feat: release v0.1.60

README.md

@@ -11,8 +11,8 @@
 [![Deploy: Docker](https://img.shields.io/badge/Deploy-Docker-2496ed.svg)](./Dockerfile)
 [![GitHub stars](https://img.shields.io/github/stars/shy3130/tickflow-stock-panel?style=social)](https://github.com/shy3130/tickflow-stock-panel/stargazers)
 
-基于 [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) 数据 · 🚀 **开箱即用**(单容器 / Free 模式)
-能力驱动,适配 Free → Expert 全档位订阅 · 🔌 **自由接入第三方扩展数据**(例如 Tushare、自有量化项目数据)
+基于 [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) 数据 · 🚀 **开箱即用**(单容器 / None 模式)
+能力驱动,适配 None → Expert 全档位订阅 · 🔌 **自由接入第三方扩展数据**(例如 Tushare、自有量化项目数据)
 
 **[核心功能](#-核心功能)** · **[快速开始](#-快速开始)** · **[配置](#️-配置)** · **[路线图](#-路线图)**
 
@@ -28,14 +28,14 @@
 ## 🎯 项目定位
 
 让任何**个人散户 / 量化爱好者**,**零运维**地拥有一套**与自己订阅档位严格匹配**的 A 股分析、选股、监控工作台。  
-基于 [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) Key **低成本**获取数据。**填写邀请码 `V3KDKGXPEA` 免费领取概念行业等扩展数据**。<br>
-**任意接入第三方数据**(Tushare 等),页面可视化自定义配置扩展数据表。
+基于 [TickFlow](https://tickflow.org/auth/register?ref=V3KDKGXPEA) Key **零成本**获取数据，并使用策略定制+监控+回测功能。
+**内置ths概念、ths行业数据**。可接入第三方自有个性化扩展数据（人气、资金流向等）。
 
 **项目所需配置**:
 
 | 配置项 | 说明 | 是否必填 |
 | :--- | :--- | :--- |
-| **TickFlow API Key** | 数据源凭证,留空启用 None 模式，获取免费key后开启free模式可定制策略+回测 | 可选 |
+| **TickFlow API Key** | 数据源凭证,留空启用 None 模式；免费注册 Key 后进入 Free 模式，可使用历史日K与自选股实时监控 | 可选 |
 | **AI 大模型 API Key** | 用于 AI 生成策略、个股分析、财务分析等,任意 OpenAI 兼容接口,留空关闭 | 可选 |
 
 <table>
@@ -169,7 +169,8 @@
 
 ### 🧰 数据与扩展
 
-- **多源数据**:TickFlow 日 K / 分钟 K / 指数 / 财务(利润 / 资产负债 / 现金流)/ 自选行情
+- **多源数据**:TickFlow 日 K / 分钟 K / 指数 / 财务(利润 / 资产负债 / 现金流)/ 实时行情
+- **实时行情分档**:None 仅历史日K(当日数据通常盘后 1-2 小时可用);Free 可监控自选页前 5 个标的(最低 6 秒刷新);Starter+ 使用全市场实时行情
 - **🔌 第三方数据接入(重点)** —— TickFlow 之外的数据也能用:
   - 支持 **Tushare** 等第三方数据源,通过 **HTTP 定时拉取**自动入库
   - 支持 **CSV / Excel 上传** · **JSON 写入**,自动 schema 发现与符号归一
@@ -196,7 +197,7 @@
 ### 方式 A:Dev 模式(二次开发,最推荐)
 
 ```bash
-cp .env.example .env       # 填 TICKFLOW_API_KEY,留空则启用 Free 试用
+cp .env.example .env       # 填 TICKFLOW_API_KEY,留空则启用 None 模式
 ```
 
 **一键启动**(推荐,自动检查\下载依赖 / 释放端口 / 同时起前后端,Ctrl-C 一并关闭):
@@ -211,7 +212,7 @@ cp .env.example .env       # 填 TICKFLOW_API_KEY,留空则启用 Free 试用
 ### 方式 B:Docker(最省心,可部署)
 
 ```bash
-cp .env.example .env       # 按需填写 Key(留空即 Free 模式,可直接体验)
+cp .env.example .env       # 按需填写 Key(留空即 None 模式,可直接体验历史日K)
 docker compose up --build
 # 打开 http://localhost:3018
 ```
@@ -269,9 +270,9 @@ pnpm dev                   # http://localhost:3011
 
 1. 打开面板 → **设置 → 凭据与能力** → 点 **重新检测**,确认 Tier Label
 2. 点 **立即跑盘后管道** —— 拉日 K + 计算 enriched 表
-   - **Free 用户**:只同步内置 DEMO_SYMBOLS(浦发 / 招商 / 茅台等 10 只)
+   - **None / Free 用户**:历史日K走 free-api 通道;当日数据通常盘后 1-2 小时可用
    - **Starter+**:同步全 A 或可获取的 instruments 列表
-3. **自选**页:添加跟踪标的;点代码进 **K 线**页看蜡烛图 + 买卖点
+3. **自选**页:添加跟踪标的;Free 档实时行情会自动监控自选页前 5 个标的,可用「移到顶部」调整优先级;点代码进 **K 线**页看蜡烛图 + 买卖点
 4. **选股**页:点任一内置策略卡片即时扫描;或用自定义信号组合条件
 5. **回测**页:选策略 / 信号 + 时间区间 → 跑回测 → 看净值 / 夏普 / 交易明细(SSE 实时进度)
 6. **监控中心**页:配置监控规则(策略/个股信号/价格/市场异动),盘中 SSE 实时弹窗通知 + 持久化触发记录;或在个股详情页点「加监控」快速添加
@@ -284,13 +285,15 @@ pnpm dev                   # http://localhost:3011
 
 ### 数据源:TickFlow
 
-TickFlow 提供订阅制 A 股数据。**留空 `TICKFLOW_API_KEY` 即启用 Free 模式,无需注册即可体验**。
+TickFlow 提供订阅制 A 股数据。**留空 `TICKFLOW_API_KEY` 即启用 None 模式,可通过 free-api 使用历史日K;当日数据通常需盘后 1-2 小时可用**。免费注册并填写 Key 后进入 Free 模式，可开启自选股实时监控。
 
 ```ini
-TICKFLOW_API_KEY=              # 留空 = Free 模式;填入 Key = 按订阅档位解锁
+TICKFLOW_API_KEY=              # 留空 = None 模式;填入 Key = 按订阅档位解锁
 ```
 
-> 完整能力矩阵见 [tickflow.org/pricing](https://tickflow.org/pricing/)。系统启动时会自动探测你的真实能力集,UI 显示「≈ Pro」等友好标签。
+> 完整能力矩阵见 [tickflow.org/pricing](https://tickflow.org/pricing/)。系统启动时会自动探测你的真实能力集,UI 显示「Free / Starter / Pro / Expert」等友好标签。高等档位包含较低档位的全部权益。
+>
+> 当前面板使用的实时能力:Free = 自选页前 5 个标的实时监控(最低 6 秒刷新);Starter+ = 全市场实时行情;Pro = 分钟K + 盘口;Expert = WebSocket + 财务数据。
 
 ### AI(可选):策略生成
 

backend/app/__init__.py

@@ -2,7 +2,7 @@
 
 import sys
 
-__version__ = "0.1.53"
+__version__ = "0.1.60"
 
 # Windows 默认 stdout/stderr 编码为 GBK(cp936),TickFlow SDK 内部输出含 emoji 的
 # 指数/标的名称(如 \U0001f193)时会抛 UnicodeEncodeError,导致请求失败。

backend/app/api/analysis.py

@@ -9,8 +9,6 @@ from typing import Literal
 from fastapi import APIRouter, HTTPException, Request
 from pydantic import BaseModel, Field
 
-from app.services.ext_data import ExtConfigStore
-
 router = APIRouter(prefix="/api/analysis-menus", tags=["analysis-menus"])
 
 
@@ -113,44 +111,13 @@ def _save(request: Request, menu: AnalysisMenu) -> AnalysisMenu:
 
 
 def _default_menus(request: Request) -> list[AnalysisMenu]:
-    ext_store = ExtConfigStore(_data_dir(request))
-    menus: list[AnalysisMenu] = []
-    for cfg in ext_store.load_all():
-        fields = cfg.fields
-        concept = next((f for f in fields if "概念" in f.name or "概念" in f.label or "concept" in f.name.lower()), None)
-        if concept:
-            detail_names = ["股票简称", "股票代码", concept.name, "人气排名", "资金流向", "PE", "PB"]
-            detail_columns = []
-            for name in detail_names:
-                f = next((x for x in fields if x.name == name), None)
-                if not f:
-                    continue
-                is_num = f.dtype in ("int", "float")
-                detail_columns.append(AnalysisColumn(
-                    field=f.name,
-                    label=f.label or f.name,
-                    type="number" if is_num else "string",
-                    sortable=is_num,
-                    precision=2 if f.dtype == "float" else None,
-                ))
-            menus.append(AnalysisMenu(
-                id="concept_analysis",
-                label="概念分析",
-                icon="tags",
-                data_source=cfg.id,
-                template="dimension_rank",
-                dimension_field=concept.name,
-                group_columns=[
-                    AnalysisColumn(field="__dimension", label="概念"),
-                    AnalysisColumn(field="__count", label="股票数", type="number", sortable=True),
-                ],
-                detail_columns=detail_columns,
-                default_sort=DefaultSort(field="人气排名", order="asc") if any(c.field == "人气排名" for c in detail_columns) else None,
-                order=100,
-                builtin=True,
-            ))
-            break
-    return menus
+    """自动生成的默认分析菜单。
+
+    历史上会扫描扩展数据配置,对含「概念」字段的表自动生成一个「概念分析」菜单。
+    现已关闭自动生成 —— 内置的概念分析页(/concept-analysis)已覆盖该场景,
+    自动菜单会造成导航重复。需要时用户可在「设置 → 扩展页面」手动创建。
+    """
+    return []
 
 
 @router.get("")

backend/app/api/data.py

@@ -38,6 +38,9 @@ _table_cache: dict[str, dict | None] = {
     "index_daily": None,
     "index_enriched": None,
     "index_instruments": None,
+    "etf_daily": None,
+    "etf_enriched": None,
+    "etf_instruments": None,
     "minute": None,
     "adj_factor": None,
     "instruments": None,
@@ -262,6 +265,85 @@ def _safe_aggregate_index_instruments(repo) -> dict | None:
     }
 
 
+def _safe_aggregate_etf_instruments(repo) -> dict | None:
+    """ETF instruments 统计 — 优先独立 instruments_etf，兼容旧 instruments_index。"""
+    queries = [
+        """SELECT count(*) AS rows,
+                  count(DISTINCT symbol) AS symbols,
+                  count_if(name IS NOT NULL AND name != '') AS named
+           FROM instruments_etf""",
+        """SELECT count(*) AS rows,
+                  count(DISTINCT symbol) AS symbols,
+                  count_if(name IS NOT NULL AND name != '') AS named
+           FROM instruments_index
+           WHERE asset_type = 'etf'""",
+    ]
+    for sql in queries:
+        try:
+            row = repo.execute_one(sql)
+        except Exception as e:  # noqa: BLE001
+            logger.debug("aggregate etf instruments fallback failed: %s", e)
+            continue
+        if row and row[0]:
+            return {
+                "rows": int(row[0]),
+                "symbols_covered": int(row[1] or 0),
+                "latest_as_of": None,
+                "named": int(row[2] or 0),
+            }
+    return None
+
+
+def _safe_aggregate_etf_enriched(repo) -> dict | None:
+    """ETF enriched 统计 — 独立 kline_etf_enriched。"""
+    fields = 0
+    try:
+        cols = repo.execute_all("DESCRIBE kline_etf_enriched")
+        fields = len(cols)
+    except Exception:  # noqa: BLE001
+        pass
+    stats = _safe_aggregate(repo, "kline_etf_enriched")
+    if not stats:
+        return None
+    return {**stats, "fields": fields}
+
+
+def _safe_aggregate_etf_daily(repo) -> dict | None:
+    """ETF 日K统计 — 优先独立 kline_etf_daily，兼容旧 index 存储。"""
+    queries = [
+        """SELECT count(*) AS rows,
+                  min(date) AS earliest,
+                  max(date) AS latest,
+                  count(DISTINCT symbol) AS symbols,
+                  count(DISTINCT date) AS trading_days
+           FROM kline_etf_daily""",
+        """SELECT count(*) AS rows,
+                  min(date) AS earliest,
+                  max(date) AS latest,
+                  count(DISTINCT symbol) AS symbols,
+                  count(DISTINCT date) AS trading_days
+           FROM kline_index_daily
+           WHERE symbol IN (
+               SELECT DISTINCT symbol FROM instruments_index WHERE asset_type = 'etf'
+           )""",
+    ]
+    for sql in queries:
+        try:
+            row = repo.execute_one(sql)
+        except Exception as e:  # noqa: BLE001
+            logger.debug("aggregate etf daily fallback failed: %s", e)
+            continue
+        if row and row[0]:
+            return {
+                "rows": int(row[0]),
+                "earliest_date": str(row[1]) if row[1] else None,
+                "latest_date": str(row[2]) if row[2] else None,
+                "symbols_covered": int(row[3] or 0),
+                "trading_days": int(row[4] or 0),
+            }
+    return None
+
+
 def _safe_aggregate_adj_factor(repo) -> dict | None:
     """adj_factor 视图统计,日期范围对齐日 K 覆盖区间。"""
     try:
@@ -405,6 +487,10 @@ def _compute_storage(data_dir: Path) -> dict:
         "index_daily": data_dir / "kline_index_daily",
         "index_enriched": data_dir / "kline_index_enriched",
         "index_instruments": data_dir / "instruments_index",
+        "etf_daily": data_dir / "kline_etf_daily",
+        "etf_enriched": data_dir / "kline_etf_enriched",
+        "etf_instruments": data_dir / "instruments_etf",
+        "etf_adj_factor": data_dir / "adj_factor_etf",
         "minute": data_dir / "kline_minute",
         "adj_factor": data_dir / "adj_factor",
         "instruments": data_dir / "instruments",
@@ -507,10 +593,13 @@ def status(request: Request) -> dict:
     return {
         "daily":       _get_table_stats("daily",       lambda: _safe_aggregate_daily(repo)),
         "enriched":    _get_table_stats("enriched",    lambda: _safe_aggregate_enriched(repo)),
-        "index_daily":       _get_table_stats("index_daily",       lambda: _safe_aggregate_index_daily(repo)),
-        "index_enriched":    _get_table_stats("index_enriched",    lambda: _safe_aggregate_index_enriched(repo)),
-        "index_instruments": _get_table_stats("index_instruments", lambda: _safe_aggregate_index_instruments(repo)),
-        "minute":      _get_table_stats("minute",      lambda: _safe_aggregate_minute(repo)),
+    "index_daily":       _get_table_stats("index_daily",       lambda: _safe_aggregate_index_daily(repo)),
+    "index_enriched":    _get_table_stats("index_enriched",    lambda: _safe_aggregate_index_enriched(repo)),
+    "index_instruments": _get_table_stats("index_instruments", lambda: _safe_aggregate_index_instruments(repo)),
+    "etf_daily":         _get_table_stats("etf_daily",         lambda: _safe_aggregate_etf_daily(repo)),
+    "etf_enriched":      _get_table_stats("etf_enriched",      lambda: _safe_aggregate_etf_enriched(repo)),
+    "etf_instruments":   _get_table_stats("etf_instruments",   lambda: _safe_aggregate_etf_instruments(repo)),
+    "minute":      _get_table_stats("minute",      lambda: _safe_aggregate_minute(repo)),
         "adj_factor":  _get_table_stats("adj_factor",  lambda: _safe_aggregate_adj_factor(repo)),
         "instruments": _get_table_stats("instruments", lambda: _safe_aggregate_instruments(repo)),
         "financials":  _get_table_stats("financials",  lambda: _safe_aggregate_financials(repo)),
@@ -537,8 +626,9 @@ def clear_data(request: Request):
     deleted = 0
 
     for sub in (
-        "kline_daily", "kline_daily_enriched", "kline_index_daily", "kline_index_enriched", "kline_minute",
-        "adj_factor", "instruments", "instruments_index", "pools", "financials",
+        "kline_daily", "kline_daily_enriched", "kline_index_daily", "kline_index_enriched",
+        "kline_etf_daily", "kline_etf_enriched", "kline_etf_minute", "kline_minute",
+        "adj_factor", "adj_factor_etf", "instruments", "instruments_index", "instruments_etf", "pools", "financials",
         "backtest_results", "screener_results", "ai_cache",
     ):
         d = data_dir / sub
@@ -596,10 +686,15 @@ def clear_data(request: Request):
         "kline_enriched": f"{d}/kline_daily_enriched/**/*.parquet",
         "kline_index_daily": f"{d}/kline_index_daily/**/*.parquet",
         "kline_index_enriched": f"{d}/kline_index_enriched/**/*.parquet",
+        "kline_etf_daily": f"{d}/kline_etf_daily/**/*.parquet",
+        "kline_etf_enriched": f"{d}/kline_etf_enriched/**/*.parquet",
+        "kline_etf_minute": f"{d}/kline_etf_minute/**/*.parquet",
         "kline_minute": f"{d}/kline_minute/**/*.parquet",
         "adj_factor": f"{d}/adj_factor/**/*.parquet",
+        "adj_factor_etf": f"{d}/adj_factor_etf/**/*.parquet",
         "instruments": f"{d}/instruments/**/*.parquet",
         "instruments_index": f"{d}/instruments_index/**/*.parquet",
+        "instruments_etf": f"{d}/instruments_etf/**/*.parquet",
     }.items():
         try:
             repo.db.execute(
@@ -638,6 +733,17 @@ _TABLE_FIELD_DESC: dict[str, dict[str, str]] = {
         "amount": "成交额",
     },
     "kline_index_enriched": ENRICHED_COLUMNS,
+    "kline_etf_daily": {
+        "symbol": "ETF代码",
+        "date": "交易日期",
+        "open": "开盘价",
+        "high": "最高价",
+        "low": "最低价",
+        "close": "收盘价",
+        "volume": "成交量",
+        "amount": "成交额",
+    },
+    "kline_etf_enriched": ENRICHED_COLUMNS,
     "kline_minute": {
         "symbol": "股票代码",
         "datetime": "分钟时间戳",
@@ -675,6 +781,13 @@ _TABLE_FIELD_DESC: dict[str, dict[str, str]] = {
         "code": "指数编码(纯数字)",
         "asset_type": "资产类型(index)",
     },
+    "instruments_etf": {
+        "symbol": "ETF代码",
+        "name": "ETF名称",
+        "code": "ETF编码(纯数字)",
+        "asset_type": "资产类型(etf)",
+        "source": "数据源",
+    },
 }
 
 # view 名 → DuckDB 视图名
@@ -684,6 +797,9 @@ _SCHEMA_VIEWS: dict[str, str] = {
     "index_daily": "kline_index_daily",
     "index_enriched": "kline_index_enriched",
     "index_instruments": "instruments_index",
+    "etf_daily": "kline_etf_daily",
+    "etf_enriched": "kline_etf_enriched",
+    "etf_instruments": "instruments_etf",
     "minute": "kline_minute",
     "adj_factor": "adj_factor",
     "instruments": "instruments",

backend/app/api/market_recap.py

@@ -0,0 +1,108 @@
+"""AI 大盘复盘 API — 流式复盘 + 报告持久化。
+
+路由前缀: /api/market-recap
+
+端点:
+  POST /analyze                AI 流式大盘复盘(NDJSON)
+  GET  /reports                历史复盘列表
+  POST /reports                保存一条复盘报告
+  DELETE /reports/{report_id}  删除一条复盘报告
+"""
+from __future__ import annotations
+
+import logging
+
+from fastapi import APIRouter, HTTPException, Request
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+
+from app.services import market_recap_reports
+from app.services.market_recap import recap_market_stream
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/market-recap", tags=["market-recap"])
+
+
+class AnalyzeRequest(BaseModel):
+    """AI 大盘复盘请求。"""
+    as_of: str | None = None  # 可选:复盘日期(YYYY-MM-DD),缺省取最新有数据日
+    focus: str = ""           # 可选:用户追加的复盘关注点
+
+
+@router.post("/analyze")
+async def analyze_market(request: Request, req: AnalyzeRequest):
+    """AI 大盘复盘 — NDJSON 流式返回。
+
+    装配市场总览(指数/涨跌/连板/封板/板块/情绪雷达)→ 复盘提示词 →
+    流式调用 LLM → 逐 chunk 以 NDJSON 推给前端(每行一个 JSON)。
+
+    协议:
+      {"type":"meta","as_of","emotion_score","emotion_label","summary"}
+      {"type":"delta","content":"..."}
+      {"type":"error","message":"..."}
+      {"type":"done"}
+    """
+    from datetime import date as date_cls
+
+    repo = request.app.state.repo
+    quote_service = getattr(request.app.state, "quote_service", None)
+    depth_service = getattr(request.app.state, "depth_service", None)
+
+    as_of = None
+    if req.as_of:
+        try:
+            as_of = date_cls.fromisoformat(req.as_of)
+        except ValueError:
+            raise HTTPException(400, f"as_of 格式应为 YYYY-MM-DD,收到: {req.as_of}")
+
+    async def stream_gen():
+        async for chunk in recap_market_stream(repo, quote_service, depth_service, as_of, req.focus):
+            yield chunk + "\n"
+
+    return StreamingResponse(
+        stream_gen(),
+        media_type="application/x-ndjson",
+        headers={"Cache-Control": "no-cache", "X-Accel-Buffering": "no"},
+    )
+
+
+# ================================================================
+# 报告 CRUD(历史复盘持久化)
+# ================================================================
+
+class SaveReportRequest(BaseModel):
+    """保存一条 AI 大盘复盘报告。"""
+    as_of: str
+    focus: str = ""
+    content: str
+    summary: str = ""
+    emotion_score: int | None = None
+    emotion_label: str = ""
+
+
+@router.get("/reports")
+def list_reports(request: Request):
+    """获取全部历史复盘(按时间降序,后端已裁剪到上限)。"""
+    return {"reports": market_recap_reports.list_reports()}
+
+
+@router.post("/reports")
+def save_report(request: Request, req: SaveReportRequest):
+    """保存一条复盘报告。"""
+    report = market_recap_reports.save_report({
+        "as_of": req.as_of,
+        "focus": req.focus,
+        "content": req.content,
+        "summary": req.summary,
+        "emotion_score": req.emotion_score,
+        "emotion_label": req.emotion_label,
+    })
+    return {"ok": True, "report": report}
+
+
+@router.delete("/reports/{report_id}")
+def delete_report(request: Request, report_id: str):
+    """删除一条复盘报告。"""
+    ok = market_recap_reports.delete_report(report_id)
+    return {"ok": ok}

backend/app/api/overview.py

@@ -343,216 +343,18 @@ def _pct_band_rows(values: list[float]) -> list[dict]:
 
 
 def _build_overview(request: Request, as_of: date | None = None) -> dict:
-    repo = request.app.state.repo
-    svc = ScreenerService(repo)
-    as_of = as_of or svc.latest_date()
-    status = _quote_status(request)
-    indices = _index_quotes(request, as_of)
+    """装配市场总览(委托给 services.market_overview_builder,保持行为一致)。
 
-    if not as_of:
-        return {
-            "as_of": None,
-            "quote_status": status,
-            "indices": indices,
-            "breadth": {"total": 0, "up": 0, "down": 0, "flat": 0, "up_pct": 0, "down_pct": 0},
-            "amount": {"total": 0, "avg": 0},
-            "boards": [],
-            "limit": {"limit_up": 0, "broken": 0, "failed": 0, "limit_down": 0, "max_boards": 0, "tiers": []},
-            "distribution": [],
-            "trend": {"above_ma5": 0, "above_ma20": 0, "above_ma60": 0, "above_ma5_pct": 0, "above_ma20_pct": 0, "above_ma60_pct": 0, "new_high": 0, "new_low": 0},
-            "activity": {"avg_turnover": 0, "high_turnover": 0, "high_vol_ratio": 0, "vol_ratio": 1},
-            "radar": [],
-            "emotion": {"score": 50, "label": "暂无"},
-            "top_gainers": [],
-            "top_losers": [],
-            "turnover_leaders": [],
-            "active_leaders": [],
-            "concept_rank": {"leading": [], "lagging": []},
-            "industry_rank": {"leading": [], "lagging": []},
-        }
-
-    df = svc._load_enriched_for_date(as_of)
-    if df.is_empty():
-        rows: list[dict] = []
-    else:
-        cols = [
-            "symbol", "name", "close", "change_pct", "amount", "turnover_rate", "volume",
-            "vol_ratio_5d", "consecutive_limit_ups", "signal_limit_up", "signal_broken_limit_up", "signal_limit_down",
-            "ma5", "ma20", "ma60", "high_60d", "low_60d", "signal_n_day_high", "signal_n_day_low",
-        ]
-        df = df.select([c for c in cols if c in df.columns])
-        rows = df.to_dicts()
-
-    # 过滤真停牌（volume=0 且 change_pct=0），保留有涨跌幅的浮点误差股以对齐同花顺口径
-    if rows and "volume" in rows[0]:
-        rows = [r for r in rows
-                if (_finite(r.get("volume")) or 0) > 0
-                or (_finite(r.get("change_pct")) or 0) != 0]
-
-    total = len(rows)
-    up = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) > 0)
-    down = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) < 0)
-    flat = max(0, total - up - down)
-    up_pct = up / total * 100 if total else 0
-    down_pct = down / total * 100 if total else 0
-
-    amounts = [_finite(r.get("amount")) or 0 for r in rows]
-    total_amount = sum(amounts)
-    avg_amount = total_amount / total if total else 0
-
-    pct_values = [_finite(r.get("change_pct")) for r in rows]
-    pct_values = [v for v in pct_values if v is not None]
-    avg_pct = sum(pct_values) / len(pct_values) if pct_values else 0
-    median_pct = sorted(pct_values)[len(pct_values) // 2] if pct_values else 0
-    strong_up = sum(1 for v in pct_values if v >= 0.03)
-    strong_down = sum(1 for v in pct_values if v <= -0.03)
-
-    limit_up = sum(1 for r in rows if bool(r.get("signal_limit_up")) or (_finite(r.get("consecutive_limit_ups")) or 0) > 0)
-    broken = sum(1 for r in rows if bool(r.get("signal_broken_limit_up")))
-    limit_down = sum(1 for r in rows if bool(r.get("signal_limit_down")))
-    max_boards = max([int(_finite(r.get("consecutive_limit_ups")) or 0) for r in rows], default=0)
-
-    # 五档 sealed 修正: 假涨停/假跌停不计入(需 Pro+ depth5.batch 能力)
-    depth_svc = getattr(request.app.state, "depth_service", None)
-    sealed_ready = False
-    fake_up = 0
-    fake_down = 0
-    if depth_svc:
-        up_map = depth_svc.get_sealed_map(as_of, is_down=False)
-        down_map = depth_svc.get_sealed_map(as_of, is_down=True)
-        sealed_ready = bool(up_map or down_map) and depth_svc.is_sealed_ready(as_of)
-        if up_map:
-            fake_up = sum(1 for v in up_map.values() if v.get("sealed") is False)
-        if down_map:
-            fake_down = sum(1 for v in down_map.values() if v.get("sealed") is False)
-    if sealed_ready:
-        limit_up = max(0, limit_up - fake_up)
-        limit_down = max(0, limit_down - fake_down)
-
-    seal_rate = limit_up / (limit_up + broken) * 100 if (limit_up + broken) > 0 else 0
-
-    def above_ma_count(ma_key: str) -> int:
-        return sum(1 for r in rows if (_finite(r.get("close")) is not None and _finite(r.get(ma_key)) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get(ma_key)) or 0)))
-
-    above_ma5 = above_ma_count("ma5")
-    above_ma20 = above_ma_count("ma20")
-    above_ma60 = above_ma_count("ma60")
-    new_high = sum(1 for r in rows if bool(r.get("signal_n_day_high")) or (_finite(r.get("close")) is not None and _finite(r.get("high_60d")) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get("high_60d")) or 0)))
-    new_low = sum(1 for r in rows if bool(r.get("signal_n_day_low")) or (_finite(r.get("close")) is not None and _finite(r.get("low_60d")) is not None and (_finite(r.get("close")) or 0) <= (_finite(r.get("low_60d")) or 0)))
-
-    turnovers = [_finite(r.get("turnover_rate")) for r in rows]
-    turnovers = [v for v in turnovers if v is not None]
-    avg_turnover = sum(turnovers) / len(turnovers) if turnovers else 0
-    high_turnover = sum(1 for v in turnovers if v >= 5)
-
-    boards_map: dict[str, dict] = {}
-    for r in rows:
-        b = _board(str(r.get("symbol") or ""))
-        item = boards_map.setdefault(b, {"board": b, "count": 0, "up": 0, "down": 0, "amount": 0.0})
-        item["count"] += 1
-        change = _finite(r.get("change_pct")) or 0
-        if change > 0:
-            item["up"] += 1
-        elif change < 0:
-            item["down"] += 1
-        item["amount"] += _finite(r.get("amount")) or 0
-    boards = sorted(boards_map.values(), key=lambda x: x["amount"], reverse=True)
-    for b in boards:
-        count = b["count"] or 1
-        b["up_pct"] = b["up"] / count * 100
-
-    tiers_map: dict[int, int] = {}
-    for r in rows:
-        n = int(_finite(r.get("consecutive_limit_ups")) or 0)
-        if n > 0:
-            tiers_map[n] = tiers_map.get(n, 0) + 1
-    tiers = [{"boards": k, "count": v} for k, v in sorted(tiers_map.items(), key=lambda item: -item[0])]
-
-    index_changes = [_finite(r.get("change_pct")) for r in indices]
-    index_changes = [v for v in index_changes if v is not None]
-    avg_index_pct = sum(index_changes) / len(index_changes) if index_changes else 0
-    vol_ratios = [_finite(r.get("vol_ratio_5d")) for r in rows]
-    vol_ratios = [v for v in vol_ratios if v is not None]
-    avg_vol_ratio = sum(vol_ratios) / len(vol_ratios) if vol_ratios else 1
-    high_vol_ratio = sum(1 for v in vol_ratios if v >= 1.5)
-
-    concept_rank = _dimension_rank(rows, request, "concept")
-    industry_rank = _dimension_rank(rows, request, "industry", level=2)
-
-    strong_diff_pct = (strong_up - strong_down) / total * 100 if total else 0
-    high_vol_pct = high_vol_ratio / total * 100 if total else 0
-    strong_down_pct = strong_down / total * 100 if total else 0
-    tier2_count = sum(t["count"] for t in tiers if t["boards"] >= 2)
-    mainline_items = [*concept_rank["leading"][:3], *industry_rank["leading"][:3]]
-    mainline_avg = max([_finite(item.get("avg_pct")) or 0 for item in mainline_items], default=0)
-    mainline_cover_pct = max([(_finite(item.get("count")) or 0) / total * 100 for item in mainline_items], default=0) if total else 0
-    mainline_score = round(_score(mainline_avg, -0.005, 0.03) * 0.65 + _score(mainline_cover_pct, 1, 12) * 0.35) if mainline_items else 50
-
-    radar = [
-        {"key": "index", "label": "指数", "value": _score(avg_index_pct, -2.5, 2.5)},
-        {"key": "profit", "label": "赚钱", "value": round(_score(up_pct, 20, 80) * 0.45 + _score(avg_pct, -0.02, 0.02) * 0.25 + _score(median_pct, -0.02, 0.02) * 0.20 + _score(strong_diff_pct, -8, 8) * 0.10)},
-        {"key": "money", "label": "量能", "value": round(_score(avg_vol_ratio, 0.6, 1.8) * 0.70 + _score(high_vol_pct, 2, 12) * 0.30)},
-        {"key": "speculation", "label": "投机", "value": round(_score(limit_up, 5, 90) * 0.25 + _score(seal_rate, 30, 85) * 0.35 + _score(max_boards, 1, 8) * 0.25 + _score(tier2_count, 0, 30) * 0.15)},
-        {"key": "resilience", "label": "抗跌", "value": 100 - round(_score(down_pct, 20, 80) * 0.55 + _score(strong_down_pct, 1, 12) * 0.45)},
-        {"key": "mainline", "label": "主线", "value": mainline_score},
-    ]
-    emotion_score = round(sum(r["value"] for r in radar) / len(radar)) if radar else 50
-    if emotion_score >= 70:
-        emotion_label = "强势"
-    elif emotion_score >= 55:
-        emotion_label = "偏暖"
-    elif emotion_score >= 45:
-        emotion_label = "震荡"
-    elif emotion_score >= 30:
-        emotion_label = "偏冷"
-    else:
-        emotion_label = "冰点"
-
-    return _json_safe({
-        "as_of": str(as_of),
-        "quote_status": status,
-        "indices": indices,
-        "breadth": {
-            "total": total,
-            "up": up,
-            "down": down,
-            "flat": flat,
-            "up_pct": up_pct,
-            "down_pct": down_pct,
-            "avg_pct": avg_pct,
-            "median_pct": median_pct,
-            "strong_up": strong_up,
-            "strong_down": strong_down,
-        },
-        "amount": {"total": total_amount, "avg": avg_amount},
-        "boards": boards,
-        "limit": {"limit_up": limit_up, "broken": broken, "failed": 0, "limit_down": limit_down, "max_boards": max_boards, "seal_rate": seal_rate, "tiers": tiers, "sealed_ready": sealed_ready, "fake_up": fake_up, "fake_down": fake_down},
-        "distribution": _pct_band_rows(pct_values),
-        "trend": {
-            "above_ma5": above_ma5,
-            "above_ma20": above_ma20,
-            "above_ma60": above_ma60,
-            "above_ma5_pct": above_ma5 / total * 100 if total else 0,
-            "above_ma20_pct": above_ma20 / total * 100 if total else 0,
-            "above_ma60_pct": above_ma60 / total * 100 if total else 0,
-            "new_high": new_high,
-            "new_low": new_low,
-        },
-        "activity": {
-            "avg_turnover": avg_turnover,
-            "high_turnover": high_turnover,
-            "high_vol_ratio": high_vol_ratio,
-            "vol_ratio": avg_vol_ratio,
-        },
-        "radar": radar,
-        "emotion": {"score": emotion_score, "label": emotion_label},
-        "top_gainers": _top_rows(rows, "change_pct", True),
-        "top_losers": _top_rows(rows, "change_pct", False),
-        "turnover_leaders": _top_rows(rows, "amount", True),
-        "active_leaders": _top_rows(rows, "turnover_rate", True),
-        "concept_rank": concept_rank,
-        "industry_rank": industry_rank,
-    })
+    逻辑已抽离至 build_market_overview,以解耦对 Request 的依赖,
+    使大盘复盘等无 Request 的调用方可复用同一装配逻辑。
+    """
+    from app.services.market_overview_builder import build_market_overview
+    return build_market_overview(
+        repo=request.app.state.repo,
+        quote_service=getattr(request.app.state, "quote_service", None),
+        depth_service=getattr(request.app.state, "depth_service", None),
+        as_of=as_of,
+    )
 
 
 @router.get("/market")

backend/app/api/settings.py

@@ -287,6 +287,16 @@ def get_preferences() -> dict:
         "indices_nav_pinned": preferences.get_indices_nav_pinned(),
         "minute_sync_enabled": preferences.get_minute_sync_enabled(),
         "minute_sync_days": preferences.get_minute_sync_days(),
+        "daily_data_provider": preferences.get_daily_data_provider(),
+        "adj_factor_provider": preferences.get_adj_factor_provider(),
+        "minute_data_provider": preferences.get_minute_data_provider(),
+        "realtime_data_provider": preferences.get_realtime_data_provider(),
+        "realtime_watchlist_symbols": preferences.get_realtime_watchlist_symbols(),
+        **preferences.get_realtime_quote_scope(),
+        "pipeline_pull_a_share": preferences.get_pipeline_pull_a_share(),
+        "pipeline_pull_etf": preferences.get_pipeline_pull_etf(),
+        "pipeline_pull_index": preferences.get_pipeline_pull_index(),
+        "pipeline_index_symbols": preferences.get_pipeline_index_symbols(),
         "pipeline_schedule": preferences.get_pipeline_schedule(),
         "instruments_schedule": preferences.get_instruments_schedule(),
         "enriched_batch_size": preferences.get_enriched_batch_size(),
@@ -384,11 +394,19 @@ class RealtimeQuotesPrefs(BaseModel):
     realtime_quotes_enabled: bool
 
 
+class RealtimeQuoteScopePrefs(BaseModel):
+    realtime_pull_stock: bool | None = None
+    realtime_pull_etf: bool | None = None
+    realtime_pull_index: bool | None = None
+    realtime_index_mode: str | None = None
+    realtime_index_symbols: list[str] | None = None
+
+
 @router.put("/preferences/realtime-quotes")
 def update_realtime_quotes(req: RealtimeQuotesPrefs, request: Request) -> dict:
     """保存全局实时行情开关。
 
-    none/free 档无实时行情权限:拒绝开启,persist 为关闭并返回 allowed=False,
+    none 档无实时行情权限；free 档开启自选股实时；starter+ 开启全市场实时。
     前端据此把开关置灰 / 回弹。
     """
     from app.services import preferences
@@ -401,6 +419,9 @@ def update_realtime_quotes(req: RealtimeQuotesPrefs, request: Request) -> dict:
         if qs:
             qs.disable()
         return {"realtime_quotes_enabled": False, "realtime_allowed": False}
+    if req.realtime_quotes_enabled and qs and qs.realtime_mode() == "watchlist" and not preferences.get_realtime_watchlist_symbols():
+        preferences.save({"realtime_quotes_enabled": False})
+        return {"realtime_quotes_enabled": False, "realtime_allowed": True, "mode": "watchlist", "error": "watchlist_empty"}
 
     preferences.save({"realtime_quotes_enabled": req.realtime_quotes_enabled})
     if qs:
@@ -412,6 +433,26 @@ def update_realtime_quotes(req: RealtimeQuotesPrefs, request: Request) -> dict:
     return {"realtime_quotes_enabled": req.realtime_quotes_enabled, "realtime_allowed": allowed}
 
 
+@router.put("/preferences/realtime-quote-scope")
+def update_realtime_quote_scope(req: RealtimeQuoteScopePrefs) -> dict:
+    """保存盘中实时行情范围；独立于盘后管道范围。"""
+    from app.services import preferences
+    cfg = req.model_dump(exclude_none=True)
+    return preferences.set_realtime_quote_scope(cfg)
+
+
+class RealtimeWatchlistPrefs(BaseModel):
+    symbols: list[str] = []
+
+
+@router.put("/preferences/realtime-watchlist")
+def update_realtime_watchlist(req: RealtimeWatchlistPrefs) -> dict:
+    """兼容旧入口；Free 实时标的由自选页前 5 个决定。"""
+    from app.services import preferences
+    symbols = preferences.set_realtime_watchlist_symbols(req.symbols)
+    return {"realtime_watchlist_symbols": symbols}
+
+
 class IndicesNavPinnedPrefs(BaseModel):
     indices_nav_pinned: bool
 
