feat: AI分析第三档——海外期货章节、报告分卡片渲染、红绿着色、期号；LLM改流式+分段生成绕开网关120s超时

backend/routes/ai_analysis.py

@@ -43,8 +43,11 @@ def _can_trigger(trade_date: str) -> tuple[bool, str]:
 async def get_latest_report():
     conn = get_connection()
     try:
+        # issue_number：按报告日期序数作为总期号
         row = conn.execute(
-            "SELECT * FROM ai_reports ORDER BY trade_date DESC, id DESC LIMIT 1"
+            """SELECT r.*,
+                      (SELECT COUNT(*) FROM ai_reports WHERE trade_date <= r.trade_date) AS issue_number
+               FROM ai_reports r ORDER BY r.trade_date DESC, r.id DESC LIMIT 1"""
         ).fetchone()
         if not row:
             raise HTTPException(status_code=404, detail="暂无分析报告")

backend/routes/market_dashboard.py

@@ -165,6 +165,7 @@ async def _build_dashboard() -> dict:
             skyrocket_data,
             sector_flow_data,
             margin_data,
+            global_markets_data,
         ) = await asyncio.gather(
             fuyao_client.hot_stock_list("day"),
             fuyao_client.dragon_tiger_list("all"),
@@ -173,6 +174,7 @@ async def _build_dashboard() -> dict:
             fuyao_client.skyrocket_list("day"),
             market_extra.fetch_sector_fund_flow(),
             market_extra.fetch_margin_summary(),
+            market_extra.fetch_global_markets(),
             return_exceptions=True,
         )
     except Exception:
@@ -183,6 +185,7 @@ async def _build_dashboard() -> dict:
         skyrocket_data = {}
         sector_flow_data = None
         margin_data = None
+        global_markets_data = None
 
     # ── 解析指数 ──
     indices = []
@@ -565,6 +568,7 @@ async def _build_dashboard() -> dict:
         "sectorStrength": sector_strength[:31],
         "conceptStrength": concept_strength[:10],
         "sectorFundFlow": sector_flow_data if isinstance(sector_flow_data, dict) else None,
+        "globalMarkets": global_markets_data if isinstance(global_markets_data, dict) else None,
         "events": events,
         "limitLadder": limit_ladder,
         "updateTime": datetime.now(BJT).strftime("%Y-%m-%d %H:%M:%S"),