evotraders/backend/services/gateway.py

# -*- coding: utf-8 -*-
"""
WebSocket Gateway for frontend communication
"""
import asyncio
import json
import logging
from datetime import datetime, timedelta
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Set

import websockets
from websockets.asyncio.server import ServerConnection

from backend.config.bootstrap_config import (
    get_bootstrap_config_for_run,
    resolve_runtime_config,
    update_bootstrap_values_for_run,
)
from backend.agents.agent_workspace import load_agent_workspace_config
from backend.agents.skills_manager import SkillsManager
from backend.agents.toolkit_factory import load_agent_profiles
from backend.data.provider_utils import normalize_symbol
from backend.data.market_ingest import ingest_symbols
from backend.enrich.llm_enricher import llm_enrichment_enabled
from backend.enrich.news_enricher import enrich_news_for_symbol
from backend.explain.range_explainer import build_range_explanation
from backend.explain.similarity_service import find_similar_days
from backend.explain.story_service import get_or_create_stock_story
from backend.llm.models import get_agent_model_info
from backend.utils.msg_adapter import FrontendAdapter
from backend.utils.terminal_dashboard import get_dashboard
from backend.core.pipeline import TradingPipeline
from backend.core.state_sync import StateSync
from backend.services.market import MarketService
from backend.services.storage import StorageService
from backend.data.provider_router import get_provider_router
from backend.tools.data_tools import get_prices
from backend.tools.data_tools import get_company_news
from backend.core.scheduler import Scheduler

logger = logging.getLogger(__name__)
EDITABLE_AGENT_WORKSPACE_FILES = {
    "SOUL.md",
    "PROFILE.md",
    "AGENTS.md",
    "MEMORY.md",
    "POLICY.md",
    "HEARTBEAT.md",
    "ROLE.md",
    "STYLE.md",
}


class Gateway:
    """WebSocket Gateway for frontend communication"""

    def __init__(
        self,
        market_service: MarketService,
        storage_service: StorageService,
        pipeline: TradingPipeline,
        state_sync: Optional[StateSync] = None,
        scheduler_callback: Optional[Callable] = None,
        scheduler: Optional[Scheduler] = None,
        config: Dict[str, Any] = None,
    ):
        self.market_service = market_service
        self.storage = storage_service
        self.pipeline = pipeline
        self.scheduler_callback = scheduler_callback
        self.scheduler = scheduler
        self.config = config or {}

        self.mode = self.config.get("mode", "live")
        self.is_backtest = self.mode == "backtest" or self.config.get(
            "backtest_mode",
            False,
        )

        self.state_sync = state_sync or StateSync(storage=storage_service)
        # self.state_sync.set_mode(self.is_backtest)
        self.state_sync.set_broadcast_fn(self.broadcast)
        self.pipeline.state_sync = self.state_sync

        self.connected_clients: Set[ServerConnection] = set()
        self.lock = asyncio.Lock()
        self._cycle_lock = asyncio.Lock()
        self._backtest_task: Optional[asyncio.Task] = None
        self._manual_cycle_task: Optional[asyncio.Task] = None
        self._backtest_start_date: Optional[str] = None
        self._backtest_end_date: Optional[str] = None
        self._dashboard = get_dashboard()
        self._market_status_task: Optional[asyncio.Task] = None
        self._watchlist_ingest_task: Optional[asyncio.Task] = None

        # Session tracking for live returns
        self._session_start_portfolio_value: Optional[float] = None
        self._provider_router = get_provider_router()
        self._loop: Optional[asyncio.AbstractEventLoop] = None
        self._project_root = Path(__file__).resolve().parents[2]

    async def start(self, host: str = "0.0.0.0", port: int = 8766):
        """Start gateway server"""
        logger.info(f"Starting gateway on {host}:{port}")
        self._loop = asyncio.get_running_loop()
        self._provider_router.add_listener(self._on_provider_usage_changed)

        # Initialize terminal dashboard
        self._dashboard.set_config(
            mode=self.mode,
            config_name=self.config.get("config_name", "default"),
            host=host,
            port=port,
            poll_interval=self.config.get("poll_interval", 10),
            mock=self.config.get("mock_mode", False),
            tickers=self.config.get("tickers", []),
            initial_cash=self.storage.initial_cash,
            start_date=self._backtest_start_date or "",
            end_date=self._backtest_end_date or "",
            data_sources=self._provider_router.get_usage_snapshot(),
        )
        self._dashboard.start()

        self.state_sync.load_state()
        self.market_service.set_price_recorder(self.storage.record_price_point)
        self.state_sync.update_state("status", "running")
        self.state_sync.update_state("server_mode", self.mode)
        self.state_sync.update_state("is_backtest", self.is_backtest)
        self.state_sync.update_state(
            "is_mock_mode",
            self.config.get("mock_mode", False),
        )
        self.state_sync.update_state("tickers", self.config.get("tickers", []))
        self.state_sync.update_state(
            "runtime_config",
            {
                "tickers": self.config.get("tickers", []),
                "schedule_mode": self.config.get("schedule_mode", "daily"),
                "interval_minutes": self.config.get("interval_minutes", 60),
                "trigger_time": self.config.get("trigger_time", "09:30"),
                "initial_cash": self.config.get(
                    "initial_cash",
                    self.storage.initial_cash,
                ),
                "margin_requirement": self.config.get("margin_requirement"),
                "max_comm_cycles": self.config.get("max_comm_cycles"),
                "enable_memory": self.config.get("enable_memory", False),
            },
        )
        self.state_sync.update_state(
            "data_sources",
            self._provider_router.get_usage_snapshot(),
        )

        # Load and display existing portfolio state if available
        summary = self.storage.load_file("summary")
        if summary:
            holdings = self.storage.load_file("holdings") or []
            trades = self.storage.load_file("trades") or []
            current_date = self.state_sync.state.get("current_date")
            self._dashboard.update(
                date=current_date or "-",
                status="running",
                portfolio=summary,
                holdings=holdings,
                trades=trades,
            )
            logger.info(
                "Loaded existing portfolio: $%s",
                f"{summary.get('totalAssetValue', 0):,.2f}",
            )

        await self.market_service.start(broadcast_func=self.broadcast)

        if self.scheduler:
            await self.scheduler.start(self.on_strategy_trigger)
        elif self.scheduler_callback:
            await self.scheduler_callback(callback=self.on_strategy_trigger)

        # Start market status monitoring (only for live mode)
        if not self.is_backtest:
            self._market_status_task = asyncio.create_task(
                self._market_status_monitor(),
            )

        async with websockets.serve(
            self.handle_client,
            host,
            port,
            ping_interval=30,
            ping_timeout=60,
        ):
            logger.info(
                f"Gateway started: ws://{host}:{port}, mode={self.mode}",
            )
            await asyncio.Future()

    def _on_provider_usage_changed(self, snapshot: Dict[str, Any]):
        """Handle provider routing updates from the shared router."""
        self.state_sync.update_state("data_sources", snapshot)
        self._dashboard.update(data_sources=snapshot)
        if self._loop and self._loop.is_running():
            asyncio.run_coroutine_threadsafe(
                self.broadcast(
                    {
                        "type": "data_sources_update",
                        "data_sources": snapshot,
                    },
                ),
                self._loop,
            )

    @property
    def state(self) -> Dict[str, Any]:
        return self.state_sync.state

    @staticmethod
    def _news_rows_need_enrichment(rows: List[Dict[str, Any]]) -> bool:
        if not rows:
            return True
        return all(
            not row.get("sentiment")
            and not row.get("relevance")
            and not row.get("key_discussion")
            for row in rows
        )

    async def handle_client(self, websocket: ServerConnection):
        """Handle WebSocket client connection"""
        async with self.lock:
            self.connected_clients.add(websocket)

        await self._send_initial_state(websocket)
        await self._handle_client_messages(websocket)

        async with self.lock:
            self.connected_clients.discard(websocket)

    async def _send_initial_state(self, websocket: ServerConnection):
        state_payload = self.state_sync.get_initial_state_payload(
            include_dashboard=True,
        )
        state_payload["data_sources"] = (
            self._provider_router.get_usage_snapshot()
        )
        # Include market status in initial state
        state_payload[
            "market_status"
        ] = self.market_service.get_market_status()

