update

app/ui/streamlit_app.py

@@ -58,6 +58,7 @@ from app.utils.portfolio import (
 )
 from app.agents.registry import default_agents
 from app.utils.tuning import log_tuning_result
+from app.backtest.engine import BacktestEngine, PortfolioState
 
 
 LOGGER = get_logger(__name__)
@@ -67,6 +68,9 @@ _DECISION_ENV_BATCH_RESULTS_KEY = "decision_env_batch_results"
 _DASHBOARD_CONTAINERS: Optional[tuple[object, object]] = None
 _DASHBOARD_ELEMENTS: Optional[Dict[str, object]] = None
 _SIDEBAR_LISTENER_ATTACHED = False
+# ADD: simple in-memory cache for provider model discovery
+_MODEL_CACHE: Dict[str, Dict[str, object]] = {}
+_CACHE_TTL_SECONDS = 300
 
 
 def _sidebar_metrics_listener(metrics: Dict[str, object]) -> None:
@@ -210,6 +214,16 @@ def _discover_provider_models(provider: LLMProvider, base_override: str = "", ap
     timeout = float(provider.default_timeout or 30.0)
     mode = provider.mode or ("ollama" if provider.key == "ollama" else "openai")
 
+    # ADD: simple cache by provider+base URL
+    cache_key = f"{provider.key}|{base_url}"
+    now = datetime.now()
+    cached = _MODEL_CACHE.get(cache_key)
+    if cached:
+        ts = cached.get("ts")
+        if isinstance(ts, float) and (now.timestamp() - ts) < _CACHE_TTL_SECONDS:
+            models = list(cached.get("models") or [])
+            return models, None
+
     try:
         if mode == "ollama":
             url = base_url.rstrip('/') + "/api/tags"
@@ -221,6 +235,7 @@ def _discover_provider_models(provider: LLMProvider, base_override: str = "", ap
                 name = item.get("name") or item.get("model") or item.get("tag")
                 if name:
                     models.append(str(name).strip())
+            _MODEL_CACHE[cache_key] = {"ts": now.timestamp(), "models": sorted(set(models))}
             return sorted(set(models)), None
 
         api_key = (api_override or provider.api_key or "").strip()
@@ -239,6 +254,7 @@ def _discover_provider_models(provider: LLMProvider, base_override: str = "", ap
             for item in payload.get("data", [])
             if item.get("id")
         ]
+        _MODEL_CACHE[cache_key] = {"ts": now.timestamp(), "models": sorted(set(models))}
         return sorted(set(models)), None
     except RequestException as exc:  # noqa: BLE001
         return [], f"HTTP 错误：{exc}"
@@ -345,7 +361,7 @@ def render_today_plan() -> None:
     if latest_trade_date:
         st.caption(f"最新交易日：{latest_trade_date.isoformat()}（统计数据请见左侧系统监控）")
     else:
-        st.caption("统计与决策概览现已移至左侧“系统监控”侧栏。")
+        st.caption("统计与决策概览现已移至左侧'系统监控'侧栏。")
     try:
         with db_session(read_only=True) as conn:
             date_rows = conn.execute(
@@ -384,6 +400,8 @@ def render_today_plan() -> None:
         return
 
     ts_code = st.selectbox("标的", symbols, index=0)
+    # ADD: batch selection for re-evaluation
+    batch_symbols = st.multiselect("批量重评估（可多选）", symbols, default=[])
 
     with db_session(read_only=True) as conn:
         rows = conn.execute(
@@ -523,7 +541,16 @@ def render_today_plan() -> None:
 
     st.subheader("部门意见")
     if dept_records:
-        dept_df = pd.DataFrame(dept_records)
+        # ADD: keyword filter for department summaries
+        keyword = st.text_input("筛选摘要/信号关键词", value="")
+        filtered = dept_records
+        if keyword.strip():
+            kw = keyword.strip()
+            filtered = [
+                item for item in dept_records
+                if kw in str(item.get("摘要", "")) or kw in str(item.get("核心信号", ""))
+            ]
+        dept_df = pd.DataFrame(filtered)
         st.dataframe(dept_df, width='stretch', hide_index=True)
         for code, details in dept_details.items():
             with st.expander(f"{code} 补充详情", expanded=False):
@@ -636,6 +663,122 @@ def render_today_plan() -> None:
 
     st.caption("数据来源：agent_utils、investment_pool、portfolio_positions、portfolio_trades、portfolio_snapshots。")
 
