backend/queue/consumer.py

"""
Evaluation Worker / Consumer for Job Queue

Provides worker functionality for processing evaluation jobs from the queue.
Handles job execution, checkpointing, and progress reporting.
"""

import asyncio
import os
import socket
import uuid
from dataclasses import dataclass
from datetime import datetime
from typing import Optional

from backend.core.config import settings
from backend.logging.logger import get_logger

from .job_schema import (
    JobProgressUpdate,
    JobStatus,
    EvaluationJob,
)
from .producer import _job_queue, get_job_producer
from .status_tracker import get_status_tracker


logger = get_logger("queue.consumer", component="queue")


@dataclass
class WorkerConfig:
    """Configuration for evaluation worker."""
    worker_id: str
    max_concurrent_jobs: int = 1
    job_timeout_seconds: int = 3600
    heartbeat_interval_seconds: int = 30
    enable_checkpointing: bool = True


class EvaluationWorker:
    """
    Worker that processes evaluation jobs from the queue.
    
    Responsibilities:
    - Poll queue for new jobs
    - Execute evaluation jobs
    - Handle checkpointing
    - Report progress
    - Manage job lifecycle
    """
    
    def __init__(self, config: Optional[WorkerConfig] = None):
        self.config = config or WorkerConfig(
            worker_id=f"worker-{socket.gethostname()}-{os.getpid()}",
        )
        self._status_tracker = get_status_tracker()
        self._producer = get_job_producer()
        self._active_jobs: dict[uuid.UUID, asyncio.Task] = {}
        self._running = False
        self._current_job: Optional[EvaluationJob] = None
    
    async def start(self) -> None:
        """Start the worker."""
        self._running = True
        logger.info(
            "Worker started",
            worker_id=self.config.worker_id,
            max_concurrent=self.config.max_concurrent_jobs,
        )
        
        while self._running:
            try:
                # Poll for jobs
                await self._poll_and_process()
                
                # Brief sleep to prevent CPU spinning
                await asyncio.sleep(1)
                
            except asyncio.CancelledError:
                logger.info("Worker cancelled", worker_id=self.config.worker_id)
                break
            except Exception as e:
                logger.error(
                    "Worker error",
                    worker_id=self.config.worker_id,
                    error=str(e),
                )
                await asyncio.sleep(5)
        
        # Cancel active jobs
        for job_id, task in self._active_jobs.items():
            if not task.done():
                task.cancel()
                logger.info("Cancelled active job", job_id=str(job_id))
        
        logger.info("Worker stopped", worker_id=self.config.worker_id)
    
    async def stop(self) -> None:
        """Stop the worker."""
        self._running = False
    
    async def _poll_and_process(self) -> None:
        """Poll queue and process available jobs."""
        # Check if we can accept more jobs
        if len(self._active_jobs) >= self.config.max_concurrent_jobs:
            return
        
        # Find a queued job
        for job in _job_queue:
            if job.status == JobStatus.QUEUED:
                # Check if already being processed
                if job.job_id in self._active_jobs:
                    continue
                
                # Start processing the job
                await self._process_job(job)
                break
    
    async def _process_job(self, job: EvaluationJob) -> None:
        """Process a single evaluation job."""
        job_id_str = str(job.job_id)
        
        try:
            # Mark job as started
            self._current_job = job
            await self._status_tracker.start_job(job.job_id, self.config.worker_id)
            job.status = JobStatus.RUNNING
            job.started_at = datetime.utcnow()
            
            logger.info(
                "Processing job",
                job_id=job_id_str,
                worker_id=self.config.worker_id,
                model=job.model_name,
            )
            
            # Create task for async processing
            task = asyncio.create_task(self._execute_job(job))
            self._active_jobs[job.job_id] = task
            