        # Include live returns if session is active
        if self.storage.is_live_session_active:
            live_returns = self.storage.get_live_returns()
            if "portfolio" in state_payload:
                state_payload["portfolio"].update(live_returns)

        await websocket.send(
            json.dumps(
                {"type": "initial_state", "state": state_payload},
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_client_messages(
        self,
        websocket: ServerConnection,
    ):
        try:
            async for message in websocket:
                data = json.loads(message)
                msg_type = data.get("type", "unknown")

                if msg_type == "ping":
                    await websocket.send(
                        json.dumps(
                            {
                                "type": "pong",
                                "timestamp": datetime.now().isoformat(),
                            },
                            ensure_ascii=False,
                        ),
                    )
                elif msg_type == "get_state":
                    await self._send_initial_state(websocket)
                elif msg_type == "start_backtest":
                    await self._handle_start_backtest(data)
                elif msg_type == "trigger_strategy":
                    await self._handle_manual_trigger(websocket, data)
                elif msg_type == "update_runtime_config":
                    await self._handle_update_runtime_config(websocket, data)
                elif msg_type == "reload_runtime_assets":
                    await self._handle_reload_runtime_assets()
                elif msg_type == "update_watchlist":
                    await self._handle_update_watchlist(websocket, data)
                elif msg_type == "get_agent_skills":
                    await self._handle_get_agent_skills(websocket, data)
                elif msg_type == "get_agent_profile":
                    await self._handle_get_agent_profile(websocket, data)
                elif msg_type == "get_skill_detail":
                    await self._handle_get_skill_detail(websocket, data)
                elif msg_type == "create_agent_local_skill":
                    await self._handle_create_agent_local_skill(websocket, data)
                elif msg_type == "update_agent_local_skill":
                    await self._handle_update_agent_local_skill(websocket, data)
                elif msg_type == "delete_agent_local_skill":
                    await self._handle_delete_agent_local_skill(websocket, data)
                elif msg_type == "remove_agent_skill":
                    await self._handle_remove_agent_skill(websocket, data)
                elif msg_type == "update_agent_skill":
                    await self._handle_update_agent_skill(websocket, data)
                elif msg_type == "get_agent_workspace_file":
                    await self._handle_get_agent_workspace_file(websocket, data)
                elif msg_type == "update_agent_workspace_file":
                    await self._handle_update_agent_workspace_file(websocket, data)
                elif msg_type == "get_stock_history":
                    await self._handle_get_stock_history(websocket, data)
                elif msg_type == "get_stock_explain_events":
                    await self._handle_get_stock_explain_events(websocket, data)
                elif msg_type == "get_stock_news":
                    await self._handle_get_stock_news(websocket, data)
                elif msg_type == "get_stock_news_for_date":
                    await self._handle_get_stock_news_for_date(websocket, data)
                elif msg_type == "get_stock_news_timeline":
                    await self._handle_get_stock_news_timeline(websocket, data)
                elif msg_type == "get_stock_news_categories":
                    await self._handle_get_stock_news_categories(websocket, data)
                elif msg_type == "get_stock_range_explain":
                    await self._handle_get_stock_range_explain(websocket, data)
                elif msg_type == "get_stock_story":
                    await self._handle_get_stock_story(websocket, data)
                elif msg_type == "get_stock_similar_days":
                    await self._handle_get_stock_similar_days(websocket, data)
                elif msg_type == "run_stock_enrich":
                    await self._handle_run_stock_enrich(websocket, data)

        except websockets.ConnectionClosed:
            pass
        except json.JSONDecodeError:
            pass

    async def _handle_get_stock_history(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        if not ticker:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_history_loaded",
                        "ticker": "",
                        "prices": [],
                        "source": None,
                        "error": "invalid ticker",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        lookback_days = data.get("lookback_days", 90)
        try:
            lookback_days = max(7, min(int(lookback_days), 365))
        except (TypeError, ValueError):
            lookback_days = 90

        end_date = self.state_sync.state.get("current_date")
        if not end_date:
            end_date = datetime.now().strftime("%Y-%m-%d")

        try:
            end_dt = datetime.strptime(end_date, "%Y-%m-%d")
        except ValueError:
            end_dt = datetime.now()
            end_date = end_dt.strftime("%Y-%m-%d")

        start_date = (end_dt - timedelta(days=lookback_days)).strftime(
            "%Y-%m-%d",
        )

        prices = await asyncio.to_thread(
            self.storage.market_store.get_ohlc,
            ticker,
            start_date,
            end_date,
        )
        source = "polygon"
        if not prices:
            prices = await asyncio.to_thread(
                get_prices,
                ticker,
                start_date,
                end_date,
            )
            usage_snapshot = self._provider_router.get_usage_snapshot()
            source = usage_snapshot.get("last_success", {}).get("prices")
            if prices:
                await asyncio.to_thread(
                    self.storage.market_store.upsert_ohlc,
                    ticker,
                    [price.model_dump() for price in prices],
                    source=source or "provider",
                )

        await websocket.send(
            json.dumps(
                {
                    "type": "stock_history_loaded",
                    "ticker": ticker,
                    "prices": [
                        price if isinstance(price, dict) else price.model_dump()
                        for price in prices
                    ][-120:],
                    "source": source,
                    "start_date": start_date,
                    "end_date": end_date,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_explain_events(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        snapshot = self.storage.runtime_db.get_stock_explain_snapshot(ticker)
        await websocket.send(
            json.dumps(
                {
                    "type": "stock_explain_events_loaded",
                    "ticker": ticker,
                    "events": snapshot.get("events", []),
                    "signals": snapshot.get("signals", []),
                    "trades": snapshot.get("trades", []),
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_news(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        if not ticker:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_news_loaded",
                        "ticker": "",
                        "news": [],
                        "source": None,
                        "error": "invalid ticker",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        lookback_days = data.get("lookback_days", 30)
        limit = data.get("limit", 12)
        try:
            lookback_days = max(7, min(int(lookback_days), 180))
        except (TypeError, ValueError):
            lookback_days = 30
        try:
            limit = max(1, min(int(limit), 30))
        except (TypeError, ValueError):
            limit = 12

        end_date = self.state_sync.state.get("current_date")
        if not end_date:
            end_date = datetime.now().strftime("%Y-%m-%d")

        try:
            end_dt = datetime.strptime(end_date, "%Y-%m-%d")
        except ValueError:
            end_dt = datetime.now()
            end_date = end_dt.strftime("%Y-%m-%d")

        start_date = (end_dt - timedelta(days=lookback_days)).strftime(
            "%Y-%m-%d",
        )

        news_rows = await asyncio.to_thread(
            self.storage.market_store.get_news_items_enriched,
            ticker,
            start_date=start_date,
            end_date=end_date,
            limit=limit,
        )
        source = "polygon"
        if self._news_rows_need_enrichment(news_rows):
            news = await asyncio.to_thread(
                get_company_news,
                ticker,
                end_date,
                start_date,
                limit,
            )
            if news:
                usage_snapshot = self._provider_router.get_usage_snapshot()
                source = usage_snapshot.get("last_success", {}).get("company_news")
                await asyncio.to_thread(
                    self.storage.market_store.upsert_news,
                    ticker,
                    [item.model_dump() for item in news],
                    source=source or "provider",
                )
            await asyncio.to_thread(
                enrich_news_for_symbol,
                self.storage.market_store,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=max(limit, 50),
            )
            news_rows = await asyncio.to_thread(
                self.storage.market_store.get_news_items_enriched,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=limit,
            )
            source = source or "market_store"

        await websocket.send(
            json.dumps(
                {
                    "type": "stock_news_loaded",
                    "ticker": ticker,
                    "news": news_rows[-limit:],
                    "source": source,
                    "start_date": start_date,
                    "end_date": end_date,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_news_for_date(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        trade_date = str(data.get("date") or "").strip()
        if not ticker or not trade_date:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_news_for_date_loaded",
                        "ticker": ticker,
                        "date": trade_date,
                        "news": [],
                        "error": "ticker and date are required",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        limit = data.get("limit", 20)
        try:
            limit = max(1, min(int(limit), 50))
        except (TypeError, ValueError):
            limit = 20

