from pathlib import Path
from typing import Any, Dict

from app.backends.base import BaseVideoBackend
from app.utils.ffmpeg_utils import extract_first_frame, frames_to_video
from app.utils.files import TASK_FIRST_FRAME_NAME, TASK_VIDEO_NAME
from app.utils.image_utils import make_dummy_frame


class LTXBackend(BaseVideoBackend):
    backend_name = "ltx_backend"
    model_name = "LTX-Video"

    def __init__(self, model_dir: Path):
        self.model_dir = model_dir
        self._loaded = False
        self._pipeline = None

    def load(self) -> None:
        if self._loaded:
            return
        # TODO: Replace with real LTX loading, e.g. DiffusionPipeline.from_pretrained(...)
        self.model_dir.mkdir(parents=True, exist_ok=True)
        self._pipeline = "ltx_pipeline_placeholder"
        self._loaded = True

    def is_loaded(self) -> bool:
        return self._loaded

    def generate(self, task_id: str, request_data: Dict[str, Any], output_dir: str) -> Dict[str, str]:
        self.load()
        output = Path(output_dir)
        frames_dir = output / "frames"
        frames_dir.mkdir(parents=True, exist_ok=True)

        duration = int(request_data["duration_sec"])
        fps = int(request_data["fps"])
        width = int(request_data["width"])
        height = int(request_data["height"])
        prompt = request_data["prompt"]

        total_frames = duration * fps
        for i in range(total_frames):
            frame_path = frames_dir / f"frame_{i:04d}.jpg"
            make_dummy_frame(frame_path, width, height, f"LTX preview | {prompt[:60]}", i)

        video_path = output / TASK_VIDEO_NAME
        frames_to_video(str(frames_dir / "frame_%04d.jpg"), fps, video_path)

        first_frame_path = output / TASK_FIRST_FRAME_NAME
        extract_first_frame(video_path, first_frame_path)

        return {
            "video_path": str(video_path.resolve()),
            "first_frame_path": str(first_frame_path.resolve()),
        }