1

backend/app/config.py

@@ -109,7 +109,9 @@ class Settings(BaseSettings):
 
     # 加密货币交易智能体配置
     crypto_symbols: str = "BTCUSDT,ETHUSDT"  # 监控的交易对，逗号分隔
-    crypto_llm_threshold: float = 0.70  # 触发 LLM 分析的置信度阈值
+    crypto_llm_threshold: float = 0.70  # 旧的统一阈值，兼容保留
+    crypto_intraday_signal_threshold: float = 0.68  # 日内信号置信度阈值
+    crypto_trend_signal_threshold: float = 0.72  # 趋势信号置信度阈值
 
     # 价格监控模式配置
     use_bitget_websocket: bool = True  # 是否使用 Bitget WebSocket 实时价格（默认 False 使用 Binance 轮询）
@@ -119,14 +121,14 @@ class Settings(BaseSettings):
     crypto_min_volatility_percent: float = 0.5  # 最小波动率（百分比），低于此值跳过分析
     crypto_min_price_range_percent: float = 0.3  # 最小价格变动范围（百分比），低于此值跳过分析
     crypto_5m_surge_threshold: float = 1.0  # 5分钟突发波动阈值（百分比），超过此值即使1小时波动率低也会触发分析
-    crypto_intraday_llm_cooldown_minutes: int = 15  # 日内 LLM 分析冷却时间
-    crypto_trend_llm_cooldown_minutes: int = 60  # 趋势 LLM 分析冷却时间
+    crypto_intraday_llm_cooldown_minutes: int = 8  # 日内 LLM 分析冷却时间
+    crypto_trend_llm_cooldown_minutes: int = 25  # 趋势 LLM 分析冷却时间
     crypto_force_llm_surge_threshold: float = 1.2  # 15分钟突发波动强制触发 LLM 的阈值
     crypto_force_llm_trade_zone_pct: float = 0.25  # 接近关键交易区时强制触发 LLM 的距离阈值
     crypto_event_analysis_enabled: bool = True  # 是否启用实时行情事件触发分析
     crypto_event_analysis_window_minutes: int = 5  # 实时行情异动检测窗口
     crypto_event_analysis_price_change_percent: float = 0.8  # 检测窗口内涨跌超过该阈值触发日内分析
-    crypto_event_analysis_cooldown_minutes: int = 10  # 同一交易对事件触发分析冷却
+    crypto_event_analysis_cooldown_minutes: int = 5  # 同一交易对事件触发分析冷却
 
     # Brave Search API 配置
     brave_api_key: str = ""

backend/app/crypto_agent/crypto_agent.py

@@ -503,7 +503,8 @@ class CryptoAgent:
         last_symbol = self._analysis_monitor.get("last_analysis_symbol") or "-"
         last_status = self._analysis_monitor.get("last_analysis_status") or "unknown"
         last_detail = self._analysis_monitor.get("last_analysis_detail") or "最近一轮分析已完成"
-        threshold = self.settings.crypto_llm_threshold * 100
+        intraday_threshold = self._get_signal_threshold_pct(signal_type='short_term')
+        trend_threshold = self._get_signal_threshold_pct(signal_type='medium_term')
 
         title = "💓 [分析心跳] 系统运行正常"
         content = "\n".join([
@@ -513,7 +514,7 @@ class CryptoAgent:
             f"**完成分析**: {symbol_completed} 个交易对",
             f"**跳过分析**: {symbol_skipped} 次",
             f"**分析异常**: {symbol_errors} 次",
-            f"**信号阈值**: {threshold:.0f}%",
+            f"**信号阈值**: 日内 {intraday_threshold:.0f}% / 趋势 {trend_threshold:.0f}%",
             f"**最近分析对象**: {last_symbol}",
             f"**最近状态**: {last_status}",
             f"**最近说明**: {last_detail}",
@@ -615,20 +616,9 @@ class CryptoAgent:
         return False, ""
 
