"""
Tool_OCR - FastAPI Application Entry Point (V2)
Main application setup with CORS, routes, and startup/shutdown events
"""

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from contextlib import asynccontextmanager
import logging
import signal
import sys
import asyncio
from pathlib import Path
from typing import Optional

from app.core.config import settings


# =============================================================================
# Section 6.1: Signal Handlers
# =============================================================================

# Flag to indicate graceful shutdown is in progress
_shutdown_requested = False
_shutdown_complete = asyncio.Event()

# Track active connections for draining
_active_connections = 0
_connection_lock = asyncio.Lock()


async def increment_connections():
    """Track active connection count"""
    global _active_connections
    async with _connection_lock:
        _active_connections += 1


async def decrement_connections():
    """Track active connection count"""
    global _active_connections
    async with _connection_lock:
        _active_connections -= 1


def get_active_connections() -> int:
    """Get current active connection count"""
    return _active_connections


def is_shutdown_requested() -> bool:
    """Check if graceful shutdown has been requested"""
    return _shutdown_requested


def _signal_handler(signum: int, frame) -> None:
    """
    Signal handler for SIGTERM and SIGINT.

    Initiates graceful shutdown by setting the shutdown flag.
    The actual cleanup is handled by the lifespan context manager.
    """
    global _shutdown_requested
    signal_name = signal.Signals(signum).name
    logger = logging.getLogger(__name__)

    if _shutdown_requested:
        logger.warning(f"Received {signal_name} again, forcing immediate exit...")
        sys.exit(1)

    logger.info(f"Received {signal_name}, initiating graceful shutdown...")
    _shutdown_requested = True

    # Try to stop the event loop gracefully
    try:
        loop = asyncio.get_event_loop()
        if loop.is_running():
            # Schedule shutdown event
            loop.call_soon_threadsafe(_shutdown_complete.set)
    except RuntimeError:
        pass  # No event loop running


def setup_signal_handlers():
    """
    Set up signal handlers for graceful shutdown.

    Handles:
    - SIGTERM: Standard termination signal (from systemd, docker, etc.)
    - SIGINT: Keyboard interrupt (Ctrl+C)
    """
    logger = logging.getLogger(__name__)

    try:
        # SIGTERM - Standard termination signal
        signal.signal(signal.SIGTERM, _signal_handler)
        logger.info("SIGTERM handler installed")

        # SIGINT - Keyboard interrupt
        signal.signal(signal.SIGINT, _signal_handler)
        logger.info("SIGINT handler installed")

    except (ValueError, OSError) as e:
        # Signal handling may not be available in all contexts
        logger.warning(f"Could not install signal handlers: {e}")

# Ensure log directory exists before configuring logging
Path(settings.log_file).parent.mkdir(parents=True, exist_ok=True)

# Configure logging - Force configuration to override uvicorn's settings
logging.basicConfig(
    level=getattr(logging, settings.log_level),
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    handlers=[
        logging.FileHandler(settings.log_file),
        logging.StreamHandler(),
    ],
    force=True  # Force reconfiguration (Python 3.8+)
)

# Also explicitly configure root logger and app loggers
root_logger = logging.getLogger()
root_logger.setLevel(getattr(logging, settings.log_level))

# Configure app-specific loggers
for logger_name in ['app', 'app.services', 'app.services.pdf_generator_service', 'app.services.ocr_service']:
    app_logger = logging.getLogger(logger_name)
    app_logger.setLevel(getattr(logging, settings.log_level))
    app_logger.propagate = True  # Ensure logs propagate to root logger

logger = logging.getLogger(__name__)


async def drain_connections(timeout: float = 30.0):
    """
    Wait for active connections to complete (connection draining).

    Args:
        timeout: Maximum time to wait for connections to drain
    """
    logger.info(f"Draining connections (timeout={timeout}s)...")
    start_time = asyncio.get_event_loop().time()

    while get_active_connections() > 0:
        elapsed = asyncio.get_event_loop().time() - start_time
        if elapsed >= timeout:
            logger.warning(
                f"Connection drain timeout after {timeout}s. "
                f"{get_active_connections()} connections still active."
            )
            break

        logger.info(f"Waiting for {get_active_connections()} active connections...")
        await asyncio.sleep(1.0)

    if get_active_connections() == 0:
        logger.info("All connections drained successfully")


@asynccontextmanager
async def lifespan(app: FastAPI):
    """Application lifespan events"""
    # Startup
    logger.info("Starting Tool_OCR V2 application...")

