ai_v/services/generation_service.py
公司git cf9100fcc3 ```
feat(api): 统一图像生成功能至generations接口

- 将gpt-image-2模型统一使用AI_BASE_URL下的generations接口,
  不再区分有无参考图走不同接口
- 在payload中添加response_format字段并移除output_format字段
- 更新图像数据处理逻辑,将image_data转换为image数组格式

refactor(config): 更新图像生成API配置

- 将GPT_IMAGE_GENERATION_API从硬编码URL改为使用AI_BASE_URL动态构建

refactor(generation_service): 简化图像生成请求验证逻辑

- 移除has_reference_images判断逻辑,统一使用generations接口
- 积分模式下gpt-image-2改用PREMIUM_KEY而非专用编辑key
- 移除不必要的image_data变量声明

refactor(task_service): 移除废弃的图像处理函数

- 删除_base64相关处理函数(_decode_base64_image等)
- 移除_minio上传相关函数(_upload_image_bytes_to_minio等)
- 移除gpt-image-2特定处理逻辑(_process_gpt_image_edit)
- 简化图像生成任务处理流程
```
2026-05-14 12:30:10 +08:00

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import json
import threading
import uuid
import requests
from config import Config
from extensions import db, redis_client
from models import GenerationRecord, SystemDict, User
from services.logger import system_logger
from services.task_service import process_image_generation, process_video_generation
from utils import get_api_candidates, get_proxied_url, should_switch_to_backup
def get_model_cost(model_value, is_video=False):
"""获取模型消耗积分。"""
dict_type = "video_model" if is_video else "ai_model"
model_dict = SystemDict.query.filter_by(dict_type=dict_type, value=model_value).first()
if model_dict:
return model_dict.cost
# 默认计费兜底
if is_video:
return 15 if "pro" in model_value.lower() or "3.1" in model_value else 10
return 1
def validate_generation_request(user, data):
"""校验生图请求并返回 (api_key, target_api, cost, use_trial, error)。"""
mode = data.get("mode", "trial")
is_premium = data.get("is_premium", False)
input_key = data.get("apiKey")
model_value = data.get("model")
is_gemini_flash_image_preview = model_value == "gemini-3.1-flash-image-preview"
is_gpt_image_edit = model_value == "gpt-image-2"
if isinstance(is_premium, str):
is_premium = is_premium.lower() in ("1", "true", "yes", "on")
# gpt-image-2 统一走 AI_BASE_URL 下的 generations 接口,参考图放在 image 数组中。
target_api = (
Config.GPT_IMAGE_GENERATION_API
if is_gpt_image_edit
else Config.AI_API
)
api_key = None
use_trial = False
if mode == "key":
api_key = input_key or user.api_key
if not api_key:
return None, None, 0, False, "请先输入您的 API 密钥"
# 用户手动输入了新 key 时,同步保存到账号
if input_key and input_key != user.api_key:
user.api_key = input_key
db.session.commit()
else:
if user.points <= 0:
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"
# 积分模式下gpt-image-2 跟随 AI_BASE_URL 的内置高级线路。
if is_gpt_image_edit:
api_key = Config.PREMIUM_KEY
elif is_premium:
api_key = (
Config.GEMINI_FLASH_IMAGE_PREMIUM_KEY
if is_gemini_flash_image_preview
else Config.PREMIUM_KEY
)
elif is_gemini_flash_image_preview:
api_key = Config.PREMIUM_KEY
else:
api_key = Config.TRIAL_KEY
target_api = (
Config.GPT_IMAGE_GENERATION_API
if is_gpt_image_edit
else Config.TRIAL_API
)
use_trial = True
# 计算本次任务消耗
cost = get_model_cost(model_value, is_video=False)
if use_trial and is_premium:
cost *= 2
if use_trial and user.points < cost:
return None, None, cost, True, f"可用积分不足,本次需要 {cost} 积分"
return api_key, target_api, cost, use_trial, None
def deduct_points(user_id, cost):
"""原子扣减积分。"""
user = db.session.query(User).filter_by(id=user_id).populate_existing().with_for_update().first()
if user:
user.points -= cost
