小鱼开发
512 lines
16 KiB
Python
512 lines
16 KiB
Python
"""
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视频生成 API 路由
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================
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提供数字人视频、文生视频、图生视频功能。
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基于 KlingAI API 实现。
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"""
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import logging
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import uuid
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from datetime import datetime
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from pathlib import Path
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from fastapi import APIRouter, File, Form, HTTPException, UploadFile
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from fastapi.responses import FileResponse, StreamingResponse
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from pydantic import BaseModel, Field
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from app.ai.providers.klingai_provider import KlingAIProvider
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from app.config import get_settings
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from app.core.config_loader import get_config_loader
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from app.schemas.common import ApiResponse, success_response
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from app.schemas.segment import Segment
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from app.services.kling_video_service import get_kling_video_service
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router = APIRouter(prefix="/video", tags=["Video"])
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# 视频文件存储目录
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VIDEO_STORAGE_DIR = Path("data/video")
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VIDEO_STORAGE_DIR.mkdir(parents=True, exist_ok=True)
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# 上传文件临时目录
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UPLOAD_DIR = Path("data/uploads")
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UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
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logger = logging.getLogger(__name__)
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# ============ 数据模型 ============
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class DigitalHuman(BaseModel):
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"""数字人信息"""
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id: str
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name: str
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desc: str
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avatar_url: str | None = None
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type: str = "preset" # preset, custom, upload
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class VideoGenerateRequest(BaseModel):
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"""视频生成请求"""
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project_id: str = Field(..., description="项目ID")
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human_id: int | None = Field(None, description="数字人主体ID（分镜类型使用）")
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segments: list[Segment] = Field(..., description="分镜列表")
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class VideoGenerateResponse(BaseModel):
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"""视频生成响应"""
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job_id: str = Field(..., description="作业ID")
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task_id: str = Field(..., description="任务ID（与job_id相同）")
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status: str = Field(..., description="作业状态")
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message: str = Field(..., description="状态消息")
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sse_url: str = Field(..., description="SSE进度流URL")
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class VideoJobStatus(BaseModel):
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"""视频作业状态"""
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job_id: str
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project_id: str
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status: str # pending, processing, completed, partial, failed
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progress: int
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total_segments: int
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completed_segments: int
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failed_segments: int
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created_at: float
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updated_at: float
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error_message: str | None = None
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class ShotResult(BaseModel):
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"""单个分镜结果"""
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segment_id: str
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type: str
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status: str
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task_id: str | None = None
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video_url: str | None = None
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local_path: str | None = None
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error_message: str | None = None
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class VideoJobDetail(BaseModel):
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"""视频作业详情"""
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job_id: str
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project_id: str
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status: str
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progress: int
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total_segments: int
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completed_segments: int
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failed_segments: int
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segments: list[ShotResult]
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created_at: float
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updated_at: float
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# ============ 内存存储 ============
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# 数字人库
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digital_humans_db: dict[str, DigitalHuman] = {
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"dh_001": DigitalHuman(
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id="dh_001",
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name="商务男士",
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desc="专业稳重的商务形象，适合正式场合",
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type="preset",
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),
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"dh_002": DigitalHuman(
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id="dh_002",
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name="亲和女士",
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desc="温和亲切的女性形象，适合讲解分享",
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type="preset",
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),
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"dh_003": DigitalHuman(
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id="dh_003",
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name="活力青年",
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desc="年轻有活力的形象，适合轻松内容",
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type="preset",
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),
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"dh_004": DigitalHuman(
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id="dh_004", name="知性女性", desc="知性优雅的形象，适合知识分享", type="preset"
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),
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}
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# ============ 辅助函数 ============
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async def get_klingai_provider() -> KlingAIProvider:
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"""获取 KlingAI Provider 实例
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API Key 从 Settings 读取（符合配置规范）
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"""
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settings = get_settings()
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config_loader = get_config_loader()
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platform = config_loader.get_platform("klingai")
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# 从 Settings 读取 AK/SK（符合配置规范：.env → Settings → 服务层）
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access_key = settings.KLINGAI_ACCESS_KEY
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secret_key = settings.KLINGAI_SECRET_KEY
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if not access_key or not secret_key:
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raise HTTPException(
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status_code=400,
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detail="KlingAI 未配置，请设置 KLINGAI_ACCESS_KEY 和 KLINGAI_SECRET_KEY",
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)
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# 从 YAML 读取 base_url（模型配置）
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base_url = platform.base_url if platform else None
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return KlingAIProvider(
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{
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"access_key": access_key,