@@ -464,6 +505,34 @@ def update_realtime_monitor_config(req: RealtimeMonitorConfigIn, request: Reques
     return result
 
 
+class PipelinePullTypesIn(BaseModel):
+    """盘后管道拉取内容开关(A股 / ETF / 指数 独立控制)。"""
+    pipeline_pull_a_share: bool | None = None
+    pipeline_pull_etf: bool | None = None
+    pipeline_pull_index: bool | None = None
+
+
+@router.put("/preferences/pipeline-pull-types")
+def update_pipeline_pull_types(req: PipelinePullTypesIn) -> dict:
+    """更新盘后管道拉取内容开关。"""
+    from app.services import preferences
+    cfg = req.model_dump(exclude_none=True)
+    return preferences.set_pipeline_pull_types(cfg)
+
+
+class PipelineIndexSymbolsIn(BaseModel):
+    """指数自定义拉取代码(逗号/换行/空格分隔,空串表示全量)。"""
+    symbols: str = ""
+
+
+@router.put("/preferences/pipeline-index-symbols")
+def update_pipeline_index_symbols(req: PipelineIndexSymbolsIn) -> dict:
+    """保存指数自定义拉取代码。"""
+    from app.services import preferences
+    symbols = preferences.set_pipeline_index_symbols(req.symbols)
+    return {"pipeline_index_symbols": symbols}
+
+
 class QuoteIntervalIn(BaseModel):
     interval: float
 

backend/app/api/watchlist.py

@@ -27,28 +27,48 @@ class BatchAddRequest(BaseModel):
     note: str = ""
 
 
+def _with_names(rows: list[dict], request: Request) -> list[dict]:
+    if not rows:
+        return rows
+    try:
+        df_i = request.app.state.repo.get_instruments()
+        if df_i.is_empty() or "symbol" not in df_i.columns or "name" not in df_i.columns:
+            return rows
+        name_by_symbol = dict(df_i.select(["symbol", "name"]).iter_rows())
+        return [{**row, "name": name_by_symbol.get(row.get("symbol"))} for row in rows]
+    except Exception as e:  # noqa: BLE001
+        logger.debug("attach watchlist names failed: %s", e)
+        return rows
+
+
 @router.get("")
-def list_all():
-    return {"symbols": watchlist.list_symbols()}
+def list_all(request: Request):
+    return {"symbols": _with_names(watchlist.list_symbols(), request)}
 
 
 @router.post("")
-def add_one(req: AddRequest):
+def add_one(req: AddRequest, request: Request):
     rows = watchlist.add(req.symbol, req.note)
-    return {"symbols": rows}
+    return {"symbols": _with_names(rows, request)}
 
 
 @router.post("/batch")
-def add_batch(req: BatchAddRequest):
+def add_batch(req: BatchAddRequest, request: Request):
     for sym in req.symbols:
         watchlist.add(sym, req.note)
-    return {"symbols": watchlist.list_symbols(), "added": len(req.symbols)}
+    return {"symbols": _with_names(watchlist.list_symbols(), request), "added": len(req.symbols)}
+
+
+@router.post("/{symbol}/top")
+def move_one_to_top(symbol: str, request: Request):
+    rows = watchlist.move_to_top(symbol)
+    return {"symbols": _with_names(rows, request)}
 
 
 @router.delete("/{symbol}")
-def remove_one(symbol: str):
+def remove_one(symbol: str, request: Request):
     rows = watchlist.remove(symbol)
-    return {"symbols": rows}
+    return {"symbols": _with_names(rows, request)}
 
 
 @router.delete("")

backend/app/data_providers/__init__.py

@@ -0,0 +1,8 @@
+"""Market data provider abstraction.
+
+Providers normalize external data sources into the internal parquet schema.
+"""
+from app.data_providers.base import AssetType, MarketDataProvider, ProviderCapabilities
+from app.data_providers.registry import get_provider
+
+__all__ = ["AssetType", "MarketDataProvider", "ProviderCapabilities", "get_provider"]

backend/app/data_providers/base.py

@@ -0,0 +1,68 @@
+"""Provider contracts for external market data sources.
+
+The first implementation wraps TickFlow. Other providers (Tushare/AkShare/etc.)
+should return the same normalized Polars schemas so storage, indicators and
+backtests stay data-source agnostic.
+"""
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Literal, Protocol
+
+import polars as pl
+
+AssetType = Literal["stock", "index", "etf"]
+
+
+@dataclass(frozen=True)
+class ProviderCapabilities:
+    instruments: bool = False
+    daily: bool = False
+    adj_factor: bool = False
+    minute: bool = False
+    realtime: bool = False
+    financial: bool = False
+
+
+class MarketDataProvider(Protocol):
+    name: str
+    capabilities: ProviderCapabilities
+
+    def get_instruments(self, asset_type: AssetType) -> pl.DataFrame:
+        """Return normalized instruments: symbol/name/code/exchange/asset_type/source."""
+
+    def get_daily(
+        self,
+        symbols: list[str],
+        start_time: datetime | None,
+        end_time: datetime | None,
+        asset_type: AssetType,
+    ) -> pl.DataFrame:
+        """Return normalized daily K rows."""
+
+    def get_adj_factors(
+        self,
+        symbols: list[str],
+        start_time: datetime | None,
+        end_time: datetime | None,
+        asset_type: AssetType,
+    ) -> pl.DataFrame:
+        """Return normalized adjustment factors: symbol/trade_date/ex_factor."""
+
+    def get_minute(
+        self,
+        symbols: list[str],
+        start_time: datetime | None,
+        end_time: datetime | None,
+        asset_type: AssetType,
+        freq: str = "1m",
+    ) -> pl.DataFrame:
+        """Return normalized minute K rows. Implementations may return empty."""
+
+    def get_realtime(
+        self,
+        universes: list[str] | None = None,
+        symbols: list[str] | None = None,
+    ) -> pl.DataFrame:
+        """Return normalized realtime quotes. Implementations may return empty."""

backend/app/data_providers/normalizer.py

@@ -0,0 +1,99 @@
+"""Normalize provider responses into internal Polars schemas."""
+from __future__ import annotations
+
+import polars as pl
+
+from app.indicators.pipeline import filter_halt_days
+
+DAILY_COLS = ["symbol", "date", "open", "high", "low", "close", "volume", "amount"]
+ADJ_FACTOR_COLS = ["symbol", "trade_date", "ex_factor"]
+INSTRUMENT_COLS = ["symbol", "name", "code", "exchange", "asset_type", "source"]
+
+
+def to_polars(data) -> pl.DataFrame:
+    if data is None:
+        return pl.DataFrame()
+    if isinstance(data, pl.DataFrame):
+        return data
+    if isinstance(data, dict):
+        rows: list[dict] = []
+        for sym, values in data.items():
+            for item in values or []:
+                row = dict(item or {})
+                row.setdefault("symbol", sym)
+                rows.append(row)
+        return pl.DataFrame(rows) if rows else pl.DataFrame()
+    if hasattr(data, "reset_index"):
+        return pl.from_pandas(data.reset_index())
+    try:
+        return pl.DataFrame(data)
+    except Exception:  # noqa: BLE001
+        return pl.DataFrame()
+
+
+def normalize_daily(data, default_symbol: str | None = None, source: str = "tickflow") -> pl.DataFrame:  # noqa: ARG001
+    df = to_polars(data)
+    if df.is_empty():
+        return df
+    rename_map = {
+        "ts_code": "symbol",
+        "trade_date": "date",
+        "datetime": "date",
+        "vol": "volume",
+        "amt": "amount",
+    }
+    df = df.rename({k: v for k, v in rename_map.items() if k in df.columns})
+    if "symbol" not in df.columns and default_symbol:
+        df = df.with_columns(pl.lit(default_symbol).alias("symbol"))
+    if "date" in df.columns and df.schema["date"] != pl.Date:
+        df = df.with_columns(pl.col("date").cast(pl.Date, strict=False))
+    for col in ("open", "high", "low", "close", "volume", "amount"):
+        if col in df.columns:
+            df = df.with_columns(pl.col(col).cast(pl.Float64, strict=False))
+    df = filter_halt_days(df)
+    keep = [c for c in DAILY_COLS if c in df.columns]
+    return df.select(keep) if keep else pl.DataFrame()
+
+
+def normalize_adj_factors(data, source: str = "tickflow") -> pl.DataFrame:  # noqa: ARG001
+    df = to_polars(data)
+    if df.is_empty():
+        return df
+    rename_map = {
+        "timestamp": "trade_date",
+        "date": "trade_date",
+        "adj_factor": "ex_factor",
+    }
+    df = df.rename({k: v for k, v in rename_map.items() if k in df.columns})
+    if "trade_date" in df.columns:
+        if df.schema["trade_date"] in {pl.Int64, pl.Int32, pl.UInt64, pl.UInt32, pl.Float64, pl.Float32}:
+            df = df.with_columns(
+                pl.from_epoch(pl.col("trade_date").cast(pl.Int64), time_unit="ms").dt.date().alias("trade_date")
+            )
+        else:
+            df = df.with_columns(pl.col("trade_date").cast(pl.Date, strict=False))
+    if "ex_factor" in df.columns:
+        df = df.with_columns(pl.col("ex_factor").cast(pl.Float64, strict=False))
+    keep = [c for c in ADJ_FACTOR_COLS if c in df.columns]
+    return df.select(keep).drop_nulls() if len(keep) == len(ADJ_FACTOR_COLS) else pl.DataFrame()
+
+
+def normalize_instruments(rows: list[dict], asset_type: str, source: str = "tickflow") -> pl.DataFrame:
+    if not rows:
+        return pl.DataFrame()
+    out: list[dict] = []
+    for item in rows:
+        symbol = item.get("symbol")
+        if not symbol:
+            continue
+        out.append({
+            "symbol": str(symbol),
+            "name": item.get("name") or str(symbol),
+            "code": item.get("code") or str(symbol).split(".")[0],
+            "exchange": item.get("exchange"),
+            "asset_type": asset_type,
+            "source": source,
+        })
+    if not out:
+        return pl.DataFrame()
+    return pl.DataFrame(out).select(INSTRUMENT_COLS).unique(subset=["symbol"], keep="last").sort("symbol")

backend/app/data_providers/registry.py

@@ -0,0 +1,15 @@
+"""Provider registry."""
+from __future__ import annotations
+
+from app.data_providers.tickflow_provider import TickFlowProvider
+
+_PROVIDERS = {
+    "tickflow": TickFlowProvider,
+}
+
+
+def get_provider(name: str = "tickflow"):
+    provider_cls = _PROVIDERS.get((name or "tickflow").lower())
+    if provider_cls is None:
+        raise ValueError(f"Unsupported data provider: {name}")
+    return provider_cls()

backend/app/data_providers/schemas.py

@@ -0,0 +1,18 @@
+"""Internal provider schema column lists."""
+from __future__ import annotations
+
+DAILY_COLUMNS = [
+    "symbol", "asset_type", "source", "date", "open", "high", "low", "close",
+    "volume", "amount", "pre_close", "change_pct",
+]
+
+ADJ_FACTOR_COLUMNS = ["symbol", "asset_type", "source", "trade_date", "ex_factor"]
+
+INSTRUMENT_COLUMNS = [
+    "symbol", "name", "exchange", "asset_type", "source", "list_date", "status",
+]
+
+MINUTE_COLUMNS = [
+    "symbol", "asset_type", "source", "datetime", "open", "high", "low", "close",
+    "volume", "amount", "freq",
+]

backend/app/data_providers/tickflow_provider.py

@@ -0,0 +1,120 @@
+"""TickFlow provider implementation."""
+from __future__ import annotations
+
+import logging
+from datetime import datetime
+
+import polars as pl
+
+from app.data_providers.base import AssetType, ProviderCapabilities
+from app.data_providers.normalizer import normalize_adj_factors, normalize_daily, normalize_instruments
+from app.tickflow.client import get_client
+
+logger = logging.getLogger(__name__)
+
+_EXCHANGES = ["SH", "SZ", "BJ"]
+
+
+class TickFlowProvider:
+    name = "tickflow"
+    capabilities = ProviderCapabilities(
+        instruments=True,
+        daily=True,
+        adj_factor=True,
+        minute=True,
+        realtime=True,
+        financial=True,
+    )
+
+    def get_instruments(self, asset_type: AssetType) -> pl.DataFrame:
+        tf = get_client()
+        instrument_type = "stock" if asset_type == "stock" else asset_type
+        rows: list[dict] = []
+        for ex in _EXCHANGES:
+            try:
+                items = tf.exchanges.get_instruments(ex, instrument_type=instrument_type)
+                rows.extend([it for it in (items or []) if isinstance(it, dict)])
+            except Exception as e:  # noqa: BLE001
+                logger.warning("TickFlow instruments %s/%s failed: %s", ex, instrument_type, e)
+        return normalize_instruments(rows, asset_type=asset_type, source=self.name)
+
+    def get_daily(
+        self,
+        symbols: list[str],
+        start_time: datetime | None,
+        end_time: datetime | None,
+        asset_type: AssetType,  # noqa: ARG002
+    ) -> pl.DataFrame:
+        if not symbols:
+            return pl.DataFrame()
+        tf = get_client()
+        kwargs = {
+            "period": "1d",
+            "adjust": "none",
+            "count": 10000 if start_time and end_time else 250,
+            "as_dataframe": True,
+            "show_progress": False,
+        }
+        if start_time and end_time:
+            from app.services.kline_sync import _datetime_to_ms
+            kwargs["start_time"] = _datetime_to_ms(start_time)
+            kwargs["end_time"] = _datetime_to_ms(end_time)
+        raw = tf.klines.batch(symbols, **kwargs)
+        frames: list[pl.DataFrame] = []
+        if isinstance(raw, dict):
+            for sym, sub in raw.items():
+                normalized = normalize_daily(sub, default_symbol=sym, source=self.name)
+                if not normalized.is_empty():
+                    frames.append(normalized)
+        else:
+            normalized = normalize_daily(raw, source=self.name)
+            if not normalized.is_empty():
+                frames.append(normalized)
+        return pl.concat(frames, how="diagonal_relaxed") if frames else pl.DataFrame()
+
+    def get_adj_factors(
+        self,
+        symbols: list[str],
+        start_time: datetime | None,
+        end_time: datetime | None,
+        asset_type: AssetType,  # noqa: ARG002
+    ) -> pl.DataFrame:
+        if not symbols:
+            return pl.DataFrame()
+        tf = get_client()
+        kwargs = {"as_dataframe": False}
+        if start_time or end_time:
+            from app.services.kline_sync import _datetime_to_ms
+            if start_time:
+                kwargs["start_time"] = _datetime_to_ms(start_time)
+            if end_time:
+                kwargs["end_time"] = _datetime_to_ms(end_time)
+        raw = tf.klines.ex_factors(symbols, **kwargs)
+        return normalize_adj_factors(raw, source=self.name)
+
+    def get_minute(
+        self,
+        symbols: list[str],
+        start_time: datetime | None,
+        end_time: datetime | None,
+        asset_type: AssetType,  # noqa: ARG002
+        freq: str = "1m",  # noqa: ARG002
+    ) -> pl.DataFrame:
+        # Existing minute sync remains in app.services.kline_sync for now.
+        return pl.DataFrame()
+
+    def get_realtime(
+        self,
+        universes: list[str] | None = None,
+        symbols: list[str] | None = None,
+    ) -> pl.DataFrame:
+        tf = get_client()
+        if universes and symbols:
+            raise ValueError("TickFlow realtime accepts either universes or symbols, not both")
+        if universes:
+            resp = tf.quotes.get_by_universes(universes=universes)
+        elif symbols:
+            resp = tf.quotes.get(symbols=symbols)
+        else:
+            return pl.DataFrame()
+        return pl.DataFrame(resp or [])

backend/app/jobs/daily_pipeline.py

@@ -1,7 +1,7 @@
 """盘后管道 + 盘前维表同步。
 
 调度:
-  09:10 盘前 — 同步标的维表 instruments (全量覆盖)
+  09:10 盘前 — 同步个股维表 instruments (全量覆盖)
   15:30 盘后 — 日K同步 + 增量除权因子 + enriched 计算 + 刷新视图
 
 盘后同步策略:
@@ -20,7 +20,7 @@ from apscheduler.triggers.cron import CronTrigger
 
 from app.indicators.pipeline import run_pipeline
 from app.config import settings
-from app.services import index_sync, instrument_sync, kline_sync
+from app.services import index_sync, instrument_sync, kline_sync, preferences as _prefs
 from app.tickflow.capabilities import Cap, CapabilitySet
 from app.tickflow.pools import DEMO_SYMBOLS, get_pool
 from app.tickflow.repository import KlineRepository
@@ -69,7 +69,7 @@ def _resolve_universe(capset: CapabilitySet) -> list[str]:
 
 
 def run_instruments_sync(repo: KlineRepository) -> dict:
-    """盘前同步标的维表。"""
+    """盘前同步个股维表。"""
     rows = instrument_sync.sync_instruments(repo.store.data_dir)
     _refresh_instruments_view(repo)
     _invalidate("instruments")
@@ -89,12 +89,12 @@ def run_now(
     emit = on_progress or _noop
     skipped: list[str] = []
 
-    # Step 0: 先同步标的维表, 再解析标的池 — 确保标的池基于最新 instruments
-    emit("sync_instruments", 2, "同步标的维表…")
+    # Step 0: 先同步个股维表, 再解析标的池 — 确保标的池基于最新 instruments
+    emit("sync_instruments", 2, "同步个股维表…")
     inst_rows = instrument_sync.sync_instruments(repo.store.data_dir)
     if inst_rows > 0:
         _refresh_instruments_view(repo)
-    emit("sync_instruments", 8, f"标的维表同步完成,{inst_rows} 只标的")
+    emit("sync_instruments", 8, f"个股维表同步完成,{inst_rows} 只标的")
     _invalidate("instruments")
 
     emit("resolve_universe", 9, "解析标的池…")
@@ -111,7 +111,12 @@ def run_now(
     today_exists = latest_daily and latest_daily >= today
     new_daily_days = 0
 
-    if today_exists and capset.has(Cap.QUOTE_POOL):
+    # A 股日K拉取开关(默认开);关闭时跳过日K同步,保留已有数据
+    pull_a_share = _prefs.get_pipeline_pull_a_share()
+    if not pull_a_share:
+        emit("sync_daily", 45, "已跳过 A 股日K同步(拉取内容未勾选)")
+        logger.info("sync_daily: skipped (pipeline_pull_a_share=False)")
+    elif today_exists and capset.has(Cap.QUOTE_POOL):
         # 付费档:今天有数据(QuoteService 已落盘)→ 实时行情覆写,确保最新。
         # free/none 档无 quote.pool 能力,即便今天已有数据(如从 expert 降级),
         # 也降级到下方 batch 路径刷新,避免调用无权限的实时行情接口。
@@ -291,33 +296,98 @@ def run_now(
     _refresh_single_view(repo, "kline_enriched")
     _invalidate("enriched")
 
-    # Step 2.3: 指数同步 — 独立 kline_index_* 存储，不进入股票选股/策略链路。
+    # Step 2.3: 指数 / ETF 同步 — 物理分开存储；ETF 可复权，指数不复权。
     written_index_daily = 0
+    written_etf_daily = 0
     index_count = 0
-    if capset.has(Cap.KLINE_DAILY_BATCH):
-        emit("sync_index", 88, "同步指数列表与日K…")
+    etf_count = 0
+    etf_adj_symbols = 0
+    pull_index = _prefs.get_pipeline_pull_index()
+    pull_etf = _prefs.get_pipeline_pull_etf()
+
+    if capset.has(Cap.KLINE_DAILY_BATCH) and (pull_index or pull_etf):
+        _types = []
+        if pull_index:
+            _types.append("指数")
+        if pull_etf:
+            _types.append("ETF")
+        emit("sync_index", 88, f"同步{'+'.join(_types)}日K…")
         try:
-            index_count = index_sync.sync_index_instruments(repo)
-            index_dir = repo.store.data_dir / "kline_index_enriched"
-            index_dates = sorted(
-                d.name[5:] for d in index_dir.glob("date=*")
-                if d.is_dir() and d.name.startswith("date=")
-            ) if index_dir.exists() else []
-            index_start = _date.fromisoformat(index_dates[-1]) if index_dates else today - _td(days=365)
-            written_index_daily = index_sync.sync_and_persist_index_daily(
-                repo,
-                capset,
-                start_date=_dt.combine(index_start, _dt.min.time()),
-                end_date=_dt.combine(today, _dt.min.time()),
-            )
+            if pull_index:
+                index_count = index_sync.sync_index_instruments(repo, pull_index=True, pull_etf=False)
+                index_dir = repo.store.data_dir / "kline_index_enriched"
+                index_dates = sorted(
+                    d.name[5:] for d in index_dir.glob("date=*")
+                    if d.is_dir() and d.name.startswith("date=")
+                ) if index_dir.exists() else []
+                index_start = _date.fromisoformat(index_dates[-1]) if index_dates else today - _td(days=365)
+                written_index_daily = index_sync.sync_and_persist_index_daily(
+                    repo,
+                    capset,
+                    start_date=_dt.combine(index_start, _dt.min.time()),
+                    end_date=_dt.combine(today, _dt.min.time()),
+                )
+                _invalidate("index_instruments")
+                _invalidate("index_daily")
+                _invalidate("index_enriched")
+
+            if pull_etf:
+                etf_count = index_sync.sync_etf_instruments(repo)
+                etf_symbols: list[str] = []
+                etf_inst = repo.get_etf_instruments()
+                if not etf_inst.is_empty() and "symbol" in etf_inst.columns:
+                    etf_symbols = sorted(set(etf_inst["symbol"].to_list()))
+                if etf_symbols and capset.has(Cap.ADJ_FACTOR):
+                    try:
+                        from datetime import datetime, timedelta
+                        adj_end = datetime.now()
+                        adj_path = repo.store.data_dir / "adj_factor_etf" / "all.parquet"
+                        fallback_start = adj_end - timedelta(days=30)
+                        adj_start = fallback_start
+                        if adj_path.exists():
+                            max_date = pl.scan_parquet(adj_path).select(pl.col("trade_date").max()).collect().item()
+                            if max_date is not None:
+                                if isinstance(max_date, str):
+                                    adj_start = datetime.combine(_date.fromisoformat(max_date), datetime.min.time())
+                                elif isinstance(max_date, datetime):
+                                    adj_start = datetime.combine(max_date.date(), datetime.min.time())
+                                else:
+                                    adj_start = datetime.combine(max_date, datetime.min.time())
+                        _, affected_etfs = index_sync.sync_etf_adj_factor(
+                            etf_symbols,
+                            repo,
+                            capset,
+                            start_time=adj_start,
+                            end_time=adj_end,
+                        )
+                        etf_adj_symbols = len(affected_etfs)
+                    except Exception as e:  # noqa: BLE001
+                        logger.warning("ETF adj_factor skipped: %s", e)
+                etf_dir = repo.store.data_dir / "kline_etf_enriched"
+                etf_dates = sorted(
+                    d.name[5:] for d in etf_dir.glob("date=*")
+                    if d.is_dir() and d.name.startswith("date=")
+                ) if etf_dir.exists() else []
+                etf_start = _date.fromisoformat(etf_dates[-1]) if etf_dates else today - _td(days=365)
+                written_etf_daily = index_sync.sync_and_persist_etf_daily(
+                    repo,
+                    capset,
+                    start_date=_dt.combine(etf_start, _dt.min.time()),
+                    end_date=_dt.combine(today, _dt.min.time()),
+                )
+                _invalidate("etf_instruments")
+                _invalidate("etf_daily")
+
             repo.refresh_index_views()
-            _invalidate("index_instruments")
-            _invalidate("index_daily")
-            _invalidate("index_enriched")
-            emit("sync_index", 89, f"指数完成,{index_count} 只指数,{written_index_daily} 行日K")
+            emit(
+                "sync_index",
+                89,
+                f"同步完成,指数 {index_count} 只/{written_index_daily} 行, ETF {etf_count} 只/{written_etf_daily} 行"
+                + (f", ETF复权 {etf_adj_symbols} 只" if etf_adj_symbols else ""),
+            )
         except Exception as e:  # noqa: BLE001
-            logger.warning("sync_index failed: %s", e)
-            emit("sync_index", 89, f"指数同步失败:{e}")
+            logger.warning("sync_index/etf failed: %s", e)
+            emit("sync_index", 89, f"指数/ETF同步失败:{e}")
     else:
         skipped.append("sync_index")
 
@@ -364,6 +434,9 @@ def run_now(
         "enriched_days": written_enriched,
         "index_count": index_count,
         "index_daily_rows": written_index_daily,
+        "etf_count": etf_count,
+        "etf_daily_rows": written_etf_daily,
+        "etf_adj_factor_symbols": etf_adj_symbols,
         "minute_rows": written_minute,
         "skipped_stages": skipped,
     }
@@ -377,10 +450,15 @@ def _refresh_views(repo: KlineRepository) -> None:
         "kline_enriched": f"{d}/kline_daily_enriched/**/*.parquet",
         "kline_index_daily": f"{d}/kline_index_daily/**/*.parquet",
         "kline_index_enriched": f"{d}/kline_index_enriched/**/*.parquet",
+        "kline_etf_daily": f"{d}/kline_etf_daily/**/*.parquet",
+        "kline_etf_enriched": f"{d}/kline_etf_enriched/**/*.parquet",
+        "kline_etf_minute": f"{d}/kline_etf_minute/**/*.parquet",
         "kline_minute": f"{d}/kline_minute/**/*.parquet",
         "adj_factor": f"{d}/adj_factor/**/*.parquet",
+        "adj_factor_etf": f"{d}/adj_factor_etf/**/*.parquet",
         "instruments": f"{d}/instruments/**/*.parquet",
         "instruments_index": f"{d}/instruments_index/**/*.parquet",
+        "instruments_etf": f"{d}/instruments_etf/**/*.parquet",
     }
     for name, path in views.items():
         try:
@@ -390,6 +468,7 @@ def _refresh_views(repo: KlineRepository) -> None:
             )
         except Exception as e:  # noqa: BLE001
             logger.warning("refresh view %s failed: %s", name, e)
+    repo.store._register_unified_views()
 
 
 def _refresh_single_view(repo: KlineRepository, name: str) -> None:
@@ -400,10 +479,15 @@ def _refresh_single_view(repo: KlineRepository, name: str) -> None:
         "kline_enriched": f"{d}/kline_daily_enriched/**/*.parquet",
         "kline_index_daily": f"{d}/kline_index_daily/**/*.parquet",
         "kline_index_enriched": f"{d}/kline_index_enriched/**/*.parquet",
+        "kline_etf_daily": f"{d}/kline_etf_daily/**/*.parquet",
+        "kline_etf_enriched": f"{d}/kline_etf_enriched/**/*.parquet",
+        "kline_etf_minute": f"{d}/kline_etf_minute/**/*.parquet",
         "kline_minute": f"{d}/kline_minute/**/*.parquet",
         "adj_factor": f"{d}/adj_factor/**/*.parquet",
+        "adj_factor_etf": f"{d}/adj_factor_etf/**/*.parquet",
         "instruments": f"{d}/instruments/**/*.parquet",
         "instruments_index": f"{d}/instruments_index/**/*.parquet",
+        "instruments_etf": f"{d}/instruments_etf/**/*.parquet",
     }
     path = paths.get(name)
     if not path:
@@ -457,7 +541,7 @@ def _run_tracked(fn, job_label: str) -> None:
 def start_scheduler(repo: KlineRepository, capset: CapabilitySet) -> AsyncIOScheduler:
     """启动调度器。
 
-    工作日 09:10 — 同步标的维表
+    工作日 09:10 — 同步个股维表
     工作日 HH:MM — 盘后管道（时间由用户偏好决定，默认 15:30）
     """
     from app.services import preferences
@@ -469,9 +553,9 @@ def start_scheduler(repo: KlineRepository, capset: CapabilitySet) -> AsyncIOSche
     # 盘前: 同步 instruments（时间由偏好决定）
     def _instruments_task(on_progress=None):
         emit = on_progress or _noop
-        emit("sync_instruments", 0, "同步标的维表…")
+        emit("sync_instruments", 0, "同步个股维表…")
         result = run_instruments_sync(repo)
-        emit("done", 100, f"标的维表同步完成,{result.get('instruments_rows', 0)} 只标的")
+        emit("done", 100, f"个股维表同步完成,{result.get('instruments_rows', 0)} 只标的")
         return result
 
     scheduler.add_job(

backend/app/main.py

@@ -11,7 +11,7 @@ from fastapi.responses import FileResponse
 from fastapi.staticfiles import StaticFiles
 
 from app import __version__
-from app.api import analysis, backtest, data, ext_data, financials, indices, intraday, kline, monitor_rules, alerts, overview, pipeline, screener, settings as settings_api, signals, stock_analysis, strategy, watchlist
+from app.api import analysis, backtest, data, ext_data, financials, indices, intraday, kline, market_recap, monitor_rules, alerts, overview, pipeline, screener, settings as settings_api, signals, stock_analysis, strategy, watchlist
 from app.api.routes import router as core_router
 from app.config import settings
 from app.jobs import daily_pipeline
@@ -193,6 +193,7 @@ app.include_router(data.router)
 app.include_router(ext_data.router)
 app.include_router(financials.router)
 app.include_router(stock_analysis.router)
+app.include_router(market_recap.router)
 app.include_router(settings_api.router)
 app.include_router(strategy.router)
 app.include_router(signals.router)

backend/app/services/index_sync.py

@@ -1,4 +1,9 @@
-"""指数数据同步服务。"""
+"""指数 / ETF 数据同步服务。
+
+标的列表优先用免费的 exchanges.get_instruments(type=index/etf) 拉取
+(None/Free 档均可用,无需 quote.pool 权限);付费档可额外用
+quotes.get_by_universes 作为补充来源。日K统一走 klines.batch。
+"""
 from __future__ import annotations
 
 import logging
@@ -15,9 +20,15 @@ from app.tickflow.repository import KlineRepository
 
 logger = logging.getLogger(__name__)
 
+# exchanges.get_instruments 查询的交易所(沪深京)
+_EXCHANGES = ["SH", "SZ", "BJ"]
+
 
 def _quotes_to_index_instruments(resp) -> pl.DataFrame:
-    """将 TickFlow quotes 响应规范为指数 instruments。"""
+    """将 TickFlow quotes 响应(get_by_universes)规范为指数 instruments。
+
+    付费档(Starter+)的补充来源,免费档用不到。
+    """
     if resp is None:
         return pl.DataFrame()
 
@@ -61,33 +72,119 @@ def _quotes_to_index_instruments(resp) -> pl.DataFrame:
     return result.unique(subset=["symbol"], keep="last").sort("symbol")
 
 
-def sync_index_instruments(repo: KlineRepository) -> int:
-    """同步 CN_Index 指数标的维表，返回指数数量。"""
+def _fetch_instruments_by_type(instrument_type: str, asset_type_label: str) -> pl.DataFrame:
+    """用免费的 exchanges.get_instruments 拉取指定类型的标的列表。
+
+    None/Free 档均可使用(标的信息查询免费开放)。
+    instrument_type: 'index' / 'etf'
+    asset_type_label: 写入 instruments 表的 asset_type 标记('index' / 'etf')
+    """
     tf = get_client()
-    resp = None
-    errors: list[str] = []
-    for kwargs in (
-        {"universes": ["CN_Index"]},
-        {"universes": ["CN_Index"], "as_dataframe": False},
-    ):
+    rows: list[dict] = []
+    for ex in _EXCHANGES:
         try:
-            resp = tf.quotes.get_by_universes(**kwargs)
-            if resp is not None and len(resp) > 0:
-                break
+            items = tf.exchanges.get_instruments(ex, instrument_type=instrument_type)
+            for it in items or []:
+                item = it if isinstance(it, dict) else {}
+                symbol = item.get("symbol")
+                if not symbol:
+                    continue
+                rows.append({
+                    "symbol": str(symbol),
+                    "name": item.get("name") or str(symbol),
+                })
         except Exception as e:  # noqa: BLE001
-            errors.append(str(e))
-            resp = None
+            logger.warning("get_instruments(%s, type=%s) failed: %s", ex, instrument_type, e)
 
-    if resp is None or len(resp) == 0:
-        logger.warning("CN_Index universe returned empty: %s", "; ".join(errors))
-        return 0
+    if not rows:
+        return pl.DataFrame()
 
-    instruments = _quotes_to_index_instruments(resp)
-    if instruments.is_empty():
+    return (
+        pl.DataFrame(rows)
+        .with_columns([
+            pl.col("symbol").str.split(".").list.first().alias("code"),
+            pl.lit(asset_type_label).alias("asset_type"),
+        ])
+        .unique(subset=["symbol"], keep="last")
+        .sort("symbol")
+    )
+
+
+def sync_index_instruments(
+    repo: KlineRepository,
+    pull_index: bool = True,
+    pull_etf: bool = True,
+) -> int:
+    """同步指数 / ETF 标的维表,返回标的总数。
+
+    新版物理分开保存: 指数写 instruments_index, ETF 写 instruments_etf。
+    读取层仍兼容旧版 instruments_index 中 asset_type='etf' 的历史数据。
+    """
+    index_parts: list[pl.DataFrame] = []
+    etf_parts: list[pl.DataFrame] = []
+
+    # 1) 免费通道:按开关分别拉 index / etf
+    if pull_index:
+        index_df = _fetch_instruments_by_type("index", "index")
+        if not index_df.is_empty():
+            index_parts.append(index_df)
+    if pull_etf:
+        etf_df = _fetch_instruments_by_type("etf", "etf")
+        if not etf_df.is_empty():
+            etf_parts.append(etf_df)
+
+    # 2) 付费补充:Starter+ 用 get_by_universes 补指数(仅当开启指数拉取)
+    if pull_index:
+        capset = None
+        try:
+            from app.tickflow import policy
+            capset = policy.detect_capabilities(force=False)
+        except Exception:  # noqa: BLE001
+            pass
+        if capset is not None and capset.has(Cap.QUOTE_POOL):
+            tf = get_client()
+            for kwargs in (
+                {"universes": ["CN_Index"]},
+                {"universes": ["CN_Index"], "as_dataframe": False},
+            ):
+                try:
+                    resp = tf.quotes.get_by_universes(**kwargs)
+                    if resp is not None and len(resp) > 0:
+                        sup = _quotes_to_index_instruments(resp)
+                        if not sup.is_empty():
+                            index_parts.append(sup)
+                        break
+                except Exception as e:  # noqa: BLE001
+                    logger.debug("CN_Index universe supplement failed: %s", e)
+
+    total = 0
+    if index_parts:
+        index_inst = pl.concat(index_parts, how="diagonal_relaxed").unique(subset=["symbol"], keep="last").sort("symbol")
+        if not index_inst.is_empty():
+            repo.save_index_instruments(index_inst)
+            total += index_inst.height
+    if etf_parts:
+        etf_inst = pl.concat(etf_parts, how="diagonal_relaxed").unique(subset=["symbol"], keep="last").sort("symbol")
+        if not etf_inst.is_empty():
+            repo.save_etf_instruments(etf_inst)
+            total += etf_inst.height
+
+    if total == 0:
+        logger.warning("指数/ETF 标的列表为空(pull_index=%s, pull_etf=%s)", pull_index, pull_etf)
         return 0
-    repo.save_index_instruments(instruments)
     repo.refresh_index_views()
-    return instruments.height
+    logger.info("指数/ETF 标的同步完成: %d 只", total)
+    return total
+
+
+def sync_etf_instruments(repo: KlineRepository) -> int:
+    """单独同步 ETF 标的维表(返回 ETF 数量)。"""
+    etf_df = _fetch_instruments_by_type("etf", "etf")
+    if etf_df.is_empty():
+        return 0
+    repo.save_etf_instruments(etf_df)
+    repo.refresh_index_views()
+    return etf_df.height
 
 
 def sync_and_persist_index_daily(
@@ -96,19 +193,30 @@ def sync_and_persist_index_daily(
     count: int | None = None,
     start_date: datetime | None = None,
     end_date: datetime | None = None,
+    symbols_override: list[str] | None = None,
 ) -> int:
-    """同步指数日K到独立 parquet，并计算指数 enriched。"""
+    """同步指数/ETF 日K到独立 parquet,并计算 enriched。
+
+    symbols_override 非空时,只拉这些代码(跳过 instruments 表),用于自定义范围。
+    否则取 index_instruments 表全量(指数+ETF 合并存储)。
+    """
     if not capset.has(Cap.KLINE_DAILY_BATCH):
         return 0
 
