feat: AI分析加入前日报告上下文 + 隐藏模型名 + Docker上海时区

Dockerfile

@@ -20,6 +20,10 @@ RUN find /usr/local/lib/python3.11 -type d -name "__pycache__" -exec rm -rf {} +
 FROM python:3.11-slim
 WORKDIR /app
 
+# 设置上海时区
+ENV TZ=Asia/Shanghai
+RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
+
 # 仅复制已编译好的包，无需 gcc
 COPY --from=python-deps /usr/local/lib/python3.11/site-packages /usr/local/lib/python3.11/site-packages
 

backend/services/ai_service.py

@@ -39,6 +39,8 @@ SYSTEM_PROMPT = """你是一位专业的A股市场分析师，擅长从数据中
 
 DAILY_ANALYSIS_PROMPT = """请对 {trade_date} 的A股市场进行收盘分析，生成一份完整的分析报告。
 
+{prev_report_section}
+
 请先调用以下工具获取数据：
 1. get_market_dashboard - 获取市场整体数据
 2. get_theme_history(date="{trade_date}") - 获取今日题材涨幅
@@ -107,9 +109,13 @@ async def collect_ai_analysis(trade_date: str) -> dict:
     Returns:
         {"id": int, "tokens_used": int, "tools_used": list}
     """
+    prev_report_section = _get_prev_report_section(trade_date)
     messages = [
         {"role": "system", "content": SYSTEM_PROMPT},
-        {"role": "user", "content": DAILY_ANALYSIS_PROMPT.format(trade_date=trade_date)}
+        {"role": "user", "content": DAILY_ANALYSIS_PROMPT.format(
+            trade_date=trade_date,
+            prev_report_section=prev_report_section
+        )}
     ]
 
     tools_used = []
@@ -185,3 +191,29 @@ def _save_report(trade_date: str, content: str, summary: str, tools_used: list,
         return cursor.lastrowid
     finally:
         conn.close()
+
+
+def _get_prev_report_section(trade_date: str) -> str:
+    """获取前一个交易日的报告摘要，用于上下文参考"""
+    conn = get_connection()
+    try:
+        row = conn.execute(
+            "SELECT trade_date, content FROM ai_reports WHERE trade_date < ? AND report_type = 'daily' ORDER BY trade_date DESC LIMIT 1",
+            (trade_date,)
+        ).fetchone()
+        if not row:
+            return ""
+        prev_date = row["trade_date"]
+        prev_content = row["content"] or ""
+        # 取报告的前1500字符作为参考上下文
+        truncated = prev_content[:1500]
+        if len(prev_content) > 1500:
+            truncated += "\n...(已截断)"
+        return f"""以下是前一个交易日（{prev_date}）的分析报告，请参考其中的分析逻辑和关注方向，结合今日数据进行对比分析：
+
+{truncated}
+
+---
+"""
+    finally:
+        conn.close()

src/routes/ai-analysis.tsx

@@ -86,7 +86,6 @@ function AiAnalysisPage() {
                     <Clock className="h-3.5 w-3.5 shrink-0" />
                     <span className="truncate">{report.created_at}</span>
                   </span>
-                  <span className="truncate">{report.model}</span>
                   <span>{report.tokens_used?.toLocaleString()} tokens</span>
                   {report.toolsUsed && report.toolsUsed.length > 0 && (
                     <span className="flex items-center gap-1.5">