功能更新

backend/app/schemas.py

@@ -24,7 +24,7 @@ class CandleOut(BaseModel):
 
 # ---------- Backtest ----------
 class BacktestRequest(BaseModel):
-    symbol: str = "DEMO"
+    symbol: str = "000001"
     timeframe: str = "1d"
     strategy: str = "macd_cross"        # macd_cross | ma_cross | single_ma
     params: dict[str, float] = Field(default_factory=dict)  # 各策略参数
@@ -82,6 +82,68 @@ class SyncRequest(BaseModel):
     force: bool = False            # True => 忽略缓存重新拉取
 
 
+# ---------- Event Backtest（自然语言事件回测） ----------
+class EventBacktestSpec(BaseModel):
+    """事件回测参数：entry 条件在信号日 D 收盘确认 -> D+1 买入 -> 持有 N 日卖出。"""
+    entry: ScreenConditions
+    entry_timing: Literal["next_open", "next_close"] = "next_open"  # 次日开盘/收盘买入
+    holding_days: int = Field(default=3, ge=1, le=250)               # 买入后再持有 N 个交易日
+    exit_timing: Literal["close", "open"] = "close"                  # 到期按收盘/开盘卖出
+
+
+class EventBacktestRequest(BaseModel):
+    text: str = Field(min_length=2, max_length=500)
+    spec: EventBacktestSpec | None = None   # 直传则跳过 LLM 解析（调参重跑）
+    ts_code: str | None = None              # 指定则只回测该股；空则全市场
+    start: datetime | None = None
+    end: datetime | None = None
+
+
+class EventTradeOut(BaseModel):
+    ts_code: str
+    name: str | None = None
+    entry_date: datetime
+    entry_price: float
+    exit_date: datetime
+    exit_price: float
+    ret_pct: float                          # 区间收益率 %（复权校正）
+
+
+class EventYearStatOut(BaseModel):
+    year: int
+    samples: int
+    mean_pct: float
+    median_pct: float
+    win_rate: float
+
+
+class EventStatsOut(BaseModel):
+    samples: int
+    stocks: int
+    mean_pct: float
+    median_pct: float
+    win_rate: float                         # %
+    std_pct: float = 0.0
+    p10_pct: float = 0.0
+    p25_pct: float = 0.0
+    p75_pct: float = 0.0
+    p90_pct: float = 0.0
+    max_pct: float = 0.0
+    min_pct: float = 0.0
+    by_year: list[EventYearStatOut] = Field(default_factory=list)
+
+
+class EventBacktestResponse(BaseModel):
+    text: str
+    spec: EventBacktestSpec
+    universe: str                            # "all" 或 ts_code
+    start: datetime
+    end: datetime
+    stats: EventStatsOut
+    trades: list[EventTradeOut] = Field(default_factory=list)  # 最好+最差样本（各 100）
+    total: int
+
+
 class SyncResponse(BaseModel):
     symbol: str
     bars: int
@@ -197,7 +259,7 @@ class PreviewInfoOut(BaseModel):
 class PreviewResponse(BaseModel):
     ts_code: str
     symbol: str
-    source: str                        # qfq=回测缓存全量前复权 | market=近段未复权兜底
+    source: str                        # bfq|qfq|hfq=实际复权口径（本地 adj_factor 换算） | market=近段未复权兜底
     info: PreviewInfoOut
     candles: list[CandleOut]
     indicators: dict[str, dict[str, list[float | None]]] = Field(default_factory=dict)
@@ -220,3 +282,61 @@ class CurrentUserOut(BaseModel):
 class LoginResponse(BaseModel):
     user: CurrentUserOut
     expires_at: datetime
+
+
+# ---------- 股票列表（全市场浏览） ----------
+class StockListItemOut(BaseModel):
+    ts_code: str
+    symbol: str
+    name: str
+    industry: str | None = None
+    market: str | None = None
+    close: float | None = None       # 最新收盘（candles 未复权）
+    prev_close: float | None = None
+    pct_chg: float | None = None     # 最新两根日线计算
+    last_ts: datetime | None = None
+    bar_count: int | None = None     # 本地缓存日线条数
+    watched: bool = False            # 是否自选（当前用户）
+
+
+class StockListResponse(BaseModel):
+    total: int
+    items: list[StockListItemOut]
+
+
+# ---------- 看股页筛选项 ----------
+class FacetItemOut(BaseModel):
+    name: str
+    count: int
+
+
+class StockFacetsResponse(BaseModel):
+    industries: list[FacetItemOut] = Field(default_factory=list)
+    areas: list[FacetItemOut] = Field(default_factory=list)
+
+
+# ---------- 用户偏好 / 自选股 / 提问历史 ----------
+class PreferencesOut(BaseModel):
+    prefs: dict[str, object] = Field(default_factory=dict)  # key -> JSON 值
+
+
+class PreferencesUpdate(BaseModel):
+    prefs: dict[str, object]  # 部分更新：只覆盖出现的 key（值为 null 表示删除）
+
+
+class WatchlistOp(BaseModel):
+    ts_code: str = Field(min_length=6, max_length=12)
+
+
+class ScreenerQueryOut(BaseModel):
+    id: int
+    text: str
+    conditions: ScreenConditions | None = None
+    hit_count: int | None = None
+    created_at: datetime
+
+    model_config = {"from_attributes": True}
+
+
+class ScreenerQueryListResponse(BaseModel):
+    items: list[ScreenerQueryOut]