-    instruments = repo.get_index_instruments()
-    if instruments.is_empty():
-        sync_index_instruments(repo)
+    if symbols_override:
+        symbols = sorted(set(s for s in symbols_override if s))
+        if not symbols:
+            return 0
+    else:
         instruments = repo.get_index_instruments()
-    if instruments.is_empty() or "symbol" not in instruments.columns:
-        return 0
-
-    symbols = sorted(set(instruments["symbol"].to_list()))
+        if instruments.is_empty():
+            sync_index_instruments(repo, pull_index=True, pull_etf=False)
+            instruments = repo.get_index_instruments()
+        if not instruments.is_empty() and "asset_type" in instruments.columns:
+            instruments = instruments.filter(pl.col("asset_type") != "etf")
+        if instruments.is_empty() or "symbol" not in instruments.columns:
+            return 0
+        symbols = sorted(set(instruments["symbol"].to_list()))
     lim = capset.limits(Cap.KLINE_DAILY_BATCH)
     batch_size = preferences.get_index_daily_batch_size()
     if lim and lim.batch:
@@ -139,7 +247,103 @@ def sync_and_persist_index_daily(
         enriched = compute_enriched(raw, factors=None, instruments=None)
         repo.append_index_enriched(enriched)
         total_rows += raw.height
-        logger.info("index daily synced: %d/%d chunks, +%d rows", i + 1, len(chunks), raw.height)
+        logger.info("index/etf daily synced: %d/%d chunks, +%d rows", i + 1, len(chunks), raw.height)
+        del raw, enriched
+        gc.collect()
+    repo.refresh_index_views()
+    return total_rows
+
+
+def _load_etf_factors(repo: KlineRepository) -> pl.DataFrame:
+    factor_path = repo.store.data_dir / "adj_factor_etf" / "all.parquet"
+    if not factor_path.exists():
+        return pl.DataFrame()
+    try:
+        return pl.read_parquet(factor_path)
+    except Exception as e:  # noqa: BLE001
+        logger.warning("ETF 复权因子读取失败: %s", e)
+        return pl.DataFrame()
+
+
+def sync_etf_adj_factor(
+    symbols: list[str],
+    repo: KlineRepository,
+    capset: CapabilitySet,
+    start_time: datetime | None = None,
+    end_time: datetime | None = None,
+    on_chunk_done=None,
+) -> tuple[int, list[str]]:
+    """同步 ETF 复权因子；失败由调用方降级为 warning。"""
+    return kline_sync.sync_adj_factor(
+        symbols,
+        repo,
+        capset,
+        start_time=start_time,
+        end_time=end_time,
+        on_chunk_done=on_chunk_done,
+        asset_type="etf",
+    )
+
+
+def sync_and_persist_etf_daily(
+    repo: KlineRepository,
+    capset: CapabilitySet,
+    count: int | None = None,
+    start_date: datetime | None = None,
+    end_date: datetime | None = None,
+    symbols_override: list[str] | None = None,
+) -> int:
+    """同步 ETF 日K到独立 kline_etf_* parquet,并计算 ETF enriched。"""
+    if not capset.has(Cap.KLINE_DAILY_BATCH):
+        return 0
+
+    if symbols_override:
+        symbols = sorted(set(s for s in symbols_override if s))
+    else:
+        instruments = repo.get_etf_instruments()
+        if instruments.is_empty():
+            sync_etf_instruments(repo)
+            instruments = repo.get_etf_instruments()
+        if instruments.is_empty() or "symbol" not in instruments.columns:
+            return 0
+        symbols = sorted(set(instruments["symbol"].to_list()))
+    if not symbols:
+        return 0
+
+    lim = capset.limits(Cap.KLINE_DAILY_BATCH)
+    batch_size = preferences.get_index_daily_batch_size()
+    if lim and lim.batch:
+        batch_size = min(batch_size, lim.batch)
+    rpm = lim.rpm if lim else None
+
+    end_time = end_date or datetime.now()
+    start_time = start_date or (end_time - timedelta(days=365))
+
+    total_rows = 0
+    interval = (60.0 / rpm) if rpm else 0
+    chunks = [symbols[i:i + batch_size] for i in range(0, len(symbols), batch_size)]
+    factors = _load_etf_factors(repo)
+    for i, chunk in enumerate(chunks):
+        if i > 0 and interval > 0 and len(chunks) > rpm:
+            import time
+            time.sleep(interval)
+        raw = kline_sync.sync_daily_batch(
+            chunk,
+            count=count,
+            batch_size=None,
+            start_time=start_time,
+            end_time=end_time,
+        )
+        if raw.is_empty():
+            continue
+
+        repo.append_etf_daily(raw)
+        batch_factors = factors.filter(pl.col("symbol").is_in(chunk)) if not factors.is_empty() else factors
+        # ETF 使用复权和通用技术指标；不传 instruments，避免套用 A股涨跌停/连板逻辑。
+        enriched = compute_enriched(raw, factors=batch_factors, instruments=None)
+        repo.append_etf_enriched(enriched)
+        total_rows += raw.height
+        logger.info("etf daily synced: %d/%d chunks, +%d rows", i + 1, len(chunks), raw.height)
         del raw, enriched
         gc.collect()
     repo.refresh_index_views()

backend/app/services/kline_sync.py

@@ -223,11 +223,47 @@ def sync_daily_by_quotes(repo: KlineRepository) -> int:
     return daily_df.height
 
 
+def _normalize_adj_factor(raw) -> pl.DataFrame:
+    """Normalize SDK ex_factors response to symbol/trade_date/ex_factor."""
+    if raw is None or len(raw) == 0:
+        return pl.DataFrame()
+    if isinstance(raw, dict):
+        rows: list[dict] = []
+        for sym, values in raw.items():
+            for item in values or []:
+                row = dict(item or {})
+                row.setdefault("symbol", sym)
+                rows.append(row)
+        df = pl.DataFrame(rows) if rows else pl.DataFrame()
+    elif isinstance(raw, pl.DataFrame):
+        df = raw
+    else:
+        df = pl.from_pandas(raw.reset_index() if hasattr(raw, "reset_index") else raw)
+    if df.is_empty():
+        return df
+    rename_map = {"timestamp": "trade_date", "date": "trade_date", "adj_factor": "ex_factor"}
+    df = df.rename({k: v for k, v in rename_map.items() if k in df.columns})
+    if "trade_date" in df.columns:
+        if df.schema["trade_date"] in {pl.Int64, pl.Int32, pl.UInt64, pl.UInt32, pl.Float64, pl.Float32}:
+            df = df.with_columns(
+                pl.from_epoch(pl.col("trade_date").cast(pl.Int64), time_unit="ms").dt.date().alias("trade_date")
+            )
+        else:
+            df = df.with_columns(pl.col("trade_date").cast(pl.Date, strict=False))
+    if "ex_factor" in df.columns:
+        df = df.with_columns(pl.col("ex_factor").cast(pl.Float64, strict=False))
+    cols = [c for c in ["symbol", "trade_date", "ex_factor"] if c in df.columns]
+    if len(cols) < 3:
+        return pl.DataFrame()
+    return df.select(cols).drop_nulls()
+
+
 def sync_adj_factor(symbols: list[str], repo: KlineRepository,
                     capset: CapabilitySet,
                     start_time: datetime | None = None,
                     end_time: datetime | None = None,
-                    on_chunk_done: Callable[[int, int], None] | None = None) -> tuple[int, list[str]]:
+                    on_chunk_done: Callable[[int, int], None] | None = None,
+                    asset_type: str = "stock") -> tuple[int, list[str]]:
     """同步除权因子(Starter+)。SDK 接口:`tf.klines.ex_factors(symbols=...)`。
 
     支持增量: 传 start_time/end_time 只拉取该时间范围内的新除权事件。
@@ -257,10 +293,9 @@ def sync_adj_factor(symbols: list[str], repo: KlineRepository,
             time.sleep(interval)
         try:
             raw = tf.klines.ex_factors(chunk, **sdk_kwargs)
-            if raw is not None and len(raw) > 0:
-                all_dfs.append(pl.from_pandas(
-                    raw.reset_index() if hasattr(raw, "reset_index") else raw
-                ))
+            normalized = _normalize_adj_factor(raw)
+            if not normalized.is_empty():
+                all_dfs.append(normalized)
             logger.debug("adj_factor chunk %d/%d: %d symbols", i + 1, len(chunks), len(chunk))
         except Exception as e:  # noqa: BLE001
             logger.warning("adj_factor chunk %d failed: %s", i + 1, e)
@@ -276,7 +311,8 @@ def sync_adj_factor(symbols: list[str], repo: KlineRepository,
     # 提取受影响的 symbol 列表(合并前)
     affected = new_data["symbol"].unique().to_list()
 
-    out = repo.store.data_dir / "adj_factor" / "all.parquet"
+    factor_dir = "adj_factor_etf" if asset_type == "etf" else "adj_factor"
+    out = repo.store.data_dir / factor_dir / "all.parquet"
     out.parent.mkdir(parents=True, exist_ok=True)
 
     if out.exists():

backend/app/services/market_overview_builder.py

@@ -0,0 +1,576 @@
+"""市场总览数据装配(与 HTTP Request 解耦)。
+
+本模块由 `app.api.overview._build_overview` 抽离而来,目的是让「大盘复盘」
+等无 Request 的调用方(定时任务、复盘服务)也能复用同一套聚合逻辑。
+
+行为与原 `_build_overview` 完全一致,仅把对 `request.app.state.{repo,
+quote_service,depth_service}` 的依赖改为显式参数。
+
+公共入口:
+    build_market_overview(repo, quote_service, depth_service, as_of)
+"""
+from __future__ import annotations
+
+import math
+import re
+from datetime import date
+from typing import Any
+
+import polars as pl
+
+from app.services.ext_data import ExtConfig, ExtConfigStore
+from app.services.screener import ScreenerService
+
+# ================================================================
+# 常量(与 overview.py 保持同步;复盘复盘仅 A 股核心指数)
+# ================================================================
+
+CORE_INDEX_NAMES = {
+    "000001.SH": "上证指数",
+    "399001.SZ": "深证成指",
+    "399006.SZ": "创业板指",
+    "000680.SH": "科创综指",
+}
+CORE_INDEX_SYMBOLS = tuple(CORE_INDEX_NAMES.keys())
+
+_DIMENSION_SEP = re.compile(r"[、,，;；|/\s]+")
+
+
+# ================================================================
+# 通用工具
+# ================================================================
+
+def _finite(v: Any) -> float | None:
+    if v is None:
+        return None
+    try:
+        f = float(v)
+    except (TypeError, ValueError):
+        return None
+    return f if math.isfinite(f) else None
+
+
+def _json_safe(value: Any) -> Any:
+    if isinstance(value, dict):
+        return {k: _json_safe(v) for k, v in value.items()}
+    if isinstance(value, list):
+        return [_json_safe(v) for v in value]
+    if isinstance(value, float) and not math.isfinite(value):
+        return None
+    return value
+
+
+def _board(symbol: str) -> str:
+    if symbol.endswith(".BJ"):
+        return "北交所"
+    if symbol.startswith(("300", "301")):
+        return "创业板"
+    if symbol.startswith(("688", "689")):
+        return "科创板"
+    if symbol.endswith(".SH"):
+        return "沪主板"
+    if symbol.endswith(".SZ"):
+        return "深主板"
+    return "其他"
+
+
+def _score(value: float, low: float, high: float) -> int:
+    if high <= low:
+        return 50
+    return max(0, min(100, round((value - low) / (high - low) * 100)))
+
+
+# ================================================================
+# 指数行情(实时 quote_service 优先,回退 kline_index_daily SQL)
+# ================================================================
+
+def _quote_status(quote_service) -> dict:
+    qs = quote_service
+    if not qs:
+        return {"enabled": False, "running": False, "quote_age_ms": None, "is_trading_hours": False}
+    return qs.status()
+
+
+def _index_quotes(repo, quote_service, as_of: date | None = None) -> list[dict]:
+    rows: list[dict] = []
+    if quote_service and as_of is None:
+        df = quote_service.get_index_quotes(list(CORE_INDEX_SYMBOLS))
+        if not df.is_empty():
+            rows = df.to_dicts()
+
+    if not rows and repo:
+        placeholders = ", ".join("?" for _ in CORE_INDEX_SYMBOLS)
+        try:
+            db_rows = repo.execute_all(
+                f"""
+                WITH ranked AS (
+                    SELECT symbol, date, close,
+                           row_number() OVER (PARTITION BY symbol ORDER BY date DESC) AS rn
+                    FROM kline_index_daily
+                    WHERE symbol IN ({placeholders})
+                      AND (? IS NULL OR date <= ?)
+                ), latest AS (
+                    SELECT symbol,
+                           max(CASE WHEN rn = 1 THEN date END) AS date,
+                           max(CASE WHEN rn = 1 THEN close END) AS last_price,
+                           max(CASE WHEN rn = 2 THEN close END) AS prev_close
+                    FROM ranked
+                    WHERE rn <= 2
+                    GROUP BY symbol
+                )
+                SELECT symbol, date, last_price, prev_close
+                FROM latest
+                """,
+                [*CORE_INDEX_SYMBOLS, as_of, as_of],
+            )
+        except Exception:  # noqa: BLE001
+            db_rows = []
+        for symbol, dt, last_price, prev_close in db_rows:
+            change_amount = None
+            change_pct = None
+            lp = _finite(last_price)
+            pc = _finite(prev_close)
+            if lp is not None and pc not in (None, 0):
+                change_amount = lp - pc
+                change_pct = change_amount / pc * 100
+            rows.append({
+                "symbol": symbol,
+                "name": CORE_INDEX_NAMES.get(symbol),
+                "date": str(dt) if dt else None,
+                "last_price": lp,
+                "close": lp,
+                "prev_close": pc,
+                "change_amount": change_amount,
+                "change_pct": change_pct,
+            })
+
+    by_symbol = {r.get("symbol"): r for r in rows}
+    out = []
+    for symbol in CORE_INDEX_SYMBOLS:
+        r = by_symbol.get(symbol, {"symbol": symbol})
+        out.append({
+            "symbol": symbol,
+            "name": r.get("name") or CORE_INDEX_NAMES[symbol],
+            "last_price": _finite(r.get("last_price") if r.get("last_price") is not None else r.get("close")),
+            "change_pct": _finite(r.get("change_pct")),
+            "change_amount": _finite(r.get("change_amount")),
+        })
+    return out
+
+
+# ================================================================
+# 扩展数据(行业 / 概念)维度聚合
+# ================================================================
+
+def _dimension_field(config: ExtConfig, kind: str) -> str | None:
+    candidates = ["概念", "concept", "theme"] if kind == "concept" else ["行业", "industry", "sector"]
+    for candidate in candidates:
+        needle = candidate.lower()
+        for field in config.fields:
+            haystack = f"{field.name} {field.label}".lower()
+            if needle in haystack:
+                return field.name
+    return None
+
+
+def _ext_files(data_dir, config: ExtConfig) -> list[str]:
+    base = data_dir / "ext_data" / config.id
+    if config.mode == "timeseries":
+        root = base / "timeseries"
+        return [str(p) for p in sorted(root.rglob("*.parquet")) if p.is_file()]
+    return [str(p) for p in sorted(base.glob("*.parquet")) if p.is_file()]
+
+
+def _read_ext_rows(data_dir, config: ExtConfig, dimension_field: str) -> list[dict]:
+    files = _ext_files(data_dir, config)
+    if not files:
+        return []
+    try:
+        df = pl.read_parquet(files, hive_partitioning=True)
+    except TypeError:
+        try:
+            df = pl.read_parquet(files)
+        except Exception:  # noqa: BLE001
+            return []
+    except Exception:  # noqa: BLE001
+        return []
+    if df.is_empty() or dimension_field not in df.columns:
+        return []
+
+    if config.mode == "timeseries" and "date" in df.columns:
+        latest = df.get_column("date").max()
+        if latest is not None:
+            df = df.filter(pl.col("date") == latest)
+
+    symbol_cols = ["symbol", "code", "股票代码", "代码"]
+    for mapping in (config.symbol_map, config.code_map):
+        if isinstance(mapping, dict) and mapping.get("type") == "mapped" and mapping.get("col"):
+            symbol_cols.append(str(mapping["col"]))
+    cols = []
+    for col in [dimension_field, *symbol_cols]:
+        if col in df.columns and col not in cols:
+            cols.append(col)
+    return df.select(cols).to_dicts()
+
+
+def _dimension_values(raw: Any) -> list[str]:
+    if raw is None:
+        return []
+    values = [v.strip() for v in _DIMENSION_SEP.split(str(raw).strip()) if v.strip()]
+    return values
+
+
+def _symbol_keys(row: dict, config: ExtConfig) -> list[str]:
+    fields = ["symbol", "code", "股票代码", "代码"]
+    for mapping in (config.symbol_map, config.code_map):
+        if isinstance(mapping, dict) and mapping.get("type") == "mapped" and mapping.get("col"):
+            fields.append(str(mapping["col"]))
+
+    keys: list[str] = []
+    for field in fields:
+        raw = row.get(field)
+        if raw is None:
+            continue
+        text = str(raw).strip().upper()
+        if not text:
+            continue
+        keys.append(text)
+        if "." in text:
+            keys.append(text.split(".", 1)[0])
+    return keys
+
+
+def _dimension_rank(rows: list[dict], repo, kind: str, limit: int = 5, level: int | None = None) -> dict:
+    if not rows:
+        return {"leading": [], "lagging": []}
+
+    quote_map: dict[str, dict] = {}
+    for row in rows:
+        symbol = str(row.get("symbol") or "").strip().upper()
+        if not symbol:
+            continue
+        quote_map[symbol] = row
+        quote_map[symbol.split(".", 1)[0]] = row
+
+    store = ExtConfigStore(repo.store.data_dir)
+    groups: dict[str, dict[str, dict]] = {}
+    for config in store.load_all():
+        field = _dimension_field(config, kind)
+        if not field:
+            continue
+        for ext_row in _read_ext_rows(repo.store.data_dir, config, field):
+            quote = None
+            for key in _symbol_keys(ext_row, config):
+                quote = quote_map.get(key)
+                if quote:
+                    break
+            if not quote:
+                continue
+            symbol = str(quote.get("symbol") or "")
+            for value in _dimension_values(ext_row.get(field)):
+                # 行业按 "-" 拆分级: "银行-银行-股份制银行" → level=2 取"银行"(二级)
+                if level is not None and "-" in value:
+                    parts = value.split("-")
+                    value = parts[level - 1] if level <= len(parts) else parts[-1]
+                groups.setdefault(value, {})[symbol] = quote
+
+    items = []
+    for name, by_symbol in groups.items():
+        stocks = list(by_symbol.values())
+        changes = [_finite(s.get("change_pct")) for s in stocks]
+        changes = [v for v in changes if v is not None]
+        if not changes:
+            continue
+        leader = max(stocks, key=lambda s: _finite(s.get("change_pct")) or -999)
+        items.append({
+            "name": name,
+            "count": len(stocks),
+            "avg_pct": sum(changes) / len(changes),
+            "up_count": sum(1 for v in changes if v > 0),
+            "down_count": sum(1 for v in changes if v < 0),
+            "amount": sum(_finite(s.get("amount")) or 0 for s in stocks),
+            "leader": {
+                "symbol": leader.get("symbol"),
+                "name": leader.get("name"),
+                "change_pct": _finite(leader.get("change_pct")),
+            },
+        })
+
+    leading = sorted(items, key=lambda x: x["avg_pct"], reverse=True)[:limit]
+    lagging = sorted(items, key=lambda x: x["avg_pct"])[:limit]
+    return {"leading": leading, "lagging": lagging}
+
+
+# ================================================================
+# Top 行 / 涨跌幅分桶
+# ================================================================
+
+def _top_rows(rows: list[dict], key: str, descending: bool, limit: int = 8) -> list[dict]:
+    filtered = [r for r in rows if _finite(r.get(key)) is not None]
+    filtered.sort(key=lambda r: _finite(r.get(key)) or 0, reverse=descending)
+    return [
+        {
+            "symbol": r.get("symbol"),
+            "name": r.get("name"),
+            "close": _finite(r.get("close")),
+            "change_pct": _finite(r.get("change_pct")),
+            "amount": _finite(r.get("amount")),
+            "turnover_rate": _finite(r.get("turnover_rate")),
+            "board": _board(str(r.get("symbol") or "")),
+        }
+        for r in filtered[:limit]
+    ]
+
+
+def _pct_band_rows(values: list[float]) -> list[dict]:
+    bands = [
+        ("<-5%", None, -0.05),
+        ("-5~-3%", -0.05, -0.03),
+        ("-3~-1%", -0.03, -0.01),
+        ("-1~0%", -0.01, 0),
+        ("0~1%", 0, 0.01),
+        ("1~3%", 0.01, 0.03),
+        ("3~5%", 0.03, 0.05),
+        (">5%", 0.05, None),
+    ]
+    total = len(values) or 1
+    out = []
+    for label, low, high in bands:
+        count = 0
+        for v in values:
+            if low is None and v < high:
+                count += 1
+            elif high is None and v >= low:
+                count += 1
+            elif low is not None and high is not None and low <= v < high:
+                count += 1
+        out.append({"label": label, "count": count, "pct": count / total * 100})
+    return out
+
+
+# ================================================================
+# 主装配入口
+# ================================================================
+
+def build_market_overview(
+    repo,
+    quote_service=None,
+    depth_service=None,
+    as_of: date | None = None,
+) -> dict:
+    """装配市场总览(与原 overview._build_overview 行为一致)。
+
+    Args:
+        repo: KlineRepository(必填)。
+        quote_service: QuoteService(可选;实时指数行情来源)。
+        depth_service: DepthService(可选;五档封板修正)。
+        as_of: 指定日期,None 则取最新有数据日。
+    """
+    svc = ScreenerService(repo)
+    as_of = as_of or svc.latest_date()
+    status = _quote_status(quote_service)
+    indices = _index_quotes(repo, quote_service, as_of)
+
+    if not as_of:
+        return {
+            "as_of": None,
+            "quote_status": status,
+            "indices": indices,
+            "breadth": {"total": 0, "up": 0, "down": 0, "flat": 0, "up_pct": 0, "down_pct": 0},
+            "amount": {"total": 0, "avg": 0},
+            "boards": [],
+            "limit": {"limit_up": 0, "broken": 0, "failed": 0, "limit_down": 0, "max_boards": 0, "tiers": []},
+            "distribution": [],
+            "trend": {"above_ma5": 0, "above_ma20": 0, "above_ma60": 0, "above_ma5_pct": 0, "above_ma20_pct": 0, "above_ma60_pct": 0, "new_high": 0, "new_low": 0},
+            "activity": {"avg_turnover": 0, "high_turnover": 0, "high_vol_ratio": 0, "vol_ratio": 1},
+            "radar": [],
+            "emotion": {"score": 50, "label": "暂无"},
+            "top_gainers": [],
+            "top_losers": [],
+            "turnover_leaders": [],
+            "active_leaders": [],
+            "concept_rank": {"leading": [], "lagging": []},
+            "industry_rank": {"leading": [], "lagging": []},
+        }
+
+    df = svc._load_enriched_for_date(as_of)
+    if df.is_empty():
+        rows: list[dict] = []
+    else:
+        cols = [
+            "symbol", "name", "close", "change_pct", "amount", "turnover_rate", "volume",
+            "vol_ratio_5d", "consecutive_limit_ups", "signal_limit_up", "signal_broken_limit_up", "signal_limit_down",
+            "ma5", "ma20", "ma60", "high_60d", "low_60d", "signal_n_day_high", "signal_n_day_low",
+        ]
+        df = df.select([c for c in cols if c in df.columns])
+        rows = df.to_dicts()
+
+    # 过滤真停牌（volume=0 且 change_pct=0），保留有涨跌幅的浮点误差股以对齐同花顺口径
+    if rows and "volume" in rows[0]:
+        rows = [r for r in rows
+                if (_finite(r.get("volume")) or 0) > 0
+                or (_finite(r.get("change_pct")) or 0) != 0]
+
+    total = len(rows)
+    up = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) > 0)
+    down = sum(1 for r in rows if (_finite(r.get("change_pct")) or 0) < 0)
+    flat = max(0, total - up - down)
+    up_pct = up / total * 100 if total else 0
+    down_pct = down / total * 100 if total else 0
+
+    amounts = [_finite(r.get("amount")) or 0 for r in rows]
+    total_amount = sum(amounts)
+    avg_amount = total_amount / total if total else 0
+
+    pct_values = [_finite(r.get("change_pct")) for r in rows]
+    pct_values = [v for v in pct_values if v is not None]
+    avg_pct = sum(pct_values) / len(pct_values) if pct_values else 0
+    median_pct = sorted(pct_values)[len(pct_values) // 2] if pct_values else 0
+    strong_up = sum(1 for v in pct_values if v >= 0.03)
+    strong_down = sum(1 for v in pct_values if v <= -0.03)
+
+    limit_up = sum(1 for r in rows if bool(r.get("signal_limit_up")) or (_finite(r.get("consecutive_limit_ups")) or 0) > 0)
+    broken = sum(1 for r in rows if bool(r.get("signal_broken_limit_up")))
+    limit_down = sum(1 for r in rows if bool(r.get("signal_limit_down")))
+    max_boards = max([int(_finite(r.get("consecutive_limit_ups")) or 0) for r in rows], default=0)
+
+    # 五档 sealed 修正: 假涨停/假跌停不计入(需 Pro+ depth5.batch 能力)
+    sealed_ready = False
+    fake_up = 0
+    fake_down = 0
+    if depth_service:
+        up_map = depth_service.get_sealed_map(as_of, is_down=False)
+        down_map = depth_service.get_sealed_map(as_of, is_down=True)
+        sealed_ready = bool(up_map or down_map) and depth_service.is_sealed_ready(as_of)
+        if up_map:
+            fake_up = sum(1 for v in up_map.values() if v.get("sealed") is False)
+        if down_map:
+            fake_down = sum(1 for v in down_map.values() if v.get("sealed") is False)
+    if sealed_ready:
+        limit_up = max(0, limit_up - fake_up)
+        limit_down = max(0, limit_down - fake_down)
+
+    seal_rate = limit_up / (limit_up + broken) * 100 if (limit_up + broken) > 0 else 0
+
+    def above_ma_count(ma_key: str) -> int:
+        return sum(1 for r in rows if (_finite(r.get("close")) is not None and _finite(r.get(ma_key)) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get(ma_key)) or 0)))
+
+    above_ma5 = above_ma_count("ma5")
+    above_ma20 = above_ma_count("ma20")
+    above_ma60 = above_ma_count("ma60")
+    new_high = sum(1 for r in rows if bool(r.get("signal_n_day_high")) or (_finite(r.get("close")) is not None and _finite(r.get("high_60d")) is not None and (_finite(r.get("close")) or 0) >= (_finite(r.get("high_60d")) or 0)))
+    new_low = sum(1 for r in rows if bool(r.get("signal_n_day_low")) or (_finite(r.get("close")) is not None and _finite(r.get("low_60d")) is not None and (_finite(r.get("close")) or 0) <= (_finite(r.get("low_60d")) or 0)))
+
+    turnovers = [_finite(r.get("turnover_rate")) for r in rows]
+    turnovers = [v for v in turnovers if v is not None]
+    avg_turnover = sum(turnovers) / len(turnovers) if turnovers else 0
+    high_turnover = sum(1 for v in turnovers if v >= 5)
+
+    boards_map: dict[str, dict] = {}
+    for r in rows:
+        b = _board(str(r.get("symbol") or ""))
+        item = boards_map.setdefault(b, {"board": b, "count": 0, "up": 0, "down": 0, "amount": 0.0})
+        item["count"] += 1
+        change = _finite(r.get("change_pct")) or 0
+        if change > 0:
+            item["up"] += 1
+        elif change < 0:
+            item["down"] += 1
+        item["amount"] += _finite(r.get("amount")) or 0
+    boards = sorted(boards_map.values(), key=lambda x: x["amount"], reverse=True)
+    for b in boards:
+        count = b["count"] or 1
+        b["up_pct"] = b["up"] / count * 100
+
+    tiers_map: dict[int, int] = {}
+    for r in rows:
+        n = int(_finite(r.get("consecutive_limit_ups")) or 0)
+        if n > 0:
+            tiers_map[n] = tiers_map.get(n, 0) + 1
+    tiers = [{"boards": k, "count": v} for k, v in sorted(tiers_map.items(), key=lambda item: -item[0])]
+
+    index_changes = [_finite(r.get("change_pct")) for r in indices]
+    index_changes = [v for v in index_changes if v is not None]
+    avg_index_pct = sum(index_changes) / len(index_changes) if index_changes else 0
+    vol_ratios = [_finite(r.get("vol_ratio_5d")) for r in rows]
+    vol_ratios = [v for v in vol_ratios if v is not None]
+    avg_vol_ratio = sum(vol_ratios) / len(vol_ratios) if vol_ratios else 1
+    high_vol_ratio = sum(1 for v in vol_ratios if v >= 1.5)
+
+    concept_rank = _dimension_rank(rows, repo, "concept")
+    industry_rank = _dimension_rank(rows, repo, "industry", level=2)
+
+    strong_diff_pct = (strong_up - strong_down) / total * 100 if total else 0
+    high_vol_pct = high_vol_ratio / total * 100 if total else 0
+    strong_down_pct = strong_down / total * 100 if total else 0
+    tier2_count = sum(t["count"] for t in tiers if t["boards"] >= 2)
+    mainline_items = [*concept_rank["leading"][:3], *industry_rank["leading"][:3]]
+    mainline_avg = max([_finite(item.get("avg_pct")) or 0 for item in mainline_items], default=0)
+    mainline_cover_pct = max([(_finite(item.get("count")) or 0) / total * 100 for item in mainline_items], default=0) if total else 0
+    mainline_score = round(_score(mainline_avg, -0.005, 0.03) * 0.65 + _score(mainline_cover_pct, 1, 12) * 0.35) if mainline_items else 50
+
+    radar = [
+        {"key": "index", "label": "指数", "value": _score(avg_index_pct, -2.5, 2.5)},
+        {"key": "profit", "label": "赚钱", "value": round(_score(up_pct, 20, 80) * 0.45 + _score(avg_pct, -0.02, 0.02) * 0.25 + _score(median_pct, -0.02, 0.02) * 0.20 + _score(strong_diff_pct, -8, 8) * 0.10)},
+        {"key": "money", "label": "量能", "value": round(_score(avg_vol_ratio, 0.6, 1.8) * 0.70 + _score(high_vol_pct, 2, 12) * 0.30)},
+        {"key": "speculation", "label": "投机", "value": round(_score(limit_up, 5, 90) * 0.25 + _score(seal_rate, 30, 85) * 0.35 + _score(max_boards, 1, 8) * 0.25 + _score(tier2_count, 0, 30) * 0.15)},
+        {"key": "resilience", "label": "抗跌", "value": 100 - round(_score(down_pct, 20, 80) * 0.55 + _score(strong_down_pct, 1, 12) * 0.45)},
+        {"key": "mainline", "label": "主线", "value": mainline_score},
+    ]
+    emotion_score = round(sum(r["value"] for r in radar) / len(radar)) if radar else 50
+    if emotion_score >= 70:
+        emotion_label = "强势"
+    elif emotion_score >= 55:
+        emotion_label = "偏暖"
+    elif emotion_score >= 45:
+        emotion_label = "震荡"
+    elif emotion_score >= 30:
+        emotion_label = "偏冷"
+    else:
+        emotion_label = "冰点"
+
+    return _json_safe({
+        "as_of": str(as_of),
+        "quote_status": status,
+        "indices": indices,
+        "breadth": {
+            "total": total,
+            "up": up,
+            "down": down,
+            "flat": flat,
+            "up_pct": up_pct,
+            "down_pct": down_pct,
+            "avg_pct": avg_pct,
+            "median_pct": median_pct,
+            "strong_up": strong_up,
+            "strong_down": strong_down,
+        },
+        "amount": {"total": total_amount, "avg": avg_amount},
+        "boards": boards,
+        "limit": {"limit_up": limit_up, "broken": broken, "failed": 0, "limit_down": limit_down, "max_boards": max_boards, "seal_rate": seal_rate, "tiers": tiers, "sealed_ready": sealed_ready, "fake_up": fake_up, "fake_down": fake_down},
+        "distribution": _pct_band_rows(pct_values),
+        "trend": {
+            "above_ma5": above_ma5,
+            "above_ma20": above_ma20,
+            "above_ma60": above_ma60,
+            "above_ma5_pct": above_ma5 / total * 100 if total else 0,
+            "above_ma20_pct": above_ma20 / total * 100 if total else 0,
+            "above_ma60_pct": above_ma60 / total * 100 if total else 0,
+            "new_high": new_high,
+            "new_low": new_low,
+        },
+        "activity": {
+            "avg_turnover": avg_turnover,
+            "high_turnover": high_turnover,
+            "high_vol_ratio": high_vol_pct,
+            "vol_ratio": avg_vol_ratio,
+        },
+        "radar": radar,
+        "emotion": {"score": emotion_score, "label": emotion_label},
+        "top_gainers": _top_rows(rows, "change_pct", True),
+        "top_losers": _top_rows(rows, "change_pct", False),
+        "turnover_leaders": _top_rows(rows, "amount", True),
+        "active_leaders": _top_rows(rows, "turnover_rate", True),
+        "concept_rank": concept_rank,
+        "industry_rank": industry_rank,
+    })

backend/app/services/market_recap.py

@@ -0,0 +1,356 @@
+"""AI 大盘复盘 —— 流式 LLM 复盘生成。
+
+复刻 stock_analyzer.py 的 NDJSON 流式协议(meta/delta/error/done),
+将「市场总览」聚合数据交给 LLM 生成结构化复盘报告。
+
+数据来源:services.market_overview_builder.build_market_overview
+(与 GET /api/overview/market 同源,保证复盘与看板数据口径一致)。
+
+流式协议(与 stock_analyzer / financial_analyzer 一致,前端解析无差异):
+    {"type":"meta", "as_of", "emotion_score", "emotion_label", "summary"}
+    {"type":"delta","content":"..."}   逐 chunk 文本
+    {"type":"error","message":"..."}
+    {"type":"done"}
+"""
+from __future__ import annotations
+
+import json
+import logging
+from datetime import date
+from typing import AsyncIterator
+
+from app.services.market_overview_builder import build_market_overview
+
+logger = logging.getLogger(__name__)
+
+
+# ================================================================
+# 系统提示词(市场策略师人格 + 固定七节模板)
+# ================================================================
+
+_SYSTEM_PROMPT = """你是一位拥有 15 年 A 股一线实战经验的资深市场策略师,擅长从指数结构、涨跌家数、连板梯队、板块轮动与资金情绪中提炼交易主线,产出可直接指导次日仓位与节奏的盘后复盘报告。
+
+## 输出规范
+
+用 **Markdown** 格式输出,严格遵循以下结构。不要输出任何 JSON 或代码块,直接输出 Markdown 正文。
+
+### 1. 🎯 一句话定调(1-2 句)
+用一句话概括今日市场的**核心矛盾与状态**(如"放量普涨、情绪修复,主线围绕科技扩散"/"指数虚高、个股杀跌,赚钱效应冰点")。结尾用【明日基调:进攻 / 均衡 / 防守】给出明确倾向。
+
+### 2. 📊 盘面总览
+- 三大指数(上证/深证/创业板)表现:谁强谁弱、量能配合
+- 涨跌家数、涨停/跌停/炸板结构、两市成交额(放量/缩量判断)
+- 情绪温度(强势/偏暖/震荡/偏冷/冰点)及一句话依据
+
+### 3. 📈 指数结构
+谁在护盘、谁在拖累;指数是否同步;关键支撑/压力位(基于当日点位推断);是否存在量价背离。
+
+### 4. 🔥 板块主线
+- 领涨板块:背后的逻辑(消息/业绩/资金/技术)、持续性判断、是否形成可交易主线
+- 领跌板块:风险信号、是否扩散
+- 连板梯队与投机情绪:最高连板、封板率、炸板率反映的资金激进程度
+
+### 5. 💰 资金与情绪
+成交额结构(增量/存量)、市场宽度(上涨占比、站上均线占比)、量能指标(量比)解读;风险偏好是修复还是转弱。
+
+### 6. 📰 消息催化
+结合提供的近期新闻,提炼真正影响明日交易节奏的催化或扰动。明确区分"已兑现"与"待发酵"。**若提供了"无新闻数据"的说明,则本节基于量价异动进行[推断],并如实标注,不要编造具体消息。**
+
+### 7. 🎯 明日交易计划
+- 进攻 / 均衡 / 防守:基于今日盘面给出次日基调
+- 仓位区间建议(轻仓/半仓/重仓的粗略指引)
+- 关注方向(领涨延续 / 低吸 / 反包)与回避方向(高位滞涨 / 杀跌扩散)
+- 一个明确的触发失效条件(如"若上证跌破 X 点则转为防守")
+
+### 8. ⚠️ 风险提示
+列出需要重点盯的风险点(如量能跟不上、外资流出、连板断层等)。末尾附一行:
+"> ⚠️ 本报告由 AI 基于公开行情数据生成,仅供参考,不构成任何投资建议。交易有风险,入市需谨慎。"
+
+## 分析准则(务必遵守)
+
+1. **数据说话**:每个判断引用具体数值,严禁空泛套话("情绪回暖"必须改成"涨停 68 家较前日 +22,封板率 75%")
+2. **诚实中立**:看多就写多,看空就写空,不要骑墙;数据不支持时直言无法判断
+3. **结构优先**:先看指数同步性与量能结构,再看板块与情绪,最后才是消息
+4. **不重复数字**:正文负责解读表格数据背后的含义,不要照抄罗列已提供的大段原始数字
+5. **风险前置**:任何进攻建议都要配触发失效条件
+6. **简明实战**:用交易员能扫读的密度输出,总字数 1200-2000 字,重在可执行
+
+现在请基于下方数据进行复盘。"""
+
+
+# ================================================================
+# 用户消息构建(精简切片,控制 token)
+# ================================================================
+
+def _fmt_pct(v, suffix="%") -> str:
+    if v is None:
+        return "—"
+    return f"{v:+.2f}{suffix}" if suffix else f"{v:.2f}"
+
+
+def _build_indices_block(overview: dict) -> str:
+    """指数行情精简块。"""
+    indices = overview.get("indices") or []
+    if not indices:
+        return "(暂无指数)"
+    lines = []
+    for idx in indices:
+        name = idx.get("name") or idx.get("symbol")
+        price = idx.get("last_price")
+        chg = idx.get("change_pct")
+        price_s = f"{price:.2f}" if price is not None else "—"
+        lines.append(f"- {name}: {price_s}  {_fmt_pct(chg)}")
+    return "\n".join(lines)
+
+
+def _build_breadth_block(overview: dict) -> str:
+    b = overview.get("breadth") or {}
+    amt = overview.get("amount") or {}
+    lim = overview.get("limit") or {}
+    tr = overview.get("trend") or {}
+    act = overview.get("activity") or {}
+
+    total_amount = amt.get("total") or 0
+    # 成交额单位换算为亿元(原始为元)
+    amount_yi = total_amount / 1e8 if total_amount else 0
+
+    lines = [
+        f"- 上涨/下跌/平盘: {b.get('up',0)} / {b.get('down',0)} / {b.get('flat',0)}"
+        f"  (上涨占比 {b.get('up_pct',0):.1f}%)",
+        f"- 涨停/炸板/跌停: {lim.get('limit_up',0)} / {lim.get('broken',0)} / {lim.get('limit_down',0)}"
+        f"  (封板率 {lim.get('seal_rate',0):.0f}%, 最高连板 {lim.get('max_boards',0)})",
+    ]
+    if lim.get("tiers"):
+        tiers_str = "、".join(f"{t['boards']}板×{t['count']}" for t in lim["tiers"][:5])
+        lines.append(f"- 连板梯队: {tiers_str}")
+    lines.append(f"- 两市成交额: {amount_yi:.0f} 亿元")
+    lines.append(
+        f"- 均线站位: MA5 {tr.get('above_ma5_pct',0):.0f}% / "
+        f"MA20 {tr.get('above_ma20_pct',0):.0f}% / MA60 {tr.get('above_ma60_pct',0):.0f}%"
+    )
+    lines.append(
+        f"- 量能: 平均换手 {act.get('avg_turnover',0):.2f}%, "
+        f"量比5日均 {act.get('vol_ratio',1):.2f}"
+    )
+    return "\n".join(lines)
+
+
+def _build_sector_block(rank: dict, label: str) -> str:
+    """板块排名精简块(领涨/领跌 top5)。"""
+    if not rank:
+        return f"### {label}\n(暂无数据)"
+    def _fmt(items):
+        if not items:
+            return "—"
+        return "、".join(
+            f"{it.get('name')}({(it.get('avg_pct') or 0)*100:+.2f}%,领涨:{it.get('leader',{}).get('name','—')})"
+            for it in items[:5]
+        )
+    return (
+        f"- 领涨{label}: {_fmt(rank.get('leading'))}\n"
+        f"- 领跌{label}: {_fmt(rank.get('lagging'))}"
+    )
+
+
+def _build_emotion_block(overview: dict) -> str:
+    emo = overview.get("emotion") or {}
+    radar = overview.get("radar") or []
+    score = emo.get("score", 50)
+    label = emo.get("label", "—")
+    lines = [f"- 情绪温度: {score} ({label})"]
+    if radar:
+        dims = "、".join(f"{r.get('label')}{r.get('value',0)}" for r in radar)
+        lines.append(f"- 六维雷达: {dims}")
+    return "\n".join(lines)
+
+
+def _build_user_prompt(overview: dict, news: list[dict], focus: str) -> str:
+    """构建用户消息:复盘日期 + 市场数据精简切片 + 新闻 + 关注点。"""
+    as_of = overview.get("as_of") or "今日"
+
+    parts: list[str] = [
+        f"复盘日期: {as_of}",
+        "",
+        "## 主要指数",
+        _build_indices_block(overview),
+        "",
+        "## 盘面数据",
+        _build_breadth_block(overview),
+        "",
+        "## 市场情绪",
+        _build_emotion_block(overview),
+        "",
+        "## 概念板块排名",
+        _build_sector_block(overview.get("concept_rank"), "概念"),
+        "",
+        "## 行业板块排名",
+        _build_sector_block(overview.get("industry_rank"), "行业"),
+    ]
+
+    if news:
+        news_lines = []
+        for i, n in enumerate(news[:8], 1):
+            title = (n.get("title") or "").strip()
+            snippet = (n.get("snippet") or "").strip()
+            source = (n.get("source") or "").strip()
+            pub = (n.get("published_date") or "").strip()
+            meta = " / ".join(p for p in (source, pub) if p)
+            news_lines.append(f"{i}. {title} ({meta})\n   {snippet}" if meta else f"{i}. {title}\n   {snippet}")
+        parts.extend(["", "## 近期市场新闻", "\n".join(news_lines)])
+    else:
+        parts.extend([
+            "",
+            "## 近期市场新闻",
+            "(暂无新闻数据:本功能新闻检索能力将在后续版本接入。"
+            "请按系统提示词第 6 节的说明,基于量价异动进行[推断],并如实标注,不要编造具体消息。)",
+        ])
+
+    if focus.strip():
+        parts.extend(["", f"本次复盘请特别关注: {focus.strip()}"])
+
+    return "\n".join(parts)
+
+
+# ================================================================
+# 摘要生成(供 meta 事件 / 历史报告 summary)
+# ================================================================
+
+def _recap_summary(overview: dict) -> str:
+    """一句话摘要(供 meta 事件与历史列表展示)。"""
+    indices = overview.get("indices") or []
+    emo = overview.get("emotion") or {}
+    lim = overview.get("limit") or {}
+    amt = overview.get("amount") or {}
+    total_amount = (amt.get("total") or 0) / 1e8
+
+    idx_str = "、".join(
+        f"{(i.get('name') or '')}{(i.get('change_pct') or 0):+.2f}%"
+        for i in indices[:3]
+    ) or "指数缺失"
+    return (
+        f"{idx_str} | 情绪{emo.get('score',50)}({emo.get('label','—')}) | "
+        f"涨停{lim.get('limit_up',0)} | 成交{total_amount:.0f}亿"
+    )
+
+
+# ================================================================
+# 流式主入口
+# ================================================================
+
+async def recap_market_stream(
+    repo,
+    quote_service=None,
+    depth_service=None,
+    as_of: date | None = None,
+    focus: str = "",
+    news: list[dict] | None = None,
+) -> AsyncIterator[str]:
+    """流式大盘复盘:yield 出每个 NDJSON 事件。
+
+    Args:
+        repo: KlineRepository(必填)。
+        quote_service / depth_service: 可选,数据装配依赖。
+        as_of: 复盘日期,None 取最新有数据日。
+        focus: 用户追加的复盘关注点。
+        news: 预检索的新闻列表(P1 不传,留 None 走降级说明;P3 由 news_search 注入)。
+    """
+    # 1. 装配市场总览
+    overview = build_market_overview(repo, quote_service, depth_service, as_of)
+    as_of_str = overview.get("as_of")
+
+    if not as_of_str:
+        yield json.dumps({
+            "type": "error",
+            "message": "暂无市场数据,请先在「数据」页同步日 K 与指数后再复盘",
+        }, ensure_ascii=False)
+        return
+
+    emo = overview.get("emotion") or {}
+
+    # 2. meta 事件(前端据此先渲染信号灯/看板)
+    yield json.dumps({
+        "type": "meta",
+        "as_of": as_of_str,
+        "emotion_score": emo.get("score", 50),
+        "emotion_label": emo.get("label", "—"),
+        "summary": _recap_summary(overview),
+    }, ensure_ascii=False)
+
+    # 3+4. 构建 prompt + 流式调用 LLM(整体 try-except,任何异常 yield error,避免前端卡死)
+    try:
+        from openai import AsyncOpenAI
+        from app import secrets_store
+        from app.config import settings
+
+        ai_key = secrets_store.get_ai_key()
+        if not ai_key:
+            yield json.dumps({
+                "type": "error",
+                "message": "AI API Key 未配置,请在「设置 → AI」中配置",
+            }, ensure_ascii=False)
+            return
+
+        user_prompt = _build_user_prompt(overview, news or [], focus)
+
+        user_agent = secrets_store.get_ai_config("ai_user_agent", "") or settings.ai_user_agent
+        client = AsyncOpenAI(
+            api_key=ai_key,
+            base_url=secrets_store.get_ai_config("ai_base_url", "https://api.alysc.top"),
+            timeout=180.0,
+            max_retries=2,
+            default_headers={"User-Agent": user_agent},
+        )
+
+        stream = await client.chat.completions.create(
+            model=secrets_store.get_ai_config("ai_model", "gpt-5.5"),
+            messages=[
+                {"role": "system", "content": _SYSTEM_PROMPT},
+                {"role": "user", "content": user_prompt},
+            ],
+            temperature=0.5,
+            max_tokens=4500,
+            stream=True,
+        )
+
+        async for chunk in stream:
+            delta = chunk.choices[0].delta if chunk.choices else None
+            if delta and delta.content:
+                yield json.dumps({"type": "delta", "content": delta.content}, ensure_ascii=False)
+
+    except Exception as e:  # noqa: BLE001
+        logger.exception("AI market recap failed for %s: %s", as_of_str, e)
+        yield json.dumps({"type": "error", "message": f"AI 复盘失败: {e}"}, ensure_ascii=False)
+        return
+
+    yield json.dumps({"type": "done"}, ensure_ascii=False)
+
+
+async def recap_market_once(
+    repo,
+    quote_service=None,
+    depth_service=None,
+    as_of: date | None = None,
+    focus: str = "",
+    news: list[dict] | None = None,
+) -> tuple[str | None, dict]:
+    """非流式版本(供定时任务调用):累积全部 delta,返回 (content, meta)。
+
+    content 为完整 Markdown 文本;失败时为 None。
+    meta 含 as_of / emotion_score / emotion_label / summary(即使失败也尽量回填)。
+    """
+    content_parts: list[str] = []
+    meta: dict = {"as_of": as_of.isoformat() if as_of else None}
+    async for evt in recap_market_stream(repo, quote_service, depth_service, as_of, focus, news):
+        try:
+            obj = json.loads(evt)
+        except Exception:  # noqa: BLE001
+            continue
+        t = obj.get("type")
+        if t == "meta":
+            meta = obj
+        elif t == "delta":
+            content_parts.append(obj.get("content", ""))
+        elif t == "error":
+            logger.warning("market recap error event: %s", obj.get("message"))
+            return None, meta
+    return "".join(content_parts), meta

