"""Video generation interface for AIX.

Generate videos from text descriptions or images.

Note: Video generation support varies by provider and may require additional
API keys and configuration. This module provides a unified interface but
implementation depends on available providers.

Examples:
    Text to video:
    >>> from aix.video import generate_video
    >>> video = generate_video(
    ...     "A cat walking through a garden",
    ...     duration=5
    ... )  # doctest: +SKIP
    >>> video.save("cat_video.mp4")  # doctest: +SKIP

    Image to video:
    >>> video = animate_image(
    ...     "static_image.jpg",
    ...     prompt="Make the clouds move gently"
    ... )  # doctest: +SKIP
"""

from collections.abc import Iterable
from typing import Union
from pathlib import Path
import time


class GeneratedVideo:
    """Wrapper for generated videos.

    Provides convenient access to video data and metadata.

    Examples:
        >>> video = GeneratedVideo(url="https://...")  # doctest: +SKIP
        >>> video.save("output.mp4")  # doctest: +SKIP
        >>> print(video.duration)  # doctest: +SKIP
        5.0
    """

    def __init__(
        self,
        url: str = None,
        data: bytes = None,
        model: str = None,
        prompt: str = None,
        duration: float = None,
        resolution: str = None,
        status: str = "completed",
        task_id: str = None,
    ):
        """Initialize generated video.

        Args:
            url: URL of the generated video
            data: Video data as bytes
            model: Model used for generation
            prompt: Original prompt
            duration: Video duration in seconds
            resolution: Video resolution (e.g., '1920x1080', '1280x720')
            status: Generation status ('pending', 'processing', 'completed', 'failed')
            task_id: Async task ID if generation is in progress
        """
        self.url = url
        self.data = data
        self.model = model
        self.prompt = prompt
        self.duration = duration
        self.resolution = resolution
        self.status = status
        self.task_id = task_id
        self._video_data = None

    def as_bytes(self) -> bytes:
        """Get video as bytes.

        Returns:
            Video data as bytes
        """
        if self._video_data is not None:
            return self._video_data

        if self.data:
            return self.data

        if self.url:
            import requests

            response = requests.get(self.url)
            response.raise_for_status()
            self._video_data = response.content
            return self._video_data

        raise ValueError("No video data available")

    def save(self, path: Union[str, Path]):
        """Save video to file.

        Args:
            path: Output file path

        Examples:
            >>> video.save("output.mp4")  # doctest: +SKIP
        """
        path = Path(path)
        video_bytes = self.as_bytes()

        with open(path, "wb") as f:
            f.write(video_bytes)

    def wait_until_complete(self, max_wait: int = 300, poll_interval: int = 5):
        """Wait for video generation to complete (for async operations).

        Args:
            max_wait: Maximum time to wait in seconds
            poll_interval: Time between status checks in seconds

        Raises:
            TimeoutError: If generation doesn't complete within max_wait
            RuntimeError: If generation fails
        """
        if self.status == "completed":
            return

        if not self.task_id:
            raise ValueError("No task_id available for status checking")

        start_time = time.time()

        while time.time() - start_time < max_wait:
            # This would need provider-specific implementation
            # For now, this is a placeholder
            time.sleep(poll_interval)

            # Check status (provider-specific)
            # self._check_status()

            if self.status == "completed":
                return
            elif self.status == "failed":
                raise RuntimeError("Video generation failed")

        raise TimeoutError(
            f"Video generation did not complete within {max_wait} seconds"
        )

    def __repr__(self) -> str:
        """String representation."""
        return (
            f"GeneratedVideo(model={self.model}, "
            f"duration={self.duration}s, status={self.status})"
        )


def generate_video(
    prompt: str,
    *,
    model: str = None,
    duration: float = 5.0,
    resolution: str = "1280x720",
    fps: int = 24,
    aspect_ratio: str = None,
    style: str = None,
    seed: int = None,
    **kwargs,
) -> GeneratedVideo:
    """Generate a video from a text prompt.