        news_rows = await asyncio.to_thread(
            self.storage.market_store.get_news_items_enriched,
            ticker,
            trade_date=trade_date,
            limit=limit,
        )
        if self._news_rows_need_enrichment(news_rows):
            await asyncio.to_thread(
                enrich_news_for_symbol,
                self.storage.market_store,
                ticker,
                start_date=trade_date,
                end_date=trade_date,
                limit=limit,
            )
            news_rows = await asyncio.to_thread(
                self.storage.market_store.get_news_items_enriched,
                ticker,
                trade_date=trade_date,
                limit=limit,
            )

        await websocket.send(
            json.dumps(
                {
                    "type": "stock_news_for_date_loaded",
                    "ticker": ticker,
                    "date": trade_date,
                    "news": news_rows,
                    "source": "market_store",
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_news_timeline(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        if not ticker:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_news_timeline_loaded",
                        "ticker": "",
                        "timeline": [],
                        "error": "invalid ticker",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        lookback_days = data.get("lookback_days", 90)
        try:
            lookback_days = max(7, min(int(lookback_days), 365))
        except (TypeError, ValueError):
            lookback_days = 90

        end_date = self.state_sync.state.get("current_date")
        if not end_date:
            end_date = datetime.now().strftime("%Y-%m-%d")

        try:
            end_dt = datetime.strptime(end_date, "%Y-%m-%d")
        except ValueError:
            end_dt = datetime.now()
            end_date = end_dt.strftime("%Y-%m-%d")

        start_date = (end_dt - timedelta(days=lookback_days)).strftime(
            "%Y-%m-%d",
        )
        timeline = await asyncio.to_thread(
            self.storage.market_store.get_news_timeline_enriched,
            ticker,
            start_date=start_date,
            end_date=end_date,
        )
        if not timeline:
            await asyncio.to_thread(
                enrich_news_for_symbol,
                self.storage.market_store,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=200,
            )
            timeline = await asyncio.to_thread(
                self.storage.market_store.get_news_timeline_enriched,
                ticker,
                start_date=start_date,
                end_date=end_date,
            )
        await websocket.send(
            json.dumps(
                {
                    "type": "stock_news_timeline_loaded",
                    "ticker": ticker,
                    "timeline": timeline,
                    "start_date": start_date,
                    "end_date": end_date,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_news_categories(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        if not ticker:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_news_categories_loaded",
                        "ticker": "",
                        "categories": {},
                        "error": "invalid ticker",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        lookback_days = data.get("lookback_days", 90)
        try:
            lookback_days = max(7, min(int(lookback_days), 365))
        except (TypeError, ValueError):
            lookback_days = 90

        end_date = self.state_sync.state.get("current_date")
        if not end_date:
            end_date = datetime.now().strftime("%Y-%m-%d")

        try:
            end_dt = datetime.strptime(end_date, "%Y-%m-%d")
        except ValueError:
            end_dt = datetime.now()
            end_date = end_dt.strftime("%Y-%m-%d")

        start_date = (end_dt - timedelta(days=lookback_days)).strftime(
            "%Y-%m-%d",
        )
        news_rows = await asyncio.to_thread(
            self.storage.market_store.get_news_items_enriched,
            ticker,
            start_date=start_date,
            end_date=end_date,
            limit=200,
        )
        if self._news_rows_need_enrichment(news_rows):
            await asyncio.to_thread(
                enrich_news_for_symbol,
                self.storage.market_store,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=200,
            )
        categories = await asyncio.to_thread(
            self.storage.market_store.get_news_categories_enriched,
            ticker,
            start_date=start_date,
            end_date=end_date,
            limit=200,
        )
        await websocket.send(
            json.dumps(
                {
                    "type": "stock_news_categories_loaded",
                    "ticker": ticker,
                    "categories": categories,
                    "start_date": start_date,
                    "end_date": end_date,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_range_explain(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        start_date = str(data.get("start_date") or "").strip()
        end_date = str(data.get("end_date") or "").strip()
        if not ticker or not start_date or not end_date:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_range_explain_loaded",
                        "ticker": ticker,
                        "result": {"error": "ticker, start_date, end_date are required"},
                    },
                    ensure_ascii=False,
                ),
            )
            return

        article_ids = data.get("article_ids")
        if isinstance(article_ids, list) and article_ids:
            news_rows = await asyncio.to_thread(
                self.storage.market_store.get_news_by_ids_enriched,
                ticker,
                article_ids,
            )
            if self._news_rows_need_enrichment(news_rows):
                await asyncio.to_thread(
                    enrich_news_for_symbol,
                    self.storage.market_store,
                    ticker,
                    start_date=start_date,
                    end_date=end_date,
                    limit=100,
                )
                news_rows = await asyncio.to_thread(
                    self.storage.market_store.get_news_by_ids_enriched,
                    ticker,
                    article_ids,
                )
        else:
            news_rows = await asyncio.to_thread(
                self.storage.market_store.get_news_items_enriched,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=100,
            )
        if not news_rows:
            await asyncio.to_thread(
                enrich_news_for_symbol,
                self.storage.market_store,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=100,
            )
            news_rows = await asyncio.to_thread(
                self.storage.market_store.get_news_items_enriched,
                ticker,
                start_date=start_date,
                end_date=end_date,
                limit=100,
            )

        result = await asyncio.to_thread(
            build_range_explanation,
            ticker=ticker,
            start_date=start_date,
            end_date=end_date,
            news_rows=news_rows,
        )
        await websocket.send(
            json.dumps(
                {
                    "type": "stock_range_explain_loaded",
                    "ticker": ticker,
                    "result": result,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_story(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        if not ticker:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_story_loaded",
                        "ticker": "",
                        "story": "",
                        "error": "invalid ticker",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        as_of_date = str(
            data.get("as_of_date")
            or self.state_sync.state.get("current_date")
            or datetime.now().strftime("%Y-%m-%d")
        ).strip()[:10]
        await asyncio.to_thread(
            enrich_news_for_symbol,
            self.storage.market_store,
            ticker,
            end_date=as_of_date,
            limit=80,
        )
        result = await asyncio.to_thread(
            get_or_create_stock_story,
            self.storage.market_store,
            symbol=ticker,
            as_of_date=as_of_date,
        )
        await websocket.send(
            json.dumps(
                {
                    "type": "stock_story_loaded",
                    "ticker": ticker,
                    "as_of_date": as_of_date,
                    "story": result.get("story") or "",
                    "source": result.get("source") or "local",
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_get_stock_similar_days(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        target_date = str(data.get("date") or "").strip()[:10]
        if not ticker or not target_date:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_similar_days_loaded",
                        "ticker": ticker,
                        "date": target_date,
                        "items": [],
                        "error": "ticker and date are required",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        top_k = data.get("top_k", 8)
        try:
            top_k = max(1, min(int(top_k), 20))
        except (TypeError, ValueError):
            top_k = 8

        await asyncio.to_thread(
            enrich_news_for_symbol,
            self.storage.market_store,
            ticker,
            end_date=target_date,
            limit=200,
        )
        result = await asyncio.to_thread(
            find_similar_days,
            self.storage.market_store,
            symbol=ticker,
            target_date=target_date,
            top_k=top_k,
        )
        await websocket.send(
            json.dumps(
                {
                    "type": "stock_similar_days_loaded",
                    "ticker": ticker,
                    "date": target_date,
                    **result,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_run_stock_enrich(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ):
        ticker = normalize_symbol(data.get("ticker", ""))
        start_date = str(data.get("start_date") or "").strip()[:10]
        end_date = str(data.get("end_date") or "").strip()[:10]
        story_date = str(data.get("story_date") or end_date or "").strip()[:10]
        target_date = str(data.get("target_date") or "").strip()[:10]
        force = bool(data.get("force", False))
        rebuild_story = bool(data.get("rebuild_story", True))
        rebuild_similar_days = bool(data.get("rebuild_similar_days", True))
        only_local_to_llm = bool(data.get("only_local_to_llm", False))
        limit = data.get("limit", 200)