+    st.divider()
+    st.subheader("策略重评估")
+    st.caption("对当前选中的交易日与标的，立即触发一次策略评估并回写 agent_utils。")
+    cols_re = st.columns([1,1])
+    if cols_re[0].button("对该标的重评估", key="reevaluate_current_symbol"):
+        with st.spinner("正在重评估..."):
+            try:
+                trade_date_obj = None
+                try:
+                    trade_date_obj = date.fromisoformat(str(trade_date))
+                except Exception:
+                    try:
+                        trade_date_obj = datetime.strptime(str(trade_date), "%Y%m%d").date()
+                    except Exception:
+                        pass
+                if trade_date_obj is None:
+                    raise ValueError(f"无法解析交易日：{trade_date}")
+                # snapshot before
+                with db_session(read_only=True) as conn:
+                    before_rows = conn.execute(
+                        """
+                        SELECT agent, action, utils FROM agent_utils
+                        WHERE trade_date = ? AND ts_code = ?
+                        """,
+                        (trade_date, ts_code),
+                    ).fetchall()
+                before_map = {row["agent"]: (row["action"], row["utils"]) for row in before_rows}
+                cfg = BtConfig(
+                    id="reeval_ui",
+                    name="UI Re-evaluation",
+                    start_date=trade_date_obj,
+                    end_date=trade_date_obj,
+                    universe=[ts_code],
+                    params={},
+                )
+                engine = BacktestEngine(cfg)
+                state = PortfolioState()
+                _ = engine.simulate_day(trade_date_obj, state)
+                # compare after
+                with db_session(read_only=True) as conn:
+                    after_rows = conn.execute(
+                        """
+                        SELECT agent, action, utils FROM agent_utils
+                        WHERE trade_date = ? AND ts_code = ?
+                        """,
+                        (trade_date, ts_code),
+                    ).fetchall()
+                changes = []
+                for row in after_rows:
+                    agent = row["agent"]
+                    new_action = row["action"]
+                    old_action, _old_utils = before_map.get(agent, (None, None))
+                    if new_action != old_action:
+                        changes.append({"代理": agent, "原动作": old_action, "新动作": new_action})
+                if changes:
+                    st.success("重评估完成，检测到动作变更：")
+                    st.dataframe(pd.DataFrame(changes), hide_index=True, width='stretch')
+                else:
+                    st.success("重评估完成，无动作变更。")
+                st.rerun()
+            except Exception as exc:  # noqa: BLE001
+                LOGGER.exception("重评估失败", extra=LOG_EXTRA)
+                st.error(f"重评估失败：{exc}")
+    if cols_re[1].button("批量重评估（所选）", key="reevaluate_batch", disabled=not batch_symbols):
+        with st.spinner("批量重评估执行中..."):
+            try:
+                trade_date_obj = None
+                try:
+                    trade_date_obj = date.fromisoformat(str(trade_date))
+                except Exception:
+                    try:
+                        trade_date_obj = datetime.strptime(str(trade_date), "%Y%m%d").date()
+                    except Exception:
+                        pass
+                if trade_date_obj is None:
+                    raise ValueError(f"无法解析交易日：{trade_date}")
+                progress = st.progress(0.0)
+                changes_all: List[Dict[str, object]] = []
+                for idx, code in enumerate(batch_symbols, start=1):
+                    with db_session(read_only=True) as conn:
+                        before_rows = conn.execute(
+                            "SELECT agent, action FROM agent_utils WHERE trade_date = ? AND ts_code = ?",
+                            (trade_date, code),
+                        ).fetchall()
+                    before_map = {row["agent"]: row["action"] for row in before_rows}
+                    cfg = BtConfig(
+                        id="reeval_ui_batch",
+                        name="UI Batch Re-eval",
+                        start_date=trade_date_obj,
+                        end_date=trade_date_obj,
+                        universe=[code],
+                        params={},
+                    )
+                    engine = BacktestEngine(cfg)
+                    state = PortfolioState()
+                    _ = engine.simulate_day(trade_date_obj, state)
+                    with db_session(read_only=True) as conn:
+                        after_rows = conn.execute(
+                            "SELECT agent, action FROM agent_utils WHERE trade_date = ? AND ts_code = ?",
+                            (trade_date, code),
+                        ).fetchall()
+                    for row in after_rows:
+                        agent = row["agent"]
+                        new_action = row["action"]
+                        old_action = before_map.get(agent)
+                        if new_action != old_action:
+                            changes_all.append({"代码": code, "代理": agent, "原动作": old_action, "新动作": new_action})
+                    progress.progress(idx / max(1, len(batch_symbols)))
+                st.success("批量重评估完成。")
+                if changes_all:
+                    st.dataframe(pd.DataFrame(changes_all), hide_index=True, width='stretch')
+                st.rerun()
+            except Exception as exc:  # noqa: BLE001
+                LOGGER.exception("批量重评估失败", extra=LOG_EXTRA)
+                st.error(f"批量重评估失败：{exc}")
+
 
 def render_backtest() -> None:
     LOGGER.info("渲染回测页面", extra=LOG_EXTRA)
@@ -1237,6 +1380,84 @@ def render_backtest() -> None:
                     st.session_state.pop("decision_env_batch_select", None)
                     st.success("已清除批量调参结果缓存。")
 
