820 lines
30 KiB
Python
820 lines
30 KiB
Python
import asyncio
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import base64
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import json
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import logging
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import os
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import random
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import uuid
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import websockets
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from collections import defaultdict
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from datetime import datetime
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from typing import Dict, Any, Optional, List, Set, Union
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import aiohttp
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from aiohttp import ClientTimeout
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from workflow_service.config import Settings, ComfyUIServer
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from workflow_service.database import (
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create_workflow_run,
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update_workflow_run_status,
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create_workflow_run_nodes,
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update_workflow_run_node_status,
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get_workflow_run,
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get_pending_workflow_runs,
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get_running_workflow_runs,
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get_workflow_run_nodes,
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)
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settings = Settings()
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API_INPUT_PREFIX = "INPUT_"
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API_OUTPUT_PREFIX = "OUTPUT_"
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# 配置日志
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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# 全局任务队列管理器
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class WorkflowQueueManager:
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def __init__(self):
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self.running_tasks = {} # server_url -> task_info
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self.pending_tasks = [] # 等待队列
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self.lock = asyncio.Lock()
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async def add_task(
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self,
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workflow_run_id: str,
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workflow_name: str,
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workflow_data: dict,
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api_spec: dict,
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request_data: dict,
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):
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"""添加新任务到队列"""
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async with self.lock:
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# 创建任务记录
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await create_workflow_run(
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workflow_run_id=workflow_run_id,
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workflow_name=workflow_name,
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workflow_json=json.dumps(workflow_data),
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api_spec=json.dumps(api_spec),
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request_data=json.dumps(request_data),
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)
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# 创建工作流节点记录
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nodes_data = []
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for node in workflow_data.get("nodes", []):
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nodes_data.append(
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{"id": str(node["id"]), "type": node.get("type", "unknown")}
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)
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await create_workflow_run_nodes(workflow_run_id, nodes_data)
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# 添加到待处理队列
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self.pending_tasks.append(workflow_run_id)
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logger.info(
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f"任务 {workflow_run_id} 已添加到队列，当前队列长度: {len(self.pending_tasks)}"
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)
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# 尝试处理队列
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asyncio.create_task(self._process_queue())
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return workflow_run_id
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async def _process_queue(self):
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"""处理队列中的任务"""
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async with self.lock:
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if not self.pending_tasks:
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return
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# 检查是否有空闲的服务器
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available_servers = await self._get_available_servers()
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if not available_servers:
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logger.info("没有可用的服务器，等待中...")
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return
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# 获取一个待处理任务
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workflow_run_id = self.pending_tasks.pop(0)
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server = available_servers[0]
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# 标记任务为运行中
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await update_workflow_run_status(
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workflow_run_id, "running", server.http_url
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)
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self.running_tasks[server.http_url] = {
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"workflow_run_id": workflow_run_id,
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"started_at": datetime.now(),
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}
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# 启动任务执行
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asyncio.create_task(self._execute_task(workflow_run_id, server))
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async def _get_available_servers(self) -> list[ComfyUIServer]:
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"""获取可用的服务器"""
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available_servers = []
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for server in settings.SERVERS:
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if server.http_url not in self.running_tasks:
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# 检查服务器状态
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try:
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async with aiohttp.ClientSession() as session:
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status = await get_server_status(server, session)
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if status["is_reachable"] and status["is_free"]:
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available_servers.append(server)
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except Exception as e:
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logger.warning(f"检查服务器 {server.http_url} 状态时出错: {e}")
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return available_servers
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async def _execute_task(self, workflow_run_id: str, server: ComfyUIServer):
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"""执行任务"""
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cleanup_paths = []
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try:
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# 获取工作流数据
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workflow_run = await get_workflow_run(workflow_run_id)
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if not workflow_run:
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raise Exception(f"找不到工作流运行记录: {workflow_run_id}")
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workflow_data = json.loads(workflow_run["workflow_json"])
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api_spec = json.loads(workflow_run["api_spec"])
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request_data = json.loads(workflow_run["request_data"])
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# 执行工作流
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result = await execute_prompt_on_server(
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workflow_data, api_spec, request_data, server, workflow_run_id
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)
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# 保存处理后的结果到数据库
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await update_workflow_run_status(
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workflow_run_id,
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"completed",
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result=json.dumps(result, ensure_ascii=False),
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)
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except Exception as e:
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logger.error(f"执行任务 {workflow_run_id} 时出错: {e}")
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await update_workflow_run_status(
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workflow_run_id, "failed", error_message=str(e)
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)
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finally:
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# 清理临时文件
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if cleanup_paths:
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logger.info(f"正在清理 {len(cleanup_paths)} 个临时文件...")