    Note: This is a high-level interface. Actual implementation depends on
    available video generation providers (Runway, Pika, etc.) and may require
    provider-specific API keys.

    Args:
        prompt: Text description of the video to generate
        model: Video generation model to use
        duration: Video duration in seconds (typically 2-10 seconds)
        resolution: Video resolution ('1280x720', '1920x1080', etc.)
        fps: Frames per second
        aspect_ratio: Aspect ratio ('16:9', '9:16', '1:1', etc.)
        style: Video style hint (provider-specific)
        seed: Random seed for reproducibility
        **kwargs: Additional provider-specific parameters

    Returns:
        GeneratedVideo object

    Raises:
        NotImplementedError: If no video provider is configured
        ImportError: If required provider SDK is not installed

    Examples:
        >>> from aix.video import generate_video
        >>> video = generate_video(
        ...     "A serene ocean sunset with gentle waves",
        ...     duration=5,
        ...     resolution="1920x1080"
        ... )  # doctest: +SKIP
        >>> video.save("sunset.mp4")  # doctest: +SKIP

        >>> # Specific style
        >>> video = generate_video(
        ...     "A futuristic city",
        ...     style="cyberpunk",
        ...     duration=4
        ... )  # doctest: +SKIP
    """
    # This is a placeholder implementation
    # In practice, you would integrate with specific providers

    raise NotImplementedError(
        "Video generation requires additional provider configuration. "
        "Supported providers include Runway, Pika, and others. "
        "Please configure your provider API keys and try again.\n\n"
        "Example configuration:\n"
        "  export RUNWAY_API_KEY=your-key\n"
        "  export PIKA_API_KEY=your-key\n\n"
        "Or use provider-specific functions:\n"
        "  from aix.video import generate_video_runway\n"
        "  video = generate_video_runway(prompt, ...)"
    )


def animate_image(
    image_path: Union[str, Path],
    prompt: str = None,
    *,
    model: str = None,
    duration: float = 3.0,
    motion_strength: float = 0.5,
    **kwargs,
) -> GeneratedVideo:
    """Animate a static image into a video.

    Args:
        image_path: Path to the source image
        prompt: Optional text prompt to guide the animation
        model: Video generation model to use
        duration: Animation duration in seconds
        motion_strength: Strength of motion (0.0 to 1.0)
        **kwargs: Additional provider-specific parameters

    Returns:
        GeneratedVideo object

    Examples:
        >>> from aix.video import animate_image
        >>> video = animate_image(
        ...     "landscape.jpg",
        ...     prompt="Gentle camera pan across the scene",
        ...     duration=4
        ... )  # doctest: +SKIP
        >>> video.save("animated_landscape.mp4")  # doctest: +SKIP
    """
    raise NotImplementedError(
        "Image-to-video animation requires additional provider configuration. "
        "See generate_video() documentation for setup instructions."
    )


def extend_video(
    video_path: Union[str, Path],
    prompt: str = None,
    *,
    extend_duration: float = 2.0,
    model: str = None,
    **kwargs,
) -> GeneratedVideo:
    """Extend an existing video with additional generated content.

    Args:
        video_path: Path to the source video
        prompt: Optional text prompt to guide the extension
        extend_duration: How many seconds to add
        model: Video generation model
        **kwargs: Additional provider-specific parameters

    Returns:
        GeneratedVideo object with extended content

    Examples:
        >>> from aix.video import extend_video
        >>> extended = extend_video(
        ...     "original.mp4",
        ...     prompt="Continue the same scene",
        ...     extend_duration=3
        ... )  # doctest: +SKIP
    """
    raise NotImplementedError(
        "Video extension requires additional provider configuration. "
        "See generate_video() documentation for setup instructions."
    )


def interpolate_frames(
    video_path: Union[str, Path], *, target_fps: int = 60, model: str = None, **kwargs
) -> GeneratedVideo:
    """Interpolate frames to create smoother video.

