| import asyncio
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| import json
|
| import traceback
|
|
|
| from .base import Backend
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|
|
|
|
| class AIDRAW(Backend):
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|
|
| def __init__(self, count, payload, **kwargs):
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| super().__init__(count=count, payload=payload, **kwargs)
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|
|
| self.xl = self.config.liblibai_setting['xl'][self.count]
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| self.flux = self.config.liblibai_setting['flux'][self.count]
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| site_name = 'LiblibAI_XL' if self.xl else 'LiblibAI'
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| self.model = f"{site_name} - {self.config.liblibai_setting['model_name'][self.count]}"
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| self.model_id = self.config.liblibai_setting['model'][self.count]
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| self.model_hash = "c7352c5d2f"
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| self.logger = self.setup_logger('[LiblibAI]')
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|
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| token = self.config.liblibai[self.count]
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| self.token = token
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| self.backend_name = self.config.backend_name_list[4]
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| self.workload_name = f"{self.backend_name}-{token}"
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|
|
| async def heart_beat(self, id_):
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| self.logger.info(f"{id_}开始请求")
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| for i in range(60):
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|
|
| response = await self.http_request(
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| method="POST",
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| target_url=f"https://liblib-api.vibrou.com/gateway/sd-api/generate/progress/msg/v3/{id_}",
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| headers=self.headers,
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| content=json.dumps({"flag": 0}),
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| verify=False
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| )
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|
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|
|
| if response.get('error') == "error":
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| self.logger.warning(f"Failed to request: {response}")
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| raise RuntimeError('服务器返回错误')
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| if response['code'] != 0 or response['data']['statusMsg'] == '执行异常':
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| raise RuntimeError('服务器返回错误')
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|
|
| images = response['data']['images']
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|
|
| if images is None:
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| self.logger.info(f"第{i+1}次心跳，未返回结果")
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| await asyncio.sleep(5)
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| continue
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| else:
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|
|
| for i in images:
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| if 'porn' in i['previewPath']:
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| self.nsfw_detected = True
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| self.logger.warning("API侧检测到NSFW图片")
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| else:
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| self.logger.img(f"图片url: {i['previewPath']}")
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| self.img_url.append(i['previewPath'])
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| self.comment = i['imageInfo']
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| break
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|
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| async def update_progress(self):
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|
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| pass
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|
|
| async def check_backend_usability(self):
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| pass
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|
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| async def err_formating_to_sd_style(self):
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|
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| if self.nsfw_detected:
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| await self.return_build_image()
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| else:
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| await self.download_img()
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|
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| self.format_api_respond()
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|
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| self.result = self.build_respond
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|
|
| async def posting(self):
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|
|
| if self.xl or self.flux:
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| if self.xl:
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| pre_tag, pre_ntag = tuple(self.config.liblibai_setting.get('preference')[self.count]['pretags']['xl'])
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| elif self.flux:
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| pre_tag, pre_ntag = tuple(self.config.liblibai_setting.get('preference')[self.count]['pretags']['flux'])
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| self.tags = pre_tag + self.tags
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| self.ntags = pre_ntag + self.ntags
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| if self.enable_hr:
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| self.width = int(self.width * self.hr_scale)
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| self.height = int(self.height * self.hr_scale)
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| self.enable_hr = False
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| elif self.width * self.height < 1048576:
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| self.width = int(self.width * 1.5)
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| self.height = int(self.height * 1.5)
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|
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| self.steps = self.config.liblibai_setting.get('preference')[self.count].get('steps', 12)
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|
|
| if self.flux:
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| input_ = {
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| "checkpointId": 2295774,
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| "generateType": 17,
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| "frontCustomerReq": {
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| "windowId": "",
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| "tabType": "txt2img",
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| "conAndSegAndGen": "gen"
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| },
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| "adetailerEnable": 0,
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| "text2imgV3": {
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| "clipSkip": 2,
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| "checkPointName": 2295774,
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| "prompt": self.tags,
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| "negPrompt": self.ntags,
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| "seed": self.seed,
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| "randnSource": 0,
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| "samplingMethod": 31,
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| "imgCount": self.batch_size,
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| "samplingStep": self.steps,
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| "cfgScale": self.scale,
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| "width": self.width,
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| "height": self.height
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| },
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| "taskQueuePriority": 1
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| }
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|
|
| else:
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| input_ = {
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| "checkpointId": self.model_id,
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| "generateType": 1,
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| "frontCustomerReq": {
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|
|
| "windowId": "",
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| "tabType": "txt2img",
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| "conAndSegAndGen": "gen"
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| }
|
| ,
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| "adetailerEnable": 0,
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| "text2img": {
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| "prompt": self.tags,
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| "negativePrompt": self.ntags,
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| "extraNetwork": "",
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| "samplingMethod": 0,
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| "samplingStep": self.steps,
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| "width": self.width,
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| "height": self.height,
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| "imgCount": self.batch_size,
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| "cfgScale": self.scale,
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| "seed": self.seed,
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| "seedExtra": 0,
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| "hiResFix": 0,
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| "restoreFaces": 0,
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| "tiling": 0,
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| "clipSkip": 2,
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| "randnSource": 0,
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| "tileDiffusion": None
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| }
|
| ,
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| "taskQueuePriority": 1
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| }
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|
|
| if self.enable_hr and self.flux is False and self.xl is False:
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|
|
| hr_payload = {
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| "hiresSteps": self.hr_second_pass_steps,
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| "denoisingStrength": self.denoising_strength,
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| "hiResFix": 1 if self.enable_hr else 0,
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| "hiResFixInfo": {
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| "upscaler": 6,
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| "upscaleBy": self.hr_scale,
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| "resizeWidth": int(self.width * self.hr_scale),
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| "resizeHeight": int(self.height * self.hr_scale)
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| }
|
| }
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|
|
| input_['text2img'].update(hr_payload)
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|
|
| new_headers = {
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| "Accept": "application/json, text/plain, */*",
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| "Token": self.token
|
| }
|
| self.headers.update(new_headers)
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|
|
| response = await self.http_request(
|
| method="POST",
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| target_url="https://liblib-api.vibrou.com/gateway/sd-api/generate/image",
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| headers=self.headers,
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| content=json.dumps(input_),
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| verify=False
|
| )
|
|
|
|
|
| if response.get('error') == "error":
|
| self.logger.warning(f"Failed to request: {response}")
|
| else:
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| task = response
|
| if task.get('msg') == 'Insufficient power':
|
| self.logger.warning('费用不足!')
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| self.logger.info(f"API返回{task}")
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| task_id = task['data']
|
| await self.heart_beat(task_id)
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|
|
| await self.err_formating_to_sd_style()
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|
|
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|
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|