backend/app/services/market_recap_reports.py

@@ -0,0 +1,92 @@
+"""AI 大盘复盘报告持久化存储。
+
+与 stock_reports.py(个股分析报告)/ ai_reports.py(财务分析报告)完全独立 ——
+单独的文件、字段、上限,互不影响。刻意不复用,避免引入 kind 判别字段与分支
+(解耦 > 抽象)。
+
+存储位置: data/user_data/ai_market_recaps.json (数组,按 created_at 降序)
+保留最近 MAX_REPORTS 条;超出自动裁剪最旧的。
+
+每条报告结构:
+{
+  "id": "mkr_xxx",            # 唯一 id(market-recap-report)
+  "as_of": "2026-06-27",      # 复盘日期
+  "focus": "",                # 用户追加的关心点(可为空)
+  "content": "# ...markdown", # 报告正文
+  "summary": "三大指数齐涨...",  # 一句话摘要
+  "emotion_score": 68,        # 情绪分(0-100, 复盘生成时的市场情绪雷达均分)
+  "emotion_label": "偏暖",     # 情绪标签(强势/偏暖/震荡/偏冷/冰点)
+  "created_at": "2026-06-27T15:35:00"
+}
+"""
+from __future__ import annotations
+
+import json
+import logging
+import time
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+MAX_REPORTS = 30
+
+
+def _path() -> Path:
+    from app.config import settings
+    p = settings.data_dir / "user_data" / "ai_market_recaps.json"
+    p.parent.mkdir(parents=True, exist_ok=True)
+    return p
+
+
+def list_reports() -> list[dict]:
+    """返回全部报告(按 created_at 降序)。"""
+    p = _path()
+    if not p.exists():
+        return []
+    try:
+        data = json.loads(p.read_text(encoding="utf-8"))
+        if isinstance(data, list):
+            return sorted(data, key=lambda r: r.get("created_at", ""), reverse=True)
+    except Exception as e:  # noqa: BLE001
+        logger.warning("ai_market_recaps.json malformed: %s", e)
+    return []
+
+
+def _save_all(reports: list[dict]) -> None:
+    """全量写入(裁剪到 MAX_REPORTS)。"""
+    reports.sort(key=lambda r: r.get("created_at", ""), reverse=True)
+    if len(reports) > MAX_REPORTS:
+        reports = reports[:MAX_REPORTS]
+    _path().write_text(
+        json.dumps(reports, indent=2, ensure_ascii=False), encoding="utf-8",
+    )
+
+
+def save_report(report: dict) -> dict:
+    """新增一条报告并持久化。返回保存后的报告(含 id / created_at)。"""
+    reports = list_reports()
+    if not report.get("id"):
+        report["id"] = f"mkr_{int(time.time() * 1000)}"
+    if not report.get("created_at"):
+        report["created_at"] = _now_iso()
+    reports.append(report)
+    _save_all(reports)
+    logger.info("Market recap saved: %s (as_of=%s), total %d",
+                report.get("id"), report.get("as_of"), len(reports))
+    return report
+
+
+def delete_report(report_id: str) -> bool:
+    """删除指定报告。返回是否删除成功。"""
+    reports = list_reports()
+    before = len(reports)
+    reports = [r for r in reports if r.get("id") != report_id]
+    if len(reports) < before:
+        _save_all(reports)
+        return True
+    return False
+
+
+def _now_iso() -> str:
+    from datetime import datetime
+    return datetime.now().isoformat(timespec="seconds")

backend/app/services/preferences.py

@@ -53,6 +53,29 @@ def get_realtime_quote_interval() -> float:
     return load().get("realtime_quote_interval", 10.0)
 
 
+def get_realtime_watchlist_symbols() -> list[str]:
+    """Free 档自选实时监控标的:直接取自选页前 5 个。"""
+    try:
+        from app.services import watchlist
+        rows = watchlist.list_symbols()
+    except Exception as e:  # noqa: BLE001
+        logger.warning("load watchlist for realtime failed: %s", e)
+        return []
+    out: list[str] = []
+    for row in rows:
+        symbol = str((row or {}).get("symbol") or "").strip().upper()
+        if symbol and symbol not in out:
+            out.append(symbol)
+        if len(out) >= 5:
+            break
+    return out
+
+
+def set_realtime_watchlist_symbols(symbols: list[str]) -> list[str]:  # noqa: ARG001
+    """兼容旧接口: Free 实时标的现在由自选页前 5 个决定。"""
+    return get_realtime_watchlist_symbols()
+
+
 def set_realtime_quote_interval(interval: float) -> float:
     """保存行情轮询间隔（不在此做 min/max 校验，由调用方按档位限制）。"""
     current = load()
@@ -71,6 +94,83 @@ def get_minute_sync_days() -> int:
     return max(1, min(30, load().get("minute_sync_days", 5)))
 
 
+# ===== 数据源选择 (默认 TickFlow；第一阶段仅日K切换入口) =====
+
+_ALLOWED_DATA_PROVIDERS = {"tickflow"}
+
+
+def get_daily_data_provider() -> str:
+    provider = str(load().get("daily_data_provider", "tickflow") or "tickflow").lower()
+    return provider if provider in _ALLOWED_DATA_PROVIDERS else "tickflow"
+
+
+def get_adj_factor_provider() -> str:
+    provider = str(load().get("adj_factor_provider", "same_as_daily") or "same_as_daily").lower()
+    if provider == "same_as_daily":
+        return provider
+    return provider if provider in _ALLOWED_DATA_PROVIDERS else "same_as_daily"
+
+
+def get_minute_data_provider() -> str:
+    provider = str(load().get("minute_data_provider", "tickflow") or "tickflow").lower()
+    return provider if provider in _ALLOWED_DATA_PROVIDERS else "tickflow"
+
+
+def get_realtime_data_provider() -> str:
+    # 盘中实时现阶段仅支持 TickFlow。
+    return "tickflow"
+
+
+# ===== 盘后管道拉取内容开关 (A股 / ETF / 指数 独立控制) =====
+
+def get_pipeline_pull_a_share() -> bool:
+    """A 股日K固定拉取。"""
+    return True
+
+
+def get_pipeline_pull_etf() -> bool:
+    """是否拉取 ETF 日K。默认 False(标的多,首次较慢)。"""
+    return load().get("pipeline_pull_etf", False)
+
+
+def get_pipeline_pull_index() -> bool:
+    """是否拉取指数日K。默认 True。"""
+    return load().get("pipeline_pull_index", True)
+
+
+_PIPELINE_PULL_KEYS = ("pipeline_pull_etf", "pipeline_pull_index")
+
+
+def get_pipeline_pull_types() -> dict:
+    """返回三个拉取开关的当前值。"""
+    return {
+        "pipeline_pull_a_share": get_pipeline_pull_a_share(),
+        "pipeline_pull_etf": get_pipeline_pull_etf(),
+        "pipeline_pull_index": get_pipeline_pull_index(),
+    }
+
+
+def set_pipeline_pull_types(cfg: dict) -> dict:
+    """批量保存拉取开关。只接受白名单内的布尔字段。"""
+    updates = {
+        k: bool(v) for k, v in cfg.items()
+        if k in _PIPELINE_PULL_KEYS and v is not None
+    }
+    save(updates)
+    return get_pipeline_pull_types()
+
+
+def get_pipeline_index_symbols() -> str:
+    """指数自定义拉取代码(逗号/换行/空格分隔)。空串表示全量。"""
+    return str(load().get("pipeline_index_symbols", "") or "").strip()
+
+
+def set_pipeline_index_symbols(symbols: str) -> str:
+    """保存指数自定义代码,返回规范化后的字符串。"""
+    save({"pipeline_index_symbols": symbols})
+    return get_pipeline_index_symbols()
+
+
 def get_pipeline_schedule() -> dict:
     """返回盘后管道调度时间 {"hour": 15, "minute": 30}。"""
     d = load().get("pipeline_schedule", {"hour": 15, "minute": 30})
@@ -178,6 +278,59 @@ SSE_REFRESH_PAGES_DEFAULT = {
 SIDEBAR_INDEX_SYMBOLS_DEFAULT = ["000001.SH", "399001.SZ", "399006.SZ", "000680.SH"]
 
 
+# ===== 盘中实时行情范围 (独立于盘后管道范围) =====
+
+
+def get_realtime_pull_stock() -> bool:
+    return load().get("realtime_pull_stock", True)
+
+
+def get_realtime_pull_etf() -> bool:
+    # 老用户兼容: ETF 实时默认关闭，避免升级后请求量/写盘量突然增加。
+    return load().get("realtime_pull_etf", False)
+
+
+def get_realtime_pull_index() -> bool:
+    return load().get("realtime_pull_index", True)
+
+
+def get_realtime_index_mode() -> str:
+    mode = str(load().get("realtime_index_mode", "core") or "core").lower()
+    return mode if mode in {"core", "all"} else "core"
+
+
+def get_realtime_index_symbols() -> list[str]:
+    stored = load().get("realtime_index_symbols", SIDEBAR_INDEX_SYMBOLS_DEFAULT)
+    if isinstance(stored, str):
+        import re
+        stored = [s.strip() for s in re.split(r"[,\s]+", stored) if s.strip()]
+    return [str(s) for s in stored if str(s).strip()]
+
+
+def set_realtime_quote_scope(cfg: dict) -> dict:
+    updates = {}
+    for key in ("realtime_pull_stock", "realtime_pull_etf", "realtime_pull_index"):
+        if key in cfg and cfg[key] is not None:
+            updates[key] = bool(cfg[key])
+    if "realtime_index_mode" in cfg and cfg["realtime_index_mode"] in {"core", "all"}:
+        updates["realtime_index_mode"] = cfg["realtime_index_mode"]
+    if "realtime_index_symbols" in cfg and cfg["realtime_index_symbols"] is not None:
+        updates["realtime_index_symbols"] = cfg["realtime_index_symbols"]
+    if updates:
+        save(updates)
+    return get_realtime_quote_scope()
+
+
+def get_realtime_quote_scope() -> dict:
+    return {
+        "realtime_pull_stock": get_realtime_pull_stock(),
+        "realtime_pull_etf": get_realtime_pull_etf(),
+        "realtime_pull_index": get_realtime_pull_index(),
+        "realtime_index_mode": get_realtime_index_mode(),
+        "realtime_index_symbols": get_realtime_index_symbols(),
+    }
+
+
 def get_sse_refresh_pages() -> dict[str, bool]:
     """返回每个页面的 SSE 刷新开关。"""
     stored = load().get("sse_refresh_pages", {})

backend/app/services/quote_service.py

@@ -43,6 +43,7 @@ class QuoteService:
         "expert": 1.0,
         "pro": 2.0,
         "starter": 3.0,
+        "free": 6.0,
     }
     DEFAULT_INTERVAL = 10.0
     MAX_INTERVAL = 60.0
@@ -68,6 +69,7 @@ class QuoteService:
         self._fetched_at: float = 0.0       # 拉取完成的 Unix 时间戳 (毫秒)
         self._symbol_count: int = 0
         self._index_symbol_count: int = 0
+        self._etf_symbol_count: int = 0
         self._index_quotes_cache: pl.DataFrame | None = None
 
     # ================================================================
@@ -102,11 +104,11 @@ class QuoteService:
     def enable(self) -> bool:
         """开启自动行情 (不立即启动线程，等下一个交易时段)。
 
-        none/free 档无实时行情权限,拒绝开启并返回 False;
-        starter+ 正常启动。返回值表示是否真正开启。
+        none 档无实时行情权限,拒绝开启并返回 False;
+        free 档开启自选股实时,starter+ 开启全市场实时。返回值表示是否真正开启。
         """
         if not self.is_realtime_allowed():
-            logger.warning("实时行情开启被拒:当前档位(none/free)无实时行情权限")
+            logger.warning("实时行情开启被拒:当前档位(none)无实时行情权限")
             return False
         self._enabled = True
         self._save_enabled(True)
@@ -126,14 +128,14 @@ class QuoteService:
     def boot_check(self) -> None:
         """启动时检查 preferences，若 enabled 则自动启动。
 
-        none/free 档无实时行情权限:即使 preferences 标记为 enabled,
+        none 档无实时行情权限:即使 preferences 标记为 enabled,
         也不启动,并同步 preferences 为关闭(避免 UI 误显示已开启)。
         """
         from app.services import preferences
         if not self.is_realtime_allowed():
             if preferences.get_realtime_quotes_enabled():
                 self._save_enabled(False)
-            logger.info("实时行情未启动:当前档位(none/free)无实时行情权限")
+            logger.info("实时行情未启动:当前档位(none)无实时行情权限")
             return
         if preferences.get_realtime_quotes_enabled():
             self.start()
@@ -199,13 +201,19 @@ class QuoteService:
         return tier_label().split()[0].split("+")[0].strip().lower()
 
     @classmethod
-    def is_realtime_allowed(cls) -> bool:
-        """当前档位是否允许使用实时行情。
+    def realtime_mode(cls) -> str:
+        """当前实时行情模式: none / watchlist / full_market。"""
+        tier = cls._current_tier()
+        if tier == "none":
+            return "none"
+        if tier == "free":
+            return "watchlist"
+        return "full_market"
 
-        none/free 档走 free-api 服务器,无实时行情权限 → 不允许;
-        starter+ 付费档走付费端点,有实时行情 → 允许。
-        """
-        return cls._current_tier() not in ("none", "free")
+    @classmethod
+    def is_realtime_allowed(cls) -> bool:
+        """当前档位是否允许使用实时行情。"""
+        return cls.realtime_mode() != "none"
 
     @classmethod
     def _tier_min_interval(cls) -> float:
@@ -262,13 +270,19 @@ class QuoteService:
 
     def status(self) -> dict:
         """返回行情服务状态。"""
+        from app.services import preferences
         age = (time.perf_counter() - self._fetch_time) * 1000 if self._fetch_time else -1
+        mode = self.realtime_mode()
         return {
             "enabled": self._enabled,
             "running": self._running,
+            "mode": mode,
+            "realtime_allowed": mode != "none",
+            "watchlist_symbol_count": len(preferences.get_realtime_watchlist_symbols()),
             "interval_s": self._interval,
             "symbol_count": self._symbol_count,
             "index_symbol_count": self._index_symbol_count,
+            "etf_symbol_count": self._etf_symbol_count,
             "quote_age_ms": round(age, 0) if age >= 0 else None,
             "is_trading_hours": self._is_trading_hours(),
             "last_fetch_ms": round(self._fetched_at, 0) if self._fetched_at else None,
@@ -299,17 +313,47 @@ class QuoteService:
                 waited += 0.5
 
     def _fetch_quotes(self) -> None:
-        """拉取全市场行情 → 写 daily + 计算 enriched + 更新缓存。"""
-        from app.tickflow.client import get_client
+        """按当前档位拉取行情。"""
+        if self.realtime_mode() == "watchlist":
+            self._fetch_watchlist_quotes()
+            return
+        self._fetch_full_market_quotes()
 
-        tf = get_client()
+    def _fetch_full_market_quotes(self) -> None:
+        """拉取全市场行情 → 写 daily + 计算 enriched + 更新缓存。"""
+        from app.tickflow.client import get_paid_realtime_client
+
+        tf = get_paid_realtime_client()
+        if tf is None:
+            logger.warning("实时行情拉取失败:未配置付费服务器 API Key")
+            return
         t0 = time.perf_counter()
         now_ts = time.perf_counter()
 
         try:
+            from app.services import preferences
             all_index_symbols = set(self._repo.get_index_symbol_set()) if self._repo else set()
-            all_index_symbols.update(self.CORE_INDEX_SYMBOLS)
-            resp = tf.quotes.get_by_universes(universes=["CN_Equity_A", "CN_Index"])
+            core_index_symbols = set(preferences.get_realtime_index_symbols() or self.CORE_INDEX_SYMBOLS)
+            all_index_symbols.update(core_index_symbols)
+            all_etf_symbols = set()
+            if self._repo:
+                etf_inst = self._repo.get_etf_instruments()
+                if not etf_inst.is_empty() and "symbol" in etf_inst.columns:
+                    all_etf_symbols = set(etf_inst["symbol"].cast(pl.Utf8).to_list())
+
+            universes: list[str] = []
+            if preferences.get_realtime_pull_stock():
+                universes.append("CN_Equity_A")
+            if preferences.get_realtime_pull_etf() and all_etf_symbols:
+                universes.append("CN_ETF")
+            if preferences.get_realtime_pull_index() and preferences.get_realtime_index_mode() == "all":
+                universes.append("CN_Index")
+
+            resp = []
+            if universes:
+                resp.extend(tf.quotes.get_by_universes(universes=universes) or [])
+            if preferences.get_realtime_pull_index() and preferences.get_realtime_index_mode() == "core":
+                resp.extend(tf.quotes.get(symbols=sorted(core_index_symbols)) or [])
         except Exception as e:  # noqa: BLE001
             logger.warning("行情拉取失败: %s", e)
             return
@@ -349,7 +393,11 @@ class QuoteService:
             })
 
         index_records = [r for r in records if r.get("symbol") in all_index_symbols]
-        stock_records = [r for r in records if r.get("symbol") not in all_index_symbols]
+        etf_records = [r for r in records if r.get("symbol") in all_etf_symbols]
+        stock_records = [
+            r for r in records
+            if r.get("symbol") not in all_index_symbols and r.get("symbol") not in all_etf_symbols
+        ]
 
         fetch_ms = (time.perf_counter() - t0) * 1000
         fetched_at = time.time() * 1000
@@ -361,9 +409,10 @@ class QuoteService:
             self._fetched_at = fetched_at
             self._symbol_count = len(stock_records)
             self._index_symbol_count = len(index_records)
+            self._etf_symbol_count = len(etf_records)
             self._index_quotes_cache = self._build_index_quotes(index_records)
 
-        logger.info("行情刷新: %d 只股票, %d 只指数, 耗时 %.0fms", len(stock_records), len(index_records), fetch_ms)
+        logger.info("行情刷新: %d 只股票, %d 只ETF, %d 只指数, 耗时 %.0fms", len(stock_records), len(etf_records), len(index_records), fetch_ms)
 
         # ---- 写 kline_daily (不复权原始价格, 只有 OHLCV) ----
         daily_df = self._build_daily(stock_records)
@@ -373,12 +422,22 @@ class QuoteService:
             except Exception as e:  # noqa: BLE001
                 logger.warning("日K写盘失败: %s", e)
 
+        etf_daily_df = self._build_daily(etf_records)
+        if not etf_daily_df.is_empty() and self._repo:
+            try:
+                self._repo.flush_live_daily_asset("etf", etf_daily_df)
+            except Exception as e:  # noqa: BLE001
+                logger.warning("ETF 日K写盘失败: %s", e)
+
         # ---- 构建 API 直接值的补充表 (不写 daily, 只用于 enriched 计算) ----
         quote_extra = self._build_quote_extra(stock_records)
+        etf_quote_extra = self._build_quote_extra(etf_records)
 
         # ---- 增量计算 enriched + 写盘 + 更新缓存 ----
         if not daily_df.is_empty() and self._repo:
-            self._flush_live_enriched(daily_df, quote_extra)
+            self._flush_live_enriched(daily_df, quote_extra, asset_type="stock")
+        if not etf_daily_df.is_empty() and self._repo:
+            self._flush_live_enriched(etf_daily_df, etf_quote_extra, asset_type="etf")
 
         # ---- 通知 SSE ----
         self._update_event.set()
@@ -386,6 +445,87 @@ class QuoteService:
         # ---- 策略监控 + 告警评估 ----
         self._evaluate_monitors(daily_df, quote_extra)
 
+    def _fetch_watchlist_quotes(self) -> None:
+        """Free 档自选股实时: 只拉取最多 5 个 symbols。"""
+        from app.services import preferences
+        from app.tickflow.client import get_paid_realtime_client
+
+        symbols = preferences.get_realtime_watchlist_symbols()
+        if not symbols:
+            logger.info("自选实时未配置标的, 跳过行情拉取")
+            return
+
+        tf = get_paid_realtime_client()
+        if tf is None:
+            logger.warning("自选实时拉取失败:未配置付费服务器 API Key")
+            return
+
+        t0 = time.perf_counter()
+        now_ts = time.perf_counter()
+        try:
+            resp = tf.quotes.get(symbols=symbols) or []
+        except Exception as e:  # noqa: BLE001
+            logger.warning("自选实时拉取失败: %s", e)
+            return
+
+        if not resp:
+            logger.warning("自选实时行情数据为空")
+            return
+
+        records = []
+        for q in resp:
+            ext = q.get("ext") or {}
+            last_price = q.get("last_price")
+            prev_close = q.get("prev_close")
+            change_amount = ext.get("change_amount")
+            change_pct = ext.get("change_pct")
+            if change_amount is None and last_price is not None and prev_close is not None:
+                change_amount = float(last_price) - float(prev_close)
+            if change_pct is None and change_amount is not None and prev_close not in (None, 0):
+                change_pct = float(change_amount) / float(prev_close) * 100
+            records.append({
+                "symbol": q.get("symbol"),
+                "name": q.get("name") or ext.get("name"),
+                "last_price": last_price,
+                "prev_close": prev_close,
+                "open": q.get("open"),
+                "high": q.get("high"),
+                "low": q.get("low"),
+                "volume": q.get("volume"),
+                "amount": q.get("amount"),
+                "change_pct": change_pct,
+                "change_amount": change_amount,
+                "amplitude": ext.get("amplitude"),
+                "turnover_rate": ext.get("turnover_rate"),
+                "timestamp": q.get("timestamp"),
+                "session": q.get("session"),
+            })
+
+        fetch_ms = (time.perf_counter() - t0) * 1000
+        fetched_at = time.time() * 1000
+        with self._lock:
+            self._fetch_time = now_ts
+            self._fetch_ms = fetch_ms
+            self._fetched_at = fetched_at
+            self._symbol_count = len(records)
+            self._index_symbol_count = 0
+            self._etf_symbol_count = 0
+            self._index_quotes_cache = None
+
+        logger.info("自选实时刷新: %d 只股票, 耗时 %.0fms", len(records), fetch_ms)
+
+        daily_df = self._build_daily(records)
+        quote_extra = self._build_quote_extra(records)
+        if not daily_df.is_empty() and self._repo:
+            try:
+                self._repo.merge_live_daily_asset("stock", daily_df)
+            except Exception as e:  # noqa: BLE001
+                logger.warning("自选实时日K写盘失败: %s", e)
+            self._flush_live_enriched(daily_df, quote_extra, asset_type="stock", merge=True)
+
+        self._update_event.set()
+        self._evaluate_monitors(daily_df, quote_extra)
+
     # ================================================================
     # 工具
     # ================================================================
@@ -537,8 +677,8 @@ class QuoteService:
                                 "severity": ev.get("severity", "info"),
                             })
 
-            # 刷新策略结果缓存 (实时行情开启时，每轮行情更新后自动重算)
-            if self._enabled and self._app_state:
+            # Free 自选实时只刷新少量标的, 不写全市场策略缓存。
+            if self._enabled and self._app_state and self.realtime_mode() == "full_market":
                 self._refresh_strategy_cache(enriched_today, enriched_date)
 
             # 推入待推送队列 + 通知 SSE (含背压保护)
@@ -690,7 +830,7 @@ class QuoteService:
     # enriched 增量计算
     # ================================================================
 
-    def _flush_live_enriched(self, daily_df: pl.DataFrame, quote_extra: pl.DataFrame = None) -> None:
+    def _flush_live_enriched(self, daily_df: pl.DataFrame, quote_extra: pl.DataFrame = None, asset_type: str = "stock", merge: bool = False) -> None:
         """增量计算今天的 enriched: 用昨天的递推状态 + 今天 OHLCV → 只算今天 5500 行。
 
         quote_extra: API 直接提供的补充字段 (prev_close, change_pct 等),
@@ -701,11 +841,16 @@ class QuoteService:
             t0 = time.perf_counter()
 
             # ---- 尝试增量路径 ----
-            live_agg = self._repo.get_live_agg()
-            prev_enriched, prev_date = self._repo.get_enriched_latest()
+            live_agg = self._repo.get_live_agg() if asset_type == "stock" else pl.DataFrame()
+            prev_enriched, prev_date = (
+                self._repo.get_enriched_latest()
+                if asset_type == "stock"
+                else self._repo.get_enriched_latest_asset(asset_type)
+            )
 
             use_incremental = (
-                not live_agg.is_empty()
+                asset_type == "stock"
+                and not live_agg.is_empty()
                 and not prev_enriched.is_empty()
                 and prev_date is not None
             )
@@ -736,7 +881,8 @@ class QuoteService:
                             "ok" if not live_agg.is_empty() else "空", prev_date)
 
                 cutoff = today - timedelta(days=90)
-                daily_glob = str(self._repo.store.data_dir / "kline_daily" / "**" / "*.parquet")
+                table = "kline_etf_daily" if asset_type == "etf" else "kline_daily"
+                daily_glob = str(self._repo.store.data_dir / table / "**" / "*.parquet")
                 ohlcv_cols = ["symbol", "date", "open", "high", "low", "close", "volume", "amount"]
                 hist_df = (
                     pl.scan_parquet(daily_glob)
@@ -753,14 +899,15 @@ class QuoteService:
                 full_df = pl.concat([hist_df, daily_ohlcv], how="diagonal_relaxed")
                 full_df = full_df.sort(["symbol", "date"])
 
-                factor_path = self._repo.store.data_dir / "adj_factor" / "all.parquet"
+                factor_dir = "adj_factor_etf" if asset_type == "etf" else "adj_factor"
+                factor_path = self._repo.store.data_dir / factor_dir / "all.parquet"
                 factors = pl.DataFrame()
                 if factor_path.exists():
                     try:
                         factors = pl.read_parquet(factor_path)
                     except Exception:
                         pass
-                instruments = self._repo.get_instruments()
+                instruments = self._repo.get_instruments() if asset_type == "stock" else None
 
                 enriched_full = compute_enriched(full_df, factors=factors, instruments=instruments)
                 enriched_today = enriched_full.filter(pl.col("date") == today)
@@ -769,7 +916,10 @@ class QuoteService:
                 return
 
             # ---- 写盘 + 更新缓存 ----
-            self._repo.flush_live_enriched(enriched_today)
+            if merge:
+                self._repo.merge_live_enriched_asset(asset_type, enriched_today)
+            else:
+                self._repo.flush_live_enriched_asset(asset_type, enriched_today)
 
             elapsed = time.perf_counter() - t0
             mode_label = "增量" if use_incremental else "全量"

backend/app/services/watchlist.py

@@ -63,6 +63,20 @@ def remove(symbol: str) -> list[dict]:
     return df.to_dicts()
 
 
+def move_to_top(symbol: str) -> list[dict]:
+    p = _path()
+    if not p.exists():
+        return []
+    df = pl.read_parquet(p)
+    if df.is_empty() or symbol not in df["symbol"].to_list():
+        return df.to_dicts()
+    target = df.filter(pl.col("symbol") == symbol)
+    rest = df.filter(pl.col("symbol") != symbol)
+    out = pl.concat([target, rest], how="diagonal_relaxed")
+    out.write_parquet(p)
+    return out.to_dicts()
+
+
 def clear() -> int:
     """清空自选列表。返回移除的数量。"""
     p = _path()

backend/app/tickflow/client.py

@@ -18,6 +18,7 @@ from app import secrets_store
 
 _sync_client: TickFlow | None = None
 _async_client: AsyncTickFlow | None = None
+_paid_realtime_client: TickFlow | None = None
 
 
 # ===== 服务器归属判定 =====
@@ -71,11 +72,27 @@ def get_async_client() -> AsyncTickFlow:
     return _async_client
 
 
+def get_paid_realtime_client() -> TickFlow | None:
+    """实时行情专用付费服务器客户端。
+
+    none/free 的历史日K仍走 get_client() 的 free-api；实时行情全部走付费服务器。
+    Free 档如果有有效 key，也使用这里的 paid endpoint 调按标的实时接口。
+    """
+    global _paid_realtime_client
+    key = secrets_store.get_tickflow_key()
+    if not key:
+        return None
+    if _paid_realtime_client is None:
+        _paid_realtime_client = TickFlow(api_key=key, base_url=_base_url())
+    return _paid_realtime_client
+
+
 def reset_clients() -> None:
     """Key 变化后调用 — 让下一次 get_client() 拿新实例。"""
-    global _sync_client, _async_client
+    global _sync_client, _async_client, _paid_realtime_client
     _sync_client = None
     _async_client = None
+    _paid_realtime_client = None
 
 
 def current_mode() -> str:

backend/app/tickflow/policy.py

@@ -31,9 +31,8 @@ _CAPSET_CACHE_FILE = "capabilities.json"
 # 旧缓存(无此字段或版本更低)会被判定过期,触发重新探测。
 # v2: 拆分 depth5 → depth5(单只) + depth5.batch(批量)
 # v3: 探测补全 quote.batch(此前 tiers.yaml 声明了但 _probe_real 漏探测)
-# v4: 5 档重构 —— 新增 none 档(无key/无效key),free 档重定义(走 free-api 服务器,
-#     仅历史日K)。判定改为复权因子分水岭:_classify_tier 接管档位判定。
-_CACHE_SCHEMA_VERSION = 4
+# v5: Free 档补充付费服务器 quote.by_symbol(10rpm/5标的),用于自选股实时监控。
+_CACHE_SCHEMA_VERSION = 5
 
