224 lines
7.5 KiB
Python
224 lines
7.5 KiB
Python
"""
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LLM 节点基类
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为 LLM 类节点(扩写、翻译等)提供专用基础能力
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V3 迁移说明:
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所有原实例方法(self)均已转换为类方法(cls),以适配 V3 execute 必须为 @classmethod 的要求。
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"""
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import asyncio
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from typing import Any, Callable, Dict, Optional
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from .base_node import BaseNode
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from ...utils.common import format_api_error
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class LLMNodeBase(BaseNode):
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"""
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LLM 节点基类(V3 Mixin 版本)
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提供 LLM 节点专用功能:
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- LLM Provider 配置获取
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- LLM 相关的通用逻辑
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- 动态服务/模型列表生成
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"""
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@staticmethod
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def get_llm_service_options():
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"""
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获取所有可用的 LLM 服务/模型选项列表
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返回格式: ["百度翻译", "智谱/glm-4-flash", "Ollama/qwen3:14b", ...]
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百度翻译服务无模型概念,仅显示服务名;其他服务显示为"服务名/模型名"格式
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返回:
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List[str]: 服务/模型选项列表
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"""
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from ...config_manager import config_manager
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options = []
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services = config_manager.get_all_services()
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for service in services:
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service_name = service.get('name', '')
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service_type = service.get('type', '')
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# 百度翻译特殊处理:仅显示服务名
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if service_type == 'baidu':
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options.append(service_name)
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continue
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# 其他服务:遍历 llm_models
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llm_models = service.get('llm_models', [])
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for model in llm_models:
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model_name = model.get('name', '')
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if model_name:
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# 格式: "服务名/模型名"
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options.append(f"{service_name}/{model_name}")
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# 如果没有任何选项,返回默认值避免 ComfyUI 报错
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if not options:
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options = ["智谱"]
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return options
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@staticmethod
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def get_translate_service_options():
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"""
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获取翻译服务专用的服务/模型选项列表
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与 get_llm_service_options 的区别:
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- 硬编码添加"百度翻译"选项(百度翻译使用独立配置,不在 model_services 中)
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- 专门用于翻译节点和翻译按钮
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返回格式: ["百度翻译", "智谱/glm-4-flash", "Ollama/qwen3:14b", ...]
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返回:
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List[str]: 服务/模型选项列表(包含百度翻译)
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"""
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from ...config_manager import config_manager
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options = []
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# ---硬编码添加百度翻译---
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# 百度翻译使用独立的 baidu_translate 配置,不在 model_services 列表中
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config_manager.load_config().get('baidu_translate', {})
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# 即使没有配置 app_id,也要显示百度选项
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options.append("百度翻译")
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# ---动态获取其他 LLM 服务---
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services = config_manager.get_all_services()
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for service in services:
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service_name = service.get('name', '')
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# 遍历 llm_models
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llm_models = service.get('llm_models', [])
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for model in llm_models:
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model_name = model.get('name', '')
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if model_name:
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# 格式: "服务名/模型名"
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options.append(f"{service_name}/{model_name}")
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return options
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@staticmethod
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def parse_service_model(service_model_str: str):
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"""
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解析"服务名/模型名"格式的字符串
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特殊处理:
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- "百度翻译": 返回 ('baidu', None) - 百度翻译使用独立配置
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参数:
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service_model_str: 服务/模型字符串,例如 "智谱/glm-4-flash" 或 "百度翻译"
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返回:
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Tuple[str, Optional[str]]: (service_id, model_name)
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- service_id: 服务 ID(如 'zhipu', 'baidu')
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- model_name: 模型名称,如果没有则为 None
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"""
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from ...config_manager import config_manager
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# 分割字符串
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if '/' in service_model_str:
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service_name, model_name = service_model_str.split('/', 1)
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else:
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service_name = service_model_str
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model_name = None
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# ---特殊处理:百度翻译---
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if service_name in ['百度翻译', '百度', 'baidu']:
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return 'baidu', None
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# 查找对应的 service_id
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services = config_manager.get_all_services()
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for service in services:
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if service.get('name') == service_name:
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return service.get('id'), model_name
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# 未找到,返回 None
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return None, None
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@classmethod
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def _get_provider_config(
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cls,
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config_manager: Any,
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provider: str
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) -> Optional[Dict[str, Any]]:
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"""
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获取指定 LLM Provider 的配置
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参数:
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config