"""
Foxhunt RunPod Workflow Module

Production-ready Python module for deploying and monitoring ML training on RunPod GPU infrastructure.

Features:
- Pod deployment via REST API with datacenter filtering
- S3-based log monitoring (NO SSH required)
- Automatic pod termination on training completion
- Progress tracking with rich output
- Retry logic with exponential backoff
- Comprehensive error handling

Usage:
    from foxhunt_runpod import RunPodClient, PodMonitor, S3Client

    # Deploy pod
    client = RunPodClient()
    pod = client.deploy_pod(gpu_type="RTX A4000", command="--epochs 50")

    # Monitor training
    monitor = PodMonitor(pod['id'])
    monitor.wait_until_running(timeout=300)
    monitor.stream_s3_logs(follow=True)

    # Auto-terminate on completion
    monitor.auto_terminate()
"""

from .client import RunPodClient
from .monitor import PodMonitor
from .s3_client import S3Client
from .config import RunPodConfig
from .errors import (
    RunPodError,
    PodDeploymentError,
    PodNotFoundError,
    S3Error,
    ConfigurationError,
)

__version__ = "1.0.0"
__all__ = [
    "RunPodClient",
    "PodMonitor",
    "S3Client",
    "RunPodConfig",
    "RunPodError",
    "PodDeploymentError",
    "PodNotFoundError",
    "S3Error",
    "ConfigurationError",
]