 # 探测用最小代价请求:挑流通性最好的 1 只标的试
 _PROBE_SYMBOL = "600000.SH"  # 浦发银行,长期不会退市
@@ -278,7 +277,7 @@ def detect_capabilities(force: bool = False) -> CapabilitySet:
             _persist(capset, "None", log=probe_log, missing=[], extras=[], invalid_key=True)
             return capset
         if classified.is_free:
-            # 免费有效 key:能力按 free 档(= none 档能力,走 free-api 服务器)
+            # 免费有效 key:按 free 档能力持久化(日K free-api + 按标的实时)。
             capset = _tier_to_capset(tiers["free"])
             _persist(capset, "Free", log=probe_log + ["✓ 免费有效 key(运行时走 free-api 服务器)"], missing=[], extras=[])
             return capset

backend/app/tickflow/repository.py

@@ -38,11 +38,16 @@ class DataStore:
             "kline_daily_enriched",
             "kline_index_daily",
             "kline_index_enriched",
+            "kline_etf_daily",
+            "kline_etf_enriched",
+            "kline_etf_minute",
             "kline_minute",
             "adj_factor",
+            "adj_factor_etf",
             "financials",
             "instruments",
             "instruments_index",
+            "instruments_etf",
             "instruments_ext",
             "kline_ext",
             "pools",
@@ -74,14 +79,24 @@ class DataStore:
                 SELECT * FROM read_parquet('{d}/kline_index_daily/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW kline_index_enriched AS
                 SELECT * FROM read_parquet('{d}/kline_index_enriched/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW kline_etf_daily AS
+                SELECT * FROM read_parquet('{d}/kline_etf_daily/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW kline_etf_enriched AS
+                SELECT * FROM read_parquet('{d}/kline_etf_enriched/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW kline_etf_minute AS
+                SELECT * FROM read_parquet('{d}/kline_etf_minute/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW kline_minute AS
                 SELECT * FROM read_parquet('{d}/kline_minute/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW adj_factor AS
                 SELECT * FROM read_parquet('{d}/adj_factor/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW adj_factor_etf AS
+                SELECT * FROM read_parquet('{d}/adj_factor_etf/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW instruments AS
                 SELECT * FROM read_parquet('{d}/instruments/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW instruments_index AS
                 SELECT * FROM read_parquet('{d}/instruments_index/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW instruments_etf AS
+                SELECT * FROM read_parquet('{d}/instruments_etf/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW instruments_ext AS
                 SELECT * FROM read_parquet('{d}/instruments_ext/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW kline_ext AS
@@ -104,6 +119,91 @@ class DataStore:
                 self.db.execute(sql)
             except duckdb.IOException:
                 logger.debug("view registration skipped (no parquet yet): %s", sql[:60])
+        self._register_unified_views()
+
+    def _has_parquet(self, subdir: str) -> bool:
+        return any((self.data_dir / subdir).rglob("*.parquet"))
+
+    def _register_unified_views(self) -> None:
+        """Register optional all-asset views when their backing parquet exists.
+
+        Physical storage remains split for performance and compatibility. These
+        views are convenience read models for new APIs/features.
+        """
+        daily_parts: list[str] = []
+        enriched_parts: list[str] = []
+        minute_parts: list[str] = []
+        inst_parts: list[str] = []
+
+        if self._has_parquet("kline_daily"):
+            daily_parts.append("""
+                SELECT symbol, date, open, high, low, close, volume, amount,
+                       'stock' AS asset_type, 'tickflow' AS source
+                FROM kline_daily
+            """)
+        if self._has_parquet("kline_index_daily"):
+            daily_parts.append("""
+                SELECT symbol, date, open, high, low, close, volume, amount,
+                       'index' AS asset_type, 'tickflow' AS source
+                FROM kline_index_daily
+            """)
+        if self._has_parquet("kline_etf_daily"):
+            daily_parts.append("""
+                SELECT symbol, date, open, high, low, close, volume, amount,
+                       'etf' AS asset_type, 'tickflow' AS source
+                FROM kline_etf_daily
+            """)
+
+        if self._has_parquet("kline_daily_enriched"):
+            enriched_parts.append("SELECT *, 'stock' AS asset_type, 'tickflow' AS source FROM kline_enriched")
+        if self._has_parquet("kline_index_enriched"):
+            enriched_parts.append("SELECT *, 'index' AS asset_type, 'tickflow' AS source FROM kline_index_enriched")
+        if self._has_parquet("kline_etf_enriched"):
+            enriched_parts.append("SELECT *, 'etf' AS asset_type, 'tickflow' AS source FROM kline_etf_enriched")
+
+        if self._has_parquet("kline_minute"):
+            minute_parts.append("""
+                SELECT symbol, datetime, open, high, low, close, volume, amount,
+                       'stock' AS asset_type, 'tickflow' AS source
+                FROM kline_minute
+            """)
+        if self._has_parquet("kline_etf_minute"):
+            minute_parts.append("""
+                SELECT symbol, datetime, open, high, low, close, volume, amount,
+                       'etf' AS asset_type, 'tickflow' AS source
+                FROM kline_etf_minute
+            """)
+
+        if self._has_parquet("instruments"):
+            inst_parts.append("""
+                SELECT symbol, name, code, exchange, 'stock' AS asset_type, 'tickflow' AS source
+                FROM instruments
+            """)
+        if self._has_parquet("instruments_index"):
+            inst_parts.append("""
+                SELECT symbol, name, code, NULL AS exchange, 'index' AS asset_type, 'tickflow' AS source
+                FROM instruments_index
+                WHERE coalesce(asset_type, 'index') != 'etf'
+            """)
+        if self._has_parquet("instruments_etf"):
+            inst_parts.append("""
+                SELECT symbol, name, code, NULL AS exchange, 'etf' AS asset_type, 'tickflow' AS source
+                FROM instruments_etf
+            """)
+
+        unions = {
+            "kline_daily_all": daily_parts,
+            "kline_enriched_all": enriched_parts,
+            "kline_minute_all": minute_parts,
+            "instruments_all": inst_parts,
+        }
+        for name, parts in unions.items():
+            if not parts:
+                continue
+            try:
+                self.db.execute(f"CREATE OR REPLACE VIEW {name} AS " + " UNION ALL BY NAME ".join(parts))
+            except Exception as e:  # noqa: BLE001
+                logger.debug("unified view %s skipped: %s", name, e)
 
 
 class KlineRepository:
@@ -124,13 +224,21 @@ class KlineRepository:
         self._enriched_history_cache: pl.DataFrame | None = None  # ~100万行
         self._enriched_history_start: date | None = None
         self._index_instruments_cache: pl.DataFrame | None = None
+        self._etf_enriched_cache: pl.DataFrame | None = None
+        self._etf_enriched_cache_date: date | None = None
+        self._etf_live_agg_cache: pl.DataFrame | None = None
+        self._etf_live_agg_cache_date: date | None = None
+        self._etf_instruments_cache: pl.DataFrame | None = None
 
         # parquet glob 路径
         self._enriched_glob = str(store.data_dir / "kline_daily_enriched" / "**" / "*.parquet")
         self._index_enriched_glob = str(store.data_dir / "kline_index_enriched" / "**" / "*.parquet")
+        self._etf_enriched_glob = str(store.data_dir / "kline_etf_enriched" / "**" / "*.parquet")
         self._minute_glob = str(store.data_dir / "kline_minute" / "**" / "*.parquet")
+        self._etf_minute_glob = str(store.data_dir / "kline_etf_minute" / "**" / "*.parquet")
         self._inst_glob = str(store.data_dir / "instruments" / "**" / "*.parquet")
         self._index_inst_glob = str(store.data_dir / "instruments_index" / "**" / "*.parquet")
+        self._etf_inst_glob = str(store.data_dir / "instruments_etf" / "**" / "*.parquet")
 
     def execute_all(self, sql: str, params: list | None = None) -> list[tuple]:
         """线程安全的 SELECT → fetchall。DuckDB 单 connection 非线程安全，所有读路径须走此方法。"""
@@ -150,6 +258,7 @@ class KlineRepository:
         """刷新 Polars 缓存。在 pipeline 完成后、服务启动时调用。"""
         self._refresh_instruments()
         self._refresh_index_instruments()
+        self._refresh_etf_instruments()
         self._refresh_enriched()
 
     def clear_cache(self) -> None:
@@ -167,6 +276,11 @@ class KlineRepository:
         self._live_agg_cache_date = None
         self._instruments_cache = None
         self._index_instruments_cache = None
+        self._etf_enriched_cache = None
+        self._etf_enriched_cache_date = None
+        self._etf_live_agg_cache = None
+        self._etf_live_agg_cache_date = None
+        self._etf_instruments_cache = None
 
     def _refresh_enriched(self) -> None:
         """从 parquet 加载 enriched 最新日到内存 + 构建聚合表。
@@ -462,6 +576,47 @@ class KlineRepository:
 
         return df_hist, agg_a
 
+    def _refresh_etf_enriched(self) -> None:
+        """从 ETF enriched parquet 加载最新日到内存缓存。"""
+        try:
+            enriched_dir = self.store.data_dir / "kline_etf_enriched"
+            dates = sorted(
+                p.name[5:] for p in enriched_dir.glob("date=*")
+                if p.is_dir() and p.name.startswith("date=")
+            ) if enriched_dir.exists() else []
+            if not dates:
+                self._etf_enriched_cache = None
+                self._etf_enriched_cache_date = None
+                return
+            latest = date.fromisoformat(dates[-1])
+            target_parquet = enriched_dir / f"date={dates[-1]}" / "part.parquet"
+            df_latest = pl.read_parquet(target_parquet)
+            if df_latest.is_empty():
+                return
+
+            from datetime import timedelta
+            from app.indicators.pipeline import compute_indicators, compute_signals
+            start_full = latest - timedelta(days=300)
+            read_cols = [c for c in ["symbol", "date", "open", "high", "low", "close",
+                                     "volume", "amount", "raw_close", "raw_high", "raw_low"]
+                         if c in df_latest.columns]
+            df_hist = (
+                pl.scan_parquet(self._etf_enriched_glob,
+                                cast_options=pl.ScanCastOptions(integer_cast="allow-float"))
+                .filter(pl.col("date") >= start_full)
+                .select(read_cols)
+                .sort(["symbol", "date"])
+                .collect()
+            )
+            if df_hist.is_empty():
+                self._etf_enriched_cache = df_latest.sort(["symbol"])
+            else:
+                df_full = compute_signals(compute_indicators(df_hist))
+                self._etf_enriched_cache = df_full.filter(pl.col("date") == latest).sort(["symbol"])
+            self._etf_enriched_cache_date = latest
+        except Exception as e:  # noqa: BLE001
+            logger.debug("ETF enriched 缓存刷新跳过: %s", e)
+
     def _refresh_instruments(self) -> None:
         """加载 instruments 到内存。"""
         try:
@@ -482,6 +637,28 @@ class KlineRepository:
         except Exception as e:  # noqa: BLE001
             logger.debug("index instruments 缓存刷新跳过: %s", e)
 
+    def _refresh_etf_instruments(self) -> None:
+        """加载 ETF instruments 到内存；兼容旧版 instruments_index 中的 ETF。"""
+        parts: list[pl.DataFrame] = []
+        try:
+            df = pl.scan_parquet(self._etf_inst_glob).collect()
+            if not df.is_empty():
+                parts.append(df)
+        except Exception as e:  # noqa: BLE001
+            logger.debug("etf instruments 缓存刷新跳过(new): %s", e)
+        try:
+            legacy = self.get_index_instruments()
+            if not legacy.is_empty() and "asset_type" in legacy.columns:
+                legacy = legacy.filter(pl.col("asset_type") == "etf")
+                if not legacy.is_empty():
+                    parts.append(legacy)
+        except Exception as e:  # noqa: BLE001
+            logger.debug("etf instruments legacy fallback skipped: %s", e)
+        if parts:
+            df_all = pl.concat(parts, how="diagonal_relaxed").unique(subset=["symbol"], keep="last").sort("symbol")
+            self._etf_instruments_cache = df_all
+            logger.info("ETF instruments 缓存已加载: %d 只", len(df_all))
+
     def get_enriched_latest(self) -> tuple[pl.DataFrame, date | None]:
         """返回缓存的 enriched 最新日 DataFrame + 日期。如无缓存则懒加载。"""
         if self._enriched_cache is None:
@@ -490,6 +667,18 @@ class KlineRepository:
             return pl.DataFrame(), self._enriched_cache_date
         return self._enriched_cache, self._enriched_cache_date
 
+    def get_enriched_latest_asset(self, asset_type: str) -> tuple[pl.DataFrame, date | None]:
+        """按资产类型返回最新 enriched 缓存。stock 保持旧缓存语义。"""
+        if asset_type == "stock":
+            return self.get_enriched_latest()
+        if asset_type == "etf":
+            if self._etf_enriched_cache is None:
+                self._refresh_etf_enriched()
+            if self._etf_enriched_cache is None:
+                return pl.DataFrame(), self._etf_enriched_cache_date
+            return self._etf_enriched_cache, self._etf_enriched_cache_date
+        return pl.DataFrame(), None
+
     def get_enriched_history(self, target_date: date, lookback_days: int) -> pl.DataFrame | None:
         """返回预计算的 enriched 历史数据 (仅 lookback 范围, 不含 warmup)。
 
@@ -567,6 +756,27 @@ class KlineRepository:
             return pl.DataFrame()
         return self._index_instruments_cache
 
+    def get_etf_instruments(self) -> pl.DataFrame:
+        """返回缓存的 ETF instruments DataFrame；兼容旧版 instruments_index 中的 ETF。"""
+        if self._etf_instruments_cache is None:
+            self._refresh_etf_instruments()
+        if self._etf_instruments_cache is None:
+            return pl.DataFrame()
+        return self._etf_instruments_cache
+
+    def get_instruments_asset(self, asset_type: str) -> pl.DataFrame:
+        """按资产类型返回 instruments；老 stock 路径保持原样。"""
+        if asset_type == "stock":
+            return self.get_instruments()
+        if asset_type == "index":
+            df = self.get_index_instruments()
+            if not df.is_empty() and "asset_type" in df.columns:
+                return df.filter(pl.col("asset_type") != "etf")
+            return df
+        if asset_type == "etf":
+            return self.get_etf_instruments()
+        return pl.DataFrame()
+
     def get_index_symbol_set(self) -> set[str]:
         """返回已缓存指数 symbol 集合。"""
         df = self.get_index_instruments()
@@ -656,6 +866,45 @@ class KlineRepository:
             df = df.select(existing)
         return df
 
+    def get_etf_daily(
+        self,
+        symbol: str,
+        start: date,
+        end: date,
+        columns: list[str] | None = None,
+    ) -> pl.DataFrame:
+        """ETF 日K查询 — 优先读独立 ETF enriched，兼容旧版 index enriched 中的 ETF。"""
+        from datetime import timedelta
+
+        warmup_start = start - timedelta(days=150)
+        df = self._scan_etf_daily_symbol(symbol, warmup_start, end, None)
+        if df.is_empty():
+            # 旧版 ETF 曾存入 kline_index_enriched；没有独立数据时回退读取。
+            df = self._scan_index_daily_symbol(symbol, warmup_start, end, None)
+        if not df.is_empty():
+            df = self._compute_index_enriched_range(df)
+            df = df.filter((pl.col("date") >= start) & (pl.col("date") <= end))
+        if columns and not df.is_empty():
+            existing = [c for c in columns if c in df.columns]
+            df = df.select(existing)
+        return df
+
+    def get_daily_asset(
+        self,
+        asset_type: str,
+        symbol: str,
+        start: date,
+        end: date,
+        columns: list[str] | None = None,
+    ) -> pl.DataFrame:
+        if asset_type == "stock":
+            return self.get_daily(symbol, start, end, columns)
+        if asset_type == "index":
+            return self.get_index_daily(symbol, start, end, columns)
+        if asset_type == "etf":
+            return self.get_etf_daily(symbol, start, end, columns)
+        return pl.DataFrame()
+
     def get_minute(
         self,
         symbol: str,
@@ -770,6 +1019,23 @@ class KlineRepository:
             logger.warning("指数日K查询失败: %s", e)
             return pl.DataFrame()
 
+    def _scan_etf_daily_symbol(self, symbol: str, start: date, end: date, columns: list[str] | None) -> pl.DataFrame:
+        try:
+            lf = pl.scan_parquet(self._etf_enriched_glob,
+                                 cast_options=pl.ScanCastOptions(integer_cast="allow-float")).filter(
+                (pl.col("symbol") == symbol)
+                & (pl.col("date") >= start)
+                & (pl.col("date") <= end)
+            ).sort("date")
+            if columns:
+                schema_names = lf.collect_schema().names()
+                existing = [c for c in columns if c in schema_names]
+                lf = lf.select(existing)
+            return lf.collect()
+        except Exception as e:  # noqa: BLE001
+            logger.debug("ETF 日K查询跳过: %s", e)
+            return pl.DataFrame()
+
     def _merge_cached_and_scan(
         self,
         cached: pl.DataFrame,
@@ -911,6 +1177,39 @@ class KlineRepository:
         df_storage = df.select(storage_cols)
         self._write_daily_partition(df_storage, "kline_index_enriched")
 
+    def append_etf_daily(self, df: pl.DataFrame) -> None:
+        """按日分区写入 ETF 日K数据 (merge-upsert)。"""
+        if df.is_empty():
+            return
+        self._write_daily_partition(df, "kline_etf_daily")
+
+    def append_etf_enriched(self, df: pl.DataFrame) -> None:
+        """按日分区写入 ETF enriched 数据。磁盘仅写入基础行情窄表。"""
+        if df.is_empty():
+            return
+        from app.indicators.pipeline import ENRICHED_STORAGE_COLS
+        storage_cols = [c for c in ENRICHED_STORAGE_COLS if c in df.columns]
+        df_storage = df.select(storage_cols)
+        self._write_daily_partition(df_storage, "kline_etf_enriched")
+
+    def append_daily_asset(self, asset_type: str, df: pl.DataFrame) -> None:
+        """按资产类型写入日K；stock/index 保持旧目录兼容。"""
+        if asset_type == "stock":
+            self.append_daily(df)
+        elif asset_type == "index":
+            self.append_index_daily(df)
+        elif asset_type == "etf":
+            self.append_etf_daily(df)
+
+    def append_enriched_asset(self, asset_type: str, df: pl.DataFrame) -> None:
+        """按资产类型写入 enriched；stock/index 保持旧目录兼容。"""
+        if asset_type == "stock":
+            self.append_enriched(df)
+        elif asset_type == "index":
+            self.append_index_enriched(df)
+        elif asset_type == "etf":
+            self.append_etf_enriched(df)
+
     def save_index_instruments(self, df: pl.DataFrame) -> None:
         """保存指数标的维表。"""
         if df.is_empty() or "symbol" not in df.columns:
@@ -919,8 +1218,21 @@ class KlineRepository:
         out.parent.mkdir(parents=True, exist_ok=True)
         df.unique(subset=["symbol"], keep="last").sort("symbol").write_parquet(out)
         self._index_instruments_cache = None
+        self._etf_instruments_cache = None
         self._refresh_index_instruments()
 
+    def save_etf_instruments(self, df: pl.DataFrame) -> None:
+        """保存 ETF 标的维表到独立目录。"""
+        if df.is_empty() or "symbol" not in df.columns:
+            return
+        if "asset_type" not in df.columns:
+            df = df.with_columns(pl.lit("etf").alias("asset_type"))
+        out = self.store.data_dir / "instruments_etf" / "instruments_etf.parquet"
+        out.parent.mkdir(parents=True, exist_ok=True)
+        df.unique(subset=["symbol"], keep="last").sort("symbol").write_parquet(out)
+        self._etf_instruments_cache = None
+        self._refresh_etf_instruments()
+
     def refresh_index_views(self) -> None:
         """刷新指数相关 DuckDB 视图。"""
         d = self.store.data_dir.as_posix()
@@ -929,15 +1241,23 @@ class KlineRepository:
                 SELECT * FROM read_parquet('{d}/kline_index_daily/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW kline_index_enriched AS
                 SELECT * FROM read_parquet('{d}/kline_index_enriched/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW kline_etf_daily AS
+                SELECT * FROM read_parquet('{d}/kline_etf_daily/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW kline_etf_enriched AS
+                SELECT * FROM read_parquet('{d}/kline_etf_enriched/**/*.parquet', union_by_name=true)""",
             f"""CREATE OR REPLACE VIEW instruments_index AS
                 SELECT * FROM read_parquet('{d}/instruments_index/**/*.parquet', union_by_name=true)""",
+            f"""CREATE OR REPLACE VIEW instruments_etf AS
+                SELECT * FROM read_parquet('{d}/instruments_etf/**/*.parquet', union_by_name=true)""",
         ]
         for sql in statements:
             try:
                 with self._lock:
                     self.db.execute(sql)
             except Exception as e:  # noqa: BLE001
-                logger.debug("index view refresh skipped: %s", e)
+                logger.debug("index/etf view refresh skipped: %s", e)
+        with self._lock:
+            self.store._register_unified_views()
 
     def _write_daily_partition(self, df: pl.DataFrame, table: str) -> None:
         """按 date 分区写入 parquet，每个日期一个文件，支持 merge-upsert。"""
@@ -955,11 +1275,92 @@ class KlineRepository:
             date_df = date_df.sort(["symbol", "date"])
             date_df.write_parquet(out)
 
+    def merge_live_daily_asset(self, asset_type: str, df: pl.DataFrame) -> None:
+        """按 symbol 合并当天指定资产日K分区。用于少量自选实时，不覆盖全市场。"""
+        if df.is_empty() or "date" not in df.columns:
+            return
+        table = {
+            "stock": "kline_daily",
+            "index": "kline_index_daily",
+            "etf": "kline_etf_daily",
+        }.get(asset_type)
+        if not table:
+            return
+        base = self.store.data_dir / table
+        dt = df["date"][0]
+        ds = dt.isoformat() if hasattr(dt, "isoformat") else str(dt)
+        out = base / f"date={ds}" / "part.parquet"
+        out.parent.mkdir(parents=True, exist_ok=True)
+        date_df = df.sort(["symbol", "date"])
+        if out.exists():
+            existing = pl.read_parquet(out)
+            date_df = pl.concat([existing, date_df], how="diagonal_relaxed").unique(
+                subset=["symbol", "date"], keep="last"
+            )
+        date_df.sort(["symbol", "date"]).write_parquet(out)
+
+    def merge_live_enriched_asset(self, asset_type: str, df: pl.DataFrame) -> None:
+        """按 symbol 合并当天 enriched 分区和内存缓存。用于少量自选实时。"""
+        if df.is_empty() or "date" not in df.columns:
+            return
+        dt = df["date"][0]
+        if asset_type == "stock":
+            table = "kline_daily_enriched"
+            existing_cache = self._enriched_cache if self._enriched_cache_date == dt else pl.DataFrame()
+        elif asset_type == "etf":
+            table = "kline_etf_enriched"
+            existing_cache = self._etf_enriched_cache if self._etf_enriched_cache_date == dt else pl.DataFrame()
+        elif asset_type == "index":
+            table = "kline_index_enriched"
+            existing_cache = pl.DataFrame()
+        else:
+            return
+
+        merged_cache = df
+        if existing_cache is not None and not existing_cache.is_empty():
+            merged_cache = pl.concat([existing_cache, df], how="diagonal_relaxed").unique(
+                subset=["symbol", "date"], keep="last"
+            )
+        merged_cache = merged_cache.sort(["symbol"])
+        if asset_type == "stock":
+            self._enriched_cache = merged_cache
+            self._enriched_cache_date = dt
+        elif asset_type == "etf":
+            self._etf_enriched_cache = merged_cache
+            self._etf_enriched_cache_date = dt
+
+        from app.indicators.pipeline import ENRICHED_STORAGE_COLS
+        storage_cols = [c for c in ENRICHED_STORAGE_COLS if c in df.columns]
+        df_storage = df.select(storage_cols).sort(["symbol"])
+        base = self.store.data_dir / table
+        ds = dt.isoformat() if hasattr(dt, "isoformat") else str(dt)
+        out = base / f"date={ds}" / "part.parquet"
+        out.parent.mkdir(parents=True, exist_ok=True)
+        if out.exists():
+            existing = pl.read_parquet(out)
+            df_storage = pl.concat([existing, df_storage], how="diagonal_relaxed").unique(
+                subset=["symbol", "date"], keep="last"
+            )
+        df_storage.sort(["symbol"]).write_parquet(out)
+
     def flush_live_daily(self, df: pl.DataFrame) -> None:
         """覆写当天 kline_daily 分区 (实时行情落盘, 非merge)。"""
         if df.is_empty() or "date" not in df.columns:
             return
-        base = self.store.data_dir / "kline_daily"
+        self.flush_live_daily_asset("stock", df)
+
+    def flush_live_daily_asset(self, asset_type: str, df: pl.DataFrame) -> None:
+        """覆写当天指定资产日K分区 (实时行情落盘, 非merge)。"""
+        if df.is_empty() or "date" not in df.columns:
+            return
+        table = {
+            "stock": "kline_daily",
+            "index": "kline_index_daily",
+            "etf": "kline_etf_daily",
+        }.get(asset_type)
+        if not table:
+            return
+        base = self.store.data_dir / table
         dt = df["date"][0]
         ds = dt.isoformat() if hasattr(dt, "isoformat") else str(dt)
         out = base / f"date={ds}" / "part.parquet"
@@ -971,17 +1372,30 @@ class KlineRepository:
 
         内存缓存保留完整指标列供各服务使用，磁盘仅写入 14 列存储列。
         """
+        self.flush_live_enriched_asset("stock", df)
+
+    def flush_live_enriched_asset(self, asset_type: str, df: pl.DataFrame) -> None:
+        """覆写当天指定资产 enriched 分区 (实时 enriched 落盘, 非merge)。"""
         if df.is_empty() or "date" not in df.columns:
             return
-        # 内存缓存: 保留完整 66 列
-        self._enriched_cache = df.sort(["symbol"])
         dt = df["date"][0]
-        self._enriched_cache_date = dt
-        # 磁盘写入: 仅 14 列存储列
+        if asset_type == "stock":
+            self._enriched_cache = df.sort(["symbol"])
+            self._enriched_cache_date = dt
+            table = "kline_daily_enriched"
+        elif asset_type == "etf":
+            self._etf_enriched_cache = df.sort(["symbol"])
+            self._etf_enriched_cache_date = dt
+            table = "kline_etf_enriched"
+        elif asset_type == "index":
+            table = "kline_index_enriched"
+        else:
+            return
+
         from app.indicators.pipeline import ENRICHED_STORAGE_COLS
         storage_cols = [c for c in ENRICHED_STORAGE_COLS if c in df.columns]
         df_storage = df.select(storage_cols).sort(["symbol"])
-        base = self.store.data_dir / "kline_daily_enriched"
+        base = self.store.data_dir / table
         ds = dt.isoformat() if hasattr(dt, "isoformat") else str(dt)
         out = base / f"date={ds}" / "part.parquet"
         out.parent.mkdir(parents=True, exist_ok=True)

backend/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "tickflow-stock-panel-backend"
-version = "0.1.53"
+version = "0.1.60"
 description = "A 股选股 + 监控 + 回测面板 — TickFlow 适配"
 readme = "../README.md"
 requires-python = ">=3.11"

backend/uv.lock

@@ -2491,7 +2491,7 @@ all = [
 
 [[package]]
 name = "tickflow-stock-panel-backend"
-version = "0.1.45"
+version = "0.1.60"
 source = { editable = "." }
 dependencies = [
     { name = "apscheduler" },

frontend/package.json

@@ -1,7 +1,7 @@
 {
   "name": "tickflow-stock-panel-frontend",
   "private": true,
-  "version": "0.1.53",
+  "version": "0.1.60",
   "type": "module",
   "scripts": {
     "dev": "vite",

frontend/src/components/Layout.tsx

@@ -29,7 +29,6 @@ import {
   Settings,
   Key,
   Database,
-  Timer,
   Loader2,
   LayoutDashboard,
   Tags,
@@ -42,6 +41,8 @@ import {
   Cable,
   RadioTower,
   CheckCircle2,
+  BookOpenCheck,
+  ExternalLink,
 } from 'lucide-react'
 import { Logo } from './Logo'
 import { api, type IndexQuote } from '@/lib/api'
@@ -50,6 +51,7 @@ import { setCurrentTotal as setAlertTotal, useUnreadAlerts } from '@/lib/monitor
 
 // 品牌色 — 只用于 logo / brand 区域,不影响功能语义色
 const BRAND = '#8B5CF6'
+const TICKFLOW_REGISTER_URL = 'https://tickflow.org/auth/register?ref=V3KDKGXPEA'
 
 const CORE_INDEXES = [
   { symbol: '000001.SH', name: '上证指数' },
@@ -65,14 +67,15 @@ const nav = [
   { to: '/watchlist',  label: '自选',   icon: Star },
   { to: '/screener',   label: '策略',   icon: ScanSearch },
   { to: '/backtest',   label: '回测',   icon: History },
+  { to: '/stock-analysis',    label: '个股分析', icon: TrendingUp },
   { to: '/limit-ladder', label: '连板梯队', icon: Flame },
   { to: '/concept-analysis', label: '概念分析', icon: Layers3 },
   { to: '/industry-analysis', label: '行业分析', icon: Landmark },
-  { to: '/stock-analysis',    label: '个股分析', icon: TrendingUp },
   { to: '/financials', label: '财务分析', icon: FileText },
+  { to: '/monitor', label: '监控中心', icon: RadioTower },
+  { to: '/review',      label: '复盘',   icon: BookOpenCheck },
   { to: '/indices', label: '指数', icon: BarChart3 },
   { to: '/trading', label: '交易', icon: Cable },
-  { to: '/monitor', label: '监控中心', icon: RadioTower },
   { to: '/data',       label: '数据',   icon: Database },
 ] as const
 
@@ -156,7 +159,7 @@ function TierBadge({ label, hasKey }: { label: string; hasKey?: boolean }) {
       labelTextStyle: { color: '#71717a' },
     },
     free: {
-      desc: '基础日K · 单股查询',
+      desc: '基础日K · 自选实时',
       tagBg: { background: 'rgba(113,113,122,0.3)' },
       dotStyle: { background: '#71717a' },
       labelTextStyle: { color: '#a1a1aa' },
@@ -182,8 +185,8 @@ function TierBadge({ label, hasKey }: { label: string; hasKey?: boolean }) {
   }
 
   const t = tierConfig[base] || tierConfig.none
-  // none 档显示中文「无」,无 label 时显示「无档」
-  const displayLabel = isNone ? '无' : (label || '无')
+  // none 档显示英文「None」,无 label 时也显示「None」
+  const displayLabel = isNone ? 'None' : (label || 'None')
 
   return (
     <NavLink
@@ -310,8 +313,10 @@ export function Layout() {
   const toggleQuote = useToggleRealtimeQuotes()
   const isRunning = quoteStatus?.running ?? false
   const isTrading = quoteStatus?.is_trading_hours ?? false
-  // none/free 档(无实时行情权限)→ rank < starter(1)
-  const isFreeTier = tierRank(caps?.label ?? '') < 1
+  const tier = tierRank(caps?.label ?? '')
+  const isNoneTier = tier < 0
+  const isWatchlistMode = tier === 0
+  const realtimeModeLabel = isWatchlistMode ? '自选股' : '全市场'
 
   // 轮询触发记录总数 → 更新监控中心徽标 (每 15 秒)
   const alertsTotalQuery = useQuery({
@@ -356,7 +361,12 @@ export function Layout() {
         queryKey: QK.capabilities,
         queryFn: api.capabilities,
       })
-      if (tierRank(fresh.label ?? '') < 1) return
+      const freshTier = tierRank(fresh.label ?? '')
+      if (freshTier < 0) return
+      if (freshTier === 0 && (prefs?.realtime_watchlist_symbols?.length ?? 0) === 0) {
+        navigate('/watchlist')
+        return
+      }
     }
     await toggleQuote.mutateAsync(enabled)
     // 仅在交易时段立即获取一次行情
@@ -423,7 +433,7 @@ export function Layout() {
                   <Icon className="h-4 w-4 shrink-0" />
                   <span className="flex-1">{label}</span>
                   {/* 个股分析 Beta 标识 */}
-                  {to === '/stock-analysis' && (
+                  {(to === '/stock-analysis' || to === '/review') && (
                     <span className="inline-flex items-center rounded-full border border-amber-400/30 bg-amber-400/10 px-1.5 py-0.5 text-[9px] font-semibold uppercase tracking-wider text-amber-400 shrink-0">
                       Beta
                     </span>
@@ -445,13 +455,27 @@ export function Layout() {
 
         {/* 全局行情开关 */}
         <div className="border-t border-border px-3 py-2.5 shrink-0">
-          {isFreeTier ? (
-            /* Free 档位 — 显示升级提示 */
-            <div className="flex items-center justify-between">
-              <span className="text-xs text-secondary truncate">实时行情</span>
-              <span className="text-[10px] text-accent/70 font-medium bg-accent/10 px-1.5 py-0.5 rounded">
-                需 Starter+
-              </span>
+          {isNoneTier ? (
+            <div>
+              <div className="flex items-center justify-between">
+                <span className="text-xs text-secondary truncate">实时行情</span>
+                <span className="text-[10px] text-accent/70 font-medium bg-accent/10 px-1.5 py-0.5 rounded">
+                  Free+
+                </span>
+              </div>
+              <div className="mt-1.5 text-[10px] leading-snug text-muted">
+                免费注册
+                <a
+                  href={TICKFLOW_REGISTER_URL}
+                  target="_blank"
+                  rel="noreferrer"
+                  className="mx-1 inline-flex items-baseline gap-0.5 text-accent/80 hover:text-accent hover:underline"
+                >
+                  TickFlow
+                  <ExternalLink className="h-2.5 w-2.5 self-center" />
+                </a>
+                开启个股监控
+              </div>
             </div>
           ) : (
             /* Starter+ — 开关 + 跳转设置 */
@@ -465,14 +489,14 @@ export function Layout() {
                       : 'bg-muted'
                 }`} />
                 <span className="text-xs text-secondary truncate">
-                  实时行情
+                  实时行情 · {realtimeModeLabel}
                 </span>
                 <button
                   onClick={() => navigate('/settings?tab=monitoring')}
                   className="text-secondary hover:text-foreground transition-colors shrink-0"
                   title="实时监控设置"
                 >
-                  <Timer className="h-3 w-3" />
+                  <Settings className="h-3 w-3" />
                 </button>
               </div>
               <button
@@ -492,7 +516,7 @@ export function Layout() {
           )}
 
           {/* 状态提示 */}
-          {realtimeEnabled && !isFreeTier && (
+          {realtimeEnabled && !isNoneTier && (
             <div className="mt-1.5 text-[10px] leading-snug">
               {isRunning && isTrading ? (
                 <span className="text-accent">行情运行中</span>
@@ -501,7 +525,7 @@ export function Layout() {
               ) : null}
             </div>
           )}
-          {showSidebarQuotes && !isFreeTier && (
+          {showSidebarQuotes && !isWatchlistMode && !isNoneTier && (
             <SidebarIndexQuotes rows={sidebarIndexQuotes?.rows} items={sidebarIndexes} />
           )}
         </div>

frontend/src/components/data/ActiveJobCard.tsx

@@ -8,7 +8,7 @@ import type { PipelineJob } from '@/lib/api'
 export const STAGE_LABELS: Record<string, string> = {
   init: '初始化',
   resolve_universe: '解析标的池',
-  sync_instruments: '同步标的维表',
+  sync_instruments: '同步个股维表',
   sync_daily: '同步日 K',
   sync_adj: '同步除权因子',
   compute_enriched: '计算技术指标',

frontend/src/components/data/PageSettingsModal.tsx

@@ -0,0 +1,121 @@
+import { useState } from 'react'
+import { Check } from 'lucide-react'
+import { storage } from '@/lib/storage'
+
+export type CardKey =
+  | 'instruments' | 'daily' | 'adj_factor' | 'enriched'
+  | 'index' | 'etf' | 'minute' | 'financials'
+
+interface CardDef {
+  key: CardKey
+  label: string
+  desc: string
+  /** 档位能力不足时该卡片是否默认隐藏(减少干扰) */
+  defaultHiddenIfNoCap: boolean
+}
+
+/** 数据画像卡片定义 —— 顺序即弹窗展示顺序 */
+export const DATA_CARD_DEFS: CardDef[] = [
+  { key: 'instruments', label: '个股维表', desc: 'A 股股票元数据', defaultHiddenIfNoCap: false },
+  { key: 'daily',       label: '日 K',     desc: 'A 股日K线数据',          defaultHiddenIfNoCap: false },
+  { key: 'enriched',    label: 'Enriched', desc: '技术指标计算结果',       defaultHiddenIfNoCap: false },
+  { key: 'index',       label: '指数',     desc: '主要市场指数日K',        defaultHiddenIfNoCap: false },
+  { key: 'etf',         label: 'ETF',      desc: '场内交易基金日K',         defaultHiddenIfNoCap: false },
+  { key: 'adj_factor',  label: '除权因子', desc: '复权计算因子',           defaultHiddenIfNoCap: true },
+  { key: 'minute',      label: '分钟 K',   desc: '分钟级K线(需 Pro+)',     defaultHiddenIfNoCap: true },
+  { key: 'financials',  label: '财务数据', desc: '财报数据(需 Expert)',    defaultHiddenIfNoCap: true },
+]
+
+const CAP_KEY_MAP: Partial<Record<CardKey, string>> = {
+  adj_factor: 'adj_factor',
+  minute: 'kline.minute.batch',
+  financials: 'financial',
+}
+
+/**
+ * 读取卡片显隐状态。结合档位能力决定默认值:
+ * - 用户显式设置过 → 用设置值
+ * - 未设置 + defaultHiddenIfNoCap + 当前无能力 → 隐藏
+ * - 其他 → 显示
+ */
+export function getCardVisibility(
+  caps: Record<string, unknown> | undefined,
+): Record<string, boolean> {
+  const has = (capKey: string) => !capKey || !!caps?.[capKey]
+  const override = storage.dataCardVisible.get({})
+  const result: Record<string, boolean> = {}
+  for (const def of DATA_CARD_DEFS) {
+    if (def.key in override) {
+      result[def.key] = override[def.key]
+    } else {
+      result[def.key] = def.defaultHiddenIfNoCap ? has(CAP_KEY_MAP[def.key] ?? '') : true
+    }
+  }
+  return result
+}
+
+export function PageSettingsModal({
+  caps,
+}: {
+  caps: Record<string, unknown> | undefined
+}) {
+  const [visible, setVisible] = useState<Record<string, boolean>>(() => getCardVisibility(caps))
+
+  const toggle = (key: CardKey) => {
+    const next = { ...visible, [key]: !visible[key] }
+    setVisible(next)
+    storage.dataCardVisible.set(next)
+    window.dispatchEvent(new CustomEvent('data-card-visible-change'))
+  }
+
+  const reset = () => {
+    storage.dataCardVisible.set({})
+    setVisible(getCardVisibility(caps))
+    window.dispatchEvent(new CustomEvent('data-card-visible-change'))
+  }
+
+  return (
+    <div className="space-y-2.5">
+      <p className="text-xs text-secondary leading-relaxed">
+        勾选要在数据画像区显示的卡片。未勾选的卡片将隐藏,不影响数据本身。
+      </p>
+      <div className="space-y-1.5">
+        {DATA_CARD_DEFS.map((def) => {
+          const on = visible[def.key] ?? true
+          return (
+            <label
+              key={def.key}
+              className={`flex items-center gap-2.5 rounded-card border px-3 py-2 cursor-pointer transition-colors ${
+                on ? 'border-accent/40 bg-accent/[0.05]' : 'border-border bg-base/30 hover:border-border/70'
+              }`}
+            >
+              <button
+                type="button"
+                onClick={() => toggle(def.key)}
+                className={`flex h-4 w-4 shrink-0 items-center justify-center rounded border transition-colors ${
+                  on ? 'bg-accent border-accent' : 'bg-base border-border'
+                }`}
+                role="checkbox"
+                aria-checked={on}
+              >
+                {on && <Check className="h-3 w-3 text-white" strokeWidth={3} />}
+              </button>
+              <div className="min-w-0 flex-1">
+                <div className="text-xs font-medium text-foreground">{def.label}</div>
+                <div className="text-[10px] text-muted leading-snug">{def.desc}</div>
+              </div>
+            </label>
+          )
+        })}
+      </div>
+      <div className="flex items-center justify-end pt-1">
+        <button
+          onClick={reset}
+          className="px-2 py-0.5 rounded-btn text-[10px] text-secondary hover:text-foreground transition-colors"
+        >
+          恢复默认
+        </button>
+      </div>
+    </div>
+  )
+}

frontend/src/components/data/PipelineScopeConfig.tsx

@@ -0,0 +1,86 @@
+import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query'
+import { Check, Loader2 } from 'lucide-react'
+import { api } from '@/lib/api'
+import { QK } from '@/lib/queryKeys'
+
+type PullKey = 'pipeline_pull_a_share' | 'pipeline_pull_etf' | 'pipeline_pull_index'
+
+interface ScopeItem {
+  key: PullKey
+  label: string
+  desc: string
+  defaultOn: boolean
+}
+
+const ITEMS: ScopeItem[] = [
+  { key: 'pipeline_pull_a_share', label: 'A股', desc: '沪深京 A 股日K(约 5500 只)', defaultOn: true },
+  { key: 'pipeline_pull_index', label: '指数', desc: '主要市场指数(默认全量约 600 只)', defaultOn: true },
+  { key: 'pipeline_pull_etf', label: 'ETF', desc: '场内交易基金(约 1500 只,首次较慢)', defaultOn: false },
+]
+
+export function PipelineScopeConfig() {
+  const qc = useQueryClient()
+  const prefs = useQuery({ queryKey: QK.preferences, queryFn: api.preferences })
+
+  const updateToggle = useMutation({
+    mutationFn: (cfg: Partial<Record<PullKey, boolean>>) => api.updatePipelinePullTypes(cfg),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: QK.preferences })
+      qc.invalidateQueries({ queryKey: QK.dataStatus })
+    },
+  })
+
+  const getValue = (key: PullKey, def: boolean) => prefs.data?.[key] ?? def
+
+  return (
+    <div className="space-y-2.5">
+      <p className="text-xs text-secondary leading-relaxed">
+        勾选盘后管道每次自动拉取的数据类型。仅影响后续同步,已存储的历史数据不受影响。
+      </p>
+      <div className="space-y-1.5">
+        {ITEMS.map((item) => {
+          const locked = item.key === 'pipeline_pull_a_share'
+          const on = locked || getValue(item.key, item.defaultOn)
+          return (
+            <div key={item.key}>
+              <label
+                className={`flex items-start gap-2.5 rounded-card border px-3 py-2.5 transition-colors ${
+                  locked ? 'cursor-default' : 'cursor-pointer'
+                } ${on ? 'border-accent/40 bg-accent/[0.05]' : 'border-border bg-base/30 hover:border-border/70'}`}
+              >
+                <button
+                  type="button"
+                  onClick={() => {
+                    if (!locked) updateToggle.mutate({ [item.key]: !on } as never)
+                  }}
+                  disabled={locked || updateToggle.isPending}
+                  className={`mt-0.5 flex h-4 w-4 shrink-0 items-center justify-center rounded border transition-colors ${
+                    on ? 'bg-accent border-accent' : 'bg-base border-border'
+                  } ${locked ? 'opacity-80' : ''}`}
+                  role="checkbox"
+                  aria-checked={on}
+                >
+                  {on && <Check className="h-3 w-3 text-white" strokeWidth={3} />}
+                </button>
+                <div className="min-w-0 flex-1">
+                  <div className="flex items-center gap-1.5">
+                    <span className="text-xs font-medium text-foreground">{item.label}</span>
+                  </div>
+                  <div className="text-[10px] text-muted leading-snug mt-0.5">{item.desc}</div>
+                </div>
+              </label>
+            </div>
+          )
+        })}
+      </div>
+      {updateToggle.isPending && (
+        <div className="flex items-center gap-1.5 text-[10px] text-muted">
+          <Loader2 className="h-3 w-3 animate-spin" />保存中…
+        </div>
+      )}
+      <div className="text-[10px] text-muted leading-relaxed pt-1">
+        数据通道基于免费接口,所有档位均可拉取。
+      </div>
+    </div>
+  )
+}

frontend/src/components/data/SchemaModal.tsx

@@ -4,7 +4,7 @@ import { api, type EnrichedField } from '@/lib/api'
 import { QK } from '@/lib/queryKeys'
 
 const TABLE_TITLES: Record<string, string> = {
-  instruments: '标的维表',
+  instruments: '个股维表',
   daily: '日 K',
   adj_factor: '除权因子',
   enriched: 'Enriched',
@@ -12,6 +12,9 @@ const TABLE_TITLES: Record<string, string> = {
   index_instruments: '指数维表',
   index_daily: '指数日 K',
   index_enriched: '指数 Enriched',
+  etf_instruments: 'ETF 维表',
+  etf_daily: 'ETF 日 K',
+  etf_enriched: 'ETF Enriched',
 }
 
 function categorize(name: string): string {

frontend/src/components/data/StatCard.tsx

@@ -5,7 +5,7 @@ import { fmtDate } from '@/lib/format'
 import { Skeleton } from './Skeleton'
 
