FIX 增加jm_router
This commit is contained in:
parent
ef687a0487
commit
6740c4a03f
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@ -19,10 +19,6 @@ dependencies = [
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"av",
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"imageio",
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"loguru",
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"openai-whisper",
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"sentry-sdk",
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"pydantic",
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"pydantic_settings",
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"conformer==0.3.2",
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"einops>0.6.1"
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"pydantic_settings"
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]
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@ -6,7 +6,7 @@ from sentry_sdk.integrations.fastapi import FastApiIntegration
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from fastapi.middleware.cors import CORSMiddleware
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from .utils.KVCache import MediaSourceKVCache
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from .router import ffmpeg, cache, comfyui, google, task
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from .router import ffmpeg, cache, comfyui, google, task, jm_router
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from .models.settings.cluster import WorkerConfig
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config = WorkerConfig()
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@ -88,3 +88,4 @@ web_app.include_router(cache.router)
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web_app.include_router(google.router)
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web_app.include_router(task.router)
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web_app.include_router(jm_router.router)
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@ -0,0 +1,325 @@
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# -*- coding:utf-8 -*-
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"""
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File jm_api_local.py
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Author silence
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Date 2025/6/27 10:15
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"""
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import random
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import uvicorn
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import json
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from fastapi import APIRouter, HTTPException, FastAPI
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import requests
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import time
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from loguru import logger
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from typing import List
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from pydantic import BaseModel
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import asyncio
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router = APIRouter(prefix='/jm_router', tags=['Jm_router'])
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api_key = '21575c22-14aa-40ca-8aa8-f00ca27a3a17'
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jm_default_prompts = [
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'女人扭动身体向摄像机展示身材，一只手撩了一下头发，镜头从左向右移动并放大画面',
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'女人扭动身体向摄像机展示身材，一只手撩了一下头发后放在了裤子上，镜头从左向右移动',
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'时尚模特抬头自信的展示身材，扭动身体，一只手放在了头上，镜头逐渐放大聚焦在了下衣上',
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'自信步伐跟拍模特，模特步伐自信地同时行走，镜头紧紧跟随。抬起手捋一捋头发。传递出自信与时尚的气息。',
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'女生两只手捏着拳头轻盈的左右摇摆跳舞，动作幅度不大，然后把手摊开放在胸口再做出像popping心脏跳动的动作，左右身体都要非常协调',
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'一个年轻女子自信地在相机前展示了她优美的身材，以自然的流体动作自由地摇摆，左手撩了一下头发之后停在了胸前。一个美女自拍跳舞扭动身体的视频，手从下到上最后放在胸前，妩媚的表情',
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'美女向后退了一步站在那里展示服装，双手轻轻提了一下裤子两侧，镜头从上到下逐渐放大',
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'女人低头看向裤子，向镜头展示身材，一只手放在了头上做pose动作',
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'美女向后退了一步站在那里展示服装，低头并用手抚摸裤子，镜头从上到下逐渐放大',
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'美女向后退了一步站在那里展示服装，双手从上到下整理衣服，自然扭动身体，自信的表情'
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]
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logger.bind(name='jm_api')
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async def submit_task(prompt: str, img_url: str, duration: str = '5'):
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try:
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headers = {
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {api_key}',
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}
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json_data = {
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'model': 'doubao-seedance-1-0-lite-i2v-250428',
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'content': [
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{
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'type': 'text',
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'text': f'{prompt} --resolution 720p --dur {duration} --camerafixed false',
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},
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{
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'type': 'image_url',
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'image_url': {
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'url': img_url,
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},
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},
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],
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}
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response = requests.post('https://ark.cn-beijing.volces.com/api/v3/contents/generations/tasks', headers=headers,
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json=json_data)
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logger.info(f'submit task: {json.dumps(response.json())}')
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resp_json = response.json()
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job_id = resp_json['id']
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return {"data": job_id, 'status': True}
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except Exception as e:
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logger.error(e)
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return {"data": None, "status": False}
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async def sync_query_status(job_id: str):
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def query_status(t_id: str):
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resp_dict = {'status': False, 'data': None, 'msg': ''}
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try:
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headers = {
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {api_key}',
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}
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response = requests.get(f'https://ark.cn-beijing.volces.com/api/v3/contents/generations/tasks/{t_id}',
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headers=headers)
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resp_json = response.json()
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resp_dict['status'] = resp_json['status'] == 'succeeded'
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resp_dict['msg'] = resp_json['status']
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resp_dict['data'] = resp_json['content']['video_url'] if 'content' in resp_json else None
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except Exception as e:
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raise ValueError(str(e))
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finally:
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return resp_dict
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timeout = 180
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interval = 2
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end = time.time() + timeout
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final_result = {"status": False, "data": None, "msg": ""}
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success = False
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while time.time() < end:
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tmp_data = query_status(job_id)
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if tmp_data['status']:
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final_result['status'] = True
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final_result['data'] = tmp_data['data']
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success = True
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break
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elif tmp_data['msg'] == 'running':
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time.sleep(interval)
