update

app/ui/streamlit_app.py

@@ -415,13 +415,10 @@ def render_today_plan() -> None:
         LOGGER.exception("加载 agent_utils 失败", extra=LOG_EXTRA)
         st.warning("暂未写入部门/代理决策，请先运行回测或策略评估流程。")
         return
-
     trade_dates = [row["trade_date"] for row in date_rows]
     if not trade_dates:
         st.info("暂无决策记录，完成一次回测后即可在此查看部门意见与投票结果。")
         return
-
-    # ADD: read default selection from URL
     q = _get_query_params()
     default_trade_date = q.get("date", [trade_dates[0]])[0]
     try:
@@ -429,7 +426,6 @@ def render_today_plan() -> None:
     except ValueError:
         default_idx = 0
     trade_date = st.selectbox("交易日", trade_dates, index=default_idx)
-
     with db_session(read_only=True) as conn:
         code_rows = conn.execute(
             """
@@ -441,22 +437,9 @@ def render_today_plan() -> None:
             (trade_date,),
         ).fetchall()
     symbols = [row["ts_code"] for row in code_rows]
-    if not symbols:
+    detail_tab, assistant_tab = st.tabs(["标的详情", "投资助理模式"])
-        st.info("所选交易日暂无 agent_utils 记录。")
+    with assistant_tab:
-        return
-
-    # ADD: 投资助理模式开关（不指定具体标的）
-    assistant_mode = st.checkbox(
-        "投资助理（不指定标的）",
-        value=False,
-        help="开启后不显示具体标的，展示基于候选投资池的组合级建议与汇总信息。",
-    )
-
-    if assistant_mode:
-        ts_code = None
-        batch_symbols = []
         st.info("已开启投资助理模式：以下内容为组合级（去标的）建议，不包含任何具体标的代码。")
-        # 展示候选池聚合信息（不暴露具体代码）
         try:
             candidates = list_investment_pool(trade_date=trade_date)
             if candidates:
@@ -525,6 +508,9 @@ def render_today_plan() -> None:
         except Exception:
             LOGGER.exception("加载候选池聚合信息失败", extra=LOG_EXTRA)
             st.error("加载候选池数据时发生错误。")
+    with detail_tab:
+        if not symbols:
+            st.info("所选交易日暂无 agent_utils 记录。")
         else:
             default_ts = q.get("code", [symbols[0]])[0]
             try:
@@ -532,10 +518,8 @@ def render_today_plan() -> None:
             except ValueError:
                 default_ts_idx = 0
             ts_code = st.selectbox("标的", symbols, index=default_ts_idx)
-        # ADD: batch selection for re-evaluation
             batch_symbols = st.multiselect("批量重评估（可多选）", symbols, default=[])
 
-    # 一键重评估所有标的按钮
             if st.button("一键重评估所有标的", type="primary", width='stretch'):
                 with st.spinner("正在对所有标的进行重评估，请稍候..."):
                     try:
@@ -616,10 +600,7 @@ def render_today_plan() -> None:
                     except Exception as exc:
                         LOGGER.exception("一键重评估失败", extra=LOG_EXTRA)
                         st.error(f"一键重评估执行过程中发生错误：{exc}")
-
-    # sync URL params
             _set_query_params(date=str(trade_date), code=str(ts_code))
-
             with db_session(read_only=True) as conn:
                 rows = conn.execute(
                     """
@@ -630,21 +611,17 @@ def render_today_plan() -> None:
                     """,
                     (trade_date, ts_code),
                 ).fetchall()
-
             if not rows:
                 st.info("未查询到详细决策记录，稍后再试。")
                 return
-
             try:
                 feasible_actions = json.loads(rows[0]["feasible"] or "[]")
             except (KeyError, TypeError, json.JSONDecodeError):
                 feasible_actions = []
-
             global_info = None
             dept_records: List[Dict[str, object]] = []
             dept_details: Dict[str, Dict[str, object]] = {}
             agent_records: List[Dict[str, object]] = []
-
             for item in rows:
                 agent_name = item["agent"]
                 action = item["action"]
@@ -715,10 +692,8 @@ def render_today_plan() -> None:
                             "BUY_L": score_map.get("BUY_L", 0.0),