 // 卡片能力定义：capKey → 查 capability limits；tierReq → 无权限时显示的档位要求
-// capKey 为空串表示该数据在 free-api 服务器(无档/免费档)即可获取,无需付费能力门控。
+// capKey 为空串表示该数据在 free-api 服务器(None 档/Free 档)即可获取,无需付费能力门控。
 export const CARD_META: Record<string, {
   capKey: string   // 对应的 capability key，空串表示本地计算 / free 服务器可用
   tierReq: string  // 最低档位要求（无权限时显示）
@@ -15,6 +15,8 @@ export const CARD_META: Record<string, {
   daily:       { capKey: 'kline.daily.batch',       tierReq: 'Starter+' },
   adj_factor:  { capKey: 'adj_factor',              tierReq: 'Starter+' },
   enriched:    { capKey: '',                        tierReq: '' },
+  // ETF 复用日K批量能力(免费档 kline.daily.batch 即可),不显示档位徽章
+  etf:         { capKey: 'kline.daily.batch',       tierReq: '' },
   minute:      { capKey: 'kline.minute.batch',      tierReq: 'Pro+' },
   financials:  { capKey: 'financial',                tierReq: 'Expert' },
 }

frontend/src/lib/api.ts

@@ -196,6 +196,7 @@ export interface WatchlistEntry {
   symbol: string
   added_at: string
   note?: string
+  name?: string | null
 }
 
 export interface Quote {
@@ -317,6 +318,18 @@ export interface OverviewMarket {
   industry_rank: { leading: OverviewDimensionRankItem[]; lagging: OverviewDimensionRankItem[] }
 }
 
+// ===== 大盘复盘 =====
+export interface AiReviewReport {
+  id: string
+  as_of: string
+  focus?: string
+  content: string
+  summary?: string
+  emotion_score?: number | null
+  emotion_label?: string
+  created_at: string
+}
+
 // ===== Strategy Engine =====
 export interface StrategyParamDef {
   id: string
@@ -642,6 +655,20 @@ export interface Preferences {
   indices_nav_pinned: boolean
   minute_sync_enabled: boolean
   minute_sync_days: number
+  daily_data_provider?: string
+  adj_factor_provider?: string
+  minute_data_provider?: string
+  realtime_data_provider?: string
+  realtime_watchlist_symbols?: string[]
+  realtime_pull_stock?: boolean
+  realtime_pull_etf?: boolean
+  realtime_pull_index?: boolean
+  realtime_index_mode?: 'core' | 'all'
+  realtime_index_symbols?: string[]
+  pipeline_pull_a_share: boolean
+  pipeline_pull_etf: boolean
+  pipeline_pull_index: boolean
+  pipeline_index_symbols: string
   pipeline_schedule: { hour: number; minute: number }
   instruments_schedule: { hour: number; minute: number }
   enriched_batch_size: number
@@ -708,11 +735,30 @@ export const api = {
       method: 'PUT',
       body: JSON.stringify({ minute_sync_enabled: enabled, minute_sync_days: days }),
     }),
+  updatePipelinePullTypes: (cfg: Partial<Pick<Preferences, 'pipeline_pull_a_share' | 'pipeline_pull_etf' | 'pipeline_pull_index'>>) =>
+    request<{
+      pipeline_pull_a_share: boolean
+      pipeline_pull_etf: boolean
+      pipeline_pull_index: boolean
+    }>('/api/settings/preferences/pipeline-pull-types', {
+      method: 'PUT',
+      body: JSON.stringify(cfg),
+    }),
+  updatePipelineIndexSymbols: (symbols: string) =>
+    request<{ pipeline_index_symbols: string }>('/api/settings/preferences/pipeline-index-symbols', {
+      method: 'PUT',
+      body: JSON.stringify({ symbols }),
+    }),
   updateRealtimeQuotes: (enabled: boolean) =>
-    request<{ realtime_quotes_enabled: boolean }>('/api/settings/preferences/realtime-quotes', {
+    request<{ realtime_quotes_enabled: boolean; realtime_allowed?: boolean; mode?: string; error?: string }>('/api/settings/preferences/realtime-quotes', {
       method: 'PUT',
       body: JSON.stringify({ realtime_quotes_enabled: enabled }),
     }),
+  updateRealtimeQuoteScope: (cfg: Partial<Pick<Preferences, 'realtime_pull_stock' | 'realtime_pull_etf' | 'realtime_pull_index' | 'realtime_index_mode' | 'realtime_index_symbols'>>) =>
+    request<Partial<Preferences>>('/api/settings/preferences/realtime-quote-scope', {
+      method: 'PUT',
+      body: JSON.stringify(cfg),
+    }),
   updateIndicesNavPinned: (pinned: boolean) =>
     request<{ indices_nav_pinned: boolean }>('/api/settings/preferences/indices-nav-pinned', {
       method: 'PUT',
@@ -722,9 +768,13 @@ export const api = {
     request<{
       enabled: boolean
       running: boolean
+      mode?: 'none' | 'watchlist' | 'full_market'
+      realtime_allowed?: boolean
       interval_s: number
       symbol_count: number
+      watchlist_symbol_count?: number
       index_symbol_count?: number
+      etf_symbol_count?: number
       quote_age_ms: number | null
       is_trading_hours: boolean
       last_fetch_ms: number | null
@@ -951,6 +1001,11 @@ export const api = {
       `/api/watchlist/${encodeURIComponent(symbol)}`,
       { method: 'DELETE' },
     ),
+  watchlistMoveToTop: (symbol: string) =>
+    request<{ symbols: WatchlistEntry[] }>(
+      `/api/watchlist/${encodeURIComponent(symbol)}/top`,
+      { method: 'POST' },
+    ),
   watchlistClear: () =>
     request<{ removed: number }>('/api/watchlist', { method: 'DELETE' }),
   watchlistQuotes: () => request<{ quotes: Quote[] }>('/api/watchlist/quotes'),
@@ -1372,6 +1427,68 @@ export const api = {
     }
   },
 
+  // ===== 大盘复盘 =====
+  reviewReportsList: () =>
+    request<{ reports: AiReviewReport[] }>('/api/market-recap/reports'),
+
+  reviewReportSave: (r: {
+    as_of: string; focus?: string; content: string
+    summary?: string; emotion_score?: number | null; emotion_label?: string
+  }) =>
+    request<{ ok: boolean; report: AiReviewReport }>('/api/market-recap/reports', {
+      method: 'POST', body: JSON.stringify(r),
+    }),
+
+  reviewReportDelete: (reportId: string) =>
+    request<{ ok: boolean }>(`/api/market-recap/reports/${encodeURIComponent(reportId)}`, { method: 'DELETE' }),
+
+  /**
+   * AI 大盘复盘 — 流式调用(NDJSON,与个股/财务分析同协议)。
+   * meta 里带 as_of / emotion_score / emotion_label / summary,供前端先渲染信号灯。
+   */
+  async *reviewStream(asOf?: string, focus?: string): AsyncGenerator<{
+    type: 'meta' | 'delta' | 'error' | 'done'
+    as_of?: string
+    emotion_score?: number
+    emotion_label?: string
+    summary?: string
+    content?: string
+    message?: string
+  }> {
+    const res = await fetch('/api/market-recap/analyze', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ as_of: asOf ?? null, focus: focus ?? '' }),
+    })
+    if (!res.ok) {
+      let detail = ''
+      try { const j = JSON.parse(await res.text()); detail = j.detail ?? j.message ?? '' } catch { /* ignore */ }
+      const msg = detail || `${res.status} ${res.statusText}`
+      toast(msg, 'error')
+      throw new Error(msg)
+    }
+    if (!res.body) throw new Error('响应无 body')
+
+    const reader = res.body.getReader()
+    const decoder = new TextDecoder()
+    let buf = ''
+    for (;;) {
+      const { done, value } = await reader.read()
+      if (done) break
+      buf += decoder.decode(value, { stream: true })
+      const lines = buf.split('\n')
+      buf = lines.pop() ?? ''
+      for (const line of lines) {
+        const s = line.trim()
+        if (!s) continue
+        try { yield JSON.parse(s) } catch { /* ignore */ }
+      }
+    }
+    if (buf.trim()) {
+      try { yield JSON.parse(buf.trim()) } catch { /* ignore */ }
+    }
+  },
+
   // ===== Strategy Engine =====
   strategyList: () =>
     request<{ strategies: StrategyDetail[] }>('/api/strategies'),
@@ -1540,6 +1657,9 @@ export interface DataStatus {
   index_daily: TableStats | null
   index_enriched: TableStats | null
   index_instruments: InstrumentsStats | null
+  etf_daily: TableStats | null
+  etf_enriched: TableStats | null
+  etf_instruments: InstrumentsStats | null
   minute: TableStats | null
   adj_factor: TableStats | null
   instruments: InstrumentsStats | null
@@ -1555,6 +1675,14 @@ export interface DataStatus {
     index_enriched_size_mb?: number
     index_instruments_files?: number
     index_instruments_size_mb?: number
+    etf_daily_files?: number
+    etf_daily_size_mb?: number
+    etf_enriched_files?: number
+    etf_enriched_size_mb?: number
+    etf_instruments_files?: number
+    etf_instruments_size_mb?: number
+    etf_adj_factor_files?: number
+    etf_adj_factor_size_mb?: number
     minute_files: number
     minute_size_mb: number
     adj_factor_files: number

frontend/src/lib/capability-labels.tsx

@@ -1,6 +1,6 @@
 // capability 内部名 → 用户能理解的中文标签
 export const CAP_LABELS: Record<string, { name: string; hint: string }> = {
-  'quote.by_symbol':         { name: '实时行情(按标的)', hint: '查询单只股票当前价' },
+  'quote.by_symbol':         { name: '自选股实时监控', hint: 'Free 可按标的查询实时行情,用于少量自选股监控' },
   'quote.batch':             { name: '实时行情(批量)',   hint: '一次拿多只股票的价' },
   'quote.pool':              { name: '标的池查询',        hint: '按沪深300等池子拿行情' },
   'kline.daily.by_symbol':   { name: '日 K(按标的)',    hint: '单只股票历史日 K' },
@@ -16,7 +16,7 @@ export const CAP_LABELS: Record<string, { name: string; hint: string }> = {
 
 // 套餐等级 —— 用于按档位门控功能(如专线端点 / 按月扩展分钟K)。
 // 基础档提取与后端 quote_service.py 一致:取 label 第一个词("Pro +" → "pro")。
-// none = 无档(无 key / 无效 key),低于 free,仅历史日K无实时行情。
+// none = None 档(无 key / 无效 key),低于 free,仅历史日K无实时行情。
 export const TIER_RANK: Record<string, number> = { none: -1, free: 0, starter: 1, pro: 2, expert: 3 }
 export const EXPERT_RANK = TIER_RANK.expert
 
@@ -45,19 +45,19 @@ const TIER_STYLE: Record<string, TierStyle> = {
     labelTextStyle: { color: '#71717a' },
   },
   free: {
-    desc: '基础日K · 单股查询',
+    desc: '历史日K · 自选实时',
     tagBg: { background: 'rgba(113,113,122,0.3)' },
     dotStyle: { background: '#71717a' },
     labelTextStyle: { color: '#a1a1aa' },
   },
   starter: {
-    desc: '批量同步 · 行情池',
+    desc: '除权因子 · 全市场实时',
     tagBg: { background: 'rgba(59,130,246,0.2)' },
     dotStyle: { background: '#3b82f6' },
     labelTextStyle: { color: '#60a5fa' },
   },
   pro: {
-    desc: '分钟K · 实时行情 · 盘口',
+    desc: '分钟K · 盘口',
     tagBg: { background: 'linear-gradient(135deg, rgba(168,85,247,0.2), rgba(124,58,237,0.15))' },
     dotStyle: { background: 'linear-gradient(135deg, #a855f7, #7c3aed)' },
     labelTextStyle: { background: 'linear-gradient(135deg, #c084fc, #a855f7)', WebkitBackgroundClip: 'text', backgroundClip: 'text', color: 'transparent' },
@@ -92,8 +92,8 @@ export function tierTextStyle(label: string): { color?: string; background?: str
 export function TierTag({ label, className = '' }: { label: string; className?: string }) {
   const t = tierStyle(label)
   const base = tierBaseName(label)
-  // none 档显示中文「无」,其余档显示英文档名
-  const display = base === 'none' ? '无' : base
+  // none 档显示英文「None」,其余档显示英文档名
+  const display = base === 'none' ? 'None' : base
   return (
     <span
       className={`inline-flex h-[18px] max-w-[80px] shrink-0 items-center overflow-hidden rounded px-1.5 text-[10px] font-bold font-mono leading-none ${className}`}

frontend/src/lib/queryKeys.ts

@@ -70,6 +70,9 @@ export const QK = {
   monitorRules:         ['monitor-rules'] as const,
   monitorRuleOptions:   ['monitor-rule-options'] as const,
   alerts:               (source?: string) => ['alerts', source ?? ''] as const,
+
+  // AI 大盘复盘
+  reviewReports:        ['review-reports'] as const,
 } as const
 
 // ===== SSE 应该 invalidate 的 key 前缀列表 =====

frontend/src/lib/storage.ts

@@ -107,4 +107,7 @@ export const storage = {
 
   /** 行业分析页面字段配置 */
   industryAnalysisConfig: kv<Record<string, any>>('industry-analysis-config'),
+
+  /** 数据页画像卡片显隐 (卡片key → 是否显示) */
+  dataCardVisible: kv<Record<string, boolean>>('data-card-visible'),
 } as const

frontend/src/pages/Dashboard.tsx

@@ -1,8 +1,8 @@
-import { useState, type ReactNode } from 'react'
+import { useState, useEffect, useRef, type ReactNode } from 'react'
 import { Link } from 'react-router-dom'
-import { useQuery } from '@tanstack/react-query'
-import { motion } from 'framer-motion'
-import { Activity, AlertTriangle, ArrowDownRight, ArrowUpRight, BarChart3, BellRing, Check, Copy, Flame, Gauge, LineChart, Loader2, RefreshCw, Sparkles, Target, Timer, ExternalLink } from 'lucide-react'
+import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
+import { motion, AnimatePresence } from 'framer-motion'
+import { Activity, ArrowDownRight, ArrowUpRight, BarChart3, BellRing, Database, Flame, Gauge, LineChart, Loader2, Play, RefreshCw, Sparkles, Target, Timer } from 'lucide-react'
 import { DatePicker } from '@/components/DatePicker'
 import { api, type MarketSnapshotRow, type OverviewDimensionRankItem, type OverviewMarket, type AlertEvent } from '@/lib/api'
 import { QK } from '@/lib/queryKeys'
@@ -10,6 +10,8 @@ import { fmtBigNum, fmtPct } from '@/lib/format'
 import { useDataStatus, useCapabilities, useSettings } from '@/lib/useSharedQueries'
 import { SealedBadge } from '@/components/SealedBadge'
 import { StockPreviewDialog } from '@/components/StockPreviewDialog'
+import { SettingsModal } from '@/components/data/SettingsModal'
+import { STAGE_LABELS } from '@/components/data/ActiveJobCard'
 import { cn } from '@/lib/cn'
 import { cnSignal } from '@/lib/signals'
 import { boardTag } from '@/components/stock-table/primitives'
@@ -469,9 +471,11 @@ function HotRankCard({ title, rank, configUrl }: { title: string; rank?: Overvie
 }
 
 export function Dashboard() {
+  const qc = useQueryClient()
   const [selectedDate, setSelectedDate] = useState<string | undefined>()
   const [manualFetching, setManualFetching] = useState(false)
-  const [copiedCode, setCopiedCode] = useState(false)
+  // 首次使用(无数据 + 未完成引导)自动弹窗: 同一会话只弹一次
+  const [showWelcomeModal, setShowWelcomeModal] = useState(false)
   const dataStatus = useDataStatus({ staleTime: 60_000 })
   const overview = useQuery({
     queryKey: QK.overviewMarket(selectedDate),
@@ -485,15 +489,67 @@ export function Dashboard() {
   const hasDepth = !!caps.data?.capabilities?.['depth5.batch']
   const sealedReady = !!data?.limit?.sealed_ready
   const isSealedDegrade = !hasDepth || !sealedReady
-  // none 档(无 key / 无效 key)→ 显示升级提示横幅
+  // none 档(无 key / 无效 key): 不再阻断功能, 仅实时行情等扩展能力受限
   const isNoKey = settings.data?.mode === 'none'
-  // 无本地数据(enriched/daily 都没有)→ 提示去数据页同步
+  // 无本地数据(enriched/daily 都没有)→ 常驻引导卡片
   // 注: 后端 status 的 rows 为性能刻意返回 0, 用 trading_days 判断是否有数据
   const ds = dataStatus.data
   const hasNoData = !!ds
     && (ds.enriched?.trading_days ?? 0) === 0
     && (ds.daily?.trading_days ?? 0) === 0
 
+  // ===== 盘后管道触发(看板内一键获取数据) =====
+  const [fetchJobId, setFetchJobId] = useState<string | null>(null)
+  const fetchStatus = useQuery({
+    queryKey: QK.pipelineJob(fetchJobId ?? ''),
+    queryFn: () => api.pipelineJob(fetchJobId!),
+    enabled: !!fetchJobId,
+    refetchInterval: (q: any) => {
+      const j = q.state.data
+      return j && (j.status === 'succeeded' || j.status === 'failed') ? false : 1_000
+    },
+  })
+  const startFetch = useMutation({
+    mutationFn: api.pipelineRun,
+    onSuccess: ({ job_id }) => setFetchJobId(job_id),
+  })
+  const isFetching = startFetch.isPending
+    || fetchStatus.data?.status === 'running'
+    || fetchStatus.data?.status === 'pending'
+  const fetchFailed = fetchStatus.data?.status === 'failed'
+  const fetchSucceeded = fetchStatus.data?.status === 'succeeded'
+
+  // 首次使用且无数据 → 自动弹一次引导弹窗(同会话只弹一次)
+  useEffect(() => {
+    if (!hasNoData) return
+    if (settings.data?.onboarding_completed === false) return  // 还在引导流程中,不重复弹
+    if (sessionStorage.getItem('tf_welcome_shown')) return
+    sessionStorage.setItem('tf_welcome_shown', '1')
+    setShowWelcomeModal(true)
+  }, [hasNoData, settings.data?.onboarding_completed])
+
+  // 同步完成后刷新看板数据
+  useEffect(() => {
+    if (fetchSucceeded) {
+      qc.invalidateQueries({ queryKey: QK.dataStatus })
+      qc.invalidateQueries({ queryKey: QK.overviewMarket(undefined) })
+    }
+  }, [fetchSucceeded, qc])
+
+  // 组件重新挂载时(从其他页面切回)恢复正在运行的同步任务进度。
+  // 原因: fetchJobId 是组件内状态, 切走页面时组件卸载、状态丢失, 切回后进度卡片消失。
+  // 修复: 挂载时若无本地数据且未跟踪任何 job, 查一次后端是否有 active job, 有则接管。
+  const resumeTriedRef = useRef(false)
+  useEffect(() => {
+    if (resumeTriedRef.current) return
+    if (!hasNoData) return
+    if (fetchJobId) return
+    resumeTriedRef.current = true
+    api.pipelineJobs(1).then(({ active_id }) => {
+      if (active_id) setFetchJobId(active_id)
+    }).catch(() => { /* 查询失败不阻塞, 用户仍可手动点击获取 */ })
+  }, [hasNoData, fetchJobId])
+
   // 手动刷新: 显示旋转动画; SSE 自动刷新: 静默, 无体感
   const handleRefresh = () => {
     setManualFetching(true)
@@ -530,59 +586,31 @@ export function Dashboard() {
 
   return (
     <div className="min-h-full bg-base p-3">
-      {/* none 档(无 key)提示横幅 —— 引导用户领取免费 Key 解锁完整能力 */}
-      {isNoKey && (
-        <div className="mb-3 flex items-center gap-2 rounded-card border border-warning/40 bg-warning/10 px-3 py-2 text-xs">
-          <AlertTriangle className="h-4 w-4 shrink-0 text-warning" />
-          <span className="text-secondary leading-relaxed">
-            当前未配置 API Key,批量同步、实时行情等能力不可用。
-            <a
-              href="https://tickflow.org/auth/register?ref=V3KDKGXPEA"
-              target="_blank"
-              rel="noreferrer"
-              className="mx-1 inline-flex items-baseline gap-0.5 font-medium text-warning hover:underline"
-            >
-              前往 TickFlow 官网
-              <ExternalLink className="h-3 w-3 self-center" />
-            </a>
-            免费注册(或填邀请码{' '}
-            <span className="font-mono font-semibold text-warning inline-flex items-baseline gap-1">
-              V3KDKGXPEA
-              <button
-                type="button"
-                onClick={() => {
-                  navigator.clipboard?.writeText('V3KDKGXPEA').then(() => {
-                    setCopiedCode(true)
-                    setTimeout(() => setCopiedCode(false), 1500)
-                  })
-                }}
-                className="text-warning/60 hover:text-warning transition-colors self-center"
-                aria-label="复制邀请码"
-                tabIndex={-1}
-              >
-                {copiedCode ? <Check className="h-3 w-3" /> : <Copy className="h-3 w-3" />}
-              </button>
-            </span>
-            )即可领取免费 API Key,无需付费即可体验。
-          </span>
-        </div>
-      )}
-      {/* 无本地数据提示 —— 引导用户去数据页同步 (仅当已配置 Key 时显示, 无 Key 时优先提示配置 Key) */}
-      {hasNoData && !isNoKey && (
-        <div className="mb-3 flex items-center gap-2 rounded-card border border-warning/40 bg-warning/10 px-3 py-2 text-xs">
-          <AlertTriangle className="h-4 w-4 shrink-0 text-warning" />
-          <span className="text-secondary leading-relaxed">
-            当前暂无数据,请前往数据页面同步行情数据完成后查看。
-            <Link
-              to="/data"
-              className="ml-1 shrink-0 inline-flex items-center gap-0.5 font-medium text-warning hover:underline"
-            >
-              前往同步数据
-              <ArrowUpRight className="h-3 w-3 self-center" />
-            </Link>
-          </span>
-        </div>
+      {/* 无本地数据常驻引导卡片 —— 一键触发盘后管道获取数据(无 Key 也可) */}
+      {hasNoData && (
+        <FetchDataCard
+          isFetching={isFetching}
+          isStarting={startFetch.isPending}
+          fetchFailed={fetchFailed}
+          stage={fetchStatus.data?.stage}
+          fetchPct={fetchStatus.data?.progress}
+          onStart={() => startFetch.mutate()}
+          isNoKey={isNoKey}
+        />
       )}
+      {/* 首次使用自动弹窗(同会话仅一次) */}
+      <AnimatePresence>
+        {showWelcomeModal && (
+          <WelcomeFetchModal
+            isNoKey={isNoKey}
+            onClose={() => setShowWelcomeModal(false)}
+            onStart={() => {
+              startFetch.mutate()
+              setShowWelcomeModal(false)
+            }}
+          />
+        )}
+      </AnimatePresence>
       <div className="mb-3 flex flex-wrap items-center justify-between gap-2 rounded-card border border-border bg-surface/85 px-3 py-2">
         <div className="flex items-center gap-2">
           <Gauge className="h-4 w-4 text-accent" />
@@ -720,3 +748,134 @@ export function Dashboard() {
     </div>
   )
 }
+
+// ===== 无数据常驻引导卡片: 一键触发盘后管道获取行情数据(无 Key 也可) =====
+function FetchDataCard({
+  isFetching, isStarting, fetchFailed, stage, fetchPct, onStart, isNoKey,
+}: {
+  isFetching: boolean
+  isStarting: boolean
+  fetchFailed: boolean
+  stage?: string
+  fetchPct?: number
+  onStart: () => void
+  isNoKey: boolean
+}) {
+  const stageText = stage ? (STAGE_LABELS[stage] ?? stage) : '正在同步行情数据…'
+  return (
+    <div className="mb-3 rounded-card border border-border bg-surface/85 p-3.5">
+      <div className="flex items-start gap-3">
+        <div className="rounded-lg bg-accent/10 p-2 shrink-0">
+          <Database className="h-4 w-4 text-accent" />
+        </div>
+        <div className="min-w-0 flex-1">
+          <div className="text-sm font-medium text-foreground">当前暂无数据</div>
+          <p className="mt-1 text-xs text-secondary leading-relaxed">
+            首次使用需获取行情数据后才能查看看板。系统将从免费数据源拉取近 1 年全 A 股日K(约 5500 只),预计 1-3 分钟,期间可继续浏览其他页面。
+          </p>
+          {isNoKey && (
+            <p className="mt-1 text-[11px] text-warning/80 leading-relaxed">
+              ⓘ 无需 API Key,当前为 None 档即可获取历史日K,可制定策略+回测。配置免费 Key 可解锁实时行情监控能力。
+            </p>
+          )}
+
+          {isFetching ? (
+            <div className="mt-3">
+              <div className="flex items-center justify-between text-[11px] text-muted mb-1.5">
+                <span className="inline-flex items-center gap-1.5">
+                  <Loader2 className="h-3 w-3 animate-spin" />
+                  {isStarting ? '正在启动同步任务…' : stageText}
+                </span>
+                <span className="font-mono tabular">
+                  {typeof fetchPct === 'number' ? `${Math.round(fetchPct)}%` : ''}
+                </span>
+              </div>
+              <div className="h-1.5 rounded-full bg-elevated overflow-hidden">
+                <motion.div
+                  className="h-full bg-accent"
+                  initial={{ width: 0 }}
+                  animate={{ width: `${Math.max(2, Math.min(100, fetchPct ?? 0))}%` }}
+                  transition={{ duration: 0.4, ease: 'easeOut' }}
+                />
+              </div>
+            </div>
+          ) : fetchFailed ? (
+            <div className="mt-3 flex items-center gap-2">
+              <span className="text-xs text-danger">同步失败,请重试</span>
+              <button
+                onClick={onStart}
+                className="inline-flex items-center gap-1.5 px-3 h-8 rounded-btn bg-accent text-white text-xs font-medium hover:bg-accent/90 transition-colors"
+              >
+                <Play className="h-3.5 w-3.5" />重新获取
+              </button>
+            </div>
+          ) : (
+            <div className="mt-3 flex items-center gap-3">
+              <button
+                onClick={onStart}
+                className="inline-flex items-center gap-1.5 px-4 h-8 rounded-btn bg-accent text-white text-xs font-medium hover:bg-accent/90 transition-colors"
+              >
+                <Play className="h-3.5 w-3.5" />立即获取数据
+              </button>
+              <Link
+                to="/data"
+                className="inline-flex items-center gap-0.5 text-xs text-secondary hover:text-accent transition-colors"
+              >
+                前往数据页
+                <ArrowUpRight className="h-3 w-3 self-center" />
+              </Link>
+            </div>
+          )}
+        </div>
+      </div>
+    </div>
+  )
+}
+
+// ===== 首次使用自动弹窗: 询问用户后触发盘后管道 =====
+function WelcomeFetchModal({
+  isNoKey, onClose, onStart,
+}: {
+  isNoKey: boolean
+  onClose: () => void
+  onStart: () => void
+}) {
+  return (
+    <SettingsModal title="欢迎首次使用 · 获取行情数据" onClose={onClose}>
+      <div className="text-center">
+        <motion.div
+          initial={{ scale: 0.85, opacity: 0 }}
+          animate={{ scale: 1, opacity: 1 }}
+          transition={{ duration: 0.4, ease: [0.16, 1, 0.3, 1] }}
+          className="mx-auto w-fit rounded-2xl bg-accent/10 p-3.5"
+        >
+          <Sparkles className="h-7 w-7 text-accent" />
+        </motion.div>
+        <h3 className="mt-4 text-base font-semibold text-foreground">首次使用,需先获取行情数据</h3>
+        <p className="mt-2 text-xs text-secondary leading-relaxed">
+          系统将从免费数据源拉取近 1 年全 A 股日K(约 5500 只),预计 1-3 分钟。
+          同步期间可继续浏览其他页面,完成后看板自动刷新。
+        </p>
+        {isNoKey && (
+          <div className="mt-3 rounded-btn bg-elevated/60 px-3 py-2 text-[11px] text-muted leading-relaxed">
+            ⓘ 当前无需 API Key,None 档即可获取历史日K数据。
+          </div>
+        )}
+        <div className="mt-5 flex items-center justify-center gap-2.5">
+          <button
+            onClick={onClose}
+            className="px-4 h-9 rounded-btn text-sm text-secondary hover:text-foreground hover:bg-elevated transition-colors"
+          >
+            稍后再说
+          </button>
+          <button
+            onClick={onStart}
+            className="inline-flex items-center gap-2 px-5 h-9 rounded-xl bg-accent text-white text-sm font-semibold shadow-lg shadow-accent/20 hover:bg-accent/90 transition-all"
+          >
+            <Play className="h-4 w-4" />开始获取
+          </button>
+        </div>
+      </div>
+    </SettingsModal>
+  )
+}

frontend/src/pages/Data.tsx

@@ -1,5 +1,4 @@
 import { useCallback, useEffect, useRef, useState } from 'react'
-import { Link } from 'react-router-dom'
 import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
 import { motion, AnimatePresence } from 'framer-motion'
 import {
@@ -9,12 +8,15 @@ import {
   HardDrive,
   Clock,
   Calendar,
+  CheckSquare,
   Trash2,
   Plus,
   Wifi,
+  SlidersHorizontal,
   AlertTriangle,
   Info,
 } from 'lucide-react'
+import { Link } from 'react-router-dom'
 import { EndpointTestDialog } from '@/components/EndpointTestDialog'
 import { api, type ExtDataConfig } from '@/lib/api'
 import {
@@ -39,6 +41,8 @@ import { ScheduleEditor } from '@/components/data/ScheduleEditor'
 import { ExtendHistoryPanel } from '@/components/data/ExtendHistoryPanel'
 import { EnrichedRebuildPanel } from '@/components/data/EnrichedRebuildPanel'
 import { MinuteSyncConfig } from '@/components/data/MinuteSyncConfig'
+import { PipelineScopeConfig } from '@/components/data/PipelineScopeConfig'
+import { PageSettingsModal, getCardVisibility } from '@/components/data/PageSettingsModal'
 import { QuoteConfigCard } from '@/components/data/QuoteConfigCard'
 import { EnrichedSchemaModal } from '@/components/data/SchemaModal'
 import { Skeleton } from '@/components/data/Skeleton'
@@ -187,7 +191,27 @@ export function Data() {
   const hasAdjCap = !!caps.data?.capabilities?.['adj_factor']
   const hasDailyBatchCap = !!caps.data?.capabilities?.['kline.daily.batch']
   const hasMinuteCap = !!caps.data?.capabilities?.['kline.minute.batch']
-  const pipelineSteps = ['日K', ...(hasAdjCap ? ['复权'] : []), '指标', '指数', ...((hasMinuteCap && minuteAuto) ? ['分钟K'] : [])]
+  const indexAuto = prefs.data?.pipeline_pull_index ?? true
+  const etfAuto = prefs.data?.pipeline_pull_etf ?? false
+  const pipelineSteps = [
+    '日K',
+    ...(hasAdjCap ? ['复权'] : []),
+    '指标',
+    ...(indexAuto ? ['指数'] : []),
+    ...(etfAuto ? ['ETF'] : []),
+    ...((hasMinuteCap && minuteAuto) ? ['分钟K'] : []),
+  ]
+
+  // 数据画像卡片显隐(由页面设置弹窗控制,存 localStorage)
+  const [cardVisibleTick, setCardVisibleTick] = useState(0)
+  useEffect(() => {
+    const handler = () => setCardVisibleTick(t => t + 1)
+    window.addEventListener('data-card-visible-change', handler)
+    return () => window.removeEventListener('data-card-visible-change', handler)
+  }, [])
+  const cardVisible = getCardVisibility(caps.data?.capabilities)
+  // 引用 cardVisibleTick 触发重渲染(避免 lint 警告)
+  void cardVisibleTick
 
   useEffect(() => {
     if (job.data && (job.data.status === 'succeeded' || job.data.status === 'failed')) {
@@ -224,6 +248,14 @@ export function Data() {
     symbols_covered: s.index_daily?.symbols_covered ?? s.index_instruments?.rows ?? 0,
     trading_days: s.index_daily?.trading_days ?? s.index_enriched?.trading_days ?? 0,
   } : null
+  // ETF 统计(后端已按 asset_type='etf' 从 index 存储中拆分)
+  const etfOverviewStats = s ? {
+    rows: 0,
+    earliest_date: s.etf_daily?.earliest_date ?? s.etf_enriched?.earliest_date ?? null,
+    latest_date: s.etf_daily?.latest_date ?? s.etf_enriched?.latest_date ?? null,
+    symbols_covered: s.etf_daily?.symbols_covered ?? s.etf_instruments?.rows ?? 0,
+    trading_days: s.etf_daily?.trading_days ?? s.etf_enriched?.trading_days ?? 0,
+  } : null
   const indexOverviewLabel = s ? '日 · 维表 · 日K · 指标' : undefined
   const indexEarliestDate = s?.index_daily?.earliest_date ?? s?.index_enriched?.earliest_date ?? null
   const indexOffsetDays = indexExtendUnit === 'month' ? indexExtendValue * 30 : indexExtendValue * 365
@@ -293,31 +325,28 @@ export function Data() {
         subtitle="本地数据画像 · 同步状态 · 历史记录"
         right={
           <div className="flex items-center gap-3">
-            {!hasData && !isLoading && !isNoKey && (
+            {!hasData && !isLoading && (
               <span className="text-xs text-accent animate-pulse">首次使用请点击右侧按钮同步数据</span>
             )}
-            {isNoKey ? (
-              <button
-                disabled
-                className="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-btn bg-gradient-to-r from-accent/25 to-accent/10 border border-accent/30 text-accent text-xs font-medium opacity-40 cursor-not-allowed transition-all duration-150"
-              >
+            <button
+              onClick={() => startSync.mutate()}
+              disabled={isStarting}
+              className="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-btn bg-gradient-to-r from-accent/25 to-accent/10 border border-accent/30 text-accent text-xs font-medium hover:from-accent/35 hover:to-accent/20 disabled:opacity-40 transition-all duration-150"
+            >
+              {(isRunning || isStarting) ? (
+                <Loader2 className="h-3.5 w-3.5 animate-spin" />
+              ) : (
                 <Play className="h-3.5 w-3.5" />
-                立即同步
-              </button>
-            ) : (
-              <button
-                onClick={() => startSync.mutate()}
-                disabled={isStarting}
-                className="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-btn bg-gradient-to-r from-accent/25 to-accent/10 border border-accent/30 text-accent text-xs font-medium hover:from-accent/35 hover:to-accent/20 disabled:opacity-40 transition-all duration-150"
-              >
-                {(isRunning || isStarting) ? (
-                  <Loader2 className="h-3.5 w-3.5 animate-spin" />
-                ) : (
-                  <Play className="h-3.5 w-3.5" />
-                )}
-                {isStarting ? '启动中…' : isRunning ? '同步中…' : '立即同步'}
-              </button>
-            )}
+              )}
+              {isStarting ? '启动中…' : isRunning ? '同步中…' : '立即同步'}
+            </button>
+            <button
+              onClick={() => setOpenSettings('pipeline-scope')}
+              className="inline-flex items-center gap-1 px-2 py-1 rounded-btn text-secondary hover:text-accent hover:bg-accent/8 text-xs transition-colors duration-150"
+            >
+              <CheckSquare className="h-3.5 w-3.5" />
+              数据范围
+            </button>
             <div className="w-px h-4 bg-border" />
             <div className="flex items-center gap-1.5">
               <button
@@ -334,6 +363,13 @@ export function Data() {
                 <Wifi className="h-3.5 w-3.5" />
                 测试端点
               </button>
+              <button
+                onClick={() => setOpenSettings('page-settings')}
+                className="inline-flex items-center gap-1 px-2 py-1 rounded-btn text-secondary hover:text-accent hover:bg-accent/8 text-xs transition-colors duration-150"
+              >
+                <SlidersHorizontal className="h-3.5 w-3.5" />
+                页面设置
+              </button>
               <button
                 onClick={() => setShowClearConfirm(true)}
                 disabled={isRunning}
@@ -348,13 +384,14 @@ export function Data() {
       />
 
