update

app/agents/departments.py

@@ -9,11 +9,12 @@ from app.agents.base import AgentAction
 from app.llm.client import call_endpoint_with_messages, run_llm_with_config, LLMError
 from app.llm.prompts import department_prompt
 from app.utils.config import AppConfig, DepartmentSettings, LLMConfig
-from app.utils.logging import get_logger
+from app.utils.logging import get_logger, get_conversation_logger
 from app.utils.data_access import DataBroker
 
 LOGGER = get_logger(__name__)
 LOG_EXTRA = {"stage": "department"}
+CONV_LOGGER = get_conversation_logger()
 
 
 @dataclass
@@ -113,6 +114,12 @@ class DepartmentAgent:
 
         primary_endpoint = llm_cfg.primary
         final_message: Optional[Dict[str, Any]] = None
+        CONV_LOGGER.info(
+            "dept=%s ts_code=%s trade_date=%s start",
+            self.settings.code,
+            context.ts_code,
+            context.trade_date,
+        )
 
         for round_idx in range(self._max_rounds):
             try:
@@ -142,6 +149,12 @@ class DepartmentAgent:
             if message.get("tool_calls"):
                 assistant_record["tool_calls"] = message.get("tool_calls")
             messages.append(assistant_record)
+            CONV_LOGGER.info(
+                "dept=%s round=%s assistant=%s",
+                self.settings.code,
+                round_idx + 1,
+                assistant_record,
+            )
 
             tool_calls = message.get("tool_calls") or []
             if tool_calls:
@@ -163,6 +176,13 @@ class DepartmentAgent:
                         }
                     )
                     delivered_requests.update(delivered)
+                    CONV_LOGGER.info(
+                        "dept=%s round=%s tool_call=%s response=%s",
+                        self.settings.code,
+                        round_idx + 1,
+                        call,
+                        tool_response,
+                    )
                 continue
 
             final_message = message
@@ -175,6 +195,11 @@ class DepartmentAgent:
                 extra=LOG_EXTRA,
             )
             final_message = message
+            CONV_LOGGER.warning(
+                "dept=%s rounds_exhausted last_message=%s",
+                self.settings.code,
+                final_message,
+            )
 
         mutable_context.raw["supplement_transcript"] = list(transcript)
 
@@ -209,6 +234,13 @@ class DepartmentAgent:
             decision.confidence,
             extra=LOG_EXTRA,
         )
+        CONV_LOGGER.info(
+            "dept=%s decision action=%s confidence=%.2f summary=%s",
+            self.settings.code,
+            decision.action.value,
+            decision.confidence,
+            summary or "",
+        )
         return decision
 
     @staticmethod
@@ -418,6 +450,11 @@ class DepartmentAgent:
                 exc,
                 extra=LOG_EXTRA,
             )
+            CONV_LOGGER.error(
+                "dept=%s legacy_call_failed err=%s",
+                self.settings.code,
+                exc,
+            )
             return DepartmentDecision(
                 department=self.settings.code,
                 action=AgentAction.HOLD,
@@ -427,6 +464,7 @@ class DepartmentAgent:
             )
 
         context.raw["supplement_transcript"] = [response]
+        CONV_LOGGER.info("dept=%s legacy_response=%s", self.settings.code, response)
         decision_data = _parse_department_response(response)
         action = _normalize_action(decision_data.get("action"))
         confidence = _clamp_float(decision_data.get("confidence"), default=0.5)

app/backtest/engine.py

@@ -251,20 +251,13 @@ class BacktestEngine:
                 method=self.cfg.method,
                 department_manager=self.department_manager,
             )
-            decisions.append(decision)
-            self.record_agent_state(context, decision)
-            if decision_callback:
-                try:
-                    decision_callback(ts_code, trade_date, context, decision)
-                except Exception:  # noqa: BLE001
-                    LOGGER.exception("决策回调执行失败", extra=LOG_EXTRA)
             try:
                 metrics_record_decision(
                     ts_code=ts_code,
                     trade_date=context.trade_date,
                     action=decision.action.value,
                     confidence=decision.confidence,
-                    summary=decision.summary,
+                    summary=_extract_summary(decision),
                     source="backtest",
                     departments={
                         code: dept.to_dict()
@@ -273,6 +266,13 @@ class BacktestEngine:
                 )
             except Exception:  # noqa: BLE001
                 LOGGER.debug("记录决策指标失败", extra=LOG_EXTRA)
+            decisions.append(decision)
+            self.record_agent_state(context, decision)
+            if decision_callback:
+                try:
+                    decision_callback(ts_code, trade_date, context, decision)
+                except Exception:  # noqa: BLE001
+                    LOGGER.exception("决策回调执行失败", extra=LOG_EXTRA)
         # TODO: translate decisions into fills, holdings, and NAV updates.
         _ = state
         return decisions
@@ -408,3 +408,9 @@ def run_backtest(
         _ = conn
         # Implementation should persist bt_nav, bt_trades, and bt_report rows.
     return result
+def _extract_summary(decision: Decision) -> str:
+    for dept_decision in decision.department_decisions.values():
+        summary = getattr(dept_decision, "summary", "")
+        if summary:
+            return str(summary)
+    return ""