user.has_used_points = True
db.session.commit()
def refund_points(user_id, cost):
"""原子退回积分。"""
try:
user = db.session.query(User).filter_by(id=user_id).populate_existing().with_for_update().first()
if user:
user.points += cost
db.session.commit()
except Exception:
db.session.rollback()
def handle_chat_generation_sync(user_id, api_key, model_value, prompt, use_trial, cost):
"""同步处理聊天类模型。"""
chat_payload = {
"model": model_value,
"messages": [{"role": "user", "content": prompt}],
}
try:
resp = None
last_error = None
candidates = get_api_candidates(Config.CHAT_API, api_key)
for idx, candidate in enumerate(candidates):
headers = {
"Authorization": f"Bearer {candidate['api_key']}",
"Content-Type": "application/json",
}
try:
resp = requests.post(
get_proxied_url(candidate["url"]),
json=chat_payload,
headers=headers,
timeout=Config.PROXY_TIMEOUT_LONG,
)
if resp.status_code == 200:
break
last_error = resp.text
has_backup = idx < len(candidates) - 1
if has_backup and should_switch_to_backup(resp.status_code):
system_logger.warning(
"聊天主线路失败,切换备用线路",
user_id=user_id,
model=model_value,
status_code=resp.status_code,
)
continue
break
except requests.RequestException as e:
last_error = str(e)
if idx < len(candidates) - 1:
system_logger.warning(
"聊天请求异常,切换备用线路",
user_id=user_id,
model=model_value,
error=last_error,
)
continue
raise
if not resp or resp.status_code != 200:
if use_trial:
refund_points(user_id, cost)
return {"error": last_error or "聊天请求失败"}, resp.status_code if resp else 500
api_result = resp.json()
content = api_result["choices"][0]["message"]["content"]
# 非验光单解读的文本生成写入历史
if prompt != "解读验光单":
new_record = GenerationRecord(
user_id=user_id,
prompt=prompt,
model=model_value,
cost=cost,
image_urls=json.dumps([{"type": "text", "content": content}]),
)
db.session.add(new_record)
db.session.commit()
return {
"data": [{"content": content, "type": "text"}],
"message": "生成成功",
}, 200
except Exception as e:
if use_trial:
refund_points(user_id, cost)
return {"error": str(e)}, 500
def start_async_image_task(app, user_id, payload, api_key, target_api, cost, mode, model_value, use_trial=False):
"""启动异步生图任务。"""
task_id = str(uuid.uuid4())
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"
system_logger.info(log_msg, model=model_value, mode=mode)
redis_client.setex(
f"task:{task_id}",
3600,
json.dumps({"status": "queued", "message": "任务已提交,等待处理..."}),
)
threading.Thread(
target=process_image_generation,
args=(app, user_id, task_id, payload, api_key, target_api, cost, use_trial),
).start()
return task_id
def validate_video_request(user, data):
"""校验视频生成请求。"""
if user.points <= 0:
return None, 0, "可用积分不足,请先充值"
model_value = data.get("model", "veo3.1")
cost = get_model_cost(model_value, is_video=True)
if user.points < cost:
return None, cost, f"积分不足,生成该视频需要 {cost} 积分"
return model_value, cost, None
def start_async_video_task(app, user_id, payload, cost, model_value):
"""启动异步视频任务。"""
api_key = Config.VIDEO_KEY
task_id = str(uuid.uuid4())
system_logger.info("用户发起视频生成任务 (积分模式)", model=model_value, cost=cost)
redis_client.setex(
f"task:{task_id}",
3600,
json.dumps({"status": "queued", "message": "视频任务已提交,准备开始处理..."}),
)
threading.Thread(
target=process_video_generation,
args=(app, user_id, task_id, payload, api_key, cost, True),
).start()
return task_id