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for path in cleanup_paths:
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try:
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if os.path.exists(path):
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os.remove(path)
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logger.info(f" - 已删除: {path}")
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except Exception as e:
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logger.warning(f" - 删除 {path} 时出错: {e}")
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# 清理运行状态
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async with self.lock:
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if server.http_url in self.running_tasks:
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del self.running_tasks[server.http_url]
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# 继续处理队列
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asyncio.create_task(self._process_queue())
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async def get_task_status(self, workflow_run_id: str) -> dict:
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"""获取任务状态"""
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workflow_run = await get_workflow_run(workflow_run_id)
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if not workflow_run:
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return {"error": "任务不存在"}
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nodes = await get_workflow_run_nodes(workflow_run_id)
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result = {
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"id": workflow_run_id,
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"status": workflow_run["status"],
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"created_at": workflow_run["created_at"],
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"started_at": workflow_run["started_at"],
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"completed_at": workflow_run["completed_at"],
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"server_url": workflow_run["server_url"],
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"error_message": workflow_run["error_message"],
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"nodes": nodes,
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}
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# 如果任务完成，从数据库获取结果
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if workflow_run["status"] == "completed" and workflow_run.get("result"):
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try:
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result["result"] = json.loads(workflow_run["result"])
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except (json.JSONDecodeError, TypeError):
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result["result"] = None
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return result
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# 全局队列管理器实例
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queue_manager = WorkflowQueueManager()
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# 定义一个自定义异常，用于封装来自ComfyUI的执行错误
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class ComfyUIExecutionError(Exception):
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def __init__(self, error_data: dict):
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self.error_data = error_data
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# 创建一个对开发者友好的异常消息
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message = (
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f"ComfyUI节点执行失败。节点ID: {error_data.get('node_id')}, "
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f"节点类型: {error_data.get('node_type')}. "
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f"错误: {error_data.get('exception_message', 'N/A')}"
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)
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super().__init__(message)
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async def get_server_status(
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server: ComfyUIServer, session: aiohttp.ClientSession
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) -> Dict[str, Any]:
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"""
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检查单个ComfyUI服务器的详细状态。
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返回一个包含可达性、队列状态和详细队列内容的字典。
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"""
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# [BUG修复] 确保初始字典结构与成功时的结构一致，以满足Pydantic模型
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status_info = {
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"is_reachable": False,
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"is_free": False,
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"queue_details": {"running_count": 0, "pending_count": 0},
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}
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try:
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queue_url = f"{server.http_url}/queue"
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async with session.get(queue_url, timeout=60) as response:
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response.raise_for_status()
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queue_data = await response.json()
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status_info["is_reachable"] = True
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running_count = len(queue_data.get("queue_running", []))
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pending_count = len(queue_data.get("queue_pending", []))
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status_info["queue_details"] = {
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"running_count": running_count,
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"pending_count": pending_count,
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}
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status_info["is_free"] = running_count == 0 and pending_count == 0
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except Exception as e:
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# 当请求失败时，将返回上面定义的、结构正确的初始 status_info
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logger.warning(f"无法检查服务器 {server.http_url} 的队列状态: {e}")
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return status_info
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async def select_server_for_execution() -> ComfyUIServer:
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"""
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智能选择一个ComfyUI服务器。
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优先选择一个空闲的服务器，如果所有服务器都忙，则随机选择一个。
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"""
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servers = settings.SERVERS
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if not servers:
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raise ValueError("没有在 COMFYUI_SERVERS_JSON 中配置任何服务器。")
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if len(servers) == 1:
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return servers[0]
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async with aiohttp.ClientSession() as session:
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tasks = [get_server_status(server, session) for server in servers]
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results = await asyncio.gather(*tasks)
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free_servers = [servers[i] for i, status in enumerate(results) if status["is_free"]]
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if free_servers:
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selected_server = random.choice(free_servers)
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logger.info(
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f"发现 {len(free_servers)} 个空闲服务器。已选择: {selected_server.http_url}"
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)
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return selected_server
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else:
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# 后备方案：选择一个可达的服务器，即使它很忙
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reachable_servers = [
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servers[i] for i, status in enumerate(results) if status["is_reachable"]
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]
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if reachable_servers:
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selected_server = random.choice(reachable_servers)
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logger.info(
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f"所有服务器当前都在忙。从可达服务器中随机选择: {selected_server.http_url}"
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)
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return selected_server
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else:
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# 最坏情况：所有服务器都不可达，抛出异常
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raise ConnectionError("所有配置的ComfyUI服务器都不可达。")
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async def execute_prompt_on_server(
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workflow_data: Dict,
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api_spec: Dict,
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request_data: Dict,
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server: ComfyUIServer,
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workflow_run_id: str,
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) -> Dict:
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"""
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在指定的服务器上执行一个准备好的prompt。
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现在支持节点级别的状态跟踪。
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"""
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client_id = str(uuid.uuid4())
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# 应用请求数据到工作流
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patched_workflow = await patch_workflow(
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workflow_data, api_spec, request_data, server
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)
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# 转换为prompt格式
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prompt = convert_workflow_to_prompt_api_format(patched_workflow)
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# 更新工作流运行状态，记录prompt_id和client_id
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await update_workflow_run_status(
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workflow_run_id,
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"running",
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server.http_url,
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None, # prompt_id将在_queue_prompt后更新
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client_id,
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)
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# 提交到ComfyUI
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prompt_id = await _queue_prompt(workflow_data, prompt, client_id, server.http_url)
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# 更新prompt_id
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await update_workflow_run_status(
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workflow_run_id, "running", server.http_url, prompt_id, client_id
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)
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logger.info(
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f"工作流 {workflow_run_id} 已在 {server.http_url} 上入队，Prompt ID: {prompt_id}"
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)
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# 获取执行结果，现在支持节点级别的状态跟踪
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results = await _get_execution_results(
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workflow_data, prompt_id, client_id, server.ws_url, workflow_run_id
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)
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return results
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async def submit_workflow_to_queue(
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workflow_name: str, workflow_data: Dict, api_spec: Dict, request_data: Dict
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) -> str:
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"""
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提交工作流到队列，立即返回任务ID。
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这是新的异步接口，调用者可以通过任务ID查询状态。
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"""
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workflow_run_id = str(uuid.uuid4())
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# 添加到队列管理器
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await queue_manager.add_task(
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workflow_run_id, workflow_name, workflow_data, api_spec, request_data
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)
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return workflow_run_id
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def parse_api_spec(workflow_data: dict) -> Dict[str, Dict[str, Any]]:
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"""
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解析工作流，并根据规范 '{基础名}_{属性名}_{可选计数}' 生成API参数名。
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"""
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spec = {"inputs": {}, "outputs": {}}
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if "nodes" not in workflow_data or not isinstance(workflow_data["nodes"], list):
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raise ValueError(
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"Invalid workflow format: 'nodes' key not found or is not a list."