     def _resolve_llm_lanes_for_symbol(self, symbol: str, data: Dict[str, pd.DataFrame]) -> tuple[List[str], Dict[str, Any], str]:
-        now = datetime.now()
         state = self._get_lane_state(symbol)
         force, force_reason = self._detect_force_llm_trigger(symbol, data)
-        lanes: List[str] = []
-
-        intraday_last = self._parse_iso_datetime(state.get("last_intraday_at"))
-        trend_last = self._parse_iso_datetime(state.get("last_trend_at"))
-        intraday_cooldown = timedelta(minutes=self.settings.crypto_intraday_llm_cooldown_minutes)
-        trend_cooldown = timedelta(minutes=self.settings.crypto_trend_llm_cooldown_minutes)
-
-        if force or intraday_last is None or not state.get("cached_intraday") or now - intraday_last >= intraday_cooldown:
-            lanes.append("intraday")
-        if force or trend_last is None or not state.get("cached_trend") or now - trend_last >= trend_cooldown:
-            lanes.append("trend")
+        lanes: List[str] = ["intraday", "trend"]
 
         cached_results = {}
         if state.get("cached_intraday"):
@@ -636,9 +626,6 @@ class CryptoAgent:
         if state.get("cached_trend"):
             cached_results["trend"] = state["cached_trend"]
 
-        if not lanes and not cached_results:
-            lanes = ["intraday", "trend"]
-
         state["last_force_reason"] = force_reason if force else ""
         return lanes, cached_results, force_reason
 
@@ -1245,7 +1232,7 @@ class CryptoAgent:
             f"📊 **监控交易对**: {len(self.symbols)} 个",
             f"   {', '.join(self.symbols)}",
             f"⏰ **运行频率**: 每5分钟轻扫描",
-            f"🧊 **LLM 冷却**: 日内 {self.settings.crypto_intraday_llm_cooldown_minutes} 分钟 / 趋势 {self.settings.crypto_trend_llm_cooldown_minutes} 分钟",
+            f"🧠 **LLM 执行**: 每轮双 lane 直接分析，不做冷却缓存",
             f"💰 **交易系统**: 已启用（后台统一监控）",
             f"🎯 **分析维度**: 技术面 + 资金面 + 情绪面",
         ]
@@ -1497,25 +1484,6 @@ class CryptoAgent:
             price_change_24h = self._calculate_price_change(data['1h'])
             logger.info(f"💰 当前价格: ${current_price:,.2f} ({price_change_24h})")
 
-            paper_symbol_cooldown = None
-            if self.settings.paper_trading_enabled:
-                paper_symbol_cooldown = self._refresh_symbol_trade_cooldown('PaperTrading', symbol)
-                if paper_symbol_cooldown.get('should_cool_down'):
-                    cooldown_until = paper_symbol_cooldown.get('cooldown_until')
-                    cooldown_text = cooldown_until.isoformat() if cooldown_until else ''
-                    self._record_analysis_event(
-                        "symbol_trade_cooldown",
-                        symbol=symbol,
-                        status="warning",
-                        detail=paper_symbol_cooldown.get('reason', '交易对处于冷却中'),
-                        extra={
-                            "platform": "PaperTrading",
-                            "losing_streak": paper_symbol_cooldown.get('losing_streak', 0),
-                            "cooldown_until": cooldown_text,
-                        },
-                    )
-                    logger.info(f"⏸️  模拟盘交易对冷却: {paper_symbol_cooldown.get('reason')} | until={cooldown_text}")
-
             # 1.5. 波动率检查（节省 LLM 调用）
             should_analyze, volatility_reason, volatility = self._check_volatility(symbol, data)
             if not should_analyze:
@@ -1545,24 +1513,19 @@ class CryptoAgent:
             logger.info(f"\n🤖 【第一阶段：市场信号分析】 lanes={lanes_to_run or ['cache_only']}")
             if force_reason:
                 logger.info(f"   ⚡ 强制触发 LLM: {force_reason}")
-            elif not lanes_to_run:
-                logger.info("   🧊 LLM 冷却中，使用上一轮 lane 缓存结果")
 