                         }
                 )
-
             if feasible_actions:
                 st.caption(f"可行操作集合：{', '.join(feasible_actions)}")
-
             st.subheader("全局策略")
             if global_info:
                 col1, col2, col3 = st.columns(3)
@@ -782,7 +757,6 @@ def render_today_plan() -> None:
                         st.json(dept_telemetry)
             else:
                 st.info("暂未写入全局策略摘要。")
-
             st.subheader("部门意见")
             if dept_records:
                 # ADD: keyword filter for department summaries
@@ -832,7 +806,6 @@ def render_today_plan() -> None:
                             st.json(telemetry)
             else:
                 st.info("暂无部门记录。")
-
             st.subheader("代理评分")
             if agent_records:
                 # ADD: sorting and CSV export for agents
@@ -857,11 +830,8 @@ def render_today_plan() -> None:
                     pass
             else:
                 st.info("暂无基础代理评分。")
-
-    # 添加相关新闻展示部分
             st.divider()
             st.subheader("相关新闻")
-    # 获取与当前标的相关的最新新闻
             try:
                 with db_session(read_only=True) as conn:
                     # 解析当前trade_date为datetime对象
@@ -959,11 +929,8 @@ def render_today_plan() -> None:
             except Exception as e:
                 LOGGER.exception("获取新闻数据失败", extra=LOG_EXTRA)
                 st.error(f"获取新闻数据时发生错误：{e}")
-
             st.divider()
-    # 提示用户跳转到单独的“投资池与仓位概览”页
             st.info("投资池与仓位概览已移至单独页面。请在侧边或页面导航中选择“投资池/仓位”以查看详细信息。")
-
             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。")
@@ -1081,129 +1048,6 @@ def render_today_plan() -> None:
                         st.error(f"批量重评估失败：{exc}")
 
 
-def render_log_viewer() -> None:
-    """渲染日志钻取与历史对比视图页面。"""
-    LOGGER.info("渲染日志视图页面", extra=LOG_EXTRA)
-    st.header("日志钻取与历史对比")
-    st.write("查看系统运行日志，支持时间范围筛选、关键词搜索和历史对比功能。")
-    
-    # 日志时间范围选择
-    col1, col2 = st.columns(2)
-    with col1:
-        start_date = st.date_input("开始日期", value=date.today() - timedelta(days=7))
-    with col2:
-        end_date = st.date_input("结束日期", value=date.today())
-    
-    # 日志级别筛选
-    log_levels = ["ALL", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
-    selected_level = st.selectbox("日志级别", log_levels, index=1)
-    
-    # 关键词搜索
-    search_query = st.text_input("搜索关键词")
-    
-    # 阶段筛选
-    with db_session(read_only=True) as conn:
-        stages = [row["stage"] for row in conn.execute("SELECT DISTINCT stage FROM run_log").fetchall()]
-    stages = [s for s in stages if s]  # 过滤空值
-    stages.insert(0, "ALL")
-    selected_stage = st.selectbox("执行阶段", stages)
-    
-    # 查询日志
-    with st.spinner("加载日志数据中..."):
-        try:
-            with db_session(read_only=True) as conn:
-                query_parts = ["SELECT ts, stage, level, msg FROM run_log WHERE 1=1"]
-                params = []
-                
-                # 添加日期过滤
-                start_ts = f"{start_date.isoformat()}T00:00:00Z"
-                end_ts = f"{end_date.isoformat()}T23:59:59Z"
-                query_parts.append("AND ts BETWEEN ? AND ?")
-                params.extend([start_ts, end_ts])
-                
-                # 添加级别过滤
-                if selected_level != "ALL":
-                    query_parts.append("AND level = ?")
-                    params.append(selected_level)
-                
-                # 添加关键词过滤
-                if search_query:
-                    query_parts.append("AND msg LIKE ?")
-                    params.append(f"%{search_query}%")
-                
-                # 添加阶段过滤
-                if selected_stage != "ALL":
-                    query_parts.append("AND stage = ?")