app/ui/streamlit_app.py

@@ -51,6 +51,60 @@ LOGGER = get_logger(__name__)
 LOG_EXTRA = {"stage": "ui"}
 
 
+def render_global_dashboard() -> None:
+    """Render a persistent sidebar with realtime LLM stats and recent decisions."""
+
+    metrics_container = st.sidebar.container()
+    decisions_container = st.sidebar.container()
+    st.session_state["dashboard_placeholders"] = (metrics_container, decisions_container)
+    _update_dashboard_sidebar()
+
+
+def _update_dashboard_sidebar(metrics: Optional[Dict[str, object]] = None) -> None:
+    placeholders = st.session_state.get("dashboard_placeholders")
+    if not placeholders:
+        return
+    metrics_container, decisions_container = placeholders
+    metrics = metrics or snapshot_llm_metrics()
+
+    metrics_container.empty()
+    with metrics_container.container():
+        st.header("系统监控")
+        col_a, col_b, col_c = st.columns(3)
+        col_a.metric("LLM 调用", metrics.get("total_calls", 0))
+        col_b.metric("Prompt Tokens", metrics.get("total_prompt_tokens", 0))
+        col_c.metric("Completion Tokens", metrics.get("total_completion_tokens", 0))
+
+        provider_calls = metrics.get("provider_calls", {})
+        model_calls = metrics.get("model_calls", {})
+        if provider_calls or model_calls:
+            with st.expander("调用分布", expanded=False):
+                if provider_calls:
+                    st.write("按 Provider：")
+                    st.json(provider_calls)
+                if model_calls:
+                    st.write("按模型：")
+                    st.json(model_calls)
+
+    decisions_container.empty()
+    with decisions_container.container():
+        st.subheader("最新决策")
+        decisions = metrics.get("recent_decisions") or llm_recent_decisions(10)
+        if decisions:
+            for record in reversed(decisions[-10:]):
+                ts_code = record.get("ts_code")
+                trade_date = record.get("trade_date")
+                action = record.get("action")
+                confidence = record.get("confidence", 0.0)
+                summary = record.get("summary")
+                st.markdown(
+                    f"**{trade_date} {ts_code}** → {action} (置信度 {confidence:.2f})"
+                )
+                if summary:
+                    st.caption(summary)
+        else:
+            st.caption("暂无决策记录。执行回测或实时评估后可在此查看。")
+
 def _discover_provider_models(provider: LLMProvider, base_override: str = "", api_override: Optional[str] = None) -> tuple[list[str], Optional[str]]:
     """Attempt to query provider API and return available model ids."""
 
@@ -159,45 +213,7 @@ def _load_daily_frame(ts_code: str, start: date, end: date) -> pd.DataFrame:
 def render_today_plan() -> None:
     LOGGER.info("渲染今日计划页面", extra=LOG_EXTRA)
     st.header("今日计划")
-    st.caption("统计数据基于最近一次渲染，刷新页面即可获取最新结果。")
-
-    metrics_state = snapshot_llm_metrics()
-    st.subheader("LLM 调用统计 (实时)")
-    stats_col1, stats_col2, stats_col3 = st.columns(3)
-    stats_col1.metric("总调用次数", metrics_state.get("total_calls", 0))
-    stats_col2.metric("Prompt Tokens", metrics_state.get("total_prompt_tokens", 0))
-    stats_col3.metric("Completion Tokens", metrics_state.get("total_completion_tokens", 0))
-    provider_calls = metrics_state.get("provider_calls", {})
-    model_calls = metrics_state.get("model_calls", {})
-    if provider_calls or model_calls:
-        with st.expander("调用明细", expanded=False):
-            if provider_calls:
-                st.write("按 Provider：")
-                st.json(provider_calls)
-            if model_calls:
-                st.write("按模型：")
-                st.json(model_calls)
-
-    st.subheader("最近决策 (全局)")
-    decision_feed = metrics_state.get("recent_decisions", []) or llm_recent_decisions(20)
-    if decision_feed:
-        for record in reversed(decision_feed[-20:]):
-            ts_code = record.get("ts_code")
-            trade_date = record.get("trade_date")
-            action = record.get("action")
-            confidence = record.get("confidence")
-            summary = record.get("summary")
-            departments = record.get("departments", {})
-            st.markdown(
-                f"**{trade_date} {ts_code}** → {action} (信心 {confidence:.2f})"
-            )
-            if summary:
-                st.caption(f"摘要：{summary}")
-            if departments:
-                st.json(departments)
-            st.divider()
-    else:
-        st.caption("暂无决策记录，执行回测或实时评估后可在此查看。")
+    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(
@@ -437,13 +453,17 @@ def render_backtest() -> None:
     if st.button("运行回测"):
         LOGGER.info("用户点击运行回测按钮", extra=LOG_EXTRA)
         decision_log_container = st.container()
-        status_placeholder = st.empty()
+        status_box = st.status("准备执行回测...", expanded=True)
         llm_stats_placeholder = st.empty()
         decision_entries: List[str] = []
 