-            if lanes_to_run:
-                self._bump_analysis_stat("llm_analyses")
-                for lane in lanes_to_run:
-                    self._bump_lane_call(lane)
-            else:
-                self._bump_analysis_stat("cache_only_runs")
+            self._bump_analysis_stat("llm_analyses")
+            for lane in lanes_to_run:
+                self._bump_lane_call(lane)
 
             self._record_analysis_event(
                 "llm_lane_plan",
                 symbol=symbol,
                 status="info",
-                detail=force_reason or (f"本轮执行 lane: {', '.join(lanes_to_run)}" if lanes_to_run else "LLM 冷却中，使用缓存 lane 结果"),
+                detail=force_reason or f"本轮执行 lane: {', '.join(lanes_to_run)}",
                 extra={
                     "lanes_to_run": lanes_to_run,
-                    "cache_only": not bool(lanes_to_run),
+                    "cache_only": False,
                     "force_reason": force_reason,
                     "trigger_source": trigger_source,
                 },
@@ -1627,19 +1590,19 @@ class CryptoAgent:
                 return
 
             # 检查是否有达到阈值的交易信号
-            threshold = self.settings.crypto_llm_threshold * 100  # 转换为百分比
-            valid_signals = [s for s in trade_signals if s.get('confidence', 0) >= threshold]
+            valid_signals = self._filter_valid_trade_signals(trade_signals)
 
             if not valid_signals:
                 self._bump_analysis_stat("threshold_filtered_runs")
                 self._analysis_monitor["last_analysis_completed_at"] = datetime.now().isoformat()
                 self._analysis_monitor["last_analysis_status"] = "completed"
-                self._analysis_monitor["last_analysis_detail"] = f"完成分析，但无信号达到阈值 {threshold}%"
+                thresholds_text = f"日内 {self._get_signal_threshold_pct(signal_type='short_term'):.0f}% / 趋势 {self._get_signal_threshold_pct(signal_type='medium_term'):.0f}%"
+                self._analysis_monitor["last_analysis_detail"] = f"完成分析，但无信号达到阈值 {thresholds_text}"
                 self._record_analysis_event(
                     "symbol_analysis_completed",
                     symbol=symbol,
                     status="success",
-                    detail=f"完成分析，但无信号达到阈值 {threshold}%",
+                    detail=f"完成分析，但无信号达到阈值 {thresholds_text}",
                     extra={
                         "trade_signals": len(trade_signals),
                         "valid_signals": 0,
@@ -1648,12 +1611,12 @@ class CryptoAgent:
                         "post_regime_lane_signal_counts": market_signal.get("post_regime_lane_signal_counts") or {},
                     },
                 )
-                logger.info(f"\n⏸️  结论: 无交易信号达到置信度阈值 ({threshold}%)，继续观望")
+                logger.info(f"\n⏸️  结论: 无交易信号达到分周期阈值（日内 {self._get_signal_threshold_pct(signal_type='short_term'):.0f}% / 趋势 {self._get_signal_threshold_pct(signal_type='medium_term'):.0f}%），继续观望")
                 return
 
             self._bump_analysis_stat("valid_signal_runs")
             self._bump_analysis_stat("valid_signals_total", len(valid_signals))
-            logger.info(f"\n✅ 发现 {len(valid_signals)} 个有效交易信号（达到 {threshold}% 阈值）")
+            logger.info(f"\n✅ 发现 {len(valid_signals)} 个有效交易信号（按周期阈值过滤）")
             for signal in valid_signals:
                 logger.info(
                     f"   - {signal.get('timeframe', signal.get('type', 'unknown'))} | "
@@ -2036,18 +1999,34 @@ class CryptoAgent:
         profile['setup_type'] = setup_type
         return profile
 