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"secret_key": secret_key,
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"base_url": base_url or "https://api-beijing.klingai.com",
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}
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)
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# ============ 新版 API 路由（推荐） ============
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@router.post("/generate", response_model=ApiResponse[VideoGenerateResponse])
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async def create_video_generation(data: VideoGenerateRequest):
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"""
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创建视频生成任务
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接收项目ID、数字人ID和分镜列表，创建视频生成作业。
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支持 SSE 流式查询进度。
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**分镜类型说明：**
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- `segment`: 分镜（带数字人），使用 omni-video 接口，需要 human_id
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- `empty_shot`: 空镜，使用文生图 + 图生视频流程
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**调用流程：**
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1. 调用此接口创建任务，获取 job_id
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2. 使用 SSE 接口 `/video/jobs/{job_id}/stream` 监听进度
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3. 或使用 `/video/jobs/{job_id}` 查询状态
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"""
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try:
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service = get_kling_video_service()
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# 转换分镜数据
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segments_data = []
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for segment in data.segments:
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segments_data.append(
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{
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"id": segment.id,
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"type": segment.type,
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"scene": segment.scene,
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"voiceover": segment.voiceover,
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"voice_id": segment.voice_id,
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}
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)
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# 创建作业
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job = await service.create_job(
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project_id=data.project_id,
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human_id=data.human_id,
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segments_data=segments_data,
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)
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# 构建SSE URL
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sse_url = f"/video/jobs/{job.job_id}/stream"
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return success_response(
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data=VideoGenerateResponse(
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job_id=job.job_id,
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task_id=job.job_id,
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status=job.status,
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message="视频生成任务已创建",
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sse_url=sse_url,
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)
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)
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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except Exception as e:
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logger.error(f"创建视频生成任务失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/jobs/{job_id}", response_model=ApiResponse[VideoJobDetail])
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async def get_video_job(job_id: str):
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"""
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查询视频生成作业详情
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获取指定作业的详细信息和所有分镜的处理结果。
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"""
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try:
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service = get_kling_video_service()
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job = service.get_job(job_id)
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if not job:
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raise HTTPException(status_code=404, detail="作业不存在")
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# 构建分镜结果
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segments = []
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for segment in job.segments:
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segments.append(
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ShotResult(
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segment_id=segment.id,
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type=segment.type,
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status=segment.status,
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task_id=segment.provider_task_id,
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video_url=segment.video_url,
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local_path=segment.local_path,
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error_message=segment.error_message,
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)
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)
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return success_response(
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data=VideoJobDetail(
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job_id=job.job_id,
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project_id=job.project_id,
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status=job.status,
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progress=job.progress,
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total_segments=len(job.segments),
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completed_segments=sum(1 for s in job.segments if s.status.value == "completed"),
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failed_segments=sum(1 for s in job.segments if s.status.value == "failed"),
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segments=segments,
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created_at=job.created_at,
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updated_at=job.updated_at,
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)
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"查询作业详情失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/jobs/{job_id}/stream")
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async def stream_video_job(job_id: str):
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"""
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SSE 流式获取视频生成进度
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使用 Server-Sent Events 实时推送视频生成进度。
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**事件类型：**
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- `start`: 开始生成
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- `processing`: 处理中（包含进度信息）
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- `finalizing`: 完成整理
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- `complete`: 全部完成
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- `error`: 发生错误
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**示例：**
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```
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const eventSource = new EventSource('/api/v1/video/jobs/{job_id}/stream');
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eventSource.onmessage = (e) => {
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const data = JSON.parse(e.data);
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console.log(data.progress + '%: ' + data.message);
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};
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```
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"""
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try:
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service = get_kling_video_service()
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# 验证作业存在
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job = service.get_job(job_id)
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if not job:
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raise HTTPException(status_code=404, detail="作业不存在")
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async def event_generator():
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"""SSE 事件生成器"""
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async for event in service.process_job_stream(job_id):
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yield f"data: {__import__('json').dumps(event, ensure_ascii=False)}\n\n"
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return StreamingResponse(
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event_generator(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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},
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"流式获取作业进度失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/jobs/{job_id}/status", response_model=ApiResponse[VideoJobStatus])
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async def get_video_job_status(job_id: str):
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"""
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获取视频生成作业状态（简化版）
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"""