         def _decision_callback(ts_code: str, trade_dt: date, ctx: AgentContext, decision: Decision) -> None:
             ts_label = trade_dt.isoformat()
-            summary = decision.summary
+            summary = ""
+            for dept_decision in decision.department_decisions.values():
+                if getattr(dept_decision, "summary", ""):
+                    summary = str(dept_decision.summary)
+                    break
             entry_lines = [
                 f"**{ts_label} {ts_code}** → {decision.action.value} (信心 {decision.confidence:.2f})",
             ]
@@ -457,67 +477,71 @@ def render_backtest() -> None:
             if dep_highlights:
                 entry_lines.append("部门意见：" + "；".join(dep_highlights))
             decision_entries.append("  \n".join(entry_lines))
-            decision_log_container.markdown("\n\n".join(decision_entries[-50:]))
-            status_placeholder.info(
-                f"最新决策：{ts_code} -> {decision.action.value} ({decision.confidence:.2f})"
-            )
+            decision_log_container.markdown("\n\n".join(decision_entries[-200:]))
+            status_box.write(f"{ts_label} {ts_code} → {decision.action.value} (信心 {decision.confidence:.2f})")
             stats = snapshot_llm_metrics()
             llm_stats_placeholder.json(
                 {
                     "LLM 调用次数": stats.get("total_calls", 0),
                     "Prompt Tokens": stats.get("total_prompt_tokens", 0),
                     "Completion Tokens": stats.get("total_completion_tokens", 0),
+                    "按 Provider": stats.get("provider_calls", {}),
+                    "按模型": stats.get("model_calls", {}),
                 }
             )
+            _update_dashboard_sidebar(stats)
 