    Args:
        video_path: Path to the source video
        target_fps: Target frames per second
        model: Frame interpolation model
        **kwargs: Additional provider-specific parameters

    Returns:
        GeneratedVideo with interpolated frames

    Examples:
        >>> from aix.video import interpolate_frames
        >>> smooth_video = interpolate_frames(
        ...     "choppy.mp4",
        ...     target_fps=60
        ... )  # doctest: +SKIP
    """
    raise NotImplementedError(
        "Frame interpolation requires additional libraries. "
        "Consider using tools like RIFE or DAIN for frame interpolation."
    )


# Provider-specific implementations (placeholders for future implementation)


def generate_video_runway(
    prompt: str, *, duration: float = 5.0, **kwargs
) -> GeneratedVideo:
    """Generate video using Runway ML.

    Requires: RUNWAY_API_KEY environment variable

    Args:
        prompt: Text description
        duration: Video duration
        **kwargs: Runway-specific parameters

    Returns:
        GeneratedVideo object
    """
    raise NotImplementedError(
        "Runway integration coming soon. "
        "Set RUNWAY_API_KEY and install: pip install runwayml"
    )


def generate_video_pika(
    prompt: str, *, duration: float = 3.0, **kwargs
) -> GeneratedVideo:
    """Generate video using Pika Labs.

    Requires: PIKA_API_KEY environment variable

    Args:
        prompt: Text description
        duration: Video duration
        **kwargs: Pika-specific parameters

    Returns:
        GeneratedVideo object
    """
    raise NotImplementedError(
        "Pika Labs integration coming soon. " "Set PIKA_API_KEY environment variable."
    )


def generate_video_stable_diffusion(
    prompt: str, *, duration: float = 2.0, **kwargs
) -> GeneratedVideo:
    """Generate video using Stable Diffusion Video.

    Requires: Stable Diffusion Video model setup

    Args:
        prompt: Text description
        duration: Video duration
        **kwargs: SD-specific parameters

    Returns:
        GeneratedVideo object
    """
    raise NotImplementedError(
        "Stable Diffusion Video integration coming soon. "
        "Install: pip install diffusers torch"
    )


# Utility functions


def get_available_providers() -> list[str]:
    """Get list of available video generation providers.

    Returns:
        List of provider names that are configured

    Examples:
        >>> from aix.video import get_available_providers
        >>> providers = get_available_providers()  # doctest: +SKIP
        >>> print(providers)  # doctest: +SKIP
        ['runway', 'pika']
    """
    available = []

    # Check for Runway
    import os

    if os.getenv("RUNWAY_API_KEY"):
        available.append("runway")

    # Check for Pika
    if os.getenv("PIKA_API_KEY"):
        available.append("pika")

    # Check for Stable Diffusion
    try:
        import diffusers

        available.append("stable-diffusion")
    except ImportError:
        pass

    return available


def estimate_cost(
    duration: float, resolution: str = "1280x720", provider: str = None
) -> dict:
    """Estimate the cost of video generation.

    Args:
        duration: Video duration in seconds
        resolution: Video resolution
        provider: Provider name (or None for all)

    Returns:
        Dict with cost estimates

    Examples:
        >>> from aix.video import estimate_cost
        >>> cost = estimate_cost(duration=5, resolution="1920x1080")  # doctest: +SKIP
        >>> print(cost)  # doctest: +SKIP
        {'runway': 0.05, 'pika': 0.03}
    """
    # Placeholder cost estimates (not real pricing)
    estimates = {}

    if provider is None or provider == "runway":
        # Rough estimate based on typical pricing
        estimates["runway"] = duration * 0.01  # $0.01 per second

    if provider is None or provider == "pika":
        estimates["pika"] = duration * 0.006  # $0.006 per second

    return estimates