       <div className="px-8 py-6 space-y-6 max-w-6xl">
-        {/* 未配置 API Key 告警条 —— 引导用户去配置 Key 后才能同步 */}
+        {/* None 档提示 —— 非阻断: 无需 Key 也可获取历史日K, 仅实时行情等扩展能力受限 */}
         {isNoKey && (
-          <div className="flex items-center gap-2 rounded-card border border-warning/40 bg-warning/10 px-3 py-2 text-xs">
-            <AlertTriangle className="h-4 w-4 shrink-0 text-warning" />
+          <div className="flex items-center gap-2 rounded-card border border-border bg-elevated/40 px-3 py-2 text-xs">
+            <Info className="h-4 w-4 shrink-0 text-muted" />
             <span className="text-secondary leading-relaxed">
-              未配置 API Key,无法同步数据,请前往
-              <Link to="/settings?tab=account" className="mx-0.5 font-medium text-warning hover:underline">
+              当前为 None 档,将使用免费数据源获取历史日K(无需注册)。
+              配置 API Key 可解锁实时行情监控等扩展能力,前往
+              <Link to="/settings?tab=account" className="mx-0.5 font-medium text-accent hover:underline">
                 配置
               </Link>
               。
@@ -411,7 +448,7 @@ export function Data() {
               <div className="space-y-2">
                 <div className="flex items-center gap-1.5 text-[10px] text-muted pb-2 border-b border-border/50">
                   <span className="text-accent/60 font-medium">盘前</span>
-                  <span>标的维表</span>
+                  <span>个股维表</span>
                   <span className="text-border">→</span>
                   <span className="text-accent/60 font-medium">盘后</span>
                   {pipelineSteps.map((step, i) => (
@@ -427,7 +464,7 @@ export function Data() {
                 </div>
                 <div className="flex items-center justify-between text-[11px]">
                   <div className="flex items-center gap-1">
-                    <span className="text-muted">盘前 · 标的维表</span>
+                    <span className="text-muted">盘前 · 个股维表</span>
                     <span className="text-muted/50">·</span>
                     <span className="font-mono text-secondary">
                       {`${String(instrumentsSched.hour).padStart(2, '0')}:${String(instrumentsSched.minute).padStart(2, '0')}`}
@@ -548,7 +585,7 @@ export function Data() {
                   </div>
                 ))
               ) : [
-                { label: '标的维表', files: s?.storage.instruments_files, size: s?.storage.instruments_size_mb },
+                { label: '个股维表', files: s?.storage.instruments_files, size: s?.storage.instruments_size_mb },
                 { label: '日 K',     files: s?.storage.daily_files,       size: s?.storage.daily_size_mb },
                 { label: '除权因子', files: s?.storage.adj_factor_files,  size: s?.storage.adj_factor_size_mb },
                 { label: 'Enriched', files: s?.storage.enriched_files,    size: s?.storage.enriched_size_mb },
@@ -583,8 +620,9 @@ export function Data() {
         <div>
           <SectionTitle icon={Database}>数据画像</SectionTitle>
           <div className="mt-3 grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 xl:grid-cols-5 gap-4 items-stretch">
+            {cardVisible.instruments && (
             <StatCard
-              title="标的维表"
+              title="个股维表"
               hint="盘前同步 · 元数据快照"
               stats={s?.instruments}
               isInstrument
@@ -599,6 +637,8 @@ export function Data() {
               auto
               onShowFields={() => setSchemaTable('instruments')}
             />
+            )}
+            {cardVisible.daily && (
             <StatCard
               title="日 K"
               hint="增量同步 · 全市场"
@@ -616,21 +656,8 @@ export function Data() {
                onSettings={hasData ? () => setOpenSettings(v => v === 'daily' ? null : 'daily') : undefined}
               settingsOpen={openSettings === 'daily'}
             />
-            <StatCard
-              title="除权因子"
-              hint="增量同步 · 全市场"
-              stats={s?.adj_factor}
-              loading={isLoading}
-              active={activeCard === 'adj_factor'}
-              done={doneStages.has('adj_factor')}
-              skipped={skippedCards.has('adj_factor')}
-              stagePct={activeCard === 'adj_factor' ? (job.data?.stage_pct ?? 0) : 0}
-              tierKey="adj_factor"
-              capLimits={caps.data?.capabilities}
-              tierLabel={caps.data?.label}
-              auto
-              onShowFields={() => setSchemaTable('adj_factor')}
-            />
+            )}
+            {cardVisible.enriched && (
             <StatCard
               title="Enriched"
               hint="复权 OHLCV + 技术指标"
@@ -650,8 +677,10 @@ export function Data() {
                onSettings={hasData ? () => setOpenSettings(v => v === 'enriched' ? null : 'enriched') : undefined}
               settingsOpen={openSettings === 'enriched'}
             />
+            )}
+            {cardVisible.index && (
             <StatCard
-              title="指数数据"
+              title="指数"
               hint="CN_Index · 独立存储"
               stats={indexOverviewStats}
               loading={isLoading}
@@ -662,7 +691,7 @@ export function Data() {
               tierKey="daily"
               capLimits={caps.data?.capabilities}
               tierLabel={caps.data?.label}
-              auto
+              auto={indexAuto}
               subLabel={indexOverviewLabel}
               fieldTabs={[
                 { label: '维表', table: 'index_instruments' },
@@ -673,6 +702,44 @@ export function Data() {
               onSettings={hasData ? () => setOpenSettings(v => v === 'index' ? null : 'index') : undefined}
               settingsOpen={openSettings === 'index'}
             />
+            )}
+            {cardVisible.etf && (
+            <StatCard
+              title="ETF"
+              hint="场内基金 · 独立存储"
+              stats={etfOverviewStats}
+              loading={isLoading}
+              tierKey="etf"
+              capLimits={caps.data?.capabilities}
+              tierLabel={caps.data?.label}
+              auto={etfAuto}
+              subLabel="维表 · 日K · 指标"
+              fieldTabs={[
+                { label: '维表', table: 'etf_instruments' },
+                { label: '日K', table: 'etf_daily' },
+                { label: '指标', table: 'etf_enriched' },
+              ] as FieldTab[]}
+              onShowFields={(t) => setSchemaTable(t ?? 'etf_daily')}
+            />
+            )}
+            {cardVisible.adj_factor && (
+            <StatCard
+              title="除权因子"
+              hint="增量同步 · 全市场"
+              stats={s?.adj_factor}
+              loading={isLoading}
+              active={activeCard === 'adj_factor'}
+              done={doneStages.has('adj_factor')}
+              skipped={skippedCards.has('adj_factor')}
+              stagePct={activeCard === 'adj_factor' ? (job.data?.stage_pct ?? 0) : 0}
+              tierKey="adj_factor"
+              capLimits={caps.data?.capabilities}
+              tierLabel={caps.data?.label}
+              auto
+              onShowFields={() => setSchemaTable('adj_factor')}
+            />
+            )}
+            {cardVisible.minute && (
             <StatCard
               title="分钟 K"
               hint="全市场同步"
@@ -690,6 +757,8 @@ export function Data() {
                onSettings={hasData ? () => setOpenSettings(v => v === 'minute' ? null : 'minute') : undefined}
               settingsOpen={openSettings === 'minute'}
             />
+            )}
+            {cardVisible.financials && (
             <StatCard
               title="财务数据"
               hint="利润表 / 资负表 / 现金流 / 指标"
@@ -699,6 +768,7 @@ export function Data() {
               capLimits={caps.data?.capabilities}
               tierLabel={caps.data?.label}
             />
+            )}
             {(extConfigs.data?.items ?? []).map((ext) => (
               <ExtDataStatCard
                 key={ext.id}
@@ -796,9 +866,25 @@ export function Data() {
         )}
       </AnimatePresence>
 
+      <AnimatePresence>
+        {openSettings === 'pipeline-scope' && (
+          <SettingsModal title="盘后管道 · 拉取内容" onClose={() => setOpenSettings(null)}>
+            <PipelineScopeConfig />
+          </SettingsModal>
+        )}
+      </AnimatePresence>
+
+      <AnimatePresence>
+        {openSettings === 'page-settings' && (
+          <SettingsModal title="页面设置 · 数据画像卡片" onClose={() => setOpenSettings(null)}>
+            <PageSettingsModal caps={caps.data?.capabilities} />
+          </SettingsModal>
+        )}
+      </AnimatePresence>
+
       <AnimatePresence>
         {openSettings === 'index' && (
-          <SettingsModal title="指数数据 · 手动获取" onClose={() => setOpenSettings(null)}>
+          <SettingsModal title="指数 · 手动获取" onClose={() => setOpenSettings(null)}>
             <div className="space-y-4">
               <div className="rounded-card border border-border bg-base/30 p-4 space-y-3">
                 <div>
@@ -936,9 +1022,9 @@ export function Data() {
                     此操作将<span className="text-danger font-medium">永久删除</span>所有已同步的本地数据，包括：
                   </p>
                   <ul className="mt-2 text-[11px] text-muted leading-relaxed space-y-0.5">
-                    <li>· 标的维表、日 K、除权因子</li>
+                    <li>· 个股维表、日 K、除权因子</li>
                     <li>· Enriched 指标数据、分钟 K</li>
-                    <li>· 财务数据、指数数据</li>
+                    <li>· 财务数据、指数、ETF</li>
                   </ul>
                   <p className="mt-2 text-[11px] text-danger/90">
                     操作不可恢复，需重新执行同步才能恢复数据。

frontend/src/pages/IndustryAnalysis.tsx

@@ -278,7 +278,11 @@ export function IndustryAnalysis() {
 
   const configsQuery = useQuery({ queryKey: QK.extData, queryFn: api.extDataList })
   const availableConfigs = configsQuery.data?.items ?? []
-  const activeConfigId = fieldConfig.configId || pickBestConfig(availableConfigs)
+  // 用户配置的 configId 可能已失效 (扩展数据被删除), 此时回退到自动选择,
+  // 避免用失效 ID 请求接口报错; 用户仍可点配置按钮重新选择。
+  const preferredConfigId = fieldConfig.configId || pickBestConfig(availableConfigs)
+  const preferredConfig = availableConfigs.find(c => c.id === preferredConfigId)
+  const activeConfigId = preferredConfig ? preferredConfigId : pickBestConfig(availableConfigs)
   const activeConfig = availableConfigs.find(c => c.id === activeConfigId)
 
   const rowsQuery = useQuery({

frontend/src/pages/Onboarding.tsx

@@ -13,7 +13,6 @@ import {
   ArrowRight,
   ArrowLeft,
   ExternalLink,
-  Copy,
   Sparkles,
   LineChart,
   ScanSearch,
@@ -22,6 +21,10 @@ import {
   Radar,
   ShieldCheck,
   BellRing,
+  TrendingUp,
+  FileText,
+  Landmark,
+  Database,
 } from 'lucide-react'
 import { api } from '@/lib/api'
 import { useCapabilities, useSettings } from '@/lib/useSharedQueries'
@@ -37,12 +40,15 @@ const STEPS = ['欢迎', '配置 Key', '能力探测', '完成'] as const
 const BRAND = '#8B5CF6'
 
 const HIGHLIGHTS = [
-  { icon: LineChart, title: '看板与自选', desc: '实时行情、MA/MACD 指标、自定义自选列表', tint: 'text-accent' },
-  { icon: ScanSearch, title: '策略选股', desc: '内置多套选股策略,一键扫描全市场命中', tint: 'text-bull' },
-  { icon: Flame, title: '连板梯队', desc: '涨停板梯队、概念行业热度、市场情绪一览', tint: 'text-warning' },
-  { icon: Radar, title: '实时监控', desc: '自定义条件 / 策略监控,触发即推送告警', tint: 'text-bear' },
-  { icon: ShieldCheck, title: '回测验证', desc: '策略历史回测、因子分析,用数据说话', tint: 'text-accent' },
-  { icon: BellRing, title: '本地优先', desc: '数据本地存储,隐私可控,断网仍可查阅', tint: 'text-bull' },
+  { icon: LineChart,   title: '看板与自选', desc: '市场全景看板、涨跌分布、情绪雷达,自定义自选列表', tint: 'text-accent' },
+  { icon: ScanSearch,  title: '策略选股',   desc: '内置多套选股策略,一键扫描全市场命中标的', tint: 'text-bull' },
+  { icon: TrendingUp,  title: '个股分析',   desc: 'AI 四维分析个股,关键价位、技术形态一目了然', tint: 'text-warning' },
+  { icon: Flame,       title: '连板梯队',   desc: '涨停梯队、封板强度、炸板监控,情绪温度计', tint: 'text-warning' },
+  { icon: Landmark,    title: '概念行业',   desc: '概念板块、行业维度的资金流向与热度排名', tint: 'text-accent' },
+  { icon: FileText,    title: '财务分析',   desc: 'AI 解读财报,利润、资负、现金流、核心指标', tint: 'text-bear' },
+  { icon: ShieldCheck, title: '回测验证',   desc: '策略历史回测、因子分析,用数据验证逻辑', tint: 'text-accent' },
+  { icon: Radar,       title: '实时监控',   desc: '自定义条件 / 策略监控,盘中触发即推送告警', tint: 'text-bear' },
+  { icon: BellRing,    title: '本地优先',   desc: '数据本地存储,隐私可控,断网仍可查阅', tint: 'text-bull' },
 ]
 
 export function Onboarding() {
@@ -180,20 +186,24 @@ function WelcomeStep({ onNext, onSkip }: { onNext: () => void; onSkip: () => voi
         花一分钟配置,即可开始使用。
       </p>
 
-      {/* 6 个特性卡片 */}
-      <div className="mt-8 grid grid-cols-2 sm:grid-cols-3 gap-3 text-left">
+      {/* 特性卡片 —— 3×3 网格,横向布局压缩高度 */}
+      <div className="mt-8 grid grid-cols-2 sm:grid-cols-3 gap-2.5 text-left">
         {HIGHLIGHTS.map((h, i) => (
           <motion.div
             key={h.title}
-            initial={{ opacity: 0, y: 10 }}
+            initial={{ opacity: 0, y: 8 }}
             animate={{ opacity: 1, y: 0 }}
-            transition={{ duration: 0.3, delay: 0.05 * i + 0.1 }}
+            transition={{ duration: 0.3, delay: 0.04 * i + 0.1 }}
             whileHover={{ y: -2 }}
-            className="group rounded-card border border-border bg-surface/80 backdrop-blur-sm p-3.5 transition-colors hover:border-accent/30"
+            className="group flex items-start gap-2.5 rounded-card border border-border bg-surface/80 backdrop-blur-sm p-2.5 transition-colors hover:border-accent/30"
           >
-            <h.icon className={`h-5 w-5 ${h.tint} transition-transform group-hover:scale-110`} />
-            <div className="mt-2 text-sm font-medium text-foreground">{h.title}</div>
-            <div className="mt-1 text-xs text-muted leading-relaxed">{h.desc}</div>
+            <div className="rounded-lg bg-elevated/50 p-1.5 shrink-0">
+              <h.icon className={`h-4 w-4 ${h.tint} transition-transform group-hover:scale-110`} />
+            </div>
+            <div className="min-w-0">
+              <div className="text-xs font-medium text-foreground">{h.title}</div>
+              <div className="mt-0.5 text-[11px] text-muted leading-snug line-clamp-2">{h.desc}</div>
+            </div>
           </motion.div>
         ))}
       </div>
@@ -225,7 +235,6 @@ function KeyStep({ onNext, onSkip, onBack }: { onNext: () => void; onSkip: () =>
 
   const [keyInput, setKeyInput] = useState('')
   const [revealing, setRevealing] = useState(false)
-  const [copiedCode, setCopiedCode] = useState(false)
   const [saved, setSaved] = useState(false)
 
   const save = useMutation({
@@ -242,7 +251,7 @@ function KeyStep({ onNext, onSkip, onBack }: { onNext: () => void; onSkip: () =>
     },
   })
 
-  // 已配置 key —— 免费档或付费档都算(只要不是无档 none)
+  // 已配置 key —— 免费档或付费档都算(只要不是 None 档)
   const alreadyHasKey = settings.data?.mode !== 'none' && settings.data?.mode !== undefined
 
   return (
@@ -254,41 +263,44 @@ function KeyStep({ onNext, onSkip, onBack }: { onNext: () => void; onSkip: () =>
         <h2 className="text-xl font-bold text-foreground">配置 TickFlow API Key</h2>
       </div>
       <p className="mt-2.5 text-sm text-secondary leading-relaxed">
-        Key 决定你能使用的数据范围。没有 Key 也能以<span className="font-medium text-foreground"> 基础模式 </span>
-        使用历史日K;配置有效 Key 后可解锁实时行情、批量同步等扩展能力。
+        本项目基于 TickFlow 这款稳定的数据源为基座进行开发,正在适配其他第三方数据源。
+        如果有任何建议或意见,欢迎发送邮件至{' '}
+        <a
+          href="mailto:415333856@qq.com"
+          className="text-accent hover:underline font-medium"
+        >
+          415333856@qq.com
+        </a>
+        。
       </p>
 
-      {/* 注册引导 */}
-      <div className="mt-5 rounded-card border border-border bg-surface/80 backdrop-blur-sm p-4 text-xs text-secondary leading-relaxed">
-        还没有 Key?前往{' '}
-        <a
-          href="https://tickflow.org/auth/register?ref=V3KDKGXPEA"
-          target="_blank"
-          rel="noreferrer"
-          className="text-accent hover:underline inline-flex items-baseline gap-0.5 font-medium"
-        >
-          tickflow.org
-          <ExternalLink className="h-3 w-3 self-center" />
-        </a>{' '}
-        注册,或填写邀请码{' '}
-        <span className="font-mono font-semibold text-accent inline-flex items-baseline gap-1">
-          V3KDKGXPEA
-          <button
-            type="button"
-            onClick={() => {
-              navigator.clipboard?.writeText('V3KDKGXPEA').then(() => {
-                setCopiedCode(true)
-                setTimeout(() => setCopiedCode(false), 1500)
-              })
-            }}
-            className="text-muted hover:text-accent transition-colors self-center"
-            aria-label="复制邀请码"
-            tabIndex={-1}
-          >
-            {copiedCode ? <Check className="h-3 w-3" /> : <Copy className="h-3 w-3" />}
-          </button>
-        </span>
-        ,即可免费领取扩展数据。
+      {/* 档位对比说明 —— None 档 vs Free 档 */}
+      <div className="mt-4 grid grid-cols-1 sm:grid-cols-2 gap-2.5">
+        {/* None 档 —— 不配置时默认 */}
+        <div className="rounded-card border border-accent/20 bg-accent/[0.04] p-3">
+          <div className="flex items-center gap-1.5">
+            <span className="inline-flex h-[18px] items-center rounded px-1.5 text-[10px] font-bold font-mono bg-accent/15 text-accent/70">None</span>
+            <span className="text-xs font-medium text-foreground">不配置(默认)</span>
+          </div>
+          <ul className="mt-2 space-y-1 text-[11px] text-muted leading-relaxed">
+            <li>· 仅历史日K数据,无实时行情</li>
+            <li>· 数据有延迟,盘后约 1-2 小时更新当天</li>
+            <li>· 可用于策略回测、盘后分析</li>
+          </ul>
+        </div>
+        {/* Free 档 —— 免费注册即可获取 */}
+        <div className="rounded-card border border-accent/35 bg-accent/[0.08] p-3">
+          <div className="flex items-center gap-1.5">
+            <span className="inline-flex h-[18px] items-center rounded px-1.5 text-[10px] font-bold font-mono bg-accent/15 text-accent">Free</span>
+            <span className="text-xs font-medium text-foreground">注册免费获取</span>
+            <span className="inline-flex items-center rounded-full bg-accent px-1.5 py-0.5 text-[10px] font-bold text-white shadow-sm shadow-accent/30">推荐</span>
+          </div>
+          <ul className="mt-2 space-y-1 text-[11px] text-secondary leading-relaxed">
+            <li>· 无需付费,注册即享</li>
+            <li>· 历史日K + 限定范围内的实时数据</li>
+            <li>· 可指定个股进行实时监控</li>
+          </ul>
+        </div>
       </div>
 
       {/* Key 已配置提示 */}
@@ -302,6 +314,27 @@ function KeyStep({ onNext, onSkip, onBack }: { onNext: () => void; onSkip: () =>
         </div>
       )}
 
+      {/* 获取 Key 的说明 —— 黄框卡片 */}
+      <div className="mt-4 flex items-start gap-2 rounded-card border border-warning/40 bg-warning/10 px-3 py-2.5 text-xs text-foreground leading-relaxed">
+        <AlertCircle className="h-4 w-4 shrink-0 text-warning mt-px" />
+        <span>
+          Key 可在{' '}
+          <a
+            href="https://tickflow.org/auth/register?ref=V3KDKGXPEA"
+            target="_blank"
+            rel="noreferrer"
+            className="text-warning hover:underline inline-flex items-baseline gap-0.5 font-medium"
+          >
+            tickflow.org
+            <ExternalLink className="h-3 w-3 self-center" />
+          </a>
+          获取。
+          <span className="block mt-1.5 text-foreground/70">
+            当前数据源基于 TickFlow 基座,其他第三方数据源正在开发适配中。
+          </span>
+        </span>
+      </div>
+
       {/* 输入 */}
       <form
         onSubmit={(e) => {
@@ -399,7 +432,7 @@ function ResultStep({ onNext, onBack }: { onNext: () => void; onBack: () => void
   const settings = useSettings()
   const caps = useCapabilities()
 
-  // 是否配置成功 —— 免费档(free)或付费档(api_key)都算;无档(none)算未配置
+  // 是否配置成功 —— 免费档(free)或付费档(api_key)都算;None 档算未配置
   const hasKey = settings.data?.mode === 'free' || settings.data?.mode === 'api_key'
   const capList = caps.data ? Object.entries(caps.data.capabilities) : []
 
@@ -458,10 +491,10 @@ function ResultStep({ onNext, onBack }: { onNext: () => void; onBack: () => void
           <div className="mx-auto w-fit rounded-xl bg-elevated p-3">
             <Zap className="h-6 w-6 text-warning" />
           </div>
-          <div className="mt-3 text-sm font-medium text-foreground">将以基础模式继续</div>
+          <div className="mt-3 text-sm font-medium text-foreground">将以 None 档继续</div>
           <p className="mt-2 text-xs text-muted leading-relaxed max-w-sm mx-auto">
-            当前未配置有效 Key,仅可使用历史日K数据。配置 Key 后可解锁实时行情、批量同步等能力,
-            随时在<span className="text-foreground font-medium"> 设置 → 账户 </span>填写。
+            当前未配置有效 Key,仍可使用看板、选股、回测等功能 —— 进入看板后可直接获取近 1 年历史日K数据。配置 Key 后可解锁实时行情监控等能力,随时在
+            <span className="text-foreground font-medium"> 设置 → 账户 </span>填写。
           </p>
         </div>
       )}
@@ -490,10 +523,16 @@ function ResultStep({ onNext, onBack }: { onNext: () => void; onBack: () => void
 // ===== Step 3: 完成 =====
 
 function FinishStep({ onNext, onBack, pending }: { onNext: () => void; onBack: () => void; pending: boolean }) {
+  const settings = useSettings()
+  // 是否已配置 Key(free 或 api_key 都算,None 档算未配置)
+  const hasKey = settings.data?.mode === 'free' || settings.data?.mode === 'api_key'
+
+  // 首要行动:获取数据(不管配没配 Key, 新用户都需要先拉数据)
+  // 快速上手入口(精简为核心功能)
   const tips = [
-    { icon: ScanSearch, text: '在「选股」页用内置策略一键扫描全市场' },
-    { icon: BellRing, text: '在「监控」页设置条件或策略告警,盘中实时推送' },
-    { icon: ShieldCheck, text: '在「回测」页用历史数据验证策略表现' },
+    { icon: TrendingUp, text: '「个股分析」:输入代码,AI 四维分析 + 关键价位' },
+    { icon: ScanSearch, text: '「选股」页:内置多套策略,一键扫描全市场' },
+    { icon: ShieldCheck, text: '「回测」页:用历史数据验证策略表现,用数据说话' },
   ]
 
   return (
@@ -520,18 +559,37 @@ function FinishStep({ onNext, onBack, pending }: { onNext: () => void; onBack: (
 
       <h1 className="mt-6 text-2xl font-bold text-foreground">一切就绪!</h1>
       <p className="mt-2.5 text-sm text-secondary leading-relaxed max-w-md mx-auto">
-        配置已完成。下面几个入口帮你快速上手,有任何问题随时在
-        <span className="text-foreground font-medium"> 设置 </span>里调整。
+        {hasKey
+          ? 'Key 已生效,进入面板后系统会自动引导你获取行情数据,完成后即可使用全部功能。'
+          : '当前为 None 档,进入面板后系统会自动引导你获取历史日K数据(无需 Key),即可开始体验。'}
       </p>
 
-      {/* 快速上手提示 */}
-      <div className="mt-6 space-y-2 text-left">
+      {/* 首要行动:获取数据 */}
+      <motion.div
+        initial={{ opacity: 0, y: 10 }}
+        animate={{ opacity: 1, y: 0 }}
+        transition={{ duration: 0.3, delay: 0.2 }}
+        className="mt-5 flex items-start gap-2.5 rounded-card border border-accent/30 bg-accent/[0.06] px-4 py-3 text-left"
+      >
+        <div className="rounded-lg bg-accent/15 p-1.5 shrink-0 mt-px">
+          <Database className="h-4 w-4 text-accent" />
+        </div>
+        <div className="min-w-0">
+          <div className="text-sm font-medium text-foreground">下一步:获取行情数据</div>
+          <p className="mt-1 text-xs text-secondary leading-relaxed">
+            进入面板后,看板会自动引导你拉取近 1 年全 A 股日K(约 5500 只,预计 1-3 分钟)。同步期间可浏览其他页面。
+          </p>
+        </div>
+      </motion.div>
+
+      {/* 快速上手入口 */}
+      <div className="mt-4 space-y-2 text-left">
         {tips.map((t, i) => (
           <motion.div
             key={i}
             initial={{ opacity: 0, x: -10 }}
             animate={{ opacity: 1, x: 0 }}
-            transition={{ duration: 0.3, delay: 0.1 * i + 0.2 }}
+            transition={{ duration: 0.3, delay: 0.1 * i + 0.3 }}
             className="flex items-center gap-3 rounded-card border border-border bg-surface/80 backdrop-blur-sm px-3.5 py-2.5"
           >
             <div className="rounded-lg bg-accent/10 p-1.5 shrink-0">