+    def _get_signal_threshold_pct(self, signal: Optional[Dict[str, Any]] = None, signal_type: Optional[str] = None) -> float:
+        resolved_type = signal_type or (signal or {}).get('timeframe') or (signal or {}).get('type') or 'medium_term'
+        if resolved_type == 'short_term':
+            threshold = getattr(self.settings, 'crypto_intraday_signal_threshold', None)
+        elif resolved_type == 'medium_term':
+            threshold = getattr(self.settings, 'crypto_trend_signal_threshold', None)
+        else:
+            threshold = None
+
+        if threshold is None:
+            threshold = getattr(self.settings, 'crypto_llm_threshold', 0.70)
+        return float(threshold) * 100
+
+    def _filter_valid_trade_signals(self, signals: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        return [
+            signal for signal in (signals or [])
+            if signal.get('action') in {'buy', 'sell'}
+            and float(signal.get('confidence', 0) or 0) >= self._get_signal_threshold_pct(signal=signal)
+        ]
+
     async def _execute_decisions(self, paper_decision: Dict[str, Any],
                                  bitget_decisions: Dict[str, Dict[str, Any]],
                                  market_signal: Dict[str, Any], current_price: float):
         """执行交易决策（模拟盘 + Bitget 独立）"""
         # 保存本轮所有达到阈值的可交易信号，避免分流后只落一条信号
-        threshold = self.settings.crypto_llm_threshold * 100
         symbol = market_signal.get('symbol')
         signals = market_signal.get('signals', [])
-        valid_signals = [
-            signal for signal in signals
-            if signal.get('action') in {'buy', 'sell'} and signal.get('confidence', 0) >= threshold
-        ]
+        valid_signals = self._filter_valid_trade_signals(signals)
 
         for signal in valid_signals:
             signal_to_save = signal.copy()
@@ -2673,12 +2652,8 @@ class CryptoAgent:
                                                current_price: float):
         """发送市场信号通知（第一阶段）- 调用前已确保有有效信号"""
         try:
-            # 获取配置的阈值
-            threshold = self.settings.crypto_llm_threshold * 100  # 转换为百分比
-
-            # 过滤达到阈值的信号（防御性检查）
             signals = market_signal.get('signals', [])
-            valid_signals = [s for s in signals if s.get('confidence', 0) >= threshold]
+            valid_signals = self._filter_valid_trade_signals(signals)
 
             if not valid_signals:
                 return
@@ -4017,12 +3992,6 @@ class CryptoAgent:
             blocked_reasons = regime_profile.get('no_trade_reasons') or ['当前市场状态不允许交易']
             return False, f"市场状态过滤: {'；'.join(blocked_reasons[:2])}"
 
-        symbol_cooldown = self._get_symbol_trade_cooldown(platform_name, signal.get('symbol', ''))
-        if symbol_cooldown and symbol_cooldown.get('should_cool_down'):
-            cooldown_until = symbol_cooldown.get('cooldown_until')
-            until_text = cooldown_until.isoformat() if cooldown_until else ''
-            return False, f"交易对冷却中: {symbol_cooldown.get('reason', '').strip()} {until_text}".strip()
-
         setup_passed, setup_reason = self._check_setup_execution_constraints(signal)
         if not setup_passed:
             return False, f"setup 过滤: {setup_reason}"
@@ -4095,12 +4064,6 @@ class CryptoAgent:
             elif signal_action == 'sell' and fr_pct < -0.05:
                 return False, f"资金费率过冷 {fr_pct:.4f}%（做空拥挤），拒绝做空"
 