-                    params.append(selected_stage)
-                
-                # 添加排序
-                query_parts.append("ORDER BY ts DESC")
-                
-                # 执行查询
-                query = " ".join(query_parts)
-                rows = conn.execute(query, params).fetchall()
-                
-                # 转换为DataFrame
-                if rows:
-                    # 将sqlite3.Row对象转换为字典列表
-                    rows_dict = [{key: row[key] for key in row.keys()} for row in rows]
-                    log_df = pd.DataFrame(rows_dict)
-                    # 格式化时间戳并确保数据类型一致
-                    log_df["ts"] = pd.to_datetime(log_df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
-                    # 确保所有列都是字符串类型，避免PyArrow序列化错误
-                    for col in log_df.columns:
-                        log_df[col] = log_df[col].astype(str)
-                else:
-                    log_df = pd.DataFrame(columns=["ts", "stage", "level", "msg"])
-                
-                # 显示日志表格
-                st.dataframe(
-                    log_df,
-                    hide_index=True,
-                    width="stretch",
-                    column_config={
-                        "ts": st.column_config.TextColumn("时间"),
-                        "stage": st.column_config.TextColumn("执行阶段"),
-                        "level": st.column_config.TextColumn("日志级别"),
-                        "msg": st.column_config.TextColumn("日志消息", width="large")
-                    }
-                )
-                
-                # 下载功能
-                if not log_df.empty:
-                    csv_data = log_df.to_csv(index=False).encode('utf-8')
-                    st.download_button(
-                        label="下载日志CSV",
-                        data=csv_data,
-                        file_name=f"logs_{start_date}_{end_date}.csv",
-                        mime="text/csv",
-                        key="download_logs"
-                    )
-                    
-                    # JSON下载
-                    json_data = log_df.to_json(orient='records', force_ascii=False, indent=2)
-                    st.download_button(
-                        label="下载日志JSON",
-                        data=json_data,
-                        file_name=f"logs_{start_date}_{end_date}.json",
-                        mime="application/json",
-                        key="download_logs_json"
-                    )
-        except Exception as e:
-            LOGGER.exception("加载日志失败", extra=LOG_EXTRA)
-            st.error(f"加载日志数据失败：{e}")
-    
-    # 历史对比功能
-    st.subheader("历史对比")
-    st.write("选择两个时间点的日志进行对比分析。")
-    
-    # 第一个时间点选择
-    col3, col4 = st.columns(2)
-    with col3:
-        compare_date1 = st.date_input("对比日期1", value=date.today() - timedelta(days=1))
-    with col4:
-        compare_date2 = st.date_input("对比日期2", value=date.today())
-
 
 def render_pool_overview() -> None:
     """单独的投资池与仓位概览页面（从今日计划中提取）。"""
@@ -2872,6 +2716,161 @@ def render_tests() -> None:
                 st.write(response)
 
 
+def render_log_viewer() -> None:
+    """渲染日志钻取与历史对比视图页面。"""
+    LOGGER.info("渲染日志视图页面", extra=LOG_EXTRA)
+    st.header("日志钻取与历史对比")
+    st.write("查看系统运行日志，支持时间范围筛选、关键词搜索和历史对比功能。")
+
+    col1, col2 = st.columns(2)
+    with col1:
+        start_date = st.date_input("开始日期", value=date.today() - timedelta(days=7))
+    with col2:
+        end_date = st.date_input("结束日期", value=date.today())
+
+    log_levels = ["ALL", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
+    selected_level = st.selectbox("日志级别", log_levels, index=1)
+
+    search_query = st.text_input("搜索关键词")
+
+    with db_session(read_only=True) as conn:
+        stages = [row["stage"] for row in conn.execute("SELECT DISTINCT stage FROM run_log").fetchall()]
+    stages = [s for s in stages if s]
+    stages.insert(0, "ALL")
+    selected_stage = st.selectbox("执行阶段", stages)
+
+    with st.spinner("加载日志数据中..."):
+        try:
+            with db_session(read_only=True) as conn:
+                query_parts = ["SELECT ts, stage, level, msg FROM run_log WHERE 1=1"]
+                params: list[object] = []
+
+                start_ts = f"{start_date.isoformat()}T00:00:00Z"
+                end_ts = f"{end_date.isoformat()}T23:59:59Z"
+                query_parts.append("AND ts BETWEEN ? AND ?")
+                params.extend([start_ts, end_ts])
+
+                if selected_level != "ALL":
+                    query_parts.append("AND level = ?")
+                    params.append(selected_level)
+
+                if search_query:
+                    query_parts.append("AND msg LIKE ?")
+                    params.append(f"%{search_query}%")
+
+                if selected_stage != "ALL":
+                    query_parts.append("AND stage = ?")
