multi_agent_framework.py

import asyncio
import uuid
import random

import numpy as np

from odds_api_connector import OddsAPIConnector
from pinnacle_arb_engine import PinnacleArbitrageEngine
from run_ultimate_backtest import RiskManagementV9
from polymarket_connector import PolymarketConnector
from logger import QuantLogger
from stat_arb_engine import StatArbMathEngine

logger = QuantLogger()

# ==========================================
# 1. 通信核心：高并发异步事件总线 (Event Bus)
# ==========================================
class EventBus:
    def __init__(self):
        self.subscribers = {}
        
    def subscribe(self, event_type, callback):
        if event_type not in self.subscribers:
            self.subscribers[event_type] = []
        self.subscribers[event_type].append(callback)
        
    async def publish(self, event_type, payload):
        if event_type in self.subscribers:
            tasks = [callback(payload) for callback in self.subscribers[event_type]]
            await asyncio.gather(*tasks)

# ==========================================
# 2. 特工基类
# ==========================================
class BaseAgent:
    def __init__(self, name, bus):
        self.name = name
        self.bus = bus
        self.logger = logger
        
    async def log(self, message, level="INFO"):
        prefix = f"[{self.name}]"
        if level == "INFO":
            self.logger.info(f"{prefix} {message}")
        elif level == "WARN":
            self.logger.warning(f"{prefix} {message}")
        elif level == "ALERT":
            self.logger.alert(f"{prefix} {message}")

# ==========================================
# 3. 基础四特工 (V11 原型)
# ==========================================
class SensorAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("🕵️ 情报特工", bus)
        
    async def start_patrol(self):
        await self.log("启动全球雷达扫描...")
        await asyncio.sleep(1)
        matches = [
            {"match_id": 201, "match_name": "France vs Italy"},
            {"match_id": 202, "match_name": "England vs Portugal"}
        ]
        for m in matches:
            await self.log(f"雷达发现高能反应: {m['match_name']}。立即推送总线！")
            await self.bus.publish("MATCH_FOUND", m)
            await asyncio.sleep(3)

class AlphaAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("🧮 量化特工", bus)
        self.bus.subscribe("MATCH_FOUND", self.handle_match)
        # 本地暂存最新的 LLM 舆情，以便叠加
        self.latest_sentiment = {}
        self.bus.subscribe("SENTIMENT_ALERT", self.update_sentiment)
        
    async def update_sentiment(self, payload):
        self.latest_sentiment[payload["match_id"]] = payload["sentiment_score"]
        
    async def handle_match(self, payload):
        match_name = payload["match_name"]
        await self.log(f"接收坐标 {match_name}，拉起 XGBoost 进行解算...")
        await asyncio.sleep(0.5)
        
        # 基础胜率与市价
        p_model = random.uniform(0.60, 0.85)
        market_odds = random.uniform(1.3, 1.7)
        
        # 如果有极端的 LLM 负面舆情，胜率被严重衰减
        sentiment = self.latest_sentiment.get(payload["match_id"], 1.0)
        p_model_adjusted = p_model * sentiment
        
        ev = p_model_adjusted * market_odds
        
        if ev > 1.05:
            await self.log(f"套利空间确认: {match_name} (最终 EV={ev:.2f})！正在向法庭提交提案。")
            proposal = {
                "proposal_id": str(uuid.uuid4())[:8],
                "match_id": payload["match_id"],
                "match_name": match_name,
                "p_model": p_model_adjusted,
                "market_odds": market_odds,
                "ev": ev
            }
            await self.bus.publish("TRADE_PROPOSAL", proposal)
        else:
            await self.log(f"解算完毕: {match_name} (EV={ev:.2f}) 太低，放弃开火。")

class CritiqueAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("⚖️ 风控法庭", bus)
        self.bus.subscribe("TRADE_PROPOSAL", self.handle_proposal)
        
        # 接收巨鲸熔断指令
        self.whale_alerts = {}
        self.bus.subscribe("WHALE_ALERT", self.receive_whale_alert)
        self.risk_mgr = RiskManagementV9(initial_capital=10000.0)
        
    async def receive_whale_alert(self, payload):
        self.whale_alerts[payload["match_id"]] = True
        
    async def handle_proposal(self, proposal):
        await self.log(f"收到 [提案 {proposal['proposal_id']}]，开始红蓝对抗审查...")
        await asyncio.sleep(0.5)
        
