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import asyncio
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import json
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import traceback
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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.model = f"SeaArt - {self.config.seaart_setting['model'][self.count]}"
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self.model_hash = "c7352c5d2f"
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self.logger = self.setup_logger('[SeaArt]')
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token = self.config.seaart[self.count]
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self.token = token
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self.backend_name = self.config.backend_name_list[6]
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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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data = json.dumps({"task_ids": [id_]})
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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="https://www.seaart.me/api/v1/task/batch-progress",
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headers=self.headers,
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content=data
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)
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if isinstance(response, dict) and 'error' in response:
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raise RuntimeError(f"请求失败，错误信息: {response.get('details')}")
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else:
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items = response.get('data', {}).get('items', [])
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if not items:
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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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for item in items:
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urls = item.get("img_uris")
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if urls 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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elif isinstance(urls, list):
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for url in urls:
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self.logger.img(f"图片url: {url['url']}")
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self.img_url.append(url['url'])
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return
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raise RuntimeError(f"任务 {id_} 在60次心跳后仍未完成")
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async def update_progress(self):
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pass
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async def check_backend_usability(self):
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pass
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async def err_formating_to_sd_style(self):
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await self.download_img()
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self.format_api_respond()
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self.result = self.build_respond
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async def posting(self):
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input_ = {
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"action": 1,
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"art_model_no": "1a486c58c2aa0601b57ddc263fc350d0",
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"category": 1,
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"speed_type": 1,
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"meta":
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{
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"prompt": self.tags,
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"negative_prompt": self.ntags,
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"restore_faces": self.restore_faces,
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"seed": self.seed,
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"sampler_name": self.sampler,
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"width": self.width,
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"height": self.height,
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"steps": self.steps,
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"cfg_scale": self.scale,
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"lora_models": [],
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"vae": "vae-ft-mse-840000-ema-pruned",
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"clip_skip": 1,
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"hr_second_pass_steps": 20,
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"lcm_mode": 0,
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"n_iter": 1,
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"embeddings": []
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}
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}
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if self.enable_hr:
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hr_payload = {
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"hr_second_pass_steps": self.hr_second_pass_steps,
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"enable_hr": True,
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"hr_upscaler": "4x-UltraSharp",
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"hr_scale": self.hr_scale,
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}
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input_['meta'].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
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}
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self.headers.update(new_headers)
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data = json.dumps(input_)
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response = await self.http_request(
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method="POST",
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target_url="https://www.seaart.me/api/v1/task/create",
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headers=self.headers,
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content=data
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)
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if isinstance(response, dict) and 'error' in response:
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self.logger.warning(f"{response.get('details')}")
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else:
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task = response
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task_id = task.get('data', {}).get('id')
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if task_id:
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await self.heart_beat(task_id)
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await self.err_formating_to_sd_style()
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