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xiaoxia-saas/apps/worker/worker_app/tasks/generation.py
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2026-08-08 10:29:24 +00:00

445 lines
15 KiB
Python
Executable File

"""
视频生成任务
支持四种剪辑模式:一镜到底、画中画、口播、口播+画中画
"""
import logging
import os
import shutil
import subprocess # nosec B404
import tempfile
from pathlib import Path
from typing import Optional
from urllib.parse import urlparse
import oss2
from worker_app.celery_app import celery_app
OUTPUT_WIDTH = 1280
OUTPUT_HEIGHT = 720
OUTPUT_FPS = 25.0
OUTPUT_DURATION_SECONDS = 5.0
FFMPEG_BIN = shutil.which("ffmpeg") or "ffmpeg"
FFPROBE_BIN = shutil.which("ffprobe") or "ffprobe"
GENERATED_FILES_DIR = Path(os.getenv("GENERATED_FILES_DIR", "/app/generated"))
GENERATED_FILES_URL_PREFIX = os.getenv("GENERATED_FILES_URL_PREFIX", "/generated-files")
PUBLIC_API_BASE_URL = os.getenv("PUBLIC_API_BASE_URL", "https://api.xiaoxiajianji.com").rstrip("/")
logger = logging.getLogger(__name__)
def _run_ffmpeg(command: list[str]) -> None:
"""执行 FFmpeg 命令"""
subprocess.run(command, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) # nosec B603
def _oss_settings() -> tuple[str, str, str, str] | None:
"""获取 OSS 配置"""
access_key_id = os.getenv("OSS_ACCESS_KEY_ID")
access_key_secret = os.getenv("OSS_ACCESS_KEY_SECRET")
endpoint = os.getenv("OSS_ENDPOINT")
bucket_name = os.getenv("OSS_BUCKET_NAME")
if not all([access_key_id, access_key_secret, endpoint, bucket_name]):
return None
return access_key_id, access_key_secret, endpoint, bucket_name
def _oss_bucket() -> oss2.Bucket | None:
"""获取 OSS Bucket"""
settings = _oss_settings()
if settings is None:
return None
access_key_id, access_key_secret, endpoint, bucket_name = settings
return oss2.Bucket(oss2.Auth(access_key_id, access_key_secret), endpoint, bucket_name)
def _normalize_storage_key(storage_key_or_url: str) -> str:
"""标准化存储键"""
if storage_key_or_url.startswith(("http://", "https://")):
return urlparse(storage_key_or_url).path.lstrip("/")
return storage_key_or_url.lstrip("/")
def _download_asset(asset_storage_key: str, local_path: Path) -> bool:
"""下载素材文件"""
bucket = _oss_bucket()
if bucket is None:
return False
try:
bucket.get_object_to_file(_normalize_storage_key(asset_storage_key), str(local_path))
return local_path.exists() and local_path.stat().st_size > 0
except Exception:
return False
def _probe_duration(local_path: Path) -> float:
"""获取视频时长"""
try:
result = subprocess.run(
[
FFPROBE_BIN,
"-v",
"error",
"-show_entries",
"format=duration",
"-of",
"default=noprint_wrappers=1:nokey=1",
str(local_path),
],
check=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
) # nosec B603
return round(float(result.stdout.strip()), 3)
except Exception:
return OUTPUT_DURATION_SECONDS
def _create_fallback_clip(
output_path: Path, title: str, width: int = OUTPUT_WIDTH, height: int = OUTPUT_HEIGHT
) -> None:
"""创建 fallback 视频(无素材时)"""
safe_title = title.replace(":", "\\:").replace("'", "\\'")[:80]
_run_ffmpeg(
[
FFMPEG_BIN,
"-y",
"-f",
"lavfi",
"-i",
f"color=c=#111827:s={width}x{height}:d={OUTPUT_DURATION_SECONDS}:r={int(OUTPUT_FPS)}",
"-vf",
f"drawtext=text='{safe_title}':fontcolor=white:fontsize=48:x=(w-text_w)/2:y=(h-text_h)/2",
"-c:v",
"libx264",
"-pix_fmt",
"yuv420p",
"-movflags",
"+faststart",
str(output_path),
]
)
def _download_voice_asset(voice_library_id: str, local_path: Path) -> bool:
"""下载配音文件"""
if not voice_library_id:
return False
bucket = _oss_bucket()
if bucket is None:
return False
storage_key = f"voice/{voice_library_id}.mp3"
try:
bucket.get_object_to_file(_normalize_storage_key(storage_key), str(local_path))
return local_path.exists() and local_path.stat().st_size > 0
except Exception:
return False
def _download_library_assets(
asset_library_id: str,
temp_path: Path,