        try:
            limit = max(10, min(int(limit), 500))
        except (TypeError, ValueError):
            limit = 200

        if not ticker or not start_date or not end_date:
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_enrich_completed",
                        "ticker": ticker,
                        "start_date": start_date,
                        "end_date": end_date,
                        "error": "ticker, start_date, end_date are required",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        if only_local_to_llm and not llm_enrichment_enabled():
            await websocket.send(
                json.dumps(
                    {
                        "type": "stock_enrich_completed",
                        "ticker": ticker,
                        "start_date": start_date,
                        "end_date": end_date,
                        "error": "only_local_to_llm requires EXPLAIN_ENRICH_USE_LLM=true and a configured LLM provider",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        result = await asyncio.to_thread(
            enrich_news_for_symbol,
            self.storage.market_store,
            ticker,
            start_date=start_date,
            end_date=end_date,
            limit=limit,
            skip_existing=not force,
            only_reanalyze_local=only_local_to_llm,
        )

        story_status = None
        if rebuild_story and story_date:
            await asyncio.to_thread(
                self.storage.market_store.delete_story_cache,
                ticker,
                as_of_date=story_date,
            )
            story_result = await asyncio.to_thread(
                get_or_create_stock_story,
                self.storage.market_store,
                symbol=ticker,
                as_of_date=story_date,
            )
            story_status = {
                "as_of_date": story_date,
                "source": story_result.get("source") or "local",
            }

        similar_status = None
        if rebuild_similar_days and target_date:
            await asyncio.to_thread(
                self.storage.market_store.delete_similar_day_cache,
                ticker,
                target_date=target_date,
            )
            similar_result = await asyncio.to_thread(
                find_similar_days,
                self.storage.market_store,
                symbol=ticker,
                target_date=target_date,
                top_k=8,
            )
            similar_status = {
                "target_date": target_date,
                "count": len(similar_result.get("items") or []),
                "error": similar_result.get("error"),
            }

        await websocket.send(
            json.dumps(
                {
                    "type": "stock_enrich_completed",
                    "ticker": ticker,
                    "start_date": start_date,
                    "end_date": end_date,
                    "story_date": story_date or None,
                    "target_date": target_date or None,
                    "force": force,
                    "only_local_to_llm": only_local_to_llm,
                    "stats": result,
                    "story_status": story_status,
                    "similar_status": similar_status,
                },
                ensure_ascii=False,
                default=str,
            ),
        )

    async def _handle_start_backtest(self, data: Dict[str, Any]):
        if not self.is_backtest:
            return
        dates = data.get("dates", [])
        if dates and self._backtest_task is None:
            task = asyncio.create_task(
                self._run_backtest_dates(dates),
            )
            task.add_done_callback(self._handle_backtest_exception)
            self._backtest_task = task

    async def _handle_manual_trigger(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Run one live/mock trading cycle on demand."""
        if self.is_backtest:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "Manual trigger is only available in live/mock mode.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        if (
            self._cycle_lock.locked()
            or (
                self._manual_cycle_task is not None
                and not self._manual_cycle_task.done()
            )
        ):
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "A trading cycle is already running.",
                    },
                    ensure_ascii=False,
                ),
            )
            await self.state_sync.on_system_message("已有任务在运行，已忽略手动触发")
            return

        requested_date = data.get("date")
        await self.state_sync.on_system_message("收到手动触发请求，准备开始新一轮分析与决策")
        task = asyncio.create_task(
            self.on_strategy_trigger(
                date=requested_date or datetime.now().strftime("%Y-%m-%d"),
            ),
        )
        task.add_done_callback(self._handle_manual_cycle_exception)
        self._manual_cycle_task = task

    async def _handle_reload_runtime_assets(self):
        """Reload prompt, skills, and safe runtime config without restart."""
        config_name = self.config.get("config_name", "default")
        runtime_config = resolve_runtime_config(
            project_root=self._project_root,
            config_name=config_name,
            enable_memory=self.config.get("enable_memory", False),
            schedule_mode=self.config.get("schedule_mode", "daily"),
            interval_minutes=self.config.get("interval_minutes", 60),
            trigger_time=self.config.get("trigger_time", "09:30"),
        )
        result = self.pipeline.reload_runtime_assets(runtime_config=runtime_config)
        runtime_updates = self._apply_runtime_config(runtime_config)
        await self.state_sync.on_system_message(
            "Runtime assets reloaded.",
        )
        await self.broadcast(
            {
                "type": "runtime_assets_reloaded",
                **result,
                **runtime_updates,
            },
        )

    async def _handle_update_runtime_config(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Persist selected runtime settings and hot-reload them."""
        updates: Dict[str, Any] = {}

        schedule_mode = str(data.get("schedule_mode", "")).strip().lower()
        if schedule_mode:
            if schedule_mode not in {"daily", "intraday"}:
                await websocket.send(
                    json.dumps(
                        {
                            "type": "error",
                            "message": "schedule_mode must be 'daily' or 'intraday'.",
                        },
                        ensure_ascii=False,
                    ),
                )
                return
            updates["schedule_mode"] = schedule_mode

        interval_minutes = data.get("interval_minutes")
        if interval_minutes is not None:
            try:
                parsed_interval = int(interval_minutes)
            except (TypeError, ValueError):
                parsed_interval = 0
            if parsed_interval <= 0:
                await websocket.send(
                    json.dumps(
                        {
                            "type": "error",
                            "message": "interval_minutes must be a positive integer.",
                        },
                        ensure_ascii=False,
                    ),
                )
                return
            updates["interval_minutes"] = parsed_interval

        trigger_time = data.get("trigger_time")
        if trigger_time is not None:
            raw_trigger = str(trigger_time).strip()
            if raw_trigger and raw_trigger != "now":
                try:
                    datetime.strptime(raw_trigger, "%H:%M")
                except ValueError:
                    await websocket.send(
                        json.dumps(
                            {
                                "type": "error",
                                "message": "trigger_time must use HH:MM or 'now'.",
                            },
                            ensure_ascii=False,
                        ),
                    )
                    return
            updates["trigger_time"] = raw_trigger or "09:30"

        max_comm_cycles = data.get("max_comm_cycles")
        if max_comm_cycles is not None:
            try:
                parsed_cycles = int(max_comm_cycles)
            except (TypeError, ValueError):
                parsed_cycles = 0
            if parsed_cycles <= 0:
                await websocket.send(
                    json.dumps(
                        {
                            "type": "error",
                            "message": "max_comm_cycles must be a positive integer.",
                        },
                        ensure_ascii=False,
                    ),
                )
                return
            updates["max_comm_cycles"] = parsed_cycles

        if not updates:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "No runtime settings were provided.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        update_bootstrap_values_for_run(
            project_root=self._project_root,
            config_name=config_name,
            updates=updates,
        )
        await self.state_sync.on_system_message("运行时调度配置已保存，正在热更新")
        await self._handle_reload_runtime_assets()

    async def _handle_update_watchlist(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Persist a new watchlist to BOOTSTRAP.md and hot-reload it."""
        tickers = self._normalize_watchlist(data.get("tickers"))
        if not tickers:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "update_watchlist requires at least one valid ticker.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        update_bootstrap_values_for_run(
            project_root=self._project_root,
            config_name=config_name,
            updates={"tickers": tickers},
        )
        await self.state_sync.on_system_message(
            f"Watchlist updated: {', '.join(tickers)}",
        )
        await self.broadcast(
            {
                "type": "watchlist_updated",
                "config_name": config_name,
                "tickers": tickers,
            },
        )
        await self._handle_reload_runtime_assets()
        self._schedule_watchlist_market_store_refresh(tickers)