-        # 6. 连败降温检查（不拒绝，但降低仓位）
-        streak_info = self._check_losing_streak(platform_name)
-        if streak_info.get('should_cool_down'):
-            signal['_streak_margin_multiplier'] = streak_info['margin_multiplier']
-            logger.warning(f"[{platform_name}] ⚠️ {streak_info['reason']}")
-
         return True, "通过风控检查"
 
     def execute_signal_with_rules(self, signal: Dict[str, Any],
@@ -4440,20 +4403,10 @@ class CryptoAgent:
             return False
 
         confidence = signal.get('confidence', 0)
-        # 使用配置文件中的阈值
-        threshold = self.settings.crypto_llm_threshold * 100  # 转换为百分比
+        threshold = self._get_signal_threshold_pct(signal=signal)
         if confidence < threshold:
             return False
 
-        # 检查冷却时间（30分钟内不重复发送相同方向的信号）
-        if symbol in self.signal_cooldown:
-            cooldown_end = self.signal_cooldown[symbol] + timedelta(minutes=30)
-            if datetime.now() < cooldown_end:
-                if symbol in self.last_signals:
-                    if self.last_signals[symbol].get('action') == action:
-                        logger.debug(f"{symbol} 信号冷却中，跳过")
-                        return False
-
         return True
 
     async def _review_and_adjust_positions(
@@ -4560,11 +4513,7 @@ class CryptoAgent:
         )
 
         signals = market_signal.get('signals', [])
-        threshold = self.settings.crypto_llm_threshold * 100
-        valid_signals = [
-            signal for signal in signals
-            if signal.get('action') in {'buy', 'sell'} and signal.get('confidence', 0) >= threshold
-        ]
+        valid_signals = self._filter_valid_trade_signals(signals)
 
         execution_preview: Dict[str, Any] = {}
 
@@ -4627,8 +4576,10 @@ class CryptoAgent:
             'execution_guardian': self.execution_guardian.get_status(),
             'llm_schedule': {
                 'scan_interval_minutes': 5,
-                'intraday_cooldown_minutes': self.settings.crypto_intraday_llm_cooldown_minutes,
-                'trend_cooldown_minutes': self.settings.crypto_trend_llm_cooldown_minutes,
+                'intraday_cooldown_minutes': 0,
+                'trend_cooldown_minutes': 0,
+                'intraday_signal_threshold': self._get_signal_threshold_pct(signal_type='short_term'),
+                'trend_signal_threshold': self._get_signal_threshold_pct(signal_type='medium_term'),
                 'force_surge_threshold': self.settings.crypto_force_llm_surge_threshold,
                 'force_trade_zone_pct': self.settings.crypto_force_llm_trade_zone_pct,
                 'event_analysis_enabled': self.settings.crypto_event_analysis_enabled,

backend/app/crypto_agent/regime_engine.py

@@ -90,15 +90,15 @@ class RegimeEngine:
                     {
                         "regime_key": "transition",
                         "market_state_label": "过渡市",
-                        "tradability": "avoid",
+                        "tradability": "selective",
                         "risk_mode": "defensive",
-                        "allowed_lanes": [],
-                        "preferred_lanes": [],
-                        "allowed_setups": [],
-                        "preferred_entry_types": [],
+                        "allowed_lanes": ["short_term"],
+                        "preferred_lanes": ["short_term", "medium_term"],
+                        "allowed_setups": ["breakout_pullback", "breakout_confirmation", "range_reversal"],
+                        "preferred_entry_types": ["limit", "market"],
                     }
                 )
-                no_trade_reasons.append("趋势与震荡切换期，方向优势不足")
+                no_trade_reasons.append("趋势与震荡切换期，只做边界确认和突破回踩")
 
         elif range_regime in {"weak_trend", "strong_trend"} and trend_direction in {"uptrend", "downtrend"}:
             allow_reversal = bool(reversal_detection.get("is_reversing")) and trend_strength != "strong"
@@ -127,7 +127,7 @@ class RegimeEngine:
                         "risk_mode": "normal" if range_regime == "strong_trend" else "reduced",
                         "allowed_lanes": ["medium_term", "short_term"],
                         "preferred_lanes": ["medium_term", "short_term"],
-                        "allowed_setups": ["trend_continuation_pullback"],
+                        "allowed_setups": ["trend_continuation_pullback", "deep_pullback_continuation"],
                         "preferred_entry_types": ["limit", "market"],
                     }
                 )

