BrainsteelFin/agents/audit.py

"""
BrainSteel Fin — Audit Agent (v2)
5-Pillar Compliance Auditor
Reviews pipeline against all 5 analysis pillars.
"""
import os, json, requests
from datetime import datetime

class AuditAgent:
    def __init__(self):
        self.name = "Audit"

    def audit_pipeline(self, brief_data, decio_data, papert_data):
        checks = []

        # Check 1: Brief delivered all 3 required points
        briefing = brief_data.get("briefing_for_decio", "")
        has_price = "BTC $" in briefing or "$" in briefing
        has_change = any(x in briefing for x in ["4h:", "24h:", "+", "-"])
        has_sr = "Sup:" in briefing and "Res:" in briefing
        checks.append({
            "check": "Brief 3 pontos",
            "passed": has_price and has_change and has_sr,
            "detail": f"price={has_price} change={has_change} sr={has_sr}"
        })

        # Check 2: Brief signal was computed correctly
        brief_conf = brief_data.get("confidence", 0)
        brief_signal = brief_data.get("signal", "NEUTRO")
        has_rsi = brief_data.get("rsi") is not None
        has_fg = brief_data.get("fear_greed") is not None
        checks.append({
            "check": "Brief pillars completos",
            "passed": has_rsi and has_fg,
            "detail": f"RSI={brief_data.get('rsi')} F&G={brief_data.get('fear_greed')} news={brief_data.get('news_sentiment','?')}"
        })

        # Check 3: Decio respected 75% rule
        decio_action = decio_data.get("action", "HOLD")
        decio_conf = decio_data.get("confidence", 0)
        sl = decio_data.get("stop_loss", 0)
        tp = decio_data.get("take_profit", 0)

        respected_75 = True
        if decio_conf < 75 and decio_action != "HOLD":
            respected_75 = False
        checks.append({
            "check": "Decio regra 75%",
            "passed": respected_75,
            "detail": f"conf={decio_conf}% action={decio_action}"
        })

        # Check 4: Decio SL/TP correct if BUY/SELL
        price = brief_data.get("price", 0)
        if decio_action in ("BUY", "SELL"):
            sl_correct = (decio_action == "BUY" and abs(sl - price * 0.98) < price * 0.01) or \
                        (decio_action == "SELL" and abs(sl - price * 1.02) < price * 0.01)
            tp_correct = (decio_action == "BUY" and abs(tp - price * 1.05) < price * 0.01) or \
                        (decio_action == "SELL" and abs(tp - price * 0.95) < price * 0.01)
        else:
            sl_correct = (sl == 0 and tp == 0)
        checks.append({
            "check": "Decio SL/TP 2%/5%",
            "passed": sl_correct,
            "detail": f"SL=${sl} TP=${tp} price=${price}"
        })

        # Check 5: PaperT logged correctly
        papert_logged = papert_data.get("log_appended", False)
        papert_status = papert_data.get("status", "")
        checks.append({
            "check": "PaperT executou log",
            "passed": papert_logged and papert_status == "validated",
            "detail": f"logged={papert_logged} status={papert_status}"
        })

        # Check 6: Portfolio updated if BUY/SELL
        portfolio = papert_data.get("portfolio", {})
        if decio_action in ("BUY", "SELL"):
            pf_updated = portfolio.get("total_trades", 0) > 0
        else:
            pf_updated = True  # No trade = no portfolio change needed
        checks.append({
            "check": "Portfolio atualizado",
            "passed": pf_updated,
            "detail": f"trades={portfolio.get('total_trades',0)} balance=${portfolio.get('current_balance','?')}"
        })

        # Score
        passed_count = sum(1 for c in checks if c["passed"])
        total = len(checks)
        score = round(passed_count / total * 100, 1)

        # Signal quality assessment
        net = brief_data.get("net_signal", 0)
        bullish = brief_data.get("bullish_signals", 0)
        bearish = brief_data.get("bearish_signals", 0)
        rsi = brief_data.get("rsi", 50)

        quality_notes = []
        if rsi > 70: quality_notes.append("RSI overbought — cautela")
        if rsi < 30: quality_notes.append("RSI oversold — oportunidade")
        if net > 2: quality_notes.append(f"Sinal bullish forte (net={net})")
        if net < -2: quality_notes.append(f"Sinal bearish forte (net={net})")
        if decio_action == "HOLD" and brief_data.get("confidence", 0) < 75:
            quality_notes.append("HOLD correto — confiança baixa preservou capital")

        return {
            "audit_id": f"AUD-{datetime.now().strftime('%Y%m%d%H%M%S')}",
            "timestamp": datetime.now().isoformat(),
            "checks": checks,
            "compliance_score": score,
            "status": "approved" if score >= 83 else "flagged" if score >= 66 else "rejected",
            "passed_count": passed_count,
            "total_checks": total,
            "quality_notes": quality_notes,
            "brief_summary": brief_data.get("summary", "")[:100],
            "decio_decision": decio_action,
            "decio_confidence": decio_conf,
            "portfolio_balance": portfolio.get("current_balance", 0),
            "portfolio_pnl": portfolio.get("total_pnl", 0),
            "portfolio_pnl_pct": portfolio.get("total_pnl_pct", 0),
        }

    def generate_llm_report(self, brief_data, decio_data):
        if not os.getenv("PAPERT_API_KEY") and not os.getenv("OPENROUTER_API_KEY", ""):
            return {"report": "OpenRouter key not available", "status": "local_only"}
        try:
            prompt = f"""Você é o Audit, auditor de compliance da BrainSteel Fin.
Gere um relatório de auditoria em português，分析昨日操作质量:

Brief: {brief_data.get('summary','N/A')}
Signal: {brief_data.get('signal','?')} ({brief_data.get('confidence','?')}% conf)
RSI: {brief_data.get('rsi','?')} | F&G: {brief_data.get('fear_greed_class','?')}
Bullish signals: {brief_data.get('bullish_signals',0)} | Bearish: {brief_data.get('bearish_signals',0)}

Decio: {decio_data.get('action','?')} conf {decio_data.get('confidence','?')}%
Justification: {decio_data.get('justification','?')[:100]}

Responda em JSON:
{{"verdict": "APROVADO|REPROVADO|FLAG",
  "risks": ["risk1","risk2"],
  "recommendations": ["rec1","rec2"],
  "score": 0-100,
  "summary_pt": "resumo em português"}}
"""
            headers = {
                "Authorization": "Bearer " + (os.getenv("PAPERT_API_KEY") or os.getenv("OPENROUTER_API_KEY", "")),
                "Content-Type": "application/json",
                "HTTP-Referer": "https://brainsteel.fin",
                "X-Title": "BrainSteel Fin"
            }
            r = requests.post(
                "https://openrouter.ai/api/v1/chat/completions",
                json={"model": "deepseek/deepseek-v4-flash:free", "messages": [{"role": "user", "content": prompt}], "max_tokens": 400},
                headers=headers, timeout=30
            )
            if r.status_code == 200:
                resp_data = r.json()
                content = resp_data["choices"][0]["message"]["content"]
                usage = resp_data.get("usage", {})
                if usage:
                    try:
                        from agents.token_tracker import log_tokens
                        log_tokens("Audit", "deepseek/deepseek-v4-flash:free", usage)
                    except:
                        pass
                content = content.strip("` \n")
                if content.startswith("json"): content = content[4:]
                return {"report": content, "status": "generated"}
        except:
            pass
        return {"report": "Audit local", "status": "error"}