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)
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nodes_map = {str(node["id"]): node for node in workflow_data["nodes"]}
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input_name_counter = defaultdict(int)
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output_name_counter = defaultdict(int)
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for node_id, node in nodes_map.items():
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title: str = node.get("title")
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if not title:
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continue
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if title.startswith(API_INPUT_PREFIX):
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base_name = title[len(API_INPUT_PREFIX) :].lower()
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if "inputs" in node:
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for a_input in node.get("inputs", []):
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if a_input.get("link") is None and "widget" in a_input:
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widget_name = a_input["widget"]["name"].lower()
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# [BUG修复] 构建有意义的基础参数名
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param_name_candidate = f"{base_name}_{widget_name}"
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input_name_counter[param_name_candidate] += 1
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count = input_name_counter[param_name_candidate]
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final_param_name = (
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f"{param_name_candidate}_{count}"
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if count > 1
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else param_name_candidate
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)
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input_type_str = a_input.get("type", "STRING").upper()
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param_type = "string"
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if "COMBO" in input_type_str:
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param_type = "UploadFile"
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elif "INT" in input_type_str:
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param_type = "int"
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elif "FLOAT" in input_type_str:
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param_type = "float"
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spec["inputs"][final_param_name] = {
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"node_id": node_id,
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"type": param_type,
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"widget_name": a_input["widget"]["name"],
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}
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elif title.startswith(API_OUTPUT_PREFIX):
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base_name = title[len(API_OUTPUT_PREFIX) :].lower()
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if "outputs" in node:
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for an_output in node.get("outputs", []):
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output_name = an_output["name"].lower()
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# [BUG修复] 构建有意义的基础参数名
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param_name_candidate = f"{base_name}_{output_name}"
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output_name_counter[param_name_candidate] += 1
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count = output_name_counter[param_name_candidate]
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final_param_name = (
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f"{param_name_candidate}_{count}"
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if count > 1
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else param_name_candidate
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)
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spec["outputs"][final_param_name] = {