    # Set up signal handlers for graceful shutdown
    setup_signal_handlers()

    # Ensure all directories exist
    settings.ensure_directories()
    logger.info("All directories created/verified")

    # Initialize memory management if enabled
    if settings.enable_model_lifecycle_management:
        try:
            from app.services.memory_manager import get_model_manager, MemoryConfig

            memory_config = MemoryConfig(
                warning_threshold=settings.memory_warning_threshold,
                critical_threshold=settings.memory_critical_threshold,
                emergency_threshold=settings.memory_emergency_threshold,
                model_idle_timeout_seconds=settings.pp_structure_idle_timeout_seconds,
                memory_check_interval_seconds=settings.memory_check_interval_seconds,
                enable_auto_cleanup=settings.enable_memory_optimization,
                enable_emergency_cleanup=settings.enable_emergency_cleanup,
                max_concurrent_predictions=settings.max_concurrent_predictions,
                enable_cpu_fallback=settings.enable_cpu_fallback,
                gpu_memory_limit_mb=settings.gpu_memory_limit_mb,
            )
            get_model_manager(memory_config)
            logger.info("Memory management initialized")
        except Exception as e:
            logger.warning(f"Failed to initialize memory management: {e}")

    # Initialize service pool if enabled
    if settings.enable_service_pool:
        try:
            from app.services.service_pool import get_service_pool, PoolConfig

            pool_config = PoolConfig(
                max_services_per_device=settings.max_services_per_device,
                max_total_services=settings.max_total_services,
                acquire_timeout_seconds=settings.service_acquire_timeout_seconds,
                max_queue_size=settings.max_queue_size,
            )
            get_service_pool(pool_config)
            logger.info("OCR service pool initialized")
        except Exception as e:
            logger.warning(f"Failed to initialize service pool: {e}")

    # Initialize prediction semaphore for controlling concurrent PP-StructureV3 predictions
    try:
        from app.services.memory_manager import get_prediction_semaphore
        get_prediction_semaphore(max_concurrent=settings.max_concurrent_predictions)
        logger.info(f"Prediction semaphore initialized (max_concurrent={settings.max_concurrent_predictions})")
    except Exception as e:
        logger.warning(f"Failed to initialize prediction semaphore: {e}")

    # Initialize cleanup scheduler if enabled
    if settings.cleanup_enabled:
        try:
            from app.services.cleanup_scheduler import start_cleanup_scheduler
            await start_cleanup_scheduler()
            logger.info("Cleanup scheduler initialized")
        except Exception as e:
            logger.warning(f"Failed to initialize cleanup scheduler: {e}")

    logger.info("Application startup complete")

    yield

    # Shutdown
    logger.info("Shutting down Tool_OCR application...")

    # Stop cleanup scheduler
    if settings.cleanup_enabled:
        try:
            from app.services.cleanup_scheduler import stop_cleanup_scheduler
            await stop_cleanup_scheduler()
            logger.info("Cleanup scheduler stopped")
        except Exception as e:
            logger.warning(f"Error stopping cleanup scheduler: {e}")

    # Connection draining - wait for active requests to complete
    await drain_connections(timeout=30.0)

    # Shutdown recovery manager if initialized
    try:
        from app.services.memory_manager import shutdown_recovery_manager
        shutdown_recovery_manager()
        logger.info("Recovery manager shutdown complete")
    except Exception as e:
        logger.debug(f"Recovery manager shutdown skipped: {e}")

    # Shutdown service pool
    if settings.enable_service_pool:
        try:
            from app.services.service_pool import shutdown_service_pool
            shutdown_service_pool()
            logger.info("Service pool shutdown complete")
        except Exception as e:
            logger.warning(f"Error shutting down service pool: {e}")

    # Shutdown prediction semaphore
    try:
        from app.services.memory_manager import shutdown_prediction_semaphore
        shutdown_prediction_semaphore()
        logger.info("Prediction semaphore shutdown complete")
    except Exception as e:
        logger.warning(f"Error shutting down prediction semaphore: {e}")

    # Shutdown memory manager
    if settings.enable_model_lifecycle_management:
        try:
            from app.services.memory_manager import shutdown_model_manager
            shutdown_model_manager()
            logger.info("Memory manager shutdown complete")
        except Exception as e:
            logger.warning(f"Error shutting down memory manager: {e}")

    logger.info("Tool_OCR shutdown complete")


# Create FastAPI application
app = FastAPI(
    title="Tool_OCR V2",
    description="OCR Processing System with External Authentication & Task Isolation",
    version="2.0.0",
    lifespan=lifespan,
)

# Configure CORS
app.add_middleware(
    CORSMiddleware,
    allow_origins=settings.cors_origins_list,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


# Health check endpoint
@app.get("/health")
async def health_check():
    """Health check endpoint with GPU status and memory management info"""
    response = {
        "status": "healthy",
        "service": "Tool_OCR V2",
        "version": "2.0.0",
    }

    # Add GPU status information
    try:
        # Use service pool if available to avoid creating new instances
        gpu_status = None
        if settings.enable_service_pool:
            try:
                from app.services.service_pool import get_service_pool
                pool = get_service_pool()
                pool_stats = pool.get_pool_stats()
                response["service_pool"] = pool_stats

                # Get GPU status from first available service
                for device, services in pool.services.items():
                    for pooled in services:
                        if hasattr(pooled.service, 'get_gpu_status'):
                            gpu_status = pooled.service.get_gpu_status()
                            break
                    if gpu_status:
                        break
            except Exception as e:
                logger.debug(f"Could not get service pool stats: {e}")

