init
This commit is contained in:
433
services/service_vectorizer.py
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433
services/service_vectorizer.py
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"""
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矢量化服务模块 - 使用统一异常处理机制
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"""
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import aiohttp
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import time
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import urllib3
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from typing import Callable, Optional, Dict, Any
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import logging
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import os
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import asyncio
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from pathlib import Path
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# 导入基础服务类
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from utils.service_base import (
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BaseService, PollingMixin, ServiceError, ServiceTimeoutError,
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ServiceNetworkError, RetryConfig, TimeoutConfig
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)
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# 禁用SSL警告
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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logger = logging.getLogger(__name__)
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class VectorizerServiceError(ServiceError):
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"""矢量化服务特定异常"""
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pass
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class VectorizerService(BaseService, PollingMixin):
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"""矢量化服务类 - 继承统一异常处理机制"""
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# def __init__(self, base_url: str = "https://frp-dad.com:50529"):
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def __init__(self, base_url: str = "https://127.0.0.1:8090"):
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# 配置重试和超时
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retry_config = RetryConfig(
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max_retries=3,
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base_delay=2.0,
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max_delay=30.0
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)
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timeout_config = TimeoutConfig(
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connection_timeout=60.0,
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read_timeout=240.0,
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total_timeout=1200.0
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)
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super().__init__(
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name="VectorizerService",
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base_url=base_url,
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retry_config=retry_config,
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timeout_config=timeout_config
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)
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async def image_to_eps(self,
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image_path: str,
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save_eps_path: Optional[str] = None,
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timeout: int = 1200,
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poll_interval: float = 2.0,
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status_callback: Optional[Callable[[str, dict], None]] = None) -> str:
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"""
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将图片转换为EPS矢量文件
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Args:
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image_path: 输入图片路径
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save_eps_path: 输出EPS文件路径（可选）
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timeout: 最大等待时间（秒）
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poll_interval: 轮询间隔（秒）
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status_callback: 状态回调函数
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Returns:
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str: EPS文件保存路径
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Raises:
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VectorizerServiceError: 矢量化服务异常
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ServiceTimeoutError: 超时异常
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ServiceNetworkError: 网络异常
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"""
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# 验证输入文件
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if not os.path.exists(image_path):
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raise VectorizerServiceError(f"输入图片文件不存在: {image_path}")
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# 设置输出路径
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if save_eps_path is None:
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save_eps_path = os.path.splitext(image_path)[0] + '.eps'
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# 确保输出目录存在
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output_dir = os.path.dirname(save_eps_path)
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if output_dir:
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os.makedirs(output_dir, exist_ok=True)
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try:
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# 1. 上传图片
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task_id = await self.execute_with_retry(
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self._upload_image,
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image_path,
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status_callback,
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error_context=" - 上传图片"
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)
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# 2. 轮询等待处理完成
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await self.execute_with_retry(
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self._wait_for_processing,
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task_id,
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timeout,
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poll_interval,
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status_callback,
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error_context=" - 等待处理完成"
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)
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# 3. 下载结果文件
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await self.execute_with_retry(
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self._download_result,
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task_id,
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save_eps_path,
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status_callback,
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error_context=" - 下载结果文件"
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)
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# 验证输出文件
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if not os.path.exists(save_eps_path) or os.path.getsize(save_eps_path) == 0:
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raise VectorizerServiceError(f"输出文件创建失败或为空: {save_eps_path}")
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self.logger.info(f"矢量化转换成功: {image_path} -> {save_eps_path}")
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if status_callback:
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status_callback('finished', {
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'message': '转换完成！',
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'input_path': image_path,
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'output_path': save_eps_path
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})
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return save_eps_path
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except (ServiceTimeoutError, ServiceNetworkError, VectorizerServiceError):
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# 直接传递这些异常
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if status_callback:
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status_callback('error', {'message': '处理失败，请稍后重试'})
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raise
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except Exception as e:
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error_msg = f"矢量化转换失败: {str(e)}"
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self.logger.error(error_msg)
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if status_callback:
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status_callback('error', {'message': error_msg})
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raise VectorizerServiceError(error_msg)
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async def _upload_image(self,
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image_path: str,
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status_callback: Optional[Callable[[str, dict], None]] = None) -> str:
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"""上传图片到矢量化服务"""
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if status_callback:
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status_callback('uploading', {'message': '正在上传图片...', 'image_path': image_path})
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async with await self.create_http_session() as session:
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with open(image_path, 'rb') as f:
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data = aiohttp.FormData()
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data.add_field('file', f, filename=os.path.basename(image_path))
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async with session.post(f"{self.base_url}/add_task", data=data, ssl=False) as resp:
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if resp.status != 200:
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error_text = await resp.text()
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raise VectorizerServiceError(f"上传失败 - HTTP {resp.status}: {error_text}")
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response_data = await resp.json()
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if response_data.get('code') != 0:
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error_msg = response_data.get('message', '未知错误')
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raise VectorizerServiceError(f"上传失败: {error_msg}")
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task_id = response_data.get('id') or response_data.get('taskid')
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if not task_id:
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raise VectorizerServiceError("上传失败，未获取到任务ID")
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self.logger.info(f"图片上传成功，任务ID: {task_id}")
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if status_callback:
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status_callback('uploaded', {
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'message': '图片上传成功，开始处理...',
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'taskid': task_id
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})
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return task_id
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async def _wait_for_processing(self,
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task_id: str,
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timeout: int,
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poll_interval: float,
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status_callback: Optional[Callable[[str, dict], None]] = None):
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"""等待处理完成"""
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start_time = time.time()
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poll_count = 0
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consecutive_failures = 0
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max_consecutive_failures = 5
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async with await self.create_http_session() as session:
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while True:
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poll_count += 1
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elapsed_time = time.time() - start_time
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# 检查超时
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if elapsed_time > timeout:
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await self.cleanup_failed_task(task_id)
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raise ServiceTimeoutError(f"处理超时 (超过{timeout}秒) - 任务ID: {task_id}")
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if status_callback:
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progress = min(90, int(90 * elapsed_time / timeout))
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status_callback('processing', {
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'message': f'正在处理中... (第{poll_count}次检查)',
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'taskid': task_id,
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'elapsed_time': elapsed_time,
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'poll_count': poll_count,
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'progress': progress
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})
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try:
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async with session.get(f"{self.base_url}/try_get",
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params={'taskid': task_id},
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ssl=False) as resp:
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if resp.status != 200:
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consecutive_failures += 1
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error_text = await resp.text()
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self.logger.warning(f"状态查询失败 - HTTP {resp.status}: {error_text}")
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if consecutive_failures >= max_consecutive_failures:
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await self.cleanup_failed_task(task_id)
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raise VectorizerServiceError(f"连续{consecutive_failures}次状态查询失败")
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await asyncio.sleep(poll_interval * 2) # 失败时等待更长时间
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continue
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# 重置失败计数
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consecutive_failures = 0
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result = await resp.json()
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if result.get('code') == 0:
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# 处理完成
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self.logger.info(f"任务处理完成 - 任务ID: {task_id}, 耗时: {elapsed_time:.2f}秒")
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if status_callback:
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status_callback('completed', {
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'message': '处理完成，准备下载...',
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'taskid': task_id,
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'total_time': elapsed_time,
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'poll_count': poll_count
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})
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return
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elif result.get('code') == -1:
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# 处理失败
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error_msg = result.get('message', '处理失败')
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await self.cleanup_failed_task(task_id)
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raise VectorizerServiceError(f"服务器处理失败: {error_msg}")
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# 其他状态码，继续等待
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self.logger.debug(f"任务处理中 - 任务ID: {task_id}, 状态码: {result.get('code')}")
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except VectorizerServiceError:
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# 直接传递服务异常
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raise
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except Exception as e:
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consecutive_failures += 1
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self.logger.warning(f"轮询检查异常 (第{consecutive_failures}次): {str(e)}")
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if consecutive_failures >= max_consecutive_failures:
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await self.cleanup_failed_task(task_id)
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raise VectorizerServiceError(f"连续{consecutive_failures}次轮询异常: {str(e)}")
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await asyncio.sleep(poll_interval)
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async def _download_result(self,
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task_id: str,
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save_path: str,
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status_callback: Optional[Callable[[str, dict], None]] = None):
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"""下载处理结果"""
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if status_callback:
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status_callback('downloading', {'message': '正在下载EPS文件...', 'taskid': task_id})
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async with await self.create_http_session() as session:
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async with session.get(f"{self.base_url}/get_image",
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params={'taskid': task_id},
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ssl=False) as resp:
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if resp.status != 200:
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error_text = await resp.text()
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raise VectorizerServiceError(f"下载失败 - HTTP {resp.status}: {error_text}")
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# 检查内容长度
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content_length = resp.headers.get('Content-Length')
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if content_length and int(content_length) == 0:
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raise VectorizerServiceError("下载的文件为空")
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# 使用临时文件确保原子写入
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temp_path = save_path + '.tmp'