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"node_id": node_id,
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"class_type": node.get("type"),
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"output_name": an_output["name"],
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"output_index": node["outputs"].index(an_output),
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}
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return spec
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async def patch_workflow(
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workflow_data: dict,
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api_spec: dict[str, dict[str, Any]],
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request_data: dict[str, Any],
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server: ComfyUIServer,
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) -> dict:
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"""
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将request_data中的参数值，patch到workflow_data中。并返回修改后的workflow_data。
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"""
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if "nodes" not in workflow_data:
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raise ValueError("无效的工作流格式")
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nodes_map = {str(node["id"]): node for node in workflow_data["nodes"]}
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for param_name, value in request_data.items():
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if param_name not in api_spec["inputs"]:
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continue
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spec = api_spec["inputs"][param_name]
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node_id = spec["node_id"]
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if node_id not in nodes_map:
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continue
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target_node = nodes_map[node_id]
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widget_name_to_patch = spec["widget_name"]
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# 找到所有属于widget的输入，并确定目标widget的索引
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widget_inputs = [
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inp for inp in target_node.get("inputs", []) if "widget" in inp
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]
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target_widget_index = -1
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for i, widget_input in enumerate(widget_inputs):
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# "widget" 字典可能不存在或没有 "name" 键
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if widget_input.get("widget", {}).get("name") == widget_name_to_patch:
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target_widget_index = i
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break
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if target_widget_index == -1:
|
||
logger.warning(
|
||
f"在节点 {node_id} 中未找到名为 '{widget_name_to_patch}' 的 widget。跳过此参数。"
|
||
)
|
||
continue
|
||
|
||
# 确保 `widgets_values` 存在且为列表
|
||
if "widgets_values" not in target_node or not isinstance(
|
||
target_node.get("widgets_values"), list
|
||
):
|
||
# 如果不存在或格式错误，根据widget数量创建一个占位符列表
|
||
target_node["widgets_values"] = [None] * len(widget_inputs)
|
||
|
||
# 确保 `widgets_values` 列表足够长
|
||
while len(target_node["widgets_values"]) <= target_widget_index:
|
||
target_node["widgets_values"].append(None)
|
||
|
||
# 根据API规范转换数据类型
|
||
target_type = str
|
||
if spec["type"] == "int":
|
||
target_type = int
|
||
elif spec["type"] == "float":
|
||
target_type = float
|
||
|
||
# 在正确的位置上更新值
|
||
try:
|
||
if target_node.get("type") == "LoadImage":
|
||
value = await upload_image_to_comfy(value, server)
|
||
target_node["widgets_values"][target_widget_index] = target_type(value)
|
||
except (ValueError, TypeError) as e:
|
||
logger.warning(
|
||
f"无法将参数 '{param_name}' 的值 '{value}' 转换为类型 '{spec['type']}'。错误: {e}"
|
||
)
|
||
continue
|
||
|
||
workflow_data["nodes"] = list(nodes_map.values())
