feat(api): 移除gpt-image-2参考图强制验证并优化图像处理逻辑 移除对gpt-image-2模型的参考图上传强制验证,支持无参考图时调用生成接口, 同时优化图像URL提取和处理逻辑以支持不同响应格式 BREAKING CHANGE: gpt-image-2不再强制要求上传参考图 ```
250 lines
8.3 KiB
Python
250 lines
8.3 KiB
Python
import json
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import threading
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import uuid
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import requests
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from config import Config
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from extensions import db, redis_client
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from models import GenerationRecord, SystemDict, User
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from services.logger import system_logger
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from services.task_service import process_image_generation, process_video_generation
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from utils import get_api_candidates, get_proxied_url, should_switch_to_backup
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def get_model_cost(model_value, is_video=False):
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"""获取模型消耗积分。"""
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dict_type = "video_model" if is_video else "ai_model"
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model_dict = SystemDict.query.filter_by(dict_type=dict_type, value=model_value).first()
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if model_dict:
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return model_dict.cost
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# 默认计费兜底
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if is_video:
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return 15 if "pro" in model_value.lower() or "3.1" in model_value else 10
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return 1
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def validate_generation_request(user, data):
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"""校验生图请求并返回 (api_key, target_api, cost, use_trial, error)。"""
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mode = data.get("mode", "trial")
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is_premium = data.get("is_premium", False)
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input_key = data.get("apiKey")
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model_value = data.get("model")
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is_gemini_flash_image_preview = model_value == "gemini-3.1-flash-image-preview"
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is_gpt_image_edit = model_value == "gpt-image-2"
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image_data = data.get("image_data", [])
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has_reference_images = bool(image_data)
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if isinstance(is_premium, str):
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is_premium = is_premium.lower() in ("1", "true", "yes", "on")
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# gpt-image-2 有参考图走 edits,无参考图走 generations;其它模型沿用现有 generations 接口
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target_api = (
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(Config.GPT_IMAGE_EDIT_API if has_reference_images else Config.GPT_IMAGE_GENERATION_API)
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if is_gpt_image_edit
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else Config.AI_API
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)
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api_key = None
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use_trial = False
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if mode == "key":
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api_key = input_key or user.api_key
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if not api_key:
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return None, None, 0, False, "请先输入您的 API 密钥"
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# 用户手动输入了新 key 时,同步保存到账号
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if input_key and input_key != user.api_key:
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user.api_key = input_key
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db.session.commit()
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else:
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if user.points <= 0:
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return None, None, 0, False, "可用积分已耗尽,请充值或切换至自定义 Key 模式"
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# 积分模式下,gpt-image-2 使用固定的专用 key
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if is_gpt_image_edit:
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api_key = Config.GPT_IMAGE_EDIT_KEY
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elif is_premium:
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api_key = (
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Config.GEMINI_FLASH_IMAGE_PREMIUM_KEY
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if is_gemini_flash_image_preview
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else Config.PREMIUM_KEY
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)
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elif is_gemini_flash_image_preview:
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api_key = Config.PREMIUM_KEY
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else:
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api_key = Config.TRIAL_KEY
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target_api = (
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(Config.GPT_IMAGE_EDIT_API if has_reference_images else Config.GPT_IMAGE_GENERATION_API)
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if is_gpt_image_edit
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else Config.TRIAL_API
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)
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use_trial = True
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# 计算本次任务消耗
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cost = get_model_cost(model_value, is_video=False)
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if use_trial and is_premium:
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cost *= 2
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if use_trial and user.points < cost:
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return None, None, cost, True, f"可用积分不足,本次需要 {cost} 积分"
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return api_key, target_api, cost, use_trial, None
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def deduct_points(user_id, cost):
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"""原子扣减积分。"""
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user = db.session.query(User).filter_by(id=user_id).populate_existing().with_for_update().first()
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if user:
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user.points -= cost
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user.has_used_points = True
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db.session.commit()
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def refund_points(user_id, cost):
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"""原子退回积分。"""
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try:
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user = db.session.query(User).filter_by(id=user_id).populate_existing().with_for_update().first()
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if user:
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user.points += cost
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db.session.commit()
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except Exception:
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db.session.rollback()
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def handle_chat_generation_sync(user_id, api_key, model_value, prompt, use_trial, cost):
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"""同步处理聊天类模型。"""
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chat_payload = {
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"model": model_value,