    async def _handle_get_agent_skills(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Return skill catalog and status for one agent."""
        agent_id = str(data.get("agent_id", "")).strip()
        if not agent_id:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "get_agent_skills requires agent_id.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        agent_asset_dir = skills_manager.get_agent_asset_dir(config_name, agent_id)
        agent_config = load_agent_workspace_config(agent_asset_dir / "agent.yaml")
        resolved_skills = set(
            skills_manager.resolve_agent_skill_names(
                config_name=config_name,
                agent_id=agent_id,
                default_skills=[],
            ),
        )
        enabled = set(agent_config.enabled_skills)
        disabled = set(agent_config.disabled_skills)

        payload = []
        for item in skills_manager.list_agent_skill_catalog(config_name, agent_id):
            if item.skill_name in disabled:
                status = "disabled"
            elif item.skill_name in enabled:
                status = "enabled"
            elif item.skill_name in resolved_skills:
                status = "active"
            else:
                status = "available"
            payload.append(
                {
                    "skill_name": item.skill_name,
                    "name": item.name,
                    "description": item.description,
                    "version": item.version,
                    "source": item.source,
                    "tools": item.tools,
                    "status": status,
                },
            )

        await websocket.send(
            json.dumps(
                {
                    "type": "agent_skills_loaded",
                    "config_name": config_name,
                    "agent_id": agent_id,
                    "skills": payload,
                },
                ensure_ascii=False,
            ),
        )

    async def _handle_get_agent_profile(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Return structured profile/config summary for one agent."""
        agent_id = str(data.get("agent_id", "")).strip()
        if not agent_id:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "get_agent_profile requires agent_id.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        asset_dir = skills_manager.get_agent_asset_dir(config_name, agent_id)
        agent_config = load_agent_workspace_config(asset_dir / "agent.yaml")
        profiles = load_agent_profiles()
        profile = profiles.get(agent_id, {})
        bootstrap = get_bootstrap_config_for_run(self._project_root, config_name)
        override = bootstrap.agent_override(agent_id)
        active_tool_groups = override.get(
            "active_tool_groups",
            agent_config.active_tool_groups or profile.get("active_tool_groups", []),
        )
        if not isinstance(active_tool_groups, list):
            active_tool_groups = []
        disabled_tool_groups = agent_config.disabled_tool_groups
        if disabled_tool_groups:
            disabled_set = set(disabled_tool_groups)
            active_tool_groups = [
                group_name
                for group_name in active_tool_groups
                if group_name not in disabled_set
            ]

        default_skills = profile.get("skills", [])
        if not isinstance(default_skills, list):
            default_skills = []
        resolved_skills = skills_manager.resolve_agent_skill_names(
            config_name=config_name,
            agent_id=agent_id,
            default_skills=default_skills,
        )
        prompt_files = agent_config.prompt_files or [
            "SOUL.md",
            "PROFILE.md",
            "AGENTS.md",
            "POLICY.md",
            "MEMORY.md",
        ]
        model_name, model_provider = get_agent_model_info(agent_id)

        await websocket.send(
            json.dumps(
                {
                    "type": "agent_profile_loaded",
                    "config_name": config_name,
                    "agent_id": agent_id,
                    "profile": {
                        "model_name": model_name,
                        "model_provider": model_provider,
                        "prompt_files": prompt_files,
                        "default_skills": default_skills,
                        "resolved_skills": resolved_skills,
                        "active_tool_groups": active_tool_groups,
                        "disabled_tool_groups": disabled_tool_groups,
                        "enabled_skills": agent_config.enabled_skills,
                        "disabled_skills": agent_config.disabled_skills,
                    },
                },
                ensure_ascii=False,
            ),
        )

    async def _handle_get_skill_detail(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Return full SKILL.md body for one skill."""
        agent_id = str(data.get("agent_id", "")).strip()
        skill_name = str(data.get("skill_name", "")).strip()
        if not skill_name:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "get_skill_detail requires skill_name.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        skills_manager = SkillsManager(project_root=self._project_root)
        try:
            if agent_id:
                config_name = self.config.get("config_name", "default")
                detail = skills_manager.load_agent_skill_document(
                    config_name=config_name,
                    agent_id=agent_id,
                    skill_name=skill_name,
                )
            else:
                detail = skills_manager.load_skill_document(skill_name)
        except FileNotFoundError:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": f"Unknown skill: {skill_name}",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        await websocket.send(
            json.dumps(
                {
                    "type": "skill_detail_loaded",
                    "agent_id": agent_id,
                    "skill": detail,
                },
                ensure_ascii=False,
            ),
        )

    async def _handle_create_agent_local_skill(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Create a new local skill for one agent and hot-reload runtime assets."""
        agent_id = str(data.get("agent_id", "")).strip()
        skill_name = str(data.get("skill_name", "")).strip()
        if not agent_id or not skill_name:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "create_agent_local_skill requires agent_id and skill_name.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        try:
            skills_manager.create_agent_local_skill(
                config_name=config_name,
                agent_id=agent_id,
                skill_name=skill_name,
            )
        except (ValueError, FileExistsError) as exc:
            await websocket.send(
                json.dumps(
                    {"type": "error", "message": str(exc)},
                    ensure_ascii=False,
                ),
            )
            return

        await self.state_sync.on_system_message(
            f"Created local skill {skill_name} for {agent_id}",
        )
        await self._handle_reload_runtime_assets()
        await websocket.send(
            json.dumps(
                {
                    "type": "agent_local_skill_created",
                    "agent_id": agent_id,
                    "skill_name": skill_name,
                },
                ensure_ascii=False,
            ),
        )
        await self._handle_get_agent_skills(websocket, {"agent_id": agent_id})
        await self._handle_get_skill_detail(
            websocket,
            {"agent_id": agent_id, "skill_name": skill_name},
        )

    async def _handle_update_agent_local_skill(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Update one agent-local SKILL.md and hot-reload runtime assets."""
        agent_id = str(data.get("agent_id", "")).strip()
        skill_name = str(data.get("skill_name", "")).strip()
        content = data.get("content")
        if not agent_id or not skill_name or not isinstance(content, str):
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "update_agent_local_skill requires agent_id, skill_name, and string content.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        try:
            skills_manager.update_agent_local_skill(
                config_name=config_name,
                agent_id=agent_id,
                skill_name=skill_name,
                content=content,
            )
        except (ValueError, FileNotFoundError) as exc:
            await websocket.send(
                json.dumps(
                    {"type": "error", "message": str(exc)},
                    ensure_ascii=False,
                ),
            )
            return

        await self.state_sync.on_system_message(
            f"Updated local skill {skill_name} for {agent_id}",
        )
        await self._handle_reload_runtime_assets()
        await websocket.send(
            json.dumps(
                {
                    "type": "agent_local_skill_updated",
                    "agent_id": agent_id,
                    "skill_name": skill_name,
                },
                ensure_ascii=False,
            ),
        )
        await self._handle_get_skill_detail(
            websocket,
            {"agent_id": agent_id, "skill_name": skill_name},
        )

    async def _handle_delete_agent_local_skill(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Delete one agent-local skill and hot-reload runtime assets."""
        agent_id = str(data.get("agent_id", "")).strip()
        skill_name = str(data.get("skill_name", "")).strip()
        if not agent_id or not skill_name:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "delete_agent_local_skill requires agent_id and skill_name.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        try:
            skills_manager.delete_agent_local_skill(
                config_name=config_name,
                agent_id=agent_id,
                skill_name=skill_name,
            )
            skills_manager.forget_agent_skill_overrides(
                config_name=config_name,
                agent_id=agent_id,
                skill_names=[skill_name],
            )
        except (ValueError, FileNotFoundError) as exc:
            await websocket.send(
                json.dumps(
                    {"type": "error", "message": str(exc)},
                    ensure_ascii=False,
                ),
            )
            return

        await self.state_sync.on_system_message(
            f"Deleted local skill {skill_name} for {agent_id}",
        )
        await self._handle_reload_runtime_assets()
        await websocket.send(
            json.dumps(
                {
                    "type": "agent_local_skill_deleted",
                    "agent_id": agent_id,
                    "skill_name": skill_name,
                },
                ensure_ascii=False,
            ),
        )
        await self._handle_get_agent_skills(websocket, {"agent_id": agent_id})