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print(f'wait next interval:{interval}')
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if not success:
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final_result['msg'] = '运行超时'
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return final_result
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async def async_query_status(job_id: str):
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resp_dict = {'status': False, 'data': None, 'msg': ''}
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try:
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headers = {
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {api_key}',
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}
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response = requests.get(f'https://ark.cn-beijing.volces.com/api/v3/contents/generations/tasks/{job_id}',
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headers=headers)
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resp_json = response.json()
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print(resp_json)
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resp_dict['status'] = resp_json['status'] == 'succeeded'
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resp_dict['msg'] = resp_json['status']
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resp_dict['data'] = resp_json['content']['video_url'] if 'content' in resp_json else None
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except Exception as e:
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logger.error(f'error:{str(e)}')
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resp_dict['msg'] = str(e)
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finally:
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return resp_dict
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class VideoTaskRequest(BaseModel):
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prompt: str
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img_url: str
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task_id: str
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duration: str = '5'
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class VideoTaskStatus(BaseModel):
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job_ids: List[str]
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class BatchVideoTaskRequest(BaseModel):
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tasks: List[VideoTaskRequest]
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@router.post('/jm/submit/task', summary='异步批量提交任务')
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async def submit_video_task(
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request: BatchVideoTaskRequest,
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):
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# 创建异步任务列表
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async def process_single_task(task: VideoTaskRequest):
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if not task.prompt:
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task.prompt = random.choice(jm_default_prompts)
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result = await submit_task(task.prompt, task.img_url, task.duration)
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return {
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"status": result.get('status', False),
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"job_id": result.get('data', ''),
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"img_url": task.img_url,
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"task_id": task.task_id
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}
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# 并发执行所有任务
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results = await asyncio.gather(
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*[process_single_task(task) for task in request.tasks]
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)
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# 分离成功和失败的任务
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successful_tasks = [
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{"task_id": r["task_id"], "img_url": r["img_url"], "job_id": r["job_id"]}
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for r in results if r["status"]
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]
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failed_tasks = [
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{"img_url": r["img_url"]}
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for r in results if not r["status"]
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]
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return {
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"status": len(successful_tasks) > 0, # 如果有任何成功任务就返回True
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"data": {
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"success": successful_tasks,
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"failed": failed_tasks
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},
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"msg": f"成功提交 {len(successful_tasks)} 个任务，失败 {len(failed_tasks)} 个任务"
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}
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@router.get('/jm/query/status', summary='查询视频生成任务状态')
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async def query_video_task(
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job_id: str,
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):
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if not job_id:
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raise HTTPException(status_code=400, detail="job_id is required")
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# 查询任务状态
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result = await async_query_status(job_id)
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return result
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@router.post('/jm/batch/query/status', summary='批量查询视频生成任务状态')
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async def batch_query_video_status(data: VideoTaskStatus):
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"""
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批量查询视频生成任务状态
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Args:
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data: VideoTaskStatus对象，包含job_ids列表
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Returns:
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dict: 按状态分类的任务信息
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{
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'data': {
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'finished': [{'job_id': 'xxx', 'video_url': 'xxx'}],
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'failed': ['失败的job_id'],
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'running': ['处理中的job_id']
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},
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'status': True,
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'msg': ''
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}
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"""
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if not data.job_ids:
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return {
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'data': {
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'finished': [],
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'failed': [],
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'running': []
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},
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'status': True,
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'msg': '任务列表为空'
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}
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logger.info(f"开始批量查询 {len(data.job_ids)} 个视频任务状态")
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# 创建异步任务列表
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async def query_single_task(job_id: str):
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try:
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result = await async_query_status(job_id)
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return {
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'job_id': job_id,
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'status': result.get('status', False),
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'msg': result.get('msg', ''),
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'data': result.get('data', None)
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}
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except Exception as e:
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logger.error(f"查询任务 {job_id} 失败: {str(e)}")
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return {
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'job_id': job_id,
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'status': False,
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'msg': f'查询异常: {str(e)}',