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try:
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service = get_kling_video_service()
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status = service.get_job_status(job_id)
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if not status:
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raise HTTPException(status_code=404, detail="作业不存在")
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return success_response(
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data=VideoJobStatus(
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job_id=str(status["job_id"]),
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project_id=str(status["project_id"]),
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status=str(status["status"]),
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progress=int(status["progress"]), # type: ignore[arg-type]
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total_segments=int(status["total_segments"]), # type: ignore[arg-type]
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completed_segments=int(status["completed_segments"]), # type: ignore[arg-type]
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failed_segments=int(status["failed_segments"]), # type: ignore[arg-type]
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created_at=float(status["created_at"]), # type: ignore[arg-type]
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updated_at=float(status["updated_at"]), # type: ignore[arg-type]
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error_message=status.get("error_message"),
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)
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"获取作业状态失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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# ============ 数字人管理 ============
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@router.get("/library", response_model=ApiResponse[list[DigitalHuman]])
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async def get_digital_humans():
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"""
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获取数字人素材库
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返回系统预设的数字人列表。
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"""
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try:
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humans = list(digital_humans_db.values())
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return success_response(data=humans)
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except Exception as e:
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logger.error(f"获取数字人库失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.post("/upload", response_model=ApiResponse[DigitalHuman])
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async def upload_video(
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file: UploadFile = File(..., description="视频文件"),
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name: str | None = Form(None, description="数字人名称"),
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):
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"""
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上传人物视频作为数字人素材
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文件要求：
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- 格式：mp4, mov
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- 时长：2-60秒
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- 分辨率：720p 或 1080p
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"""
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try:
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# 验证文件格式
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allowed_types = ["video/mp4", "video/quicktime", "video/x-msvideo"]
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if file.content_type not in allowed_types:
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raise HTTPException(
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status_code=400,
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detail=f"不支持的文件格式: {file.content_type}，请上传 mp4/mov 视频",
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)
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# 保存文件
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file_ext = Path(file.filename or "").suffix or ".mp4"
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video_id = f"upload_{uuid.uuid4().hex[:16]}"
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video_filename = f"{video_id}{file_ext}"
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video_path = UPLOAD_DIR / video_filename
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content = await file.read()
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video_path.write_bytes(content)
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logger.info(f"视频上传成功: {video_path}, 大小: {len(content)} bytes")
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# 创建数字人记录
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human = DigitalHuman(
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id=video_id,
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name=name or f"上传视频_{datetime.now().strftime('%m%d_%H%M')}",
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desc="用户上传的自定义数字人",
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type="upload",
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avatar_url=f"/api/v1/video/{video_id}/thumbnail",
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)
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# 添加到数据库
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digital_humans_db[video_id] = human
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return success_response(data=human)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"上传视频失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/{video_id}/download")
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async def download_video(video_id: str):
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"""
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下载视频文件
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支持三种查找位置：
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1. data/video/{video_id}.mp4 - 传统存储
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2. data/uploads/{video_id}.ext - 上传文件
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3. ~/Documents/Meijiaka/projects/*/videos/{video_id}.mp4 - 项目生成的视频
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文件名格式: scene_{shot_id}.mp4
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"""
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try:
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# 1. 首先查找传统存储位置
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video_path = VIDEO_STORAGE_DIR / f"{video_id}.mp4"
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found = False
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if not video_path.exists():
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# 2. 尝试从上传目录查找
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for ext in [".mp4", ".mov", ".avi"]:
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candidate = UPLOAD_DIR / f"{video_id}{ext}"
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if candidate.exists():
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video_path = candidate
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found = True
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break
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else:
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found = True
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# 3. 如果还没找到，尝试在项目视频目录中查找
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# video_id 可能是 scene_{id} 格式
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if not found:
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from app.services.kling_video_service import KlingVideoService
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# 遍历项目目录查找（递归查找）
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base_dir = KlingVideoService.BASE_STORAGE_DIR
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if base_dir.exists():
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for project_dir in base_dir.iterdir():
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if project_dir.is_dir():
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candidate = project_dir / "videos" / f"{video_id}.mp4"
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if candidate.exists():
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video_path = candidate
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found = True
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break
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if not found or not video_path.exists():
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raise HTTPException(status_code=404, detail="视频文件不存在")
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return FileResponse(path=video_path, media_type="video/mp4", filename=f"{video_id}.mp4")
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"下载视频失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/{video_id}/thumbnail")
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async def get_video_thumbnail(video_id: str):
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"""
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获取视频缩略图
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"""
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try:
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# 简化实现：返回占位图
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# 实际应该使用 FFmpeg 提取视频第一帧
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raise HTTPException(status_code=404, detail="缩略图功能暂未实现")
|
|
|
|
except Exception as e:
|
|
logger.error(f"获取缩略图失败: {e}")
|
|
raise HTTPException(status_code=500, detail=str(e))
|