+    # ADD: Comparison view for multiple backtest configurations
+    with st.expander("回测结果对比", expanded=False):
+        st.caption("从历史回测配置中选择多个进行净值曲线与指标对比。")
+        normalize_to_one = st.checkbox("归一化到 1 起点", value=True)
+        use_log_y = st.checkbox("对数坐标", value=False)
+        metric_options = ["总收益", "最大回撤", "交易数", "平均换手", "风险事件"]
+        selected_metrics = st.multiselect("显示指标列", metric_options, default=metric_options)
+        try:
+            with db_session(read_only=True) as conn:
+                cfg_rows = conn.execute(
+                    "SELECT id, name FROM bt_config ORDER BY rowid DESC LIMIT 50"
+                ).fetchall()
+        except Exception:  # noqa: BLE001
+            LOGGER.exception("读取 bt_config 失败", extra=LOG_EXTRA)
+            cfg_rows = []
+        cfg_options = [f"{row['id']} | {row['name']}" for row in cfg_rows]
+        selected_labels = st.multiselect("选择配置", cfg_options, default=cfg_options[:2])
+        selected_ids = [label.split(" | ")[0].strip() for label in selected_labels]
+        if selected_ids:
+            try:
+                with db_session(read_only=True) as conn:
+                    nav_df = pd.read_sql_query(
+                        "SELECT cfg_id, trade_date, nav FROM bt_nav WHERE cfg_id IN (%s)" % (",".join(["?"]*len(selected_ids))),
+                        conn,
+                        params=tuple(selected_ids),
+                    )
+                    rpt_df = pd.read_sql_query(
+                        "SELECT cfg_id, summary FROM bt_report WHERE cfg_id IN (%s)" % (",".join(["?"]*len(selected_ids))),
+                        conn,
+                        params=tuple(selected_ids),
+                    )
+            except Exception:  # noqa: BLE001
+                LOGGER.exception("读取回测结果失败", extra=LOG_EXTRA)
+                st.error("读取回测结果失败")
+                nav_df = pd.DataFrame()
+                rpt_df = pd.DataFrame()
+            if not nav_df.empty:
+                try:
+                    nav_df["trade_date"] = pd.to_datetime(nav_df["trade_date"], errors="coerce")
+                    pivot = nav_df.pivot_table(index="trade_date", columns="cfg_id", values="nav")
+                    if normalize_to_one:
+                        pivot = pivot.apply(lambda s: s / s.dropna().iloc[0] if s.dropna().size else s)
+                    import plotly.graph_objects as go
+                    fig = go.Figure()
+                    for col in pivot.columns:
+                        fig.add_trace(go.Scatter(x=pivot.index, y=pivot[col], mode="lines", name=str(col)))
+                    fig.update_layout(height=300, margin=dict(l=10, r=10, t=30, b=10))
+                    if use_log_y:
+                        fig.update_yaxes(type="log")
+                    st.plotly_chart(fig, use_container_width=True)
+                except Exception:  # noqa: BLE001
+                    LOGGER.debug("绘制对比曲线失败", extra=LOG_EXTRA)
+            if not rpt_df.empty:
+                try:
+                    metrics_rows: List[Dict[str, object]] = []
+                    for _, row in rpt_df.iterrows():
+                        cfg_id = row["cfg_id"]
+                        try:
+                            summary = json.loads(row["summary"]) if isinstance(row["summary"], str) else (row["summary"] or {})
+                        except json.JSONDecodeError:
+                            summary = {}
+                        record = {
+                            "cfg_id": cfg_id,
+                            "总收益": summary.get("total_return"),
+                            "最大回撤": summary.get("max_drawdown"),
+                            "交易数": summary.get("trade_count"),
+                            "平均换手": summary.get("avg_turnover"),
+                            "风险事件": summary.get("risk_events"),
+                        }
+                        metrics_rows.append({k: v for k, v in record.items() if (k == "cfg_id" or k in selected_metrics)})
+                    if metrics_rows:
+                        dfm = pd.DataFrame(metrics_rows)
+                        st.dataframe(dfm, hide_index=True, width='stretch')
+                except Exception:  # noqa: BLE001
+                    LOGGER.debug("渲染指标表失败", extra=LOG_EXTRA)
+        else:
+            st.info("请选择至少一个配置进行对比。")
+
 
 def render_settings() -> None:
     LOGGER.info("渲染设置页面", extra=LOG_EXTRA)