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try:
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with open(temp_path, 'wb') as f:
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bytes_written = 0
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while True:
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chunk = await resp.content.read(8192)
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if not chunk:
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break
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f.write(chunk)
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bytes_written += len(chunk)
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# 验证文件大小
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if bytes_written == 0:
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raise VectorizerServiceError("下载的文件为空")
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# 原子移动到最终位置
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os.rename(temp_path, save_path)
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self.logger.info(f"文件下载成功: {save_path}, 大小: {bytes_written} 字节")
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except Exception as e:
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# 清理临时文件
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if os.path.exists(temp_path):
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os.remove(temp_path)
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raise VectorizerServiceError(f"文件下载失败: {str(e)}")
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async def get_system_status(self) -> Dict[str, Any]:
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"""获取系统状态"""
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return await self.execute_with_retry(
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self._do_get_system_status,
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error_context=" - 获取系统状态"
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)
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async def _do_get_system_status(self) -> Dict[str, Any]:
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"""执行系统状态查询"""
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async with await self.create_http_session() as session:
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async with session.get(f"{self.base_url}/status", ssl=False) as resp:
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if resp.status != 200:
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error_text = await resp.text()
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raise VectorizerServiceError(f"获取系统状态失败 - HTTP {resp.status}: {error_text}")
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return await resp.json()
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async def _do_health_check(self) -> bool:
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"""执行健康检查"""
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try:
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status = await self._do_get_system_status()
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return True
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except Exception as e:
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self.logger.warning(f"健康检查失败: {str(e)}")
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return False
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async def cleanup_failed_task(self, task_id: str) -> None:
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"""清理失败的任务"""
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try:
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# 尝试取消任务（如果服务支持）
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async with await self.create_http_session() as session:
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async with session.delete(f"{self.base_url}/cancel_task",
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params={'taskid': task_id},
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ssl=False) as resp:
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if resp.status == 200:
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self.logger.info(f"任务取消成功: {task_id}")
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else:
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self.logger.warning(f"任务取消失败: {task_id}, HTTP {resp.status}")
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except Exception as e:
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self.logger.warning(f"清理任务异常: {task_id}, 错误: {str(e)}")
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await super().cleanup_failed_task(task_id)
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async def _do_health_check(self) -> bool:
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"""执行健康检查"""
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try:
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async with self.create_http_session() as session:
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# 测试系统状态端点
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async with session.get(f"{self.base_url}/system/status", ssl=False) as resp:
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if resp.status == 200:
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data = await resp.json()
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self.logger.debug(f"矢量化服务健康检查成功: {data}")
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return True
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else:
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self.logger.warning(f"矢量化服务健康检查失败: HTTP {resp.status}")
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return False
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except Exception as e:
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self.logger.warning(f"矢量化服务健康检查异常: {e}")
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return False
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@classmethod
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async def test_connection(cls, base_url: Optional[str] = None) -> tuple[bool, str]:
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"""测试矢量化服务连接"""
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service = cls(base_url) if base_url else cls()
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try:
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is_available, message = await service.test_connection()
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if is_available:
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# 额外测试系统状态
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status = await service.get_system_status()
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return True, f"连接成功: {status}"
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else:
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return False, message
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except Exception as e:
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logger.error(f"矢量化服务连接失败: {e}")
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return False, f"连接失败: {str(e)}"
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# 实现 PollingMixin 的抽象方法
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def _is_task_complete(self, result: Any) -> bool:
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"""检查任务是否完成"""
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return result.get('code') == 0
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def _is_task_failed(self, result: Any) -> bool:
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"""检查任务是否失败"""
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return result.get('code') == -1
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def _get_error_message(self, result: Any) -> str:
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"""获取错误消息"""
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return result.get('message', '未知错误')
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# 为了保持向后兼容性，保留原有的简单接口
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async def vectorize_image(image_path: str,
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save_eps_path: Optional[str] = None,
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timeout: int = 1200,
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progress_callback: Optional[Callable[[str, dict], None]] = None) -> str:
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"""
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简单的矢量化接口（向后兼容）
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Args:
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image_path: 输入图片路径
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save_eps_path: 输出EPS文件路径
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timeout: 超时时间
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progress_callback: 进度回调函数
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Returns:
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str: EPS文件路径
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"""
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service = VectorizerService()
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return await service.image_to_eps(
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image_path=image_path,
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save_eps_path=save_eps_path,
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timeout=timeout,
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status_callback=progress_callback
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)
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Reference in New Issue
Block a user