+                    params.append(selected_stage)
+
+                query_parts.append("ORDER BY ts DESC")
+
+                query = " ".join(query_parts)
+                rows = conn.execute(query, params).fetchall()
+
+                if rows:
+                    rows_dict = [{key: row[key] for key in row.keys()} for row in rows]
+                    log_df = pd.DataFrame(rows_dict)
+                    log_df["ts"] = pd.to_datetime(log_df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
+                    for col in log_df.columns:
+                        log_df[col] = log_df[col].astype(str)
+                else:
+                    log_df = pd.DataFrame(columns=["ts", "stage", "level", "msg"])
+
+                st.dataframe(
+                    log_df,
+                    hide_index=True,
+                    width="stretch",
+                    column_config={
+                        "ts": st.column_config.TextColumn("时间"),
+                        "stage": st.column_config.TextColumn("执行阶段"),
+                        "level": st.column_config.TextColumn("日志级别"),
+                        "msg": st.column_config.TextColumn("日志消息", width="large"),
+                    },
+                )
+
+                if not log_df.empty:
+                    csv_data = log_df.to_csv(index=False).encode("utf-8")
+                    st.download_button(
+                        label="下载日志CSV",
+                        data=csv_data,
+                        file_name=f"logs_{start_date}_{end_date}.csv",
+                        mime="text/csv",
+                        key="download_logs",
+                    )
+
+                    json_data = log_df.to_json(orient="records", force_ascii=False, indent=2)
+                    st.download_button(
+                        label="下载日志JSON",
+                        data=json_data,
+                        file_name=f"logs_{start_date}_{end_date}.json",
+                        mime="application/json",
+                        key="download_logs_json",
+                    )
+        except Exception as exc:  # noqa: BLE001
+            LOGGER.exception("加载日志失败", extra=LOG_EXTRA)
+            st.error(f"加载日志数据失败：{exc}")
+
+    st.subheader("历史对比")
+    st.write("选择两个时间点的日志进行对比分析。")
+
+    col3, col4 = st.columns(2)
+    with col3:
+        compare_date1 = st.date_input("对比日期1", value=date.today() - timedelta(days=1))
+    with col4:
+        compare_date2 = st.date_input("对比日期2", value=date.today())
+
+    comparison_stage = st.selectbox("对比阶段", stages, key="compare_stage")
+    st.write("选择需要比较的日志数量。")
+    compare_limit = st.slider("对比日志数量", min_value=10, max_value=200, value=50, step=10)
+
+    if st.button("生成历史对比报告"):
+        with st.spinner("生成对比报告中..."):
+            try:
+                with db_session(read_only=True) as conn:
+                    def load_logs(d: date) -> pd.DataFrame:
+                        start_ts = f"{d.isoformat()}T00:00:00Z"
+                        end_ts = f"{d.isoformat()}T23:59:59Z"
+                        query = ["SELECT ts, level, msg FROM run_log WHERE ts BETWEEN ? AND ?"]
+                        params: list[object] = [start_ts, end_ts]
+                        if comparison_stage != "ALL":
+                            query.append("AND stage = ?")
+                            params.append(comparison_stage)
+                        query.append("ORDER BY ts DESC LIMIT ?")
+                        params.append(compare_limit)
+                        sql = " ".join(query)
+                        rows = conn.execute(sql, params).fetchall()
+                        if not rows:
+                            return pd.DataFrame(columns=["ts", "level", "msg"])
+                        df = pd.DataFrame([{k: row[k] for k in row.keys()} for row in rows])
+                        df["ts"] = pd.to_datetime(df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
+                        return df
+
+                    df1 = load_logs(compare_date1)
+                    df2 = load_logs(compare_date2)
+
+                if df1.empty and df2.empty:
+                    st.info("选定日期暂无日志可对比。")
+                else:
+                    st.write("### 对比结果")
+                    col_a, col_b = st.columns(2)
+                    with col_a:
+                        st.write(f"{compare_date1} 日日志")
+                        st.dataframe(df1, hide_index=True, width="stretch")
+                    with col_b:
+                        st.write(f"{compare_date2} 日日志")
+                        st.dataframe(df2, hide_index=True, width="stretch")
+
+                    summary = {
+                        "日期1日志条数": int(len(df1)),
+                        "日期2日志条数": int(len(df2)),
+                        "新增日志条数": max(len(df2) - len(df1), 0),
+                    }
+                    st.write("摘要：", summary)
+            except Exception as exc:  # noqa: BLE001
+                LOGGER.exception("历史对比生成失败", extra=LOG_EXTRA)
+                st.error(f"生成历史对比失败：{exc}")
+
+
 def render_data_settings() -> None:
     """渲染数据源配置界面."""
     st.subheader("Tushare 数据源")