        # 检查是否被巨鲸特工标记为高危盘口
        if self.whale_alerts.get(proposal["match_id"]):
            await self.log("❌ 提案否决！该盘口已被【巨鲸特工】标记存在顶级暗箱操作风险，触发物理熔断！", "WARN")
            return
            
        bet_size = self.risk_mgr.calculate_bet_size(proposal["p_model"], proposal["market_odds"])
        await self.log(f"✅ 法庭全票通过 [提案 {proposal['proposal_id']}]。已签发 {bet_size:.2f} USDC 军费。")
        
        approved_trade = {
            "match_name": proposal["match_name"],
            "size": bet_size,
            "price": 1.0 / proposal["market_odds"]
        }
        await self.bus.publish("TRADE_APPROVED", approved_trade)

class ExecutionAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("🥷 执行特工", bus)
        self.bus.subscribe("TRADE_APPROVED", self.handle_approved_trade)
        self.exchange = PolymarketConnector()
        
    async def handle_approved_trade(self, trade):
        shares_to_buy = trade["size"] / trade["price"]
        await self.log(f"收到暗杀指令。向 {trade['match_name']} 隐蔽投放 {shares_to_buy:.2f} 份合约，单价 ${trade['price']:.3f}。")
        await asyncio.sleep(0.5)
        self.exchange.place_order(market_token="0x" + str(uuid.uuid4()).replace("-", ""), side="BUY", size=shares_to_buy, price=trade["price"])
        await self.log("任务完成。筹码已入库，未惊动市场。", "ALERT")

# ==========================================
# 4. 四大神级特工 (V11 超限战扩容)
# ==========================================
class LLMSentimentAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("📰 舆情特工", bus)
        self.bus.subscribe("MATCH_FOUND", self.analyze_sentiment)
        
    async def analyze_sentiment(self, payload):
        match_id = payload["match_id"]
        await self.log(f"收到赛事 {payload['match_name']}。正在调用 GPT-4 解析推特/ESPN 原始文本流...")
        await asyncio.sleep(0.2)
        
        # 模拟：10% 概率解析出重大利空新闻（比如当家球星骨折）
        if random.random() < 0.3:
            sentiment_score = 0.5 # 严重衰减胜率
            await self.log("🚨 警报！GPT 侦测到赛前更衣室严重内讧，释放情绪负面因子 (0.5) 给量化大脑！", "WARN")
            await self.bus.publish("SENTIMENT_ALERT", {"match_id": match_id, "sentiment_score": sentiment_score})

class WhaleTrackerAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("🐋 巨鲸特工", bus)
        self.bus.subscribe("MATCH_FOUND", self.track_whale)
        
    async def track_whale(self, payload):
        await self.log(f"正在监听 {payload['match_name']} 关联的 Polygon 链上大户合约地址...")
        await asyncio.sleep(0.3)
        
        # 模拟：如果检测到巨鲸砸盘反方向
        if random.random() < 0.2:
            await self.log("🚨 警报！嗅探到神秘巨鲸(0xABC...) 砸盘 $250,000 做空主队！立刻封锁交易通道！", "WARN")
            await self.bus.publish("WHALE_ALERT", {"match_id": payload["match_id"]})

class ArbitrageAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("💱 对冲特工", bus)
        self.bus.subscribe("TRADE_PROPOSAL", self.check_arbitrage)
        self.arb_engine = PinnacleArbitrageEngine(ev_threshold=1.05)
        self.api_connector = OddsAPIConnector()
        
    async def check_arbitrage(self, proposal):
        await self.log(f"拦截到 [提案 {proposal['proposal_id']}]。正在连接 The Odds API 获取 Pinnacle 真理赔率...")
        