backend/app/crypto_agent/setup_policy.py

@@ -42,6 +42,14 @@ class SetupPolicy:
                 continue
 
             if setup_type not in allowed_setups:
+                if tradability == "selective" and self._allow_selective_fallback(signal, lane=lane):
+                    kept.append({
+                        **signal,
+                        "setup_type": setup_type,
+                        "setup_basis": setup_basis,
+                        "entry_basis": entry_basis,
+                    })
+                    continue
                 reasons.append(f"{setup_type} 不在允许 setup 内")
                 reason_counts[f"setup_blocked:{setup_type}"] += 1
                 continue
@@ -55,6 +63,28 @@ class SetupPolicy:
 
         return kept, reasons, dict(reason_counts)
 
+    def _allow_selective_fallback(self, signal: Dict[str, Any], *, lane: str) -> bool:
+        confidence = float(signal.get("confidence", 0) or 0)
+        entry_type = signal.get("entry_type", "market")
+        location_tag = ((signal.get("market_location") or {}).get("location_tag") or "")
+        volume_context = signal.get("volume_price_context") or {}
+        pullback_quality = volume_context.get("pullback_quality") or signal.get("pullback_quality")
+        breakout_quality = volume_context.get("breakout_quality") or signal.get("breakout_quality")
+
+        if lane == "medium_term" and entry_type == "limit" and confidence >= 74:
+            if location_tag in {"near_long_zone", "near_short_zone", "near_range_support", "near_range_resistance"}:
+                return True
+            if pullback_quality == "healthy_pullback":
+                return True
+
+        if lane == "short_term" and confidence >= 72:
+            if breakout_quality in {"acceptance_breakout_up", "acceptance_breakout_down"}:
+                return True
+            if entry_type == "limit" and location_tag in {"near_long_zone", "near_short_zone", "near_range_support", "near_range_resistance"}:
+                return True
+
+        return False
+
     def _infer_setup_type(self, signal: Dict[str, Any]) -> str:
         lane = signal.get("timeframe") or signal.get("type") or "medium_term"
         action = signal.get("action")

frontend/console.html

@@ -3701,7 +3701,8 @@
                 <div class="runtime-summary-meta">
                     <div class="runtime-summary-row"><span>最近分析说明</span><strong>${monitor.last_analysis_detail || '-'}</strong></div>
                     <div class="runtime-summary-row"><span>最近完成轮次</span><strong>${monitor.last_cycle_completed_at ? `${relativeTime(monitor.last_cycle_completed_at)} / ${formatTime(monitor.last_cycle_completed_at)}` : '暂无'}</strong></div>
-                    <div class="runtime-summary-row"><span>日内 / 趋势冷却</span><strong>${schedule.intraday_cooldown_minutes || '-'}m / ${schedule.trend_cooldown_minutes || '-'}m</strong></div>
+                    <div class="runtime-summary-row"><span>日内 / 趋势冷却</span><strong>${schedule.intraday_cooldown_minutes ?? '-'}m / ${schedule.trend_cooldown_minutes ?? '-'}m</strong></div>
+                    <div class="runtime-summary-row"><span>日内 / 趋势阈值</span><strong>${schedule.intraday_signal_threshold || '-'}% / ${schedule.trend_signal_threshold || '-'}%</strong></div>
                     <div class="runtime-summary-row"><span>事件分析</span><strong>${schedule.event_analysis_enabled ? '开启' : '关闭'}</strong></div>
                     <div class="runtime-summary-row"><span>触发 / LLM</span><strong>${funnel.total_triggers || 0} / ${funnel.llm_analyses || 0}</strong></div>
                     <div class="runtime-summary-row"><span>波动率跳过 / 数据异常</span><strong>${funnel.volatility_skips || 0} / ${funnel.data_invalid_skips || 0}</strong></div>