    async def _handle_remove_agent_skill(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Remove one shared skill from the agent's installed set."""
        agent_id = str(data.get("agent_id", "")).strip()
        skill_name = str(data.get("skill_name", "")).strip()
        if not agent_id or not skill_name:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "remove_agent_skill requires agent_id and skill_name.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        skill_names = {
            item.skill_name
            for item in skills_manager.list_agent_skill_catalog(config_name, agent_id)
            if item.source != "local"
        }
        if skill_name not in skill_names:
            await websocket.send(
                json.dumps(
                    {"type": "error", "message": f"Unknown shared skill: {skill_name}"},
                    ensure_ascii=False,
                ),
            )
            return

        skills_manager.update_agent_skill_overrides(
            config_name=config_name,
            agent_id=agent_id,
            disable=[skill_name],
        )
        await self.state_sync.on_system_message(
            f"Removed shared skill {skill_name} from {agent_id}",
        )
        await self._handle_reload_runtime_assets()
        await websocket.send(
            json.dumps(
                {
                    "type": "agent_skill_removed",
                    "agent_id": agent_id,
                    "skill_name": skill_name,
                },
                ensure_ascii=False,
            ),
        )
        await self._handle_get_agent_skills(websocket, {"agent_id": agent_id})

    async def _handle_update_agent_skill(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Enable or disable one skill for one agent and hot-reload assets."""
        agent_id = str(data.get("agent_id", "")).strip()
        skill_name = str(data.get("skill_name", "")).strip()
        enabled = data.get("enabled")
        if not agent_id or not skill_name or not isinstance(enabled, bool):
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "update_agent_skill requires agent_id, skill_name, and boolean enabled.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        skill_names = {
            item.skill_name
            for item in skills_manager.list_agent_skill_catalog(config_name, agent_id)
        }
        if skill_name not in skill_names:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": f"Unknown skill: {skill_name}",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        if enabled:
            skills_manager.update_agent_skill_overrides(
                config_name=config_name,
                agent_id=agent_id,
                enable=[skill_name],
            )
            await self.state_sync.on_system_message(
                f"Enabled skill {skill_name} for {agent_id}",
            )
        else:
            skills_manager.update_agent_skill_overrides(
                config_name=config_name,
                agent_id=agent_id,
                disable=[skill_name],
            )
            await self.state_sync.on_system_message(
                f"Disabled skill {skill_name} for {agent_id}",
            )

        await websocket.send(
            json.dumps(
                {
                    "type": "agent_skill_updated",
                    "agent_id": agent_id,
                    "skill_name": skill_name,
                    "enabled": enabled,
                },
                ensure_ascii=False,
            ),
        )
        await self._handle_reload_runtime_assets()
        await self._handle_get_agent_skills(
            websocket,
            {"agent_id": agent_id},
        )

    async def _handle_get_agent_workspace_file(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Load one editable agent workspace markdown file."""
        agent_id = str(data.get("agent_id", "")).strip()
        filename = self._normalize_agent_workspace_filename(data.get("filename"))
        if not agent_id or not filename:
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "get_agent_workspace_file requires agent_id and supported filename.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        asset_dir = skills_manager.get_agent_asset_dir(config_name, agent_id)
        asset_dir.mkdir(parents=True, exist_ok=True)
        path = asset_dir / filename
        content = path.read_text(encoding="utf-8") if path.exists() else ""
        await websocket.send(
            json.dumps(
                {
                    "type": "agent_workspace_file_loaded",
                    "config_name": config_name,
                    "agent_id": agent_id,
                    "filename": filename,
                    "content": content,
                },
                ensure_ascii=False,
            ),
        )

    async def _handle_update_agent_workspace_file(
        self,
        websocket: ServerConnection,
        data: Dict[str, Any],
    ) -> None:
        """Persist one editable agent workspace markdown file and hot-reload."""
        agent_id = str(data.get("agent_id", "")).strip()
        filename = self._normalize_agent_workspace_filename(data.get("filename"))
        content = data.get("content")
        if not agent_id or not filename or not isinstance(content, str):
            await websocket.send(
                json.dumps(
                    {
                        "type": "error",
                        "message": "update_agent_workspace_file requires agent_id, supported filename, and string content.",
                    },
                    ensure_ascii=False,
                ),
            )
            return

        config_name = self.config.get("config_name", "default")
        skills_manager = SkillsManager(project_root=self._project_root)
        asset_dir = skills_manager.get_agent_asset_dir(config_name, agent_id)
        asset_dir.mkdir(parents=True, exist_ok=True)
        path = asset_dir / filename
        path.write_text(content, encoding="utf-8")
        await self.state_sync.on_system_message(
            f"Updated {filename} for {agent_id}",
        )
        await websocket.send(
            json.dumps(
                {
                    "type": "agent_workspace_file_updated",
                    "agent_id": agent_id,
                    "filename": filename,
                },
                ensure_ascii=False,
            ),
        )
        await self._handle_reload_runtime_assets()
        await self._handle_get_agent_workspace_file(
            websocket,
            {"agent_id": agent_id, "filename": filename},
        )

    @staticmethod
    def _normalize_watchlist(raw_tickers: Any) -> List[str]:
        """Parse watchlist payloads from websocket messages."""
        if raw_tickers is None:
            return []

        if isinstance(raw_tickers, str):
            candidates = raw_tickers.split(",")
        elif isinstance(raw_tickers, list):
            candidates = raw_tickers
        else:
            candidates = [raw_tickers]

        tickers: List[str] = []
        for candidate in candidates:
            symbol = normalize_symbol(str(candidate).strip().strip("\"'"))
            if symbol and symbol not in tickers:
                tickers.append(symbol)
        return tickers

    @staticmethod
    def _normalize_agent_workspace_filename(raw_name: Any) -> Optional[str]:
        """Restrict editable workspace files to a safe allowlist."""
        filename = str(raw_name or "").strip()
        if filename in EDITABLE_AGENT_WORKSPACE_FILES:
            return filename
        return None

    def _apply_runtime_config(
        self,
        runtime_config: Dict[str, Any],
    ) -> Dict[str, Any]:
        """Apply runtime config to gateway-owned services and state."""
        warnings: List[str] = []

        ticker_changes = self.market_service.update_tickers(
            runtime_config.get("tickers", []),
        )
        self.config["tickers"] = ticker_changes["active"]

        self.pipeline.max_comm_cycles = int(runtime_config["max_comm_cycles"])
        self.config["max_comm_cycles"] = self.pipeline.max_comm_cycles
        self.config["schedule_mode"] = runtime_config.get(
            "schedule_mode",
            self.config.get("schedule_mode", "daily"),
        )
        self.config["interval_minutes"] = int(
            runtime_config.get(
                "interval_minutes",
                self.config.get("interval_minutes", 60),
            ),
        )
        self.config["trigger_time"] = runtime_config.get(
            "trigger_time",
            self.config.get("trigger_time", "09:30"),
        )

        if self.scheduler:
            self.scheduler.reconfigure(
                mode=self.config["schedule_mode"],
                trigger_time=self.config["trigger_time"],
                interval_minutes=self.config["interval_minutes"],
            )

        pm_apply_result = self.pipeline.pm.apply_runtime_portfolio_config(
            margin_requirement=runtime_config["margin_requirement"],
        )
        self.config["margin_requirement"] = self.pipeline.pm.portfolio.get(
            "margin_requirement",
            runtime_config["margin_requirement"],
        )

        requested_initial_cash = float(runtime_config["initial_cash"])
        current_initial_cash = float(self.storage.initial_cash)
        initial_cash_applied = requested_initial_cash == current_initial_cash
        if not initial_cash_applied:
            if (
                self.storage.can_apply_initial_cash()
                and self.pipeline.pm.can_apply_initial_cash()
            ):
                initial_cash_applied = self.storage.apply_initial_cash(
                    requested_initial_cash,
                )
                if initial_cash_applied:
                    self.pipeline.pm.apply_runtime_portfolio_config(
                        initial_cash=requested_initial_cash,
                    )
                    self.config["initial_cash"] = self.storage.initial_cash
            else:
                warnings.append(
                    "initial_cash changed in BOOTSTRAP.md but was not applied "
                    "because the run already has positions, margin usage, or trades.",
                )