        # 1. 真实抓取 Pinnacle 赔率
        real_pinny_odds = await self.api_connector.get_pinnacle_odds(proposal['match_name'])
        
        if not real_pinny_odds:
            await self.log("无法获取该赛事的 Pinnacle 赔率流，放弃对冲拦截。", "WARN")
            return
            
        await self.log(f"🔥 成功获取 Pinnacle 实时跳动赔率: {real_pinny_odds}")
        
        # Polymarket 模拟实时市价 (基于提案)
        mock_poly_odds = {"home": proposal['market_odds'], "away": 3.80}
        
        # 2. 检查 Mode 2: Surebet (双边锁仓无风险套利)
        # 提取平博非主队(对立面)的最优合成赔率。简化处理：取平博客胜
        pinny_opposite = real_pinny_odds[2]
        surebet_res = self.arb_engine.check_surebet(mock_poly_odds["home"], pinny_opposite, total_capital=1000)
        
        if surebet_res["is_surebet"]:
            roi = surebet_res['roi_percent']
            await self.log(f"💸 [Surebet 警报] 发现跨平台无风险金矿！综合 ROI: {roi:.2f}%。执行双边锁仓！", "ALERT")
            await self.log(f"   -> Polymarket 分配: ${surebet_res['poly_stake']:.2f}")
            await self.log(f"   -> Pinnacle 备用仓分配: ${surebet_res['pinny_stake']:.2f}")
            await self.bus.publish("ARBITRAGE_EXECUTED", proposal)
            return # 如果执行了无风险套利，直接终止单边提案
            
        # 3. 检查 Mode 1: Value Betting (价值下注)
        val_bets = self.arb_engine.check_value_bet(real_pinny_odds, mock_poly_odds)
        if val_bets:
            for vb in val_bets:
                await self.log(f"🔥 [ValueBet 警报] Pinnacle 物理胜率揭示 Polymarket 存在错价！方向: {vb['side']}, EV: {vb['ev']:.2f}")
                # 这种情况下，允许原提案继续向风控法庭流转，因为它是高价值单边裸多

class MarketMakerAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("🌊 做市特工", bus)
        
    async def start_market_making(self):
        await self.log("暗池做市商程序启动。正在双边持续提供流动性 (Bid/Ask)，吃散户点差...")
        for _ in range(2):
            await asyncio.sleep(2)
            await self.log("🚰 成功搬砖一次盘口差价，白嫖收益: $2.45。持续挂单中...", "INFO")

class StatArbAgent(BaseAgent):
    def __init__(self, bus):
        super().__init__("🧲 统计套利特工", bus)
        self.math_engine = StatArbMathEngine()
        
    async def start_z_score_monitor(self):
        await self.log("Z-Score 监控雷达启动。正在扫描大盘高协整性资产对 (Pairs)...")
        # 模拟产生历史价格序列
        hist_a = np.random.normal(loc=0.5, scale=0.02, size=60).tolist()
        hist_b = np.random.normal(loc=0.45, scale=0.02, size=60).tolist()
        
        for step in range(3):
            await asyncio.sleep(2)
            
            # 模拟在某一个瞬间，资产 A 价格异动狂飙 (散户非理性情绪)
            price_a = 0.5 + (0.05 * step) 
            price_b = 0.45 + np.random.normal(0, 0.005) # 资产 B 保持不动
            
            z_score, signal = self.math_engine.analyze_pair_state(price_a, price_b, hist_a, hist_b)
            
            await self.log(f"监控到目标对价差波动: 资产 A=${price_a:.3f}, 资产 B=${price_b:.3f} | Z-Score: {z_score:.2f}")
            
            if signal == "SHORT_A_LONG_B":
                await self.log(f"🚨 [均值回归触发] Z-Score {z_score:.2f} 击穿 2.0 红线！价差极度异常。")
                await self.log("⚔️ 启动配对交易: [做空 A 资产] + [做多 B 资产]。静待恐慌情绪消散回归...")
                
            hist_a.append(price_a)
            hist_b.append(price_b)

# ==========================================
# 启动超级联合兵推 (沙盒引擎)
# ==========================================
async def main():
    logger.info("\n========== [V11 超限战扩军] 九大智能体联合推演 ==========")
    bus = EventBus()
    
    # 初始化九大特工
    sensor = SensorAgent(bus)
    AlphaAgent(bus)
    CritiqueAgent(bus)
    ExecutionAgent(bus)
    LLMSentimentAgent(bus)
    WhaleTrackerAgent(bus)
    ArbitrageAgent(bus)
    mm = MarketMakerAgent(bus)
    stat_arb = StatArbAgent(bus)
    
    logger.info("九大高阶特工入列！通讯链路加密建立。")
    logger.info("========================================================\n")
    
    # 启动异步任务组
    await asyncio.gather(
        sensor.start_patrol(),
        mm.start_market_making(),
        stat_arb.start_z_score_monitor()
    )

if __name__ == "__main__":
    asyncio.run(main())