frontend/src/pages/Review.tsx

@@ -0,0 +1,662 @@
+/**
+ * AI 大盘复盘页 —— 盘后复盘看板 + 流式 LLM 复盘报告 + 历史归档。
+ *
+ * 数据分工:
+ *  - 顶部看板(指数/涨跌/连板/封板/情绪雷达)来自 GET /api/overview/market
+ *  - 复盘报告(markdown)由 POST /api/market-recap/analyze 流式生成
+ * 视觉语言对齐 Dashboard:A 股红涨绿跌、rounded-card 卡片、SectionTitle 层级。
+ */
+import { useCallback, useEffect, useRef, useState } from 'react'
+import { Link } from 'react-router-dom'
+import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
+import { motion } from 'framer-motion'
+import {
+  BookOpenCheck, RefreshCw, Sparkles, Trash2, History, ChevronRight, AlertTriangle,
+  BarChart3, Activity, Layers, ArrowUpRight, ArrowDownRight, Database, Wand2,
+} from 'lucide-react'
+
+import { api, type OverviewMarket, type AiReviewReport } from '@/lib/api'
+import { QK } from '@/lib/queryKeys'
+import { cn } from '@/lib/cn'
+import { fmtPrice } from '@/lib/format'
+import { PageHeader } from '@/components/PageHeader'
+import { MarkdownRenderer } from '@/components/financials/MarkdownRenderer'
+import { toast } from '@/components/Toast'
+
+// ================================================================
+// 涨跌幅格式化(注意单位差异)
+// overview 的 indices.change_pct / breadth.up_pct / seal_rate / *_pct / emotion.score
+//   都是【已是百分比值】(如 1.2 表示 1.2%),直接 toFixed 即可,不要 *100。
+// ================================================================
+function fmtPctAlready(v: number | null | undefined, digits = 2, withSign = false): string {
+  if (v == null || Number.isNaN(v)) return '—'
+  const sign = withSign && v > 0 ? '+' : ''
+  return `${sign}${v.toFixed(digits)}%`
+}
+function pctClass(v: number | null | undefined): string {
+  if (v == null || Number.isNaN(v) || v === 0) return 'text-muted'
+  return v > 0 ? 'text-bull' : 'text-bear'
+}
+// A 股惯例: 强势=红, 弱式=绿(对齐 Dashboard scoreColor)
+function scoreColor(v: number | null | undefined): string {
+  if (v == null || Number.isNaN(v)) return '#71717A'
+  if (v >= 70) return '#F04438'
+  if (v >= 55) return '#FB923C'
+  if (v >= 45) return '#F59E0B'
+  if (v >= 30) return '#84CC16'
+  return '#12B76A'
+}
+
+type Phase = 'idle' | 'loading' | 'streaming' | 'done' | 'error'
+
+export function Review() {
+  const qc = useQueryClient()
+  // 复盘日期:当前固定取最新交易日(后续如需日期选择可改回 useState)
+  const asOf: string | undefined = undefined
+  const [focus, setFocus] = useState('')
+  const [phase, setPhase] = useState<Phase>('idle')
+  const [content, setContent] = useState('')
+  const [error, setError] = useState('')
+  const [meta, setMeta] = useState<{ as_of?: string; emotion_score?: number; emotion_label?: string; summary?: string } | null>(null)
+  const [viewing, setViewing] = useState<AiReviewReport | null>(null)  // 查看历史报告
+  const abortRef = useRef<AbortController | null>(null)
+  const reportEndRef = useRef<HTMLDivElement>(null)
+
+  // 看板数据(与总览页同源)
+  const marketQuery = useQuery<OverviewMarket>({
+    queryKey: QK.overviewMarket(asOf),
+    queryFn: () => api.overviewMarket(asOf),
+    staleTime: 5_000,
+    placeholderData: (prev) => prev,
+  })
+
+  // 历史报告
+  const historyQuery = useQuery<{ reports: AiReviewReport[] }>({
+    queryKey: QK.reviewReports,
+    queryFn: () => api.reviewReportsList(),
+  })
+
+  const deleteMut = useMutation({
+    mutationFn: (id: string) => api.reviewReportDelete(id),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: QK.reviewReports })
+      toast('已删除', 'success')
+    },
+    onError: () => { /* request() 已 toast */ },
+  })
+
+  // 自动滚动到报告底部(streaming 时)
+  useEffect(() => {
+    if (phase === 'streaming') {
+      reportEndRef.current?.scrollIntoView({ behavior: 'smooth', block: 'end' })
+    }
+  }, [content, phase])
+
+  // 主流程:生成复盘
+  const generate = useCallback(async () => {
+    if (phase === 'loading' || phase === 'streaming') return
+    setViewing(null)
+    setPhase('loading')
+    setContent('')
+    setError('')
+    setMeta(null)
+
+    const ctrl = new AbortController()
+    abortRef.current = ctrl
+    let buf = ''
+    let failed = false
+    try {
+      for await (const evt of api.reviewStream(asOf, focus)) {
+        if (ctrl.signal.aborted) break
+        if (evt.type === 'meta') {
+          setMeta(evt)
+        } else if (evt.type === 'delta' && evt.content) {
+          buf += evt.content
+          setContent(buf)
+          setPhase('streaming')
+        } else if (evt.type === 'error') {
+          failed = true
+          setError(evt.message ?? '复盘失败')
+          setPhase('error')
+          return
+        } else if (evt.type === 'done') {
+          setPhase('done')
+        }
+      }
+      // 流正常结束但无 done 事件,按 done 处理
+      if (buf && !failed) setPhase('done')
+    } catch (e: any) {
+      if (!ctrl.signal.aborted) {
+        setError(e?.message ?? '复盘失败')
+        setPhase('error')
+      }
+    } finally {
+      abortRef.current = null
+    }
+  }, [asOf, focus, phase])
+
+  // 保存当前报告
+  const saveCurrent = useCallback(async () => {
+    if (!content) return
+    const reportAsOf = meta?.as_of ?? marketQuery.data?.as_of ?? asOf ?? new Date().toISOString().slice(0, 10)
+    try {
+      await api.reviewReportSave({
+        as_of: reportAsOf,
+        focus,
+        content,
+        summary: meta?.summary,
+        emotion_score: meta?.emotion_score ?? null,
+        emotion_label: meta?.emotion_label ?? '',
+      })
+      qc.invalidateQueries({ queryKey: QK.reviewReports })
+      toast('复盘已归档', 'success')
+    } catch { /* request() 已 toast */ }
+  }, [content, meta, asOf, focus, marketQuery.data, qc])
+
+  // 查看历史报告
+  const viewReport = useCallback((r: AiReviewReport) => {
+    abortRef.current?.abort()
+    setViewing(r)
+    setContent(r.content)
+    setMeta({ as_of: r.as_of, emotion_score: r.emotion_score ?? undefined, emotion_label: r.emotion_label, summary: r.summary })
+    setPhase('done')
+    setError('')
+  }, [])
+
+  const isGenerating = phase === 'loading' || phase === 'streaming'
+  const displayDate = viewing?.as_of ?? meta?.as_of ?? marketQuery.data?.as_of ?? asOf ?? '最新'
+  const data = marketQuery.data
+
+  return (
+    <>
+      <PageHeader
+        title="AI 复盘"
+        titleExtra={<Sparkles className="h-4 w-4 text-accent" />}
+        subtitle={`${displayDate}${data?.emotion ? ` · 情绪 ${data.emotion.label}` : ''}`}
+        right={
+          <div className="flex items-center gap-1">
+            <button
+              onClick={() => { marketQuery.refetch() }}
+              disabled={marketQuery.isFetching}
+              className="inline-flex items-center gap-1 rounded-btn border border-border bg-elevated px-2 py-1 text-[11px] text-secondary transition-colors hover:text-foreground disabled:opacity-50"
+              title="刷新看板数据"
+            >
+              <RefreshCw className={cn('h-3 w-3', marketQuery.isFetching && 'animate-spin')} />刷新
+            </button>
+            <button
+              onClick={generate}
+              disabled={isGenerating}
+              className={cn(
+                'inline-flex items-center gap-1.5 rounded-btn px-3.5 py-1.5 text-xs font-medium transition-all',
+                isGenerating
+                  ? 'border border-accent/40 bg-accent/10 text-accent cursor-not-allowed'
+                  : 'bg-accent text-white shadow-sm shadow-accent/25 hover:bg-accent/90 hover:shadow hover:shadow-accent/30',
+              )}
+            >
+              {isGenerating ? (
+                <><RefreshCw className="h-3.5 w-3.5 animate-spin" />生成中…</>
+              ) : (
+                <><Sparkles className="h-3.5 w-3.5" />生成复盘</>
+              )}
+            </button>
+          </div>
+        }
+      />
+
+      <div className="min-h-full bg-[radial-gradient(circle_at_15%_-5%,rgba(59,130,246,0.10),transparent_30%),radial-gradient(circle_at_85%_5%,rgba(139,92,246,0.08),transparent_30%)] px-4 py-4 sm:px-6">
+        <div className="mx-auto max-w-[1440px] space-y-4">
+
+          {marketQuery.isLoading && !data ? (
+            <div className="flex h-40 items-center justify-center">
+              <div className="flex items-center gap-2 text-sm text-muted">
+                <RefreshCw className="h-4 w-4 animate-spin" /> 加载市场数据…
+              </div>
+            </div>
+          ) : !data || !data.as_of ? (
+            <div className="flex flex-col items-center justify-center gap-4 rounded-card border border-border bg-surface/80 px-6 py-16">
+              <div className="relative">
+                <div className="grid h-14 w-14 place-items-center rounded-2xl bg-gradient-to-br from-accent/20 to-purple-500/15 border border-accent/30">
+                  <Database className="h-6 w-6 text-accent" strokeWidth={1.8} />
+                </div>
+              </div>
+              <div className="text-center">
+                <div className="text-sm font-medium text-foreground">暂无市场数据</div>
+                <p className="mt-1 text-xs text-muted">复盘需要日 K 与指数,请先前往「数据」页同步</p>
+              </div>
+              <Link
+                to="/data"
+                className="inline-flex items-center gap-1.5 rounded-btn bg-accent px-4 py-2 text-xs font-medium text-white shadow-sm transition-all hover:bg-accent/90 hover:shadow"
+              >
+                <Database className="h-3.5 w-3.5" />前往数据页同步
+                <ChevronRight className="h-3.5 w-3.5" />
+              </Link>
+            </div>
+          ) : (
+            <>
+              {/* ===== 指数行情条(对齐 Dashboard IndexTicker) ===== */}
+              <div className="grid grid-cols-2 gap-2 sm:grid-cols-4">
+                {data.indices.map(item => <IndexTicker key={item.symbol} item={item} />)}
+              </div>
+
+              {/* ===== KPI 网格 ===== */}
+              <div className="grid grid-cols-2 gap-2 md:grid-cols-3 xl:grid-cols-6">
+                <KpiCell label="涨 / 平 / 跌" value={<><span className="text-bull">{data.breadth.up}</span><span className="text-muted">/</span><span className="text-muted">{data.breadth.flat}</span><span className="text-muted">/</span><span className="text-bear">{data.breadth.down}</span></>} sub={`上涨率 ${data.breadth.up_pct.toFixed(1)}%`} />
+                <KpiCell label="涨停 / 跌停" value={<><span className="text-bull">{data.limit.limit_up}</span><span className="text-muted">/</span><span className="text-bear">{data.limit.limit_down}</span></>} sub={`封板率 ${(data.limit.seal_rate ?? 0).toFixed(0)}% · 炸板 ${data.limit.broken ?? 0}`} />
+                <KpiCell label="最高连板" value={`${data.limit.max_boards || 0}板`} sub={`梯队 ${data.limit.tiers.length}档`} tone="accent" />
+                <KpiCell label="两市成交" value={`${((data.amount.total ?? 0) / 1e8).toFixed(0)}亿`} sub={`均额 ${((data.amount.avg ?? 0) / 1e8).toFixed(1)}亿`} />
+                <KpiCell label="换手 / 量比" value={`${fmtPrice(data.activity.avg_turnover, 1)}% / ${fmtPrice(data.activity.vol_ratio, 2)}`} sub={`高换手 ${data.activity.high_turnover}`} tone="accent" />
+                <KpiCell label="MA5 / 20 / 60" value={`${data.trend.above_ma5_pct.toFixed(0)}%`} sub={`${data.trend.above_ma20_pct.toFixed(0)}% / ${data.trend.above_ma60_pct.toFixed(0)}%`} />
+              </div>
+
+              {/* ===== 情绪雷达 + 板块排名 双栏 ===== */}
+              <div className="grid grid-cols-1 gap-3 lg:grid-cols-3">
+                <EmotionSection data={data} />
+                <SectorSection title="概念板块" rank={data.concept_rank} tone="concept" />
+                <SectorSection title="行业板块" rank={data.industry_rank} tone="industry" />
+              </div>
+
+              {/* ===== 关注点输入 ===== */}
+              <div className="flex items-center gap-2 rounded-card border border-border bg-surface/80 px-3.5 py-2.5 transition-colors focus-within:border-accent/40">
+                <Wand2 className="h-3.5 w-3.5 shrink-0 text-accent" />
+                <input
+                  value={focus}
+                  onChange={(e) => setFocus(e.target.value)}
+                  onKeyDown={(e) => { if (e.key === 'Enter' && !isGenerating) generate() }}
+                  placeholder="可选:补充复盘关注点,如「明日是否加仓半导体」「量能是否持续」"
+                  className="flex-1 bg-transparent text-sm text-foreground outline-none placeholder:text-muted/60"
+                />
+                {focus && (
+                  <button onClick={() => setFocus('')} className="text-xs text-muted transition-colors hover:text-foreground">清除</button>
+                )}
+              </div>
+
+              {/* ===== 报告 + 历史 双栏 ===== */}
+              <div className="grid grid-cols-1 gap-3 lg:grid-cols-[1fr_18rem]">
+                <ReportPanel
+                  phase={phase}
+                  content={content}
+                  error={error}
+                  isGenerating={isGenerating}
+                  viewing={viewing}
+                  onSave={saveCurrent}
+                  onRegenerate={generate}
+                  reportEndRef={reportEndRef}
+                />
+                <HistoryPanel
+                  reports={historyQuery.data?.reports ?? []}
+                  loading={historyQuery.isLoading}
+                  viewingId={viewing?.id ?? null}
+                  onView={viewReport}
+                  onDelete={(id) => deleteMut.mutate(id)}
+                />
+              </div>
+            </>
+          )}
+        </div>
+      </div>
+    </>
+  )
+}
+
+// ================================================================
+// 指数行情卡(对齐 Dashboard IndexTicker)
+// ================================================================
+function IndexTicker({ item }: { item: OverviewMarket['indices'][number] }) {
+  const pct = item.change_pct
+  const isUp = (pct ?? 0) >= 0
+  return (
+    <div className="grid min-w-0 grid-cols-[1fr_auto] items-center gap-x-2 gap-y-0.5 rounded-card border border-border bg-surface/80 px-3 py-2 transition-colors hover:border-accent/40">
+      <div className="truncate text-xs font-medium text-foreground">{item.name || item.symbol}</div>
+      <div className={cn('font-mono text-xs font-semibold tabular-nums', pctClass(pct))}>{fmtPctAlready(pct, 2, true)}</div>
+      <div className="font-mono text-[10px] text-muted">{item.symbol}</div>
+      <div className={cn('flex items-center gap-0.5 font-mono text-[11px] tabular-nums', pctClass(pct))}>
+        {isUp ? <ArrowUpRight className="h-3 w-3" /> : <ArrowDownRight className="h-3 w-3" />}
+        {fmtPrice(item.last_price)}
+      </div>
+    </div>
+  )
+}
+
+// ================================================================
+// KPI 单元(对齐 Dashboard KpiCell)
+// ================================================================
+function KpiCell({ label, value, sub, tone }: {
+  label: React.ReactNode
+  value: React.ReactNode
+  sub?: string
+  tone?: 'bull' | 'bear' | 'accent'
+}) {
+  const isPlain = typeof value === 'string' || typeof value === 'number'
+  const color = tone === 'bull' ? 'text-bull' : tone === 'bear' ? 'text-bear' : tone === 'accent' ? 'text-accent' : 'text-foreground'
+  return (
+    <div className="min-w-0 rounded-card border border-border bg-surface/80 px-3 py-2">
+      <div className="flex items-center gap-1 text-[11px] text-muted">{label}</div>
+      <div className={cn('mt-1 truncate font-mono text-base font-semibold leading-none tabular-nums', isPlain ? color : 'text-foreground')}>{value}</div>
+      {sub && <div className="mt-1 truncate text-[10px] text-muted">{sub}</div>}
+    </div>
+  )
+}
+
+// ================================================================
+// 章节标题(对齐 Dashboard SectionTitle)
+// ================================================================
+function SectionTitle({ icon: Icon, title, hint }: { icon: typeof Activity; title: string; hint?: React.ReactNode }) {
+  return (
+    <div className="mb-2 flex items-center justify-between gap-2">
+      <div className="flex items-center gap-1.5">
+        <Icon className="h-3.5 w-3.5 text-accent" />
+        <h2 className="text-xs font-semibold text-foreground">{title}</h2>
+      </div>
+      {hint && <span className="font-mono text-[10px] text-muted">{hint}</span>}
+    </div>
+  )
+}
+
+// ================================================================
+// 情绪雷达章节(SVG 雷达图,对齐 Dashboard EmotionRadar)
+// ================================================================
+function EmotionSection({ data }: { data: OverviewMarket }) {
+  const score = data.emotion.score
+  const color = scoreColor(score)
+  const radar = data.radar ?? []
+  const size = 220
+  const cx = size / 2
+  const cy = size / 2
+  const maxR = 68
+
+  const points = radar.map((r, i) => {
+    const angle = -Math.PI / 2 + i * 2 * Math.PI / radar.length
+    const radius = maxR * Math.max(0, Math.min(100, r.value)) / 100
+    return {
+      ...r,
+      x: cx + Math.cos(angle) * radius,
+      y: cy + Math.sin(angle) * radius,
+      lx: cx + Math.cos(angle) * (maxR + 24),
+      ly: cy + Math.sin(angle) * (maxR + 24),
+      gx: cx + Math.cos(angle) * maxR,
+      gy: cy + Math.sin(angle) * maxR,
+    }
+  })
+  const polygon = points.map(p => `${p.x},${p.y}`).join(' ')
+  const gridPolygons = [1, 0.66, 0.33].map((level, idx) => ({
+    level, idx,
+    points: radar.map((_, i) => {
+      const angle = -Math.PI / 2 + i * 2 * Math.PI / radar.length
+      return `${cx + Math.cos(angle) * maxR * level},${cy + Math.sin(angle) * maxR * level}`
+    }).join(' '),
+  }))
+
+  return (
+    <section
+      className="rounded-card border bg-surface/80 p-3"
+      style={{ borderColor: `${color}40` }}
+    >
+      <SectionTitle icon={Sparkles} title="情绪雷达" hint={`评分 ${score} · ${data.emotion.label}`} />
+      {radar.length === 0 ? (
+        <div className="flex h-44 items-center justify-center text-xs text-muted">暂无雷达数据</div>
+      ) : (
+        <div className="flex justify-center">
+          <svg viewBox={`0 0 ${size} ${size}`} className="h-52 w-full">
+            <defs>
+              <radialGradient id="reviewRadarFill" cx="50%" cy="45%" r="70%">
+                <stop offset="0%" stopColor={`${color}57`} />
+                <stop offset="100%" stopColor={`${color}1f`} />
+              </radialGradient>
+              <radialGradient id="reviewRadarCenter" cx="50%" cy="50%" r="55%">
+                <stop offset="0%" stopColor="rgba(24,24,27,0.92)" />
+                <stop offset="68%" stopColor="rgba(24,24,27,0.70)" />
+                <stop offset="100%" stopColor="rgba(24,24,27,0)" />
+              </radialGradient>
+            </defs>
+            {gridPolygons.map(g => (
+              <polygon
+                key={g.level}
+                points={g.points}
+                fill={g.idx % 2 === 0 ? 'rgba(33,33,38,0.26)' : 'rgba(24,24,27,0.16)'}
+                stroke={g.level === 1 ? 'rgba(148,163,184,0.22)' : 'rgba(148,163,184,0.12)'}
+                strokeWidth={g.level === 1 ? 1.2 : 0.8}
+              />
+            ))}
+            {points.map(p => <line key={p.key} x1={cx} y1={cy} x2={p.gx} y2={p.gy} stroke="rgba(148,163,184,0.08)" />)}
+            <polygon points={polygon} fill="url(#reviewRadarFill)" stroke={color} strokeWidth="2" />
+            {points.map(p => <circle key={p.key} cx={p.x} cy={p.y} r="2.8" fill={color} stroke="rgba(24,24,27,0.9)" strokeWidth="1" />)}
+            <circle cx={cx} cy={cy} r="26" fill="url(#reviewRadarCenter)" />
+            <text x={cx} y={cy + 6} textAnchor="middle" className="fill-foreground font-mono text-[22px] font-bold">{score}</text>
+            {points.map(p => (
+              <text key={`${p.key}-label`} x={p.lx} y={p.ly + 4} textAnchor="middle" className="fill-secondary text-[9px] font-medium">{p.label}</text>
+            ))}
+          </svg>
+        </div>
+      )}
+    </section>
+  )
+}
+
+// ================================================================
+// 板块排名章节(领涨/领跌)
+// ================================================================
+function SectorSection({ title, rank, tone }: {
+  title: string
+  rank: OverviewMarket['concept_rank'] | OverviewMarket['industry_rank']
+  tone: 'concept' | 'industry'
+}) {
+  const leading = rank?.leading ?? []
+  const lagging = rank?.lagging ?? []
+  const hasData = leading.length > 0 || lagging.length > 0
+  return (
+    <section className="rounded-card border border-border bg-surface/80 p-3">
+      <SectionTitle icon={tone === 'concept' ? Layers : BarChart3} title={title} hint="领涨/领跌" />
+      {!hasData ? (
+        <div className="py-6 text-center text-[11px] text-muted">暂无数据</div>
+      ) : (
+        <div className="grid grid-cols-2 gap-2">
+          <RankColumn rows={leading} tone="bull" />
+          <RankColumn rows={lagging} tone="bear" />
+        </div>
+      )}
+    </section>
+  )
+}
+
+function RankColumn({ rows, tone }: { rows: OverviewMarket['concept_rank']['leading']; tone: 'bull' | 'bear' }) {
+  return (
+    <div className="min-w-0 space-y-1">
+      <div className={cn('text-[10px] font-medium', tone === 'bull' ? 'text-bull' : 'text-bear')}>
+        {tone === 'bull' ? '领涨' : '领跌'}
+      </div>
+      {rows.slice(0, 5).map((r, idx) => (
+        <div key={`${r.name}-${idx}`} className="grid grid-cols-[14px_1fr_auto] items-center gap-1 rounded bg-elevated/40 px-1.5 py-1">
+          <span className="text-center font-mono text-[9px] text-muted">{idx + 1}</span>
+          <div className="min-w-0">
+            <div className="truncate text-[11px] text-foreground" title={r.name}>{r.name}</div>
+            <div className="truncate text-[9px] text-muted">{r.count}只 · {r.leader?.name ?? '—'}</div>
+          </div>
+          <div className={cn('font-mono text-[10px] font-semibold tabular-nums', pctClass(r.avg_pct))}>
+            {fmtPctAlready((r.avg_pct ?? 0) * 100, 2, true)}
+          </div>
+        </div>
+      ))}
+      {rows.length === 0 && <div className="rounded border border-dashed border-border py-3 text-center text-[10px] text-muted">—</div>}
+    </div>
+  )
+}
+
+// ================================================================
+// 报告面板(流式 + 错误 + 历史/完成态)
+// ================================================================
+function ReportPanel({
+  phase, content, error, isGenerating, viewing, onSave, onRegenerate, reportEndRef,
+}: {
+  phase: Phase
+  content: string
+  error: string
+  isGenerating: boolean
+  viewing: AiReviewReport | null
+  onSave: () => void
+  onRegenerate: () => void
+  reportEndRef: React.RefObject<HTMLDivElement>
+}) {
+  if (phase === 'error') {
+    return (
+      <div className="flex flex-col items-center justify-center gap-3 rounded-card border border-border bg-surface/80 px-6 py-14">
+        <div className="grid h-12 w-12 place-items-center rounded-full bg-danger/10">
+          <AlertTriangle className="h-5 w-5 text-danger" />
+        </div>
+        <div className="text-sm font-medium text-foreground">复盘失败</div>
+        <div className="max-w-md text-center text-xs text-secondary">{error || '请检查 AI 配置后重试'}</div>
+        <button
+          onClick={onRegenerate}
+          className="mt-1 inline-flex items-center gap-1.5 rounded-btn bg-accent/15 px-3 py-1.5 text-xs text-accent transition-colors hover:bg-accent/20"
+        >
+          <RefreshCw className="h-3.5 w-3.5" />重新生成
+        </button>
+      </div>
+    )
+  }
+
+  if (phase === 'idle' && !content) {
+    return (
+      <div className="flex min-h-[24rem] flex-col items-center justify-center gap-4 rounded-card border border-border bg-surface/80 px-6 py-12">
+        <div className="relative">
+          <div className="grid h-16 w-16 place-items-center rounded-2xl bg-gradient-to-br from-accent/20 to-purple-500/15 border border-accent/30">
+            <BookOpenCheck className="h-7 w-7 text-accent" strokeWidth={1.8} />
+          </div>
+        </div>
+        <div className="text-center">
+          <div className="text-sm font-medium text-foreground">AI 大盘复盘</div>
+          <p className="mx-auto mt-1.5 max-w-sm text-xs leading-relaxed text-muted">
+            点击右上角「生成复盘」,基于今日指数结构、涨跌家数、连板梯队、板块轮动与情绪雷达,
+            生成可直接指导次日仓位与节奏的盘后复盘报告。
+          </p>
+        </div>
+        <div className="mt-1 flex items-center gap-1.5 text-[11px] text-muted">
+          <Sparkles className="h-3 w-3 text-accent" />
+          七节结构化报告 · 一键归档 · 历史回看
+        </div>
+      </div>
+    )
+  }
+
+  const showCursor = isGenerating
+  const showSave = phase === 'done' && !!content && !viewing
+  const showViewingTag = !!viewing
+  const isLoading = phase === 'loading' && !content
+
+  return (
+    <motion.div
+      initial={{ opacity: 0 }}
+      animate={{ opacity: 1 }}
+      className="overflow-hidden rounded-card border border-border bg-surface/80"
+    >
+      <div className="flex items-center justify-between border-b border-border bg-gradient-to-r from-accent/5 to-transparent px-4 py-2.5">
+        <div className="flex items-center gap-1.5">
+          {isGenerating ? <RefreshCw className="h-3.5 w-3.5 animate-spin text-accent" /> : <BookOpenCheck className="h-3.5 w-3.5 text-accent" />}
+          <span className="text-xs font-medium text-foreground">
+            {showViewingTag ? `历史复盘 · ${viewing!.as_of}` : isGenerating ? 'AI 正在复盘…' : '复盘报告'}
+          </span>
+        </div>
+        {showSave && (
+          <button onClick={onSave} className="inline-flex items-center gap-1 rounded-btn bg-accent/10 px-2 py-1 text-[11px] text-accent transition-colors hover:bg-accent/20">
+            <History className="h-3 w-3" />归档
+          </button>
+        )}
+      </div>
+      <div className="max-h-[calc(100vh-26rem)] overflow-y-auto px-5 py-4">
+        {isLoading ? (
+          <div className="flex flex-col items-center justify-center gap-3 py-16">
+            <div className="relative">
+              <div className="grid h-11 w-11 place-items-center rounded-full bg-gradient-to-br from-accent/20 to-purple-500/15 border border-accent/30">
+                <Sparkles className="h-5 w-5 animate-pulse text-accent" />
+              </div>
+              <RefreshCw className="absolute -inset-1 h-13 w-13 animate-spin text-accent/30" style={{ animationDuration: '3s' }} />
+            </div>
+            <div className="text-xs text-secondary">AI 正在分析今日盘面…</div>
+            <div className="text-[10px] text-muted">读取指数结构 · 涨跌家数 · 连板梯队 · 板块轮动 · 情绪雷达</div>
+          </div>
+        ) : (
+          <div className="prose prose-invert max-w-none">
+            <MarkdownRenderer content={content} />
+            {showCursor && (
+              <span className="ml-0.5 inline-block h-4 w-1.5 animate-pulse rounded-sm bg-accent align-middle" />
+            )}
+          </div>
+        )}
+        <div ref={reportEndRef} />
+      </div>
+    </motion.div>
+  )
+}
+
+// ================================================================
+// 历史面板
+// ================================================================
+function HistoryPanel({
+  reports, loading, viewingId, onView, onDelete,
+}: {
+  reports: AiReviewReport[]
+  loading: boolean
+  viewingId: string | null
+  onView: (r: AiReviewReport) => void
+  onDelete: (id: string) => void
+}) {
+  return (
+    <div className="overflow-hidden rounded-card border border-border bg-surface/80">
+      <div className="flex items-center gap-1.5 border-b border-border bg-gradient-to-r from-accent/5 to-transparent px-3 py-2.5">
+        <History className="h-3.5 w-3.5 text-accent" />
+        <span className="text-xs font-medium text-foreground">历史复盘</span>
+        <span className="font-mono text-[10px] text-muted">({reports.length})</span>
+      </div>
+      <div className="max-h-[calc(100vh-26rem)] overflow-y-auto p-2">
+        {loading ? (
+          <div className="grid h-20 place-items-center"><RefreshCw className="h-4 w-4 animate-spin text-muted" /></div>
+        ) : reports.length === 0 ? (
+          <div className="flex flex-col items-center justify-center gap-2 px-3 py-10 text-center">
+            <History className="h-7 w-7 text-muted/40" strokeWidth={1.5} />
+            <div className="text-[11px] text-muted">暂无历史复盘</div>
+            <div className="text-[10px] text-muted/60">生成后点「归档」即可保存</div>
+          </div>
+        ) : (
+          <div className="space-y-1">
+            {reports.map((r) => {
+              const color = scoreColor(r.emotion_score)
+              return (
+                <div
+                  key={r.id}
+                  className={cn(
+                    'group flex items-center gap-2 rounded px-2 py-2 cursor-pointer transition-colors',
+                    viewingId === r.id ? 'bg-accent/10 ring-1 ring-accent/20' : 'hover:bg-elevated/60',
+                  )}
+                  onClick={() => onView(r)}
+                >
+                  <div
+                    className="grid h-8 w-8 shrink-0 place-items-center rounded font-mono text-[10px] font-bold tabular-nums"
+                    style={{ color, backgroundColor: `${color}1a` }}
+                  >
+                    {r.emotion_score ?? '—'}
+                  </div>
+                  <div className="min-w-0 flex-1">
+                    <div className="flex items-center gap-1.5">
+                      <span className="truncate text-[11px] font-medium text-foreground">{r.emotion_label ?? '—'}</span>
+                      <span className="font-mono text-[10px] text-muted">{r.as_of}</span>
+                    </div>
+                    <div className="mt-0.5 truncate text-[10px] text-muted">
+                      {r.summary ?? r.content.slice(0, 40)}
+                    </div>
+                  </div>
+                  <ChevronRight className="h-3.5 w-3.5 shrink-0 text-muted opacity-0 transition-opacity group-hover:opacity-100" />
+                  <button
+                    onClick={(e) => { e.stopPropagation(); onDelete(r.id) }}
+                    className="shrink-0 p-1 text-muted opacity-0 transition-all hover:text-bear group-hover:opacity-100"
+                    title="删除"
+                  >
+                    <Trash2 className="h-3.5 w-3.5" />
+                  </button>
+                </div>
+              )
+            })}
+          </div>
+        )}
+      </div>
+    </div>
+  )
+}

frontend/src/pages/Watchlist.tsx

@@ -1,7 +1,7 @@
 import React, { useState, useCallback, useRef, useEffect, useMemo } from 'react'
 import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query'
 import { motion, AnimatePresence } from 'framer-motion'
-import { Trash2, RefreshCw, Star, X, Search, LayoutGrid, List, Settings2, Plus, Check, Filter, Eye, EyeOff, Minus } from 'lucide-react'
+import { Trash2, RefreshCw, Star, X, Search, LayoutGrid, List, Settings2, Plus, Check, Filter, Eye, EyeOff, Minus, ChevronsUp } from 'lucide-react'
 import { api, type KlineRow } from '@/lib/api'
 import { QK } from '@/lib/queryKeys'
 import { storage } from '@/lib/storage'
@@ -591,6 +591,18 @@ export function Watchlist() {
     },
   })
 
+  const moveToTop = useMutation({
+    mutationFn: (sym: string) => api.watchlistMoveToTop(sym),
+    onSuccess: (data) => {
+      qc.setQueryData(QK.watchlist, data)
+      qc.invalidateQueries({ queryKey: QK.watchlist })
+      qc.invalidateQueries({ queryKey: ['watchlist-enriched'] })
+      qc.invalidateQueries({ queryKey: ['watchlist-kline-batch'] })
+      qc.invalidateQueries({ queryKey: QK.preferences })
+      qc.invalidateQueries({ queryKey: QK.quoteStatus })
+    },
+  })
+
   const clearAll = useMutation({
     mutationFn: () => api.watchlistClear(),
     onSuccess: () => {
@@ -953,13 +965,25 @@ export function Watchlist() {
                               </button>
                             </div>
                           ) : (
-                            <button
-                              onClick={() => setConfirmRemove(r.symbol)}
-                              className="p-0.5 text-muted hover:text-danger transition-colors duration-150 ease-smooth"
-                              aria-label="移除"
-                            >
-                              <Minus className="h-3.5 w-3.5" />
-                            </button>
+                            <div className="flex items-center gap-1">
+                              <button
+                                onClick={() => setConfirmRemove(r.symbol)}
+                                className="p-0.5 text-muted hover:text-danger transition-colors duration-150 ease-smooth"
+                                aria-label="移除"
+                                title="移除"
+                              >
+                                <Minus className="h-3.5 w-3.5" />
+                              </button>
+                              <button
+                                onClick={() => moveToTop.mutate(r.symbol)}
+                                disabled={moveToTop.isPending || allSymbols[0] === r.symbol}
+                                className="p-0.5 text-muted hover:text-accent transition-colors duration-150 ease-smooth disabled:opacity-30 disabled:hover:text-muted"
+                                aria-label="移到顶部"
+                                title="移到顶部"
+                              >
+                                <ChevronsUp className="h-3.5 w-3.5" />
+                              </button>
+                            </div>
                           )}
                         </div>
                       </div>

frontend/src/pages/settings/Keys.tsx

@@ -14,7 +14,6 @@ import {
   Loader2,
   Save,
   Check,
-  Copy,
   HelpCircle,
 } from 'lucide-react'
 import { api } from '@/lib/api'
@@ -34,7 +33,6 @@ export function SettingsKeysPanel() {
   const [revealing, setRevealing] = useState(false)
   const [confirmClear, setConfirmClear] = useState(false)
   const [saved, setSaved] = useState(false)
-  const [copiedCode, setCopiedCode] = useState(false)
 
   const save = useMutation({
     mutationFn: () => api.saveTickflowKey(keyInput.trim()),
@@ -89,27 +87,6 @@ export function SettingsKeysPanel() {
               </a>{' '}
               注册获取。API Key 存放为本地文件,不会上传任何第三方,请妥善保管。
             </p>
-            <p className="text-xs text-secondary leading-relaxed mb-4">
-              通过上方链接注册或填写邀请码{' '}
-              <span className="font-mono font-semibold text-accent inline-flex items-baseline gap-1">
-                V3KDKGXPEA
-                <button
-                  type="button"
-                  onClick={() => {
-                    navigator.clipboard?.writeText('V3KDKGXPEA').then(() => {
-                      setCopiedCode(true)
-                      setTimeout(() => setCopiedCode(false), 1500)
-                    })
-                  }}
-                  className="text-muted hover:text-accent transition-colors duration-150 ease-smooth self-center"
-                  aria-label="复制邀请码"
-                  tabIndex={-1}
-                >
-                  {copiedCode ? <Check className="h-3 w-3" /> : <Copy className="h-3 w-3" />}
-                </button>
-              </span>
-              ,即可免费领取概念行业等扩展数据。
-            </p>
 
             {/* 当前状态 */}
             <div className="flex items-center justify-between mb-4">
@@ -131,7 +108,7 @@ export function SettingsKeysPanel() {
                   ) : (
                     <>
                       <AlertCircle className="h-4 w-4 text-muted shrink-0" />
-                      <span className="text-sm font-medium text-muted">未配置 · Free 数据</span>
+                      <span className="text-sm font-medium text-muted">未配置</span>
                     </>
                   )}
                 </div>
@@ -220,7 +197,7 @@ export function SettingsKeysPanel() {
               <div className="mt-3 text-xs text-bear flex items-center gap-1.5">
                 <CheckCircle2 className="h-3 w-3" />
                 保存成功 — 档位 {save.data.tier_label}
-                {save.data.mode === 'free' && '(免费档 · 历史日K)'}
+                {save.data.mode === 'free' && '(免费档 · 历史日K + 自选实时监控)'}
               </div>
             )}
           </Card>
@@ -341,7 +318,7 @@ export function SettingsKeysPanel() {
           <div className="relative w-[90vw] max-w-[380px] rounded-card border border-border bg-base shadow-2xl p-6">
             <h3 className="text-sm font-medium text-foreground mb-2">清除 API Key</h3>
             <p className="text-xs text-secondary mb-5">
-              清除后将退回无档(仅历史日K),需要重新输入 Key 才能恢复。
+              清除后将退回 None 档(仅历史日K),需要重新输入 Key 才能恢复。
             </p>
             <div className="flex items-center justify-end gap-2">
               <button
@@ -407,18 +384,22 @@ function TierHelpPopover({ currentLabel }: { currentLabel: string }) {
                   return (
                     <div key={t} className="flex items-center gap-2">
                       <span className="h-1.5 w-1.5 rounded-full shrink-0" style={s.dotStyle} />
-                      <span className="font-mono font-bold w-12 shrink-0" style={s.labelTextStyle}>{t === 'none' ? '无' : t}</span>
+                      <span className="font-mono font-bold w-12 shrink-0" style={s.labelTextStyle}>{t === 'none' ? 'None' : t}</span>
                       <span className="text-secondary">{s.desc}</span>
                     </div>
                   )
                 })}
               </div>
 
+              <div className="mb-3 rounded-btn border border-warning/30 bg-warning/10 px-2.5 py-1.5 text-[11px] font-medium text-warning">
+                高等档位包含较低档位的全部权益。
+              </div>
+
               {/* 检测说明 */}
               <div className="text-secondary space-y-1.5">
                 <div className="font-medium text-foreground">档位检测说明</div>
-                <p>保存 Key 后系统会在付费端点逐一试探数据能力:连单只日K都拿不到则判为「无」(不存 Key);有日K但无复权因子则判为「Free」;有复权因子再按代表能力判定 Starter/Pro/Expert。</p>
-                <p className="text-muted">无档与免费档运行时都走免费数据通道(仅历史日K),区别仅在于是否保存了 Key。付费档走付费端点,享有实时行情等完整能力。</p>
+                <p>保存 Key 后系统会在付费端点逐一试探数据能力:连单只日K都拿不到则判为「None」(不存 Key);有日K但无复权因子则判为「Free」;有复权因子再按代表能力判定 Starter/Pro/Expert。</p>
+                <p className="text-muted">None 档与 Free 档运行时都走免费数据通道(仅历史日K),区别仅在于是否保存了 Key。付费档走付费端点,享有实时行情等完整能力。</p>
               </div>
             </motion.div>
           </>

frontend/src/pages/settings/Monitoring.tsx

@@ -1,5 +1,6 @@
 import { useState, useCallback, useEffect, useRef } from 'react'
-import { useQueryClient, useMutation } from '@tanstack/react-query'
+import { Link } from 'react-router-dom'
+import { useQueryClient, useMutation, useQuery } from '@tanstack/react-query'
 import {
   Activity,
   Shield,
@@ -46,8 +47,9 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
   const { data: intervalData } = useQuoteInterval()
   const updateInterval = useUpdateQuoteInterval()
   const toggleQuote = useToggleRealtimeQuotes()
-  // none/free 档(无实时行情权限)→ rank < starter(1)
-  const isFreeTier = tierRank(caps?.label ?? '') < 1
+  const tier = tierRank(caps?.label ?? '')
+  const isNoneTier = tier < 0
+  const isFreeTier = tier === 0
   const realtimeEnabled = prefs?.realtime_quotes_enabled ?? false
   const refreshPages = prefs?.sse_refresh_pages ?? {}
   const limitLadderMonitor = prefs?.limit_ladder_monitor_enabled ?? false
@@ -60,6 +62,16 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
   const interval = intervalData?.interval ?? 10
   const minInterval = intervalData?.min_interval ?? 5
   const maxInterval = intervalData?.max_interval ?? 60
+  const [intervalDraft, setIntervalDraft] = useState(interval)
+  const watchlistSymbols = prefs?.realtime_watchlist_symbols ?? []
+  const watchlist = useQuery({
+    queryKey: QK.watchlist,
+    queryFn: () => api.watchlistList(),
+    enabled: isFreeTier && watchlistSymbols.length > 0,
+  })
+  const watchlistNameBySymbol = new Map(
+    (watchlist.data?.symbols ?? []).map(row => [row.symbol, row.name] as const),
+  )
 
   const save = useCallback(async (cfg: Record<string, unknown>) => {
     try {
@@ -110,6 +122,18 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
     onError: () => toast('修正请求失败', 'error'),
   })
 
+  useEffect(() => {
+    setIntervalDraft(interval)
+  }, [interval])
+
+  useEffect(() => {
+    if (intervalDraft === interval) return
+    const t = window.setTimeout(() => {
+      updateInterval.mutate(intervalDraft)
+    }, 2000)
+    return () => window.clearTimeout(t)
+  }, [intervalDraft, interval, updateInterval])
+
   // highlight=depth-fix 时闪烁高亮连板梯队修正卡片
   const [flash, setFlash] = useState(false)
   const flashedRef = useRef(false)
@@ -125,8 +149,7 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
     }
   }, [highlight])
 
-  // Free 档位 — 显示升级提示
-  if (isFreeTier) {
+  if (isNoneTier) {
     return (
       <div className="flex flex-col items-center justify-center py-20 text-center">
         <div className="inline-flex items-center justify-center w-14 h-14 rounded-2xl
@@ -135,8 +158,7 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
         </div>
         <h2 className="text-lg font-medium text-foreground mb-2">实时监控</h2>
         <p className="text-sm text-secondary max-w-md mb-6">
-          实时行情轮询、策略监控等功能需要 Starter 及以上档位。
-          升级后可配置轮询间隔、选择监控策略池。
+          实时行情需要 Free 及以上档位。None 档可使用 free-api 获取历史日K（当日数据需盘后1-2小时），但不能调用付费服务器实时接口。
         </p>
         <a
           href="/settings?tab=account"
@@ -167,10 +189,12 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
             <div className="flex items-center justify-between gap-4 py-1">
               <div className="min-w-0">
                 <div className="text-sm text-foreground">轮询间隔</div>
-                <div className="text-[11px] text-muted">每轮拉取全市场行情的时间间隔</div>
+                <div className="text-[11px] text-muted">
+                  {isFreeTier ? '每轮拉取自选股实时行情的时间间隔' : '每轮拉取全市场行情的时间间隔'}
+                </div>
               </div>
               <span className="text-[11px] font-mono text-foreground shrink-0 tabular-nums">
-                {interval < 1 ? interval.toFixed(1) : interval.toFixed(0)}s
+                {intervalDraft < 1 ? intervalDraft.toFixed(1) : intervalDraft.toFixed(0)}s
               </span>
             </div>
             <div className="flex items-center gap-3 mt-2">
@@ -179,18 +203,54 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
                 min={minInterval}
                 max={maxInterval}
                 step={minInterval < 1 ? 0.1 : minInterval < 3 ? 0.5 : 1}
-                value={interval}
-                onChange={(e) => updateInterval.mutate(parseFloat(e.target.value))}
+                value={intervalDraft}
+                onChange={(e) => setIntervalDraft(parseFloat(e.target.value))}
                 className="flex-1 h-1 accent-accent cursor-pointer"
               />
               <span className="text-[10px] text-muted shrink-0">
-                {minInterval}s — {maxInterval}s
+                {intervalDraft !== interval ? '2秒后保存' : `${minInterval}s — ${maxInterval}s`}
               </span>
             </div>
           </div>
         </Card>
 
-        {/* 页面刷新 */}
+        {isFreeTier && (
+        <Card icon={Activity} title="自选股实时">
+          <div className="mb-3 rounded-btn border border-accent/25 bg-accent/10 px-3 py-2 text-xs font-medium leading-snug text-accent">
+            Free 档开启实时行情时自动监控「自选」页面前 5 个标的，最低 6 秒刷新。
+          </div>
+          {watchlistSymbols.length > 0 ? (
+            <div className="space-y-1.5">
+              {watchlistSymbols.map(symbol => {
+                const name = watchlistNameBySymbol.get(symbol)
+                return (
+                  <div key={symbol} className="flex items-center justify-between rounded-btn bg-base/50 border border-border px-2 py-1.5">
+                    <div className="min-w-0 flex items-baseline gap-1.5">
+                      <span className="text-xs font-mono text-foreground">{symbol}</span>
+                      {name && <span className="truncate text-[11px] text-secondary">{name}</span>}
+                    </div>
+                    <span className="text-[10px] text-muted shrink-0">自选页</span>
+                  </div>
+                )
+              })}
+            </div>
+          ) : (
+            <div className="rounded-btn border border-border bg-base/40 px-3 py-3 text-xs text-muted">
+              自选列表为空，Free 实时行情开启前请先添加自选股。
+            </div>
+          )}
+          <div className="mt-2 flex items-center justify-between gap-3">
+            <span className="text-[10px] text-muted">当前 {watchlistSymbols.length}/5 只</span>
+            <Link
+              to="/watchlist"
+              className="px-3 py-1 rounded-btn bg-elevated text-secondary text-xs font-medium hover:text-foreground transition-colors"
+            >
+              管理自选
+            </Link>
+          </div>
+        </Card>
+        )}
+        {!isFreeTier && (
         <Card icon={Wifi} title="页面实时刷新">
           <p className="text-xs text-secondary mb-4">
             选择哪些页面跟随 SSE 实时刷新数据。关闭的页面不会被推送，
@@ -208,7 +268,9 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
             ))}
           </div>
         </Card>
+        )}
 
+        {!isFreeTier && (
         <Card icon={BarChart3} title="左侧菜单指数">
           <p className="text-xs text-secondary mb-4">
             选择实时行情开启时，左侧菜单底部显示哪些指数点位和涨跌幅。
@@ -233,6 +295,7 @@ export function SettingsMonitoringPanel({ highlight }: { highlight?: string } =
             />
           </div>
         </Card>
+        )}
       </div>
 
       {/* ========== 右列 ========== */}

frontend/src/router.tsx

@@ -13,6 +13,7 @@ import { AnalysisDetail } from './pages/AnalysisDetail'
 import { ConceptAnalysis } from './pages/ConceptAnalysis'
 import { IndustryAnalysis } from './pages/IndustryAnalysis'
 import { StockAnalysis } from './pages/StockAnalysis'
+import { Review } from './pages/Review'
 import { LimitUpLadder } from './pages/LimitUpLadder'
 import { Branding } from './pages/Branding'
 import { Settings } from './pages/Settings'
@@ -65,6 +66,7 @@ export const router = createBrowserRouter([
       { path: 'concept-analysis', element: <ConceptAnalysis /> },
       { path: 'industry-analysis', element: <IndustryAnalysis /> },
       { path: 'stock-analysis', element: <StockAnalysis /> },
+      { path: 'review', element: <Review /> },
       { path: 'watchlist', element: <Watchlist /> },
       { path: 'screener', element: <Screener /> },
       { path: 'backtest', element: <Backtest /> },

tiers.yaml

@@ -19,20 +19,21 @@
 #   none  = 无 key / 乱填 / 无效 key。运行时走 free-api 服务器(free 通道),
 #           仅历史日K(含批量),无实时行情。不存 API Key。
 #   free  = 免费有效 key(付费端点验证:有单只日K、无复权因子)。
-#           运行时同样走 free-api 服务器(key 被忽略),能力与 none 等价;
-#           存 key 仅作档位标记,便于将来 SDK 支持免费 key 时自动升级。
-#   两者运行时服务器相同(free-api),区别只在是否存 key。
+#           历史/盘后日K仍走 free-api 服务器；实时行情走付费服务器按标的接口。
+#           可用于自选股实时监控:10 次/分,每次最多 5 标的。
+#   none 与 free 的历史日K通道相同(free-api),区别在于 free 有付费服务器按标的实时权限。
 #   starter+ 才走付费端点 api.tickflow.org,有实时行情。
 
 none:
   # 无 key / 无效 key —— 走 free-api 服务器,仅历史日K(含批量),无实时行情
   kline.daily.by_symbol: { rpm: 60, batch: 1 }
-  kline.daily.batch:     { rpm: 60, batch: 50 }   # free-api 服务器批量日K
+  kline.daily.batch:     { rpm: 60, batch: 100 }   # free-api 服务器批量日K(接口限制 60 次/分, 每批最多 100 标的)
 
 free:
-  # 免费有效 key —— 运行时同样走 free-api 服务器,能力与 none 等价
+  # 免费有效 key —— 历史日K走 free-api；自选实时走付费服务器按标的接口
+  quote.by_symbol:       { rpm: 10, batch: 5 }
   kline.daily.by_symbol: { rpm: 60, batch: 1 }
-  kline.daily.batch:     { rpm: 60, batch: 50 }   # [补] 批量日K(此前缺失)
+  kline.daily.batch:     { rpm: 60, batch: 100 }   # free-api 服务器批量日K(同 none, 60 次/分, 每批最多 100 标的)
 
 starter:
   quote.by_symbol:       { rpm: 60, batch: 50 }