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'data': None
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}
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try:
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# 并发查询所有任务
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results = await asyncio.gather(
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*[query_single_task(job_id) for job_id in data.job_ids],
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return_exceptions=True
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)
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# 分类处理结果
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finished_tasks = []
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failed_tasks = []
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running_tasks = []
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for i, result in enumerate(results):
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job_id = data.job_ids[i]
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if isinstance(result, Exception):
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logger.error(f"任务 {job_id} 查询异常: {str(result)}")
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failed_tasks.append(job_id)
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continue
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# 根据状态分类
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if result['status'] and result['data']:
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# 任务完成且有视频URL
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finished_tasks.append({
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'job_id': job_id,
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'video_url': result['data']
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})
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logger.debug(f"任务 {job_id} 已完成: {result['data']}")
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elif result['msg'] in ['running', 'pending', 'processing']:
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# 任务处理中
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running_tasks.append(job_id)
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logger.debug(f"任务 {job_id} 处理中: {result['msg']}")
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else:
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# 任务失败或其他异常状态
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failed_tasks.append(job_id)
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logger.debug(f"任务 {job_id} 失败: {result['msg']}")
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# 构造返回结果
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finished_count = len(finished_tasks)
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failed_count = len(failed_tasks)
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running_count = len(running_tasks)
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return {
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'data': {
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'finished': finished_tasks,
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'failed': failed_tasks,
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'running': running_tasks
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},
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'status': True,
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'msg': f'批量查询完成 - 已完成:{finished_count}, 失败:{failed_count}, 处理中:{running_count}'
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}
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except Exception as e:
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logger.error(f"批量查询视频任务状态异常: {str(e)}")
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return {
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'data': {
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'finished': [],
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'failed': data.job_ids.copy(), # 异常时将所有任务都标记为失败
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'running': []
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},
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'status': False,
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'msg': f'批量查询异常: {str(e)}'
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}
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if __name__ == '__main__':
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app = FastAPI()
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url = 'http://127.0.0.1:9010/docs'
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uvicorn.run(app, host='127.0.0.1', port=9010)
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@ -3,6 +3,7 @@ from BowongModalFunctions.models.settings.cluster import WorkerConfig
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from .video import app as media_app
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from .web import app as web_app
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from .ffmpeg_app import app as ffmpeg_app
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from .comfyui_api import comfyui_app as comfyui_api_app
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# from .comfyui_v1 import app as comfyui_v1_app
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# from .comfyui_v2 import app as comfyui_v2_app
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@ -15,5 +16,6 @@ app = modal.App(config.modal_app_name,
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app.include(media_app)
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app.include(ffmpeg_app)
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app.include(web_app)
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app.include(comfyui_api_app)
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# app.include(comfyui_v1_app)
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# app.include(comfyui_v2_app)
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@ -0,0 +1,33 @@
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import subprocess
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import modal
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from cluster.comfyui_v1 import comfyui_image
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image = ( # build up a Modal Image to run ComfyUI, step by step
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modal.Image.debian_slim( # start from basic Linux with Python
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python_version="3.10"
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)
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.apt_install("git", "gcc", "libportaudio2", "ffmpeg")
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.pip_install("fastapi[standard]==0.115.4")
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.pip_install("comfy_cli==0.0.0",index_url="https://packages-1747622887395:0ee15474ccd7b27b57ca63a9306327678e6c2631@g-ldyi2063-pypi.pkg.coding.net/dev/packages/simple")
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.run_commands(
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"comfy --skip-prompt install --fast-deps --nvidia --version 0.3.40"
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)
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.pip_install_from_pyproject("../pyproject_comfyui.toml")
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.run_commands("comfy node install https://e.coding.net/g-ldyi2063/dev/ComfyUI-CustomNode.git")
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)
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comfyui_app = modal.App(image=image)
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custom_secret = modal.Secret.from_name("comfyui-custom-secret", environment_name="dev")
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@comfyui_app.function(
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max_containers=1, # limit interactive session to 1 container
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secrets=[custom_secret],
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region="ap"
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)
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@modal.concurrent(
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max_inputs=10
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) # required for UI startup process which runs several API calls concurrently
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@modal.web_server(8000, startup_timeout=60)
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def ui():
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subprocess.Popen("comfy launch -- --cpu --listen 0.0.0.0 --port 8000", shell=True)
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@ -28,7 +28,7 @@ with fastapi_image.imports():
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config = WorkerConfig()
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@app.function(scaledown_window=60,
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@app.function(scaledown_window=600,
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secrets=[
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modal.Secret.from_name("cf-kv-secret"),
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],
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