import json
import os
from fastapi import FastAPI
import uvicorn
from engine.risk_engine import VertexRiskEngine
from engine.semantic import VertexSemanticAgent
from engine.web3_engine import VertexWeb3Engine

app = FastAPI()

# Archivo de persistencia de la watchlist
WATCHLIST_FILE = "app/watchlist.json"

@app.get("/batch_audit")
def run_batch_audit():
    """Audita toda la watchlist y devuelve alertas para n8n."""
    if not os.path.exists(WATCHLIST_FILE):
        return {"error": "Watchlist file not found", "alerts": []}

    try:
        with open(WATCHLIST_FILE, "r") as f:
            watchlist = json.load(f)
    except Exception as e:
        return {"error": f"Failed to read watchlist: {e}", "alerts": []}

    results = []
    for ticker in watchlist:
        try:
            # Reutilizamos la lógica del motor Némesis
            engine = VertexRiskEngine(ticker.upper())
            num_res = engine.run_audit()
            
            sem_agent = VertexSemanticAgent(ticker.upper())
            risk_text = sem_agent.get_sec_risk_factors()
            sem_res = sem_agent.judge_risks(risk_text)

            # Blindaje de tipos para evitar errores de comparación
            z_score = float(num_res.get('altman_z', 0.0))
            m_dsri = float(num_res.get('m_score_dsri', 0.0))
            s_score = float(sem_res.get('semantic_score', 0.0))

            # Lógica de Semáforo de Riesgo
            if z_score < 1.8 or m_dsri > 1.4 or s_score > 3:
                status = "RED"
            elif z_score < 3.0:
                status = "YELLOW"
            else:
                status = "GREEN"

            results.append({
                "ticker": ticker,
                "status": status,
                "z_score": z_score,
                "summary": sem_res.get("summary", ""),
                "alert": True if status == "RED" else False
            })
        except Exception as ticker_error:
            results.append({"ticker": ticker, "status": "ERROR", "msg": str(ticker_error)})

    critical_alerts = [r for r in results if r.get("status") in ["RED", "YELLOW"]]
    return {
        "total_analyzed": len(watchlist),
        "critical_count": len(critical_alerts),
        "alerts": critical_alerts,
        "full_results": results
    }

@app.get("/audit/{ticker}")
def audit_company(ticker: str):
    """Auditoría individual para el tab de Stock Audit."""
    try:
        engine = VertexRiskEngine(ticker.upper())
        num_res = engine.run_audit()
        
        sem_agent = VertexSemanticAgent(ticker.upper())
        risk_text = sem_agent.get_sec_risk_factors()
        sem_res = sem_agent.judge_risks(risk_text)

        # Blindaje de tipos
        z_score = float(num_res.get('altman_z', 0.0))
        m_dsri = float(num_res.get('m_score_dsri', 0.0))
        s_score = float(sem_res.get('semantic_score', 0.0))

        if z_score < 1.8 or m_dsri > 1.4 or s_score > 3:
            status = "RED"
            msg = "CRITICAL RISK: Red flags detected."
        elif z_score < 3.0:
            status = "YELLOW"
            msg = "CAUTION: Monitor closely."
        else:
            status = "GREEN"
            msg = "SAFE: Solid fundamentals."

        return {
            "ticker": ticker.upper(),
            "status": status,
            "numeric_analysis": {"altman_z": z_score, "m_score_dsri": m_dsri},
            "semantic_analysis": sem_res,
            "msg": msg
        }
    except Exception as e:
        return {"status": "ERROR", "msg": str(e)}

@app.get("/audit_contract/{address}")
def audit_smart_contract(address: str):
    """Auditoría de Web3 usando el nuevo motor V2."""
    try:
        web3_engine = VertexWeb3Engine(address)
        audit_res = web3_engine.get_contract_source()
        
        if not audit_res["success"]:
            return {"status": "ERROR", "msg": audit_res["error"]}
        
        source = audit_res["source_code"]
        vulnerabilities = web3_engine.scan_basic_vulnerabilities(source)
        
        return {
            "address": address,
            "status": "DANGER" if len(vulnerabilities) > 0 else "SAFE",
            "vulnerabilities": vulnerabilities,
            "source_preview": source[:500] + "..." # Ahora source es string y el slice no falla
        }
    except Exception as e:
        return {"status": "ERROR", "msg": str(e)}

@app.get("/get_settings")
async def get_settings():
    # Esta línea es la que saca las llaves de los Secrets de Hugging Face
    token = os.environ.get("BOT_TOKEN", "")
    chat = os.environ.get("CHAT_ID", "")
    
    if token and chat:
        return {"bot_token": token, "chat_id": chat, "status": "loaded_from_secrets"}
    
    return {"bot_token": "", "chat_id": "", "status": "secrets_not_found"}

if __name__ == "__main__":
    # Hugging Face SIEMPRE usa el puerto 7860 internamente
    port = int(os.environ.get("PORT", 7860))
    # Importante: host="0.0.0.0" para que sea accesible desde fuera del contenedor
    uvicorn.run(app, host="0.0.0.0", port=port)