearch(),
                 "terminate": Terminate(),
             }
         )

src/prompt/create_html.py

@@ -488,33 +488,119 @@
     <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.3/dist/js/bootstrap.bundle.min.js"></script>
 
     <script>
-        // 页面数据全局变量 - 将被填充实际数据
-        let reportData = {};
-
-        // DOM加载完成后执行
-        document.addEventListener('DOMContentLoaded', function() {
-            // 直接渲染页面，数据将在注入时被替换
-            renderPage();
-
-            // 初始化交互功能
-            initializeInteractions();
-        });
-
-        // 渲染整个页面
-        function renderPage() {
-            renderOverview();
-            renderAnalysis();
-            renderDebate();
+        // 页面初始化
+        function initializePage() {
+            try {
+                renderPage();
+                initializeInteractions();
+            } catch (error) {
+                console.error('页面渲染失败:', error);
+                const errorMessage = `
+                    <div class="alert alert-danger">
+                        <h4 class="alert-heading">页面渲染失败</h4>
+                        <p>很抱歉，在渲染页面时发生错误。错误信息：${error.message}</p>
+                        <hr>
+                        <p class="mb-0">请刷新页面重试，如果问题持续存在，请联系技术支持。</p>
+                    </div>
+                `;
+                document.getElementById('overview').innerHTML = errorMessage;
+                document.getElementById('analysis').innerHTML = '';
+                document.getElementById('debate').innerHTML = '';
+            }
         }
+
+        // DOM加载完成后执行
+          document.addEventListener('DOMContentLoaded', function() {
+              // 显示加载状态
+              document.getElementById('overview').innerHTML = '<div class="alert alert-info">数据加载中...</div>';
+
+              // 检查数据加载状态
+              if (window.dataLoadingState.isLoaded) {
+                  if (reportData && Object.keys(reportData).length > 0) {
+                      initializePage();
+                  } else {
+                      console.error('页面数据未正确加载');
+                      document.getElementById('overview').innerHTML = '<div class="alert alert-danger">数据加载失败</div>';
+                  }
+              } else {
+                  // 设置超时检查
+                  setTimeout(() => {
+                      if (!window.dataLoadingState.isLoaded) {
+                          console.error('数据加载超时');
+                          document.getElementById('overview').innerHTML = '<div class="alert alert-danger">数据加载超时</div>';
+                      }
+                  }, 5000);
+              }
+          });
+
+        // 页面数据注入点 - 将被自动替换
+         let reportData = {};
+
+         // 添加数据加载状态指示
+         window.dataLoadingState = {
+             isLoaded: false,
+             error: null
+         };
+
+         // 监听数据加载状态
+         Object.defineProperty(window.dataLoadingState, 'isLoaded', {
+             set: function(value) {
+                 this._isLoaded = value;
+                 if (value && reportData && Object.keys(reportData).length > 0) {
+                     initializePage();
+                 }
+             },
+             get: function() {
+                 return this._isLoaded;
+             }
+         });
+
+        // 验证数据完整性
+         function validateReportData() {
+             const requiredFields = [
+                 'stock_code',
+                 'battle_results',
+                 'analysis_results',
+                 'debate_results'
+             ];
+
+             const missingFields = requiredFields.filter(field => !reportData[field]);
+
+             if (missingFields.length > 0) {
+                 throw new Error(`数据不完整，缺少以下字段：${missingFields.join(', ')}`);
+             }
+
+             // 验证具体字段的数据结构
+             if (!Array.isArray(reportData.battle_results)) {
+                 throw new Error('battle_results 必须是数组类型');
+             }
+
+             if (!Array.isArray(reportData.debate_results)) {
+                 throw new Error('debate_results 必须是数组类型');
+             }
+
+             return true;
+         }
+
+         // 渲染整个页面
+         function renderPage() {
+             // 首先验证数据
+             validateReportData();
+
+             // 开始渲染各个部分
+             renderOverview();
+             renderAnalysis();
+             renderDebate();
+         }
 
         // 渲染概览部分
         function renderOverview() {
             const overview = document.getElementById('overview');
             const stockCode = reportData.stock_code || '未知';
-            const voteResults = reportData.vote_results || {};
-            const bullishCount = voteResults.bullish || 0;
-            const bearishCount = voteResults.bearish || 0;
-            const finalDecision = voteResults.final_decision || 'unknown';
+            const battleResults = reportData.battle_results || {};
+            const bullishCount = battleResults.vote_count?.bullish || 0;
+            const bearishCount = battleResults.vote_count?.bearish || 0;
+            const finalDecision = battleResults.final_decision || 'unknown';
 
             const totalVotes = bullishCount + bearishCount;
             const bullishPct = totalVotes > 0 ? (bullishCount / totalVotes * 100).toFixed(1) : 0;