video_extensions: tuple = (".mp4", ".mov", ".avi", ".mkv", ".webm"),
asset_ids: list[str] | None = None,
) -> list[str]:
"""
从素材库下载视频素材
Args:
asset_library_id: 素材库 ID
temp_path: 临时目录路径
video_extensions: 支持的视频扩展名
asset_ids: 指定素材 ID 列表,为空则下载全部 ready 视频素材
Returns:
下载成功的视频文件路径列表
"""
# 导入模型和会话
try:
from worker_app.db import SessionLocal
from packages.adapters.sqlalchemy_impl.models import AssetModel
session = SessionLocal()
try:
# 查询素材库中的视频素材
query = session.query(AssetModel).filter(
AssetModel.asset_library_id == asset_library_id,
AssetModel.status == "ready",
AssetModel.file_type.in_(["video", "video/mp4", "video/quicktime"]),
)
# 如果指定了 asset_ids,则只下载这些素材
if asset_ids:
query = query.filter(AssetModel.id.in_(asset_ids))
assets = query.order_by(AssetModel.created_at).all()
if not assets:
logger.info(f"No video assets found in library {asset_library_id}")
return []
downloaded_videos = []
for i, asset in enumerate(assets):
# 获取文件 URL 或 storage_key
storage_key = asset.file_url if asset.file_url else None
if not storage_key:
continue
local_file = temp_path / f"asset_{i}_{asset.id}.mp4"
if _download_asset(storage_key, local_file):
downloaded_videos.append(str(local_file))
logger.info(f"Downloaded asset: {asset.name} -> {local_file}")
else:
logger.warning(f"Failed to download asset: {asset.name}")
return downloaded_videos
finally:
session.close()
except Exception as e:
logger.error(f"Error downloading library assets: {e}")
return []
def _process_with_editing_mode(
video_paths: list[str],
audio_path: Optional[str],
mode: str,
output_path: Path,
output_width: int = OUTPUT_WIDTH,
output_height: int = OUTPUT_HEIGHT,
) -> None:
"""根据剪辑模式处理视频"""
from video_processing.editing_modes import (
EditingMode,
EditingModeConfig,
EditingModeProcessor,
PIPPosition,
)
config = EditingModeConfig(
mode=EditingMode(mode),
output_width=output_width,
output_height=output_height,
output_fps=int(OUTPUT_FPS),
pip_position=PIPPosition.TOP_RIGHT,
pip_scale=0.25,
transition_duration=0.5,
)
processor = EditingModeProcessor(config=config)
processor.process(
video_paths=video_paths,
audio_path=audio_path,
output_path=str(output_path),
)
@celery_app.task(bind=True, name="worker.generate_video", max_retries=2)
def generate_video(self, task_id: str) -> dict:
"""
生成视频任务
Args:
task_id: 任务 ID(从数据库加载完整任务信息)
Returns:
生成结果字典
"""
from worker_app.db import SessionLocal
from packages.adapters.sqlalchemy_impl.generation_task_repository import (
SQLAlchemyGenerationTaskRepository,
)
from packages.domain import EditingMode, GeneratedVideo, GenerationTaskStatus
# 从数据库加载任务信息
session = SessionLocal()
try:
task_repo = SQLAlchemyGenerationTaskRepository(session)
gen_task = task_repo.get(task_id)
if gen_task is None:
return {"status": "failed", "error": f"generation task {task_id} not found"}
project_id = gen_task.project_id
asset_library_id = gen_task.asset_library_id
voice_library_id = gen_task.voice_library_id or ""
mode = gen_task.strategy_id or "one_take"
task_asset_ids = list(gen_task.asset_ids or [])
batch_id = getattr(gen_task, "batch_id", "") or ""
# 新增字段:分辨率、封面、标题
output_width = getattr(gen_task, "output_width", OUTPUT_WIDTH) or OUTPUT_WIDTH
output_height = getattr(gen_task, "output_height", OUTPUT_HEIGHT) or OUTPUT_HEIGHT
cover_url = getattr(gen_task, "cover_url", "") or ""
custom_title = getattr(gen_task, "custom_title", "") or ""
finally:
session.close()
try:
editing_mode = EditingMode(mode)
except ValueError:
editing_mode = EditingMode.ONE_TAKE
output_name = f"generated-{task_id}.mp4"
storage_key = f"generated/projects/{project_id}/tasks/{task_id}/{output_name}"
try:
with tempfile.TemporaryDirectory(prefix="xiaoxia-generation-") as temp_dir:
temp_path = Path(temp_dir)
output_path = temp_path / output_name
# 从素材库下载视频素材(如果任务指定了 asset_ids 则只下载这些)
downloaded_videos = _download_library_assets(asset_library_id, temp_path, asset_ids=task_asset_ids or None)