        # Fallback: create temporary instance if no pool or no service available
        if gpu_status is None:
            from app.services.ocr_service import OCRService
            ocr_service = OCRService()
            gpu_status = ocr_service.get_gpu_status()

        response["gpu"] = {
            "available": gpu_status.get("gpu_available", False),
            "enabled": gpu_status.get("gpu_enabled", False),
            "device_name": gpu_status.get("device_name", "N/A"),
            "device_count": gpu_status.get("device_count", 0),
            "compute_capability": gpu_status.get("compute_capability", "N/A"),
        }

        # Add memory info if available
        if gpu_status.get("memory_total_mb"):
            response["gpu"]["memory"] = {
                "total_mb": round(gpu_status.get("memory_total_mb", 0), 2),
                "allocated_mb": round(gpu_status.get("memory_allocated_mb", 0), 2),
                "utilization_percent": round(gpu_status.get("memory_utilization", 0), 2),
            }

        # Add reason if GPU is not available
        if not gpu_status.get("gpu_available") and gpu_status.get("reason"):
            response["gpu"]["reason"] = gpu_status.get("reason")

    except Exception as e:
        logger.warning(f"Failed to get GPU status: {e}")
        response["gpu"] = {
            "available": False,
            "error": str(e),
        }

    # Add memory management status
    if settings.enable_model_lifecycle_management:
        try:
            from app.services.memory_manager import get_model_manager
            model_manager = get_model_manager()
            response["memory_management"] = model_manager.get_model_stats()
        except Exception as e:
            logger.debug(f"Could not get memory management stats: {e}")

    return response


# Root endpoint
@app.get("/")
async def root():
    """Root endpoint with API information"""
    return {
        "message": "Tool_OCR API V2 - External Authentication",
        "version": "2.0.0",
        "docs_url": "/docs",
        "health_check": "/health",
    }


# Include V2 API routers
from app.routers import auth, tasks, admin, translate
from fastapi import UploadFile, File, Depends, HTTPException, status
from sqlalchemy.orm import Session
import hashlib

from app.core.deps import get_db, get_current_user
from app.models.user import User
from app.models.task import TaskFile
from app.schemas.task import UploadResponse, TaskStatusEnum
from app.services.task_service import task_service

app.include_router(auth.router)
app.include_router(tasks.router)
app.include_router(admin.router)
app.include_router(translate.router)


# File upload endpoint
@app.post("/api/v2/upload", response_model=UploadResponse, tags=["Upload"], summary="Upload file for OCR")
async def upload_file(
    file: UploadFile = File(..., description="File to upload (PNG, JPG, PDF, etc.)"),
    db: Session = Depends(get_db),
    current_user: User = Depends(get_current_user)
):
    """
    Upload a file for OCR processing

    Creates a new task and uploads the file

    - **file**: File to upload
    """
    try:
        # Validate file extension
        file_ext = Path(file.filename).suffix.lower().lstrip('.')
        if file_ext not in settings.allowed_extensions_list:
            raise HTTPException(
                status_code=status.HTTP_400_BAD_REQUEST,
                detail=f"File type .{file_ext} not allowed. Allowed types: {', '.join(settings.allowed_extensions_list)}"
            )

        # Read file content
        file_content = await file.read()
        file_size = len(file_content)

        # Calculate file hash
        file_hash = hashlib.sha256(file_content).hexdigest()

        # Create task
        task = task_service.create_task(
            db=db,
            user_id=current_user.id,
            filename=file.filename,
            file_type=file.content_type
        )

        # Save file to disk
        upload_dir = Path(settings.upload_dir)
        upload_dir.mkdir(parents=True, exist_ok=True)

        # Create unique filename using task_id
        unique_filename = f"{task.task_id}_{file.filename}"
        file_path = upload_dir / unique_filename

        # Write file
        with open(file_path, "wb") as f:
            f.write(file_content)

        # Create TaskFile record
        task_file = TaskFile(
            task_id=task.id,
            original_name=file.filename,
            stored_path=str(file_path),
            file_size=file_size,
            mime_type=file.content_type,
            file_hash=file_hash
        )
        db.add(task_file)
        db.commit()

        logger.info(f"Uploaded file {file.filename} ({file_size} bytes) for task {task.task_id}, user {current_user.email}")

        return {
            "task_id": task.task_id,
            "filename": file.filename,
            "file_size": file_size,
            "file_type": file.content_type or "application/octet-stream",
            "status": TaskStatusEnum.PENDING
        }

    except HTTPException:
        raise
    except Exception as e:
        logger.exception(f"Failed to upload file for user {current_user.id}")
        raise HTTPException(
            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
            detail=f"Failed to upload file: {str(e)}"
        )


if __name__ == "__main__":
    import uvicorn

    uvicorn.run(
        "app.main:app",
        host="0.0.0.0",
        port=settings.backend_port,
        reload=True,
        log_level=settings.log_level.lower(),
    )