            # Wait for completion
            await task
            
            # Job completed successfully
            logger.info(
                "Job completed",
                job_id=job_id_str,
                worker_id=self.config.worker_id,
            )
            
        except asyncio.CancelledError:
            logger.info("Job cancelled", job_id=job_id_str)
            await self._status_tracker.fail_job(
                job.job_id,
                "Job cancelled by worker",
            )
        except Exception as e:
            logger.error(
                "Job failed",
                job_id=job_id_str,
                error=str(e),
            )
            await self._status_tracker.fail_job(
                job.job_id,
                str(e),
            )
        finally:
            # Clean up
            self._active_jobs.pop(job.job_id, None)
            self._current_job = None
            
            # Remove from queue
            _job_queue[:] = [j for j in _job_queue if j.job_id != job.job_id]
    
    async def _execute_job(self, job: EvaluationJob) -> None:
        """Execute the evaluation job."""
        # Import orchestrator here to avoid circular imports
        from backend.core.orchestrator import (
            EvaluationInput,
            EvaluationOrchestrator,
        )
        
        # Get metadata
        metadata = job.metadata or {}
        mutation_depth = metadata.get("mutation_depth", 2)
        attack_types = metadata.get("attack_types", ["jailbreak"])
        max_concurrency = metadata.get("max_concurrency", 4)
        
        # Create evaluation input
        eval_input = EvaluationInput(
            model_name=job.model_name,
            model_version=job.model_version,
            dataset_name=job.dataset_name,
            dataset_version=job.dataset_version,
            mutation_depth=mutation_depth,
            attack_types=attack_types,
            max_concurrency=max_concurrency,
        )
        
        # Create orchestrator
        orchestrator = EvaluationOrchestrator()
        
        # Track progress for checkpointing
        checkpoint_interval = job.checkpoint_interval
        completed_samples = 0
        failed_samples = 0
        
        # For checkpointing - we need to hook into the orchestrator
        # This is a simplified version - in production, you'd have more sophisticated checkpointing
        
        # Run evaluation
        output = await orchestrator.start_run(eval_input)
        
        # Wait for completion (the orchestrator runs asynchronously)
        # In a real implementation, we'd need to track progress periodically
        
        # Mark job as complete
        await self._status_tracker.complete_job(
            job.job_id,
            output.composite_score,
            output.metrics,
        )
        
        job.status = JobStatus.COMPLETED
        job.completed_at = datetime.utcnow()
        job.composite_score = output.composite_score
        job.metrics = output.metrics
        job.progress = 100.0
        
        # Update total/completed samples
        if output.metrics:
            job.total_samples = output.metrics.get("total_samples", 0)
            job.completed_samples = output.metrics.get("successful_samples", 0)
            job.failed_samples = output.metrics.get("failed_samples", 0)
    
    async def get_current_job_status(self) -> Optional[dict]:
        """Get status of current job being processed."""
        if self._current_job is None:
            return None
        
        job = self._current_job
        return {
            "job_id": str(job.job_id),
            "status": job.status.value,
            "progress": job.progress,
            "completed_samples": job.completed_samples,
            "total_samples": job.total_samples,
        }
    
    def get_worker_status(self) -> dict:
        """Get worker status."""
        return {
            "worker_id": self.config.worker_id,
            "running": self._running,
            "active_jobs": len(self._active_jobs),
            "max_concurrent_jobs": self.config.max_concurrent_jobs,
        }


# Global worker instance
_worker: Optional[EvaluationWorker] = None


def get_worker(config: Optional[WorkerConfig] = None) -> EvaluationWorker:
    """Get the global worker instance."""
    global _worker
    if _worker is None:
        _worker = EvaluationWorker(config)
    return _worker


async def start_worker() -> EvaluationWorker:
    """Start the worker and return it."""
    worker = get_worker()
    asyncio.create_task(worker.start())
    return worker


async def stop_worker() -> None:
    """Stop the worker."""
    global _worker
    if _worker is not None:
        await _worker.stop()
        _worker = None


__all__ = [
    "WorkerConfig",
    "EvaluationWorker",
    "get_worker",
    "start_worker",
    "stop_worker",
]