import os
import json
import logging
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Dict, Any, Optional
import uvicorn

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

app = FastAPI()

# Global state for the environment
class EnvironmentState:
    def __init__(self):
        self.reset()

    def reset(self):
        self.step_count = 0
        self.current_observation = {
            "anomaly_score": 0.0,
            "verdict": "normal",
            "alerts": []
        }
        self.done = False
        self.info = {}
        logger.info("Environment reset")

    def step(self, action: Dict[str, Any]) -> Dict[str, Any]:
        """
        Process one step of the environment.
        action: dictionary containing e.g., {"packet_data": "..."}
        Returns: observation, reward, done, info
        """
        self.step_count += 1
        
        # --- REPLACE THIS WITH YOUR ACTUAL MAYONE DETECTION LOGIC ---
        # Here you would call your framework's functions.
        # For now, a dummy detection:
        packet_data = action.get("packet_data", "")
        if "malicious" in packet_data.lower() or "attack" in packet_data.lower():
            anomaly_score = 0.92
            verdict = "malicious"
            alerts = ["Potential C2 beacon detected"]
        else:
            anomaly_score = 0.12
            verdict = "normal"
            alerts = []
        
        observation = {
            "anomaly_score": anomaly_score,
            "verdict": verdict,
            "alerts": alerts,
            "step": self.step_count
        }
        reward = 1.0 if verdict == "malicious" else 0.0
        done = self.step_count >= 100  # optional max steps
        info = {"model": os.getenv("MODEL_NAME", "MayOne")}
        
        self.current_observation = observation
        self.done = done
        self.info = info
        
        logger.info(f"Step {self.step_count}: verdict={verdict}")
        return {
            "observation": observation,
            "reward": reward,
            "done": done,
            "info": info
        }
    
    def get_state(self) -> Dict[str, Any]:
        return {
            "step_count": self.step_count,
            "current_observation": self.current_observation,
            "done": self.done,
            "info": self.info
        }

# Initialize global environment
env = EnvironmentState()

# --- API Endpoints required by OpenEnv ---

class ResetRequest(BaseModel):
    config: Optional[Dict[str, Any]] = None

class StepRequest(BaseModel):
    action: Dict[str, Any]

@app.post("/reset")
async def reset_endpoint(request: ResetRequest = None):
    """Reset the environment to initial state."""
    env.reset()
    # Optionally apply config if provided
    if request and request.config:
        logger.info(f"Applying config: {request.config}")
    return {"status": "ok", "observation": env.current_observation}

@app.post("/step")
async def step_endpoint(request: StepRequest):
    """Take one step in the environment."""
    result = env.step(request.action)
    return result

@app.get("/state")
async def state_endpoint():
    """Get current state of the environment."""
    return env.get_state()

@app.get("/health")
async def health():
    return {"status": "alive"}

if __name__ == "__main__":
    port = int(os.getenv("PORT", 7860))
    uvicorn.run(app, host="0.0.0.0", port=port)