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 HunyuanBackend(BaseVideoBackend): backend_name = "hunyuan_backend" model_name = "HunyuanVideo-1.5" def __init__(self, model_dir: Path, enable_cpu_offload: bool = True, enable_vae_tiling: bool = True): self.model_dir = model_dir self.enable_cpu_offload = enable_cpu_offload self.enable_vae_tiling = enable_vae_tiling self._loaded = False self._pipeline = None def load(self) -> None: if self._loaded: return # TODO: Replace with real HunyuanVideo loading and memory optimization hooks. # Example hooks: self._pipeline.enable_model_cpu_offload(), self._pipeline.vae.enable_tiling() self.model_dir.mkdir(parents=True, exist_ok=True) self._pipeline = "hunyuan_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"Hunyuan refine | {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()), }