|
||
return workflow_data
|
||
|
||
|
||
def convert_workflow_to_prompt_api_format(workflow_data: dict) -> dict:
|
||
"""
|
||
将工作流（API格式）转换为提交到/prompt端点的格式。
|
||
此函数现在能正确处理已通过 `patch_workflow` 修改的 `widgets_values`。
|
||
"""
|
||
if "nodes" not in workflow_data:
|
||
raise ValueError("无效的工作流格式")
|
||
|
||
prompt_api_format = {}
|
||
|
||
# 建立从link_id到源节点的映射
|
||
link_map = {}
|
||
for link_data in workflow_data.get("links", []):
|
||
(
|
||
link_id,
|
||
origin_node_id,
|
||
origin_slot_index,
|
||
target_node_id,
|
||
target_slot_index,
|
||
link_type,
|
||
) = link_data
|
||
|
||
# 键是目标节点的输入link_id
|
||
link_map[link_id] = [str(origin_node_id), origin_slot_index]
|
||
|
||
for node in workflow_data["nodes"]:
|
||
node_id = str(node["id"])
|
||
inputs_dict = {}
|
||
|
||
# 1. 处理控件输入 (widgets)
|
||
widgets_values = node.get("widgets_values", [])
|
||
widget_cursor = 0
|
||
for input_config in node.get("inputs", []):
|
||
# 如果是widget并且有对应的widgets_values
|
||
if "widget" in input_config and widget_cursor < len(widgets_values):
|
||
widget_name = input_config["widget"].get("name")
|
||
if widget_name:
|
||
# 使用widgets_values中的值，因为这里已经包含了API传入的修改
|
||
inputs_dict[widget_name] = widgets_values[widget_cursor]
|
||
widget_cursor += 1
|
||
|
||
# 2. 处理连接输入 (links)
|
||
for input_config in node.get("inputs", []):
|
||
if "link" in input_config and input_config["link"] is not None:
|
||
link_id = input_config["link"]
|
||
if link_id in link_map:
|
||
# 输入名称是input_config中的'name'
|
||
inputs_dict[input_config["name"]] = link_map[link_id]
|
||
|
||
prompt_api_format[node_id] = {"class_type": node["type"], "inputs": inputs_dict}
|
||
|
||
return prompt_api_format
|
||
|
||
|
||
async def _queue_prompt(
|
||
workflow: dict, prompt: dict, client_id: str, http_url: str
|
||
) -> str:
|
||
"""通过HTTP POST将工作流任务提交到指定的ComfyUI服务器。"""
|
||
for node_id in prompt:
|
||
prompt[node_id]["inputs"][f"cache_buster_{uuid.uuid4().hex}"] = random.random()
|
||
payload = {
|
||
"prompt": prompt,
|
||
"client_id": client_id,
|
||
"extra_data": {
|
||
"api_key_comfy_org": "",
|
||
"extra_pnginfo": {"workflow": workflow},
|
||
},
|
||
}
|
||
logger.info(f"提交到 ComfyUI /prompt 端点的payload: {json.dumps(payload)}")
|
||
async with aiohttp.ClientSession(timeout=ClientTimeout(total=90)) as session:
|
||
prompt_url = f"{http_url}/prompt"
|
||
try:
|
||
async with session.post(prompt_url, json=payload) as response:
|
||
logger.info(f"ComfyUI /prompt 端点返回的响应: {response}")
|
||
response.raise_for_status()
|
||
result = await response.json()
|
||
logger.info(f"ComfyUI /prompt 端点返回的响应: {result}")
|
||
if "prompt_id" not in result:
|
||
raise Exception(f"从 ComfyUI /prompt 端点返回的响应无效: {result}")
|
||
return result["prompt_id"]
|
||
except Exception as e:
|
||
logger.error(f"提交到 ComfyUI /prompt 端点时发生错误: {e}")
|
||
raise e
|
||
|
||
|
||
async def _get_execution_results(
|
||
workflow_data: Dict,
|
||
prompt_id: str,
|
||
client_id: str,
|
||
ws_url: str,
|
||
workflow_run_id: str,
|
||
) -> dict:
|
||
"""
|
||
通过WebSocket连接到指定的ComfyUI服务器，聚合执行结果。
|
||
现在支持节点级别的状态跟踪。
|
||
"""
|
||
full_ws_url = f"{ws_url}?clientId={client_id}"
|
||
aggregated_outputs = {}
|
||
|
||
try:
|
||
async with websockets.connect(full_ws_url) as websocket:
|
||
while True:
|
||
try:
|
||
out = await websocket.recv()
|
||
if not isinstance(out, str):
|
||
continue
|
||
|
||
message = json.loads(out)
|
||
msg_type = message.get("type")
|
||
data = message.get("data")
|
||
|
||
if not (data and data.get("prompt_id") == prompt_id):
|
||
continue
|
||
|
||
# 捕获并处理执行错误
|
||
if msg_type == "execution_error":
|
||
error_data = data
|
||
logger.error(
|
||
f"ComfyUI执行错误 (Prompt ID: {prompt_id}): {error_data}"
|
||
)
|
||
|
||
# 更新节点状态为失败
|
||
node_id = error_data.get("node_id")
|
||
if node_id:
|
||
await update_workflow_run_node_status(
|
||
workflow_run_id,
|
||
node_id,
|
||
"failed",
|
||
error_message=error_data.get(
|
||
"exception_message", "Unknown error"
|
||
),
|
||
)
|
||
|
||
# 抛出自定义异常，将错误详情传递出去
|
||
raise ComfyUIExecutionError(error_data)
|
||
|
||
# 处理节点开始执行
|
||
if msg_type == "executing" and data.get("node"):
|
||
node_id = data.get("node")
|
||
logger.info(f"节点 {node_id} 开始执行 (Prompt ID: {prompt_id})")
|
||
|
||
# 更新节点状态为运行中
|
||
await update_workflow_run_node_status(