audio_path = None
if voice_library_id:
local_audio = temp_path / "voice.mp3"
if _download_voice_asset(voice_library_id, local_audio):
audio_path = str(local_audio)
if downloaded_videos:
_process_with_editing_mode(
video_paths=downloaded_videos,
audio_path=audio_path,
mode=editing_mode.value,
output_path=output_path,
output_width=output_width,
output_height=output_height,
)
else:
_create_fallback_clip(
output_path, f"Generated Video {task_id[:8]}", width=output_width, height=output_height
)
file_size = output_path.stat().st_size
duration = _probe_duration(output_path)
# 上传到 OSS
bucket = _oss_bucket()
if bucket:
try:
bucket.put_object_from_file(storage_key, str(output_path))
except Exception as oss_err:
logger.warning(f"OSS upload failed: {oss_err}")
# 构建视频 URL
if bucket:
file_url = f"{PUBLIC_API_BASE_URL}/{storage_key}"
else:
file_url = f"{GENERATED_FILES_URL_PREFIX}/{task_id}/{output_name}"
# 创建 GeneratedVideo 记录 + 查重
_create_video_record_and_dedup(
task_id=task_id,
project_id=project_id,
batch_id=batch_id,
file_url=file_url,
file_size=file_size,
duration=duration,
video_path=str(output_path),
mode=editing_mode.value,
width=output_width,
height=output_height,
)
return {
"status": "completed",
"task_id": task_id,
"output_path": str(output_path),
"file_size": file_size,
"duration": duration,
"width": output_width,
"height": output_height,
"mode": editing_mode.value,
}
except Exception as error:
logger.error(f"Video generation failed: {error}")
return {
"status": "failed",
"task_id": task_id,
"error": str(error),
}
def _create_video_record_and_dedup(
*,
task_id: str,
project_id: str,
batch_id: str,
file_url: str,
file_size: int,
duration: float,
video_path: str,
mode: str,
width: int = OUTPUT_WIDTH,
height: int = OUTPUT_HEIGHT,
) -> None:
"""创建 GeneratedVideo 记录,计算指纹并执行查重(历史 + 批次)。"""
from uuid import uuid4
from video_processing.dedup import VideoDeduplicator
from worker_app.db import SessionLocal
from packages.adapters.sqlalchemy_impl.generated_video_repository import (
SQLAlchemyGeneratedVideoRepository,
)
from packages.domain import GeneratedVideo
session = SessionLocal()
try:
video_id = uuid4().hex
generated_video = GeneratedVideo(
id=video_id,
project_id=project_id,
generation_task_id=task_id,
name=f"generated-{task_id[:8]}.mp4",
file_url=file_url,
file_size=file_size,
duration=duration,
width=width,
height=height,
fps=OUTPUT_FPS,
status="completed",
generation_params={"mode": mode},
)
video_repo = SQLAlchemyGeneratedVideoRepository(session)
video_repo.create(generated_video)
# 计算视频指纹
deduplicator = VideoDeduplicator()
try:
fingerprint = deduplicator.compute_fingerprint(video_path)
except Exception as fp_err:
logger.warning(f"Fingerprint computation failed for {video_id}: {fp_err}")
session.commit()
return
generated_video.video_fingerprint = fingerprint.to_dict()
# (a) 历史成片查重
duplicate_result = deduplicator.check_duplicate(fingerprint, project_id, session)
# (b) 批次内查重(仅当有 batch_id 时)
if not duplicate_result and batch_id:
duplicate_result = deduplicator.check_batch_duplicate(fingerprint, batch_id, video_id, session)
if duplicate_result:
generated_video.is_duplicate = True
generated_video.duplicate_of = duplicate_result["duplicate_of"]
logger.info(
f"Duplicate detected: {video_id} -> {duplicate_result['duplicate_of']} "
f"(reason={duplicate_result['reason']}, similarity={duplicate_result['similarity']:.3f})"
)
else:
generated_video.is_duplicate = False
generated_video.duplicate_of = None
video_repo.update(generated_video)
session.commit()
logger.info(f"GeneratedVideo record created: {video_id} (task={task_id}, dup={generated_video.is_duplicate})")
except Exception as e:
logger.error(f"Failed to create video record / dedup for task {task_id}: {e}")
session.rollback()
finally:
session.close()