        requested_enable_memory = bool(runtime_config["enable_memory"])
        current_enable_memory = bool(self.config.get("enable_memory", False))
        if requested_enable_memory != current_enable_memory:
            warnings.append(
                "enable_memory changed in BOOTSTRAP.md but still requires a restart "
                "because long-term memory contexts are created at startup.",
            )

        self._sync_runtime_state()

        return {
            "runtime_config_requested": runtime_config,
            "runtime_config_applied": {
                "tickers": list(self.config.get("tickers", [])),
                "schedule_mode": self.config.get("schedule_mode", "daily"),
                "interval_minutes": self.config.get("interval_minutes", 60),
                "trigger_time": self.config.get("trigger_time", "09:30"),
                "initial_cash": self.storage.initial_cash,
                "margin_requirement": self.config["margin_requirement"],
                "max_comm_cycles": self.config["max_comm_cycles"],
                "enable_memory": self.config.get("enable_memory", False),
            },
            "runtime_config_status": {
                "tickers": True,
                "schedule_mode": True,
                "interval_minutes": True,
                "trigger_time": True,
                "initial_cash": initial_cash_applied,
                "margin_requirement": pm_apply_result["margin_requirement"],
                "max_comm_cycles": True,
                "enable_memory": requested_enable_memory == current_enable_memory,
            },
            "ticker_changes": ticker_changes,
            "runtime_config_warnings": warnings,
        }

    def _sync_runtime_state(self) -> None:
        """Refresh persisted state and dashboard after runtime config changes."""
        self.state_sync.update_state("tickers", self.config.get("tickers", []))
        self.state_sync.update_state(
            "runtime_config",
            {
                "tickers": self.config.get("tickers", []),
                "schedule_mode": self.config.get("schedule_mode", "daily"),
                "interval_minutes": self.config.get("interval_minutes", 60),
                "trigger_time": self.config.get("trigger_time", "09:30"),
                "initial_cash": self.storage.initial_cash,
                "margin_requirement": self.config.get("margin_requirement"),
                "max_comm_cycles": self.config.get("max_comm_cycles"),
                "enable_memory": self.config.get("enable_memory", False),
            },
        )

        self.storage.update_server_state_from_dashboard(self.state_sync.state)
        self.state_sync.save_state()

        self._dashboard.tickers = list(self.config.get("tickers", []))
        self._dashboard.initial_cash = self.storage.initial_cash
        self._dashboard.enable_memory = bool(
            self.config.get("enable_memory", False),
        )

        summary = self.storage.load_file("summary") or {}
        holdings = self.storage.load_file("holdings") or []
        trades = self.storage.load_file("trades") or []
        self._dashboard.update(
            portfolio=summary,
            holdings=holdings,
            trades=trades,
        )

    def _schedule_watchlist_market_store_refresh(
        self,
        tickers: List[str],
    ) -> None:
        """Kick off a non-blocking Polygon refresh for the updated watchlist."""
        if not tickers:
            return
        if self._watchlist_ingest_task and not self._watchlist_ingest_task.done():
            self._watchlist_ingest_task.cancel()
        self._watchlist_ingest_task = asyncio.create_task(
            self._refresh_market_store_for_watchlist(tickers),
        )

    async def _refresh_market_store_for_watchlist(
        self,
        tickers: List[str],
    ) -> None:
        """Refresh the long-lived market store after a watchlist update."""
        try:
            await self.state_sync.on_system_message(
                f"正在同步自选股市场数据: {', '.join(tickers)}",
            )
            results = await asyncio.to_thread(
                ingest_symbols,
                tickers,
                mode="incremental",
            )
            summary = ", ".join(
                f"{item['symbol']} prices={item['prices']} news={item['news']}"
                for item in results
            )
            await self.state_sync.on_system_message(
                f"自选股市场数据已同步: {summary}",
            )
        except asyncio.CancelledError:
            raise
        except Exception as exc:
            logger.warning("Watchlist market store refresh failed: %s", exc)
            await self.state_sync.on_system_message(
                f"自选股市场数据同步失败: {exc}",
            )

    async def broadcast(self, message: Dict[str, Any]):
        """Broadcast message to all connected clients"""
        if not self.connected_clients:
            return

        message_json = json.dumps(message, ensure_ascii=False, default=str)

        async with self.lock:
            tasks = [
                self._send_to_client(client, message_json)
                for client in self.connected_clients.copy()
            ]

        if tasks:
            await asyncio.gather(*tasks, return_exceptions=True)

    async def _send_to_client(
        self,
        client: ServerConnection,
        message: str,
    ):
        try:
            await client.send(message)
        except websockets.ConnectionClosed:
            async with self.lock:
                self.connected_clients.discard(client)

    async def _market_status_monitor(self):
        """Periodically check and broadcast market status changes"""
        while True:
            try:
                await self.market_service.check_and_broadcast_market_status()

                # On market open, start live session tracking
                status = self.market_service.get_market_status()
                if (
                    status["status"] == "open"
                    and not self.storage.is_live_session_active
                ):
                    self.storage.start_live_session()
                    summary = self.storage.load_file("summary") or {}
                    self._session_start_portfolio_value = summary.get(
                        "totalAssetValue",
                        self.storage.initial_cash,
                    )
                    logger.info(
                        "Session start portfolio: "
                        f"${self._session_start_portfolio_value:,.2f}",
                    )
                elif (
                    status["status"] != "open"
                    and self.storage.is_live_session_active
                ):
                    self.storage.end_live_session()
                    self._session_start_portfolio_value = None

                # Update and broadcast live returns if session is active
                if self.storage.is_live_session_active:
                    await self._update_and_broadcast_live_returns()

                await asyncio.sleep(60)  # Check every minute
            except asyncio.CancelledError:
                break
            except Exception as e:
                logger.error(f"Market status monitor error: {e}")
                await asyncio.sleep(60)

    async def _update_and_broadcast_live_returns(self):
        """Calculate and broadcast live returns for current session"""
        if not self.storage.is_live_session_active:
            return

        # Get current prices and calculate portfolio value
        prices = self.market_service.get_all_prices()
        if not prices or not any(p > 0 for p in prices.values()):
            return

        # Load current internal state to get baseline values
        state = self.storage.load_internal_state()

        # Get latest values from history (if available)
        equity_history = state.get("equity_history", [])
        baseline_history = state.get("baseline_history", [])
        baseline_vw_history = state.get("baseline_vw_history", [])
        momentum_history = state.get("momentum_history", [])

        current_equity = equity_history[-1]["v"] if equity_history else None
        current_baseline = (
            baseline_history[-1]["v"] if baseline_history else None
        )
        current_baseline_vw = (
            baseline_vw_history[-1]["v"] if baseline_vw_history else None
        )
        current_momentum = (
            momentum_history[-1]["v"] if momentum_history else None
        )

        # Update live returns with current values
        point = self.storage.update_live_returns(
            current_equity=current_equity,
            current_baseline=current_baseline,
            current_baseline_vw=current_baseline_vw,
            current_momentum=current_momentum,
        )

        # Broadcast if we have new data
        if point:
            live_returns = self.storage.get_live_returns()
            await self.broadcast(
                {
                    "type": "team_summary",
                    "equity_return": live_returns["equity_return"],
                    "baseline_return": live_returns["baseline_return"],
                    "baseline_vw_return": live_returns["baseline_vw_return"],
                    "momentum_return": live_returns["momentum_return"],
                },
            )

    async def on_strategy_trigger(self, date: str):
        """Handle trading cycle trigger"""
        if self._cycle_lock.locked():
            logger.warning("Trading cycle already running, skipping trigger for %s", date)
            await self.state_sync.on_system_message(
                f"已有交易周期在运行，跳过本次触发: {date}",
            )
            return

        async with self._cycle_lock:
            logger.info(f"Strategy triggered for {date}")

            tickers = self.config.get("tickers", [])

            if self.is_backtest:
                await self._run_backtest_cycle(date, tickers)
            else:
                await self._run_live_cycle(date, tickers)

    async def _run_backtest_cycle(self, date: str, tickers: List[str]):
        """Run backtest cycle with pre-loaded prices"""
        self.market_service.set_backtest_date(date)
        await self.market_service.emit_market_open()

        await self.state_sync.on_cycle_start(date)
        self._dashboard.update(date=date, status="Analyzing...")

        prices = self.market_service.get_open_prices()
        close_prices = self.market_service.get_close_prices()
        market_caps = self._get_market_caps(tickers, date)

        result = await self.pipeline.run_cycle(
            tickers=tickers,
            date=date,
            prices=prices,
            close_prices=close_prices,
            market_caps=market_caps,
        )

        await self.market_service.emit_market_close()
        settlement_result = result.get("settlement_result")
        self._save_cycle_results(result, date, close_prices, settlement_result)
        await self._broadcast_portfolio_updates(result, close_prices)
        await self._finalize_cycle(date)

    async def _run_live_cycle(self, date: str, tickers: List[str]):
        """
        Run live cycle with real market timing.