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"messages": [{"role": "user", "content": prompt}],
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}
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try:
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resp = None
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last_error = None
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candidates = get_api_candidates(Config.CHAT_API, api_key)
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for idx, candidate in enumerate(candidates):
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headers = {
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"Authorization": f"Bearer {candidate['api_key']}",
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"Content-Type": "application/json",
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}
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try:
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resp = requests.post(
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get_proxied_url(candidate["url"]),
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json=chat_payload,
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headers=headers,
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timeout=Config.PROXY_TIMEOUT_LONG,
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)
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if resp.status_code == 200:
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break
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last_error = resp.text
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has_backup = idx < len(candidates) - 1
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if has_backup and should_switch_to_backup(resp.status_code):
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system_logger.warning(
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"聊天主线路失败,切换备用线路",
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user_id=user_id,
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model=model_value,
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status_code=resp.status_code,
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)
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continue
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break
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except requests.RequestException as e:
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last_error = str(e)
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if idx < len(candidates) - 1:
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system_logger.warning(
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"聊天请求异常,切换备用线路",
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user_id=user_id,
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model=model_value,
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error=last_error,
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)
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continue
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raise
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if not resp or resp.status_code != 200:
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if use_trial:
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refund_points(user_id, cost)
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return {"error": last_error or "聊天请求失败"}, resp.status_code if resp else 500
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api_result = resp.json()
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content = api_result["choices"][0]["message"]["content"]
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# 非验光单解读的文本生成写入历史
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if prompt != "解读验光单":
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new_record = GenerationRecord(
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user_id=user_id,
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prompt=prompt,
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model=model_value,
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cost=cost,
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image_urls=json.dumps([{"type": "text", "content": content}]),
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)
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db.session.add(new_record)
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db.session.commit()
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return {
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"data": [{"content": content, "type": "text"}],
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"message": "生成成功",
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}, 200
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except Exception as e:
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if use_trial:
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refund_points(user_id, cost)
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return {"error": str(e)}, 500
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def start_async_image_task(app, user_id, payload, api_key, target_api, cost, mode, model_value, use_trial=False):
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"""启动异步生图任务。"""
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task_id = str(uuid.uuid4())
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log_msg = "用户发起验光单解读" if payload.get("prompt") == "解读验光单" else "用户发起生图任务"
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system_logger.info(log_msg, model=model_value, mode=mode)
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redis_client.setex(
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f"task:{task_id}",
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3600,
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json.dumps({"status": "queued", "message": "任务已提交,等待处理..."}),
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)
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threading.Thread(
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target=process_image_generation,
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args=(app, user_id, task_id, payload, api_key, target_api, cost, use_trial),
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).start()
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return task_id
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def validate_video_request(user, data):
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"""校验视频生成请求。"""
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if user.points <= 0:
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return None, 0, "可用积分不足,请先充值"
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model_value = data.get("model", "veo3.1")
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cost = get_model_cost(model_value, is_video=True)
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if user.points < cost:
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return None, cost, f"积分不足,生成该视频需要 {cost} 积分"
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return model_value, cost, None
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def start_async_video_task(app, user_id, payload, cost, model_value):
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"""启动异步视频任务。"""
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api_key = Config.VIDEO_KEY
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task_id = str(uuid.uuid4())
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system_logger.info("用户发起视频生成任务 (积分模式)", model=model_value, cost=cost)
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redis_client.setex(
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f"task:{task_id}",
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3600,
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json.dumps({"status": "queued", "message": "视频任务已提交,准备开始处理..."}),
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)
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threading.Thread(
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target=process_video_generation,
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args=(app, user_id, task_id, payload, api_key, cost, True),
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).start()
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return task_id
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