|
||
workflow_run_id, node_id, "running"
|
||
)
|
||
|
||
# 处理节点执行完成
|
||
if msg_type == "executed":
|
||
node_id = data.get("node")
|
||
output_data = data.get("output")
|
||
if node_id and output_data:
|
||
node = next(
|
||
(
|
||
x
|
||
for x in workflow_data["nodes"]
|
||
if str(x["id"]) == node_id
|
||
),
|
||
None,
|
||
)
|
||
if (
|
||
node
|
||
and node.get("title", "")
|
||
and node["title"].startswith(API_OUTPUT_PREFIX)
|
||
):
|
||
aggregated_outputs[node["title"]] = output_data
|
||
logger.info(
|
||
f"收到节点 {node_id} 的输出 (Prompt ID: {prompt_id})"
|
||
)
|
||
|
||
# 更新节点状态为完成
|
||
await update_workflow_run_node_status(
|
||
workflow_run_id,
|
||
node_id,
|
||
"completed",
|
||
output_data=json.dumps(output_data),
|
||
)
|
||
|
||
# 处理整个工作流执行完成
|
||
elif msg_type == "executing" and data.get("node") is None:
|
||
logger.info(f"Prompt ID: {prompt_id} 执行完成。")
|
||
return aggregated_outputs
|
||
|
||
except websockets.exceptions.ConnectionClosed as e:
|
||
logger.warning(
|
||
f"WebSocket 连接已关闭 (Prompt ID: {prompt_id})。错误: {e}"
|
||
)
|
||
return aggregated_outputs
|
||
except Exception as e:
|
||
# 重新抛出我们自己的异常，或者处理其他意外错误
|
||
if not isinstance(e, ComfyUIExecutionError):
|
||
logger.error(f"处理 prompt {prompt_id} 时发生意外错误: {e}")
|
||
raise e
|
||
|
||
except websockets.exceptions.InvalidURI as e:
|
||
logger.error(
|
||
f"错误: 尝试连接的WebSocket URI无效: '{full_ws_url}'. 原始URL: '{ws_url}'. 错误: {e}"
|
||
)
|
||
raise e
|
||
return aggregated_outputs
|
||
|
||
|
||
async def _get_execution_results_legacy(
|
||
prompt_id: str, client_id: str, ws_url: str
|
||
) -> dict:
|
||
"""
|
||
简化版的执行结果获取函数，不包含数据库状态跟踪。
|
||
"""
|
||
full_ws_url = f"{ws_url}?clientId={client_id}"
|
||
aggregated_outputs = {}
|
||
|
||
try:
|
||
async with websockets.connect(full_ws_url) as websocket:
|
||
while True:
|
||
try:
|
||
out = await websocket.recv()
|
||
if not isinstance(out, str):
|
||
continue
|
||
|
||
message = json.loads(out)
|
||
msg_type = message.get("type")
|
||
data = message.get("data")
|
||
|
||
if not (data and data.get("prompt_id") == prompt_id):
|
||
continue
|
||
|
||
# 捕获并处理执行错误
|
||
if msg_type == "execution_error":
|
||
error_data = data
|
||
logger.error(
|
||
f"ComfyUI执行错误 (Prompt ID: {prompt_id}): {error_data}"
|
||
)
|
||
# 抛出自定义异常，将错误详情传递出去
|
||
raise ComfyUIExecutionError(error_data)
|
||
|
||
# 处理节点执行完成
|
||
if msg_type == "executed":
|
||
node_id = data.get("node")
|
||
output_data = data.get("output")
|
||
if node_id and output_data:
|
||
aggregated_outputs[node_id] = output_data
|
||
logger.info(
|
||
f"收到节点 {node_id} 的输出 (Prompt ID: {prompt_id})"
|
||
)
|
||
|
||
# 处理整个工作流执行完成
|
||
elif msg_type == "executing" and data.get("node") is None:
|
||
logger.info(f"Prompt ID: {prompt_id} 执行完成。")
|
||
return aggregated_outputs
|
||
|
||
except websockets.exceptions.ConnectionClosed as e:
|
||
logger.warning(
|
||
f"WebSocket 连接已关闭 (Prompt ID: {prompt_id})。错误: {e}"
|
||
)
|
||
return aggregated_outputs
|
||
except Exception as e:
|
||
# 重新抛出我们自己的异常，或者处理其他意外错误
|
||
if not isinstance(e, ComfyUIExecutionError):
|
||
logger.error(f"处理 prompt {prompt_id} 时发生意外错误: {e}")
|
||
raise e
|
||
|
||
except websockets.exceptions.InvalidURI as e:
|
||
logger.error(
|
||
f"错误: 尝试连接的WebSocket URI无效: '{full_ws_url}'. 原始URL: '{ws_url}'. 错误: {e}"
|
||
)
|
||
raise e
|
||
|
||
return aggregated_outputs
|
||
|
||
|
||
async def upload_image_to_comfy(file_path: str, server: ComfyUIServer) -> str:
|
||
"""
|
||
上传文件到服务器。
|
||
file 是一个http链接
|
||
返回一个名称
|
||
"""
|
||
file_name = file_path.split("/")[-1]
|
||
file_data = await download_file(file_path)
|
||
|
||
form_data = aiohttp.FormData()
|
||
form_data.add_field("image", file_data, filename=file_name, content_type="image/*")
|
||
form_data.add_field("type", "input")
|
||
|
||
async with aiohttp.ClientSession() as session:
|
||
async with session.post(
|
||
f"{server.http_url}/api/upload/image", data=form_data
|
||
) as response:
|
||
response.raise_for_status()
|
||
result = await response.json()
|
||
return result["name"]
|
||
|
||
|
||
async def download_file(src: str) -> bytes:
|
||
"""
|
||
下载文件到本地。
|
||
"""
|
||
async with aiohttp.ClientSession() as session:
|
||
async with session.get(src) as response:
|
||
response.raise_for_status()
|
||
return await response.read()
|