        - Analysis runs immediately
        - Daily mode waits for open/close as before
        - Intraday mode executes only during market open
          and skips trading outside market hours
        """
        # Get actual trading date (might be next trading day if weekend)
        trading_date = self.market_service.get_live_trading_date()
        logger.info(
            f"Live cycle: triggered={date}, trading_date={trading_date}",
        )

        await self.state_sync.on_cycle_start(trading_date)
        self._dashboard.update(date=trading_date, status="Analyzing...")

        market_caps = self._get_market_caps(tickers, trading_date)
        schedule_mode = self.config.get("schedule_mode", "daily")
        market_status = self.market_service.get_market_status()
        current_prices = self.market_service.get_all_prices()

        if schedule_mode == "intraday":
            execute_decisions = market_status.get("status") == "open"
            if execute_decisions:
                await self.state_sync.on_system_message(
                    "定时任务触发：当前处于交易时段，本轮将执行交易决策",
                )
            else:
                await self.state_sync.on_system_message(
                    "定时任务触发：当前非交易时段，本轮仅更新数据与分析，不执行交易",
                )

            result = await self.pipeline.run_cycle(
                tickers=tickers,
                date=trading_date,
                prices=current_prices,
                market_caps=market_caps,
                execute_decisions=execute_decisions,
            )
            close_prices = current_prices
        else:
            # Daily mode keeps the original full-session behavior
            result = await self.pipeline.run_cycle(
                tickers=tickers,
                date=trading_date,
                market_caps=market_caps,
                get_open_prices_fn=self.market_service.wait_for_open_prices,
                get_close_prices_fn=self.market_service.wait_for_close_prices,
            )
            close_prices = self.market_service.get_all_prices()

        settlement_result = result.get("settlement_result")
        self._save_cycle_results(
            result,
            trading_date,
            close_prices,
            settlement_result,
        )
        await self._broadcast_portfolio_updates(result, close_prices)
        await self._finalize_cycle(trading_date)

    async def _finalize_cycle(self, date: str):
        """Finalize cycle: broadcast state and update dashboard"""
        summary = self.storage.load_file("summary") or {}

        # Include live returns if session is active
        if self.storage.is_live_session_active:
            live_returns = self.storage.get_live_returns()
            summary.update(live_returns)

        await self.state_sync.on_cycle_end(date, portfolio_summary=summary)

        holdings = self.storage.load_file("holdings") or []
        trades = self.storage.load_file("trades") or []
        leaderboard = self.storage.load_file("leaderboard") or []

        if leaderboard:
            await self.state_sync.on_leaderboard_update(leaderboard)

        self._dashboard.update(
            date=date,
            status="Running",
            portfolio=summary,
            holdings=holdings,
            trades=trades,
        )

    def _get_market_caps(
        self,
        tickers: List[str],
        date: str,
    ) -> Dict[str, float]:
        """
        Get market caps for tickers (stub implementation)

        Args:
            tickers: List of tickers
            date: Trading date

        Returns:
            Dict mapping ticker to market cap
        """
        from ..tools.data_tools import get_market_cap

        market_caps = {}
        for ticker in tickers:
            try:
                market_cap = get_market_cap(ticker, date)
                if market_cap:
                    market_caps[ticker] = market_cap
                else:
                    market_caps[ticker] = 1e9
            except Exception:
                market_caps[ticker] = 1e9

        return market_caps

    async def _broadcast_portfolio_updates(
        self,
        result: Dict[str, Any],
        prices: Dict[str, float],
    ):
        portfolio = result.get("portfolio", {})

        if portfolio:
            holdings = FrontendAdapter.build_holdings(portfolio, prices)
            if holdings:
                await self.state_sync.on_holdings_update(holdings)

            stats = FrontendAdapter.build_stats(portfolio, prices)
            if stats:
                await self.state_sync.on_stats_update(stats)

        executed_trades = result.get("executed_trades", [])
        if executed_trades:
            await self.state_sync.on_trades_executed(executed_trades)

    def _save_cycle_results(
        self,
        result: Dict[str, Any],
        date: str,
        prices: Dict[str, float],
        settlement_result: Optional[Dict[str, Any]] = None,
    ):
        portfolio = result.get("portfolio", {})
        executed_trades = result.get("executed_trades", [])

        # Extract baseline values from settlement result
        baseline_values = None
        if settlement_result:
            baseline_values = settlement_result.get("baseline_values")

        if portfolio:
            self.storage.update_dashboard_after_cycle(
                portfolio=portfolio,
                prices=prices,
                date=date,
                executed_trades=executed_trades,
                baseline_values=baseline_values,
            )

    async def _run_backtest_dates(self, dates: List[str]):
        self.state_sync.set_backtest_dates(dates)
        self._dashboard.update(days_total=len(dates), days_completed=0)

        await self.state_sync.on_system_message(
            f"Starting backtest - {len(dates)} trading days",
        )

        try:
            for i, date in enumerate(dates):
                self._dashboard.update(days_completed=i)
                await self.on_strategy_trigger(date=date)
                await asyncio.sleep(0.1)

            await self.state_sync.on_system_message(
                f"Backtest complete - {len(dates)} days",
            )

            # Update dashboard with final state
            summary = self.storage.load_file("summary") or {}
            self._dashboard.update(
                status="Complete",
                portfolio=summary,
                days_completed=len(dates),
            )
            self._dashboard.stop()
            self._dashboard.print_final_summary()
        except Exception as e:
            error_msg = f"Backtest failed: {type(e).__name__}: {str(e)}"
            logger.error(error_msg, exc_info=True)
            await self.state_sync.on_system_message(error_msg)
            self._dashboard.update(status=f"Failed: {str(e)}")
            self._dashboard.stop()
            raise
        finally:
            self._backtest_task = None

    def _handle_backtest_exception(self, task: asyncio.Task):
        """Handle exceptions from backtest task"""
        try:
            task.result()
        except asyncio.CancelledError:
            logger.info("Backtest task was cancelled")
        except Exception as e:
            logger.error(
                f"Backtest task failed with exception:{type(e).__name__}:{e}",
                exc_info=True,
            )

    def _handle_manual_cycle_exception(self, task: asyncio.Task):
        """Handle exceptions from manually-triggered live cycles."""
        self._manual_cycle_task = None
        try:
            task.result()
        except asyncio.CancelledError:
            logger.info("Manual cycle task was cancelled")
        except Exception as exc:
            logger.error(
                "Manual cycle task failed with exception:%s:%s",
                type(exc).__name__,
                exc,
                exc_info=True,
            )

    def set_backtest_dates(self, dates: List[str]):
        self.state_sync.set_backtest_dates(dates)
        if dates:
            self._backtest_start_date = dates[0]
            self._backtest_end_date = dates[-1]
            self._dashboard.days_total = len(dates)

    def stop(self):
        self.state_sync.save_state()
        self.market_service.stop()
        if self._backtest_task:
            self._backtest_task.cancel()
        if self._market_status_task:
            self._market_status_task.cancel()
        if self._watchlist_ingest_task:
            self._watchlist_ingest_task.cancel()
        self._dashboard.stop()