         reset_llm_metrics()
-        with st.spinner("正在执行回测..."):
-            try:
-                universe = [code.strip() for code in universe_text.split(',') if code.strip()]
-                LOGGER.info(
-                    "回测参数：start=%s end=%s universe=%s target=%s stop=%s hold_days=%s",
-                    start_date,
-                    end_date,
-                    universe,
-                    target,
-                    stop,
-                    hold_days,
-                    extra=LOG_EXTRA,
-                )
-                cfg = BtConfig(
-                    id="streamlit_demo",
-                    name="Streamlit Demo Strategy",
-                    start_date=start_date,
-                    end_date=end_date,
-                    universe=universe,
-                    params={
-                        "target": target,
-                        "stop": stop,
-                        "hold_days": int(hold_days),
-                    },
-                )
-                result = run_backtest(cfg, decision_callback=_decision_callback)
-                LOGGER.info(
-                    "回测完成：nav_records=%s trades=%s",
-                    len(result.nav_series),
-                    len(result.trades),
-                    extra=LOG_EXTRA,
-                )
-                st.success("回测执行完成，详见下方结果与统计。")
-                metrics = snapshot_llm_metrics()
-                llm_stats_placeholder.json(
-                    {
-                        "LLM 调用次数": metrics.get("total_calls", 0),
-                        "Prompt Tokens": metrics.get("total_prompt_tokens", 0),
-                        "Completion Tokens": metrics.get("total_completion_tokens", 0),
-                        "按 Provider": metrics.get("provider_calls", {}),
-                        "按模型": metrics.get("model_calls", {}),
-                    }
-                )
-                st.json({"nav_records": result.nav_series, "trades": result.trades})
-            except Exception as exc:  # noqa: BLE001
-                LOGGER.exception("回测执行失败", extra=LOG_EXTRA)
-                st.error(f"回测执行失败：{exc}")
+        status_box.update(label="执行回测中...", state="running")
+        try:
+            universe = [code.strip() for code in universe_text.split(',') if code.strip()]
+            LOGGER.info(
+                "回测参数：start=%s end=%s universe=%s target=%s stop=%s hold_days=%s",
+                start_date,
+                end_date,
+                universe,
+                target,
+                stop,
+                hold_days,
+                extra=LOG_EXTRA,
+            )
+            cfg = BtConfig(
+                id="streamlit_demo",
+                name="Streamlit Demo Strategy",
+                start_date=start_date,
+                end_date=end_date,
+                universe=universe,
+                params={
+                    "target": target,
+                    "stop": stop,
+                    "hold_days": int(hold_days),
+                },
+            )
+            result = run_backtest(cfg, decision_callback=_decision_callback)
+            LOGGER.info(
+                "回测完成：nav_records=%s trades=%s",
+                len(result.nav_series),
+                len(result.trades),
+                extra=LOG_EXTRA,
+            )
+            status_box.update(label="回测执行完成", state="complete")
+            st.success("回测执行完成，详见下方结果与统计。")
+            metrics = snapshot_llm_metrics()
+            llm_stats_placeholder.json(
+                {
+                    "LLM 调用次数": metrics.get("total_calls", 0),
+                    "Prompt Tokens": metrics.get("total_prompt_tokens", 0),
+                    "Completion Tokens": metrics.get("total_completion_tokens", 0),
+                    "按 Provider": metrics.get("provider_calls", {}),
+                    "按模型": metrics.get("model_calls", {}),
+                }
+            )
+            _update_dashboard_sidebar(metrics)
+            st.json({"nav_records": result.nav_series, "trades": result.trades})
+        except Exception as exc:  # noqa: BLE001
+            LOGGER.exception("回测执行失败", extra=LOG_EXTRA)
+            status_box.update(label="回测执行失败", state="error")
+            st.error(f"回测执行失败：{exc}")
 
 
 def render_settings() -> None:
@@ -1151,6 +1175,7 @@ def render_tests() -> None:
 def main() -> None:
     LOGGER.info("初始化 Streamlit UI", extra=LOG_EXTRA)
     st.set_page_config(page_title="多智能体投资助理", layout="wide")
+    render_global_dashboard()
     tabs = st.tabs(["今日计划", "回测与复盘", "数据与设置", "自检测试"])
     LOGGER.debug("Tabs 初始化完成：%s", ["今日计划", "回测与复盘", "数据与设置", "自检测试"], extra=LOG_EXTRA)
     with tabs[0]:

app/utils/logging.py

@@ -20,6 +20,9 @@ from .db import db_session
 
 _LOGGER_NAME = "app.logging"
 _IS_CONFIGURED = False
+_CONVERSATION_LOGGER_NAME = "app.conversation"
+_CONVERSATION_HANDLER: Optional[Handler] = None
+_CONVERSATION_LOGFILE: Optional[Path] = None
 
 
 class DatabaseLogHandler(Handler):
@@ -77,6 +80,7 @@ def setup_logging(
     log_dir: Path = cfg.data_paths.root / "logs"
     log_dir.mkdir(parents=True, exist_ok=True)
     logfile = log_dir / f"app_{timestamp}.log"
+    conversation_logfile = log_dir / f"agent_{timestamp}.log"
 
     root = logging.getLogger()
     root.setLevel(level)
@@ -113,6 +117,19 @@ def setup_logging(
             },
         },
     )
+    conversation_logger = logging.getLogger(_CONVERSATION_LOGGER_NAME)
+    conversation_logger.setLevel(level)
+    conversation_logger.handlers.clear()
+    conversation_logger.propagate = False
+    conv_handler = logging.FileHandler(conversation_logfile, encoding="utf-8")
+    conv_handler.setLevel(level)
+    conv_handler.setFormatter(formatter)
+    conversation_logger.addHandler(conv_handler)
+
+    global _CONVERSATION_HANDLER, _CONVERSATION_LOGFILE
+    _CONVERSATION_HANDLER = conv_handler
+    _CONVERSATION_LOGFILE = conversation_logfile
+
     return root
 
 
@@ -128,5 +145,14 @@ def get_logger(name: Optional[str] = None) -> logging.Logger:
     return logger
 
 
+def get_conversation_logger() -> logging.Logger:
+    """Return conversation logger for agent dialogues."""
+
+    setup_logging()
+    logger = logging.getLogger(_CONVERSATION_LOGGER_NAME)
+    logger.propagate = False
+    return logger
+
+
 # 默认在模块导入时完成配置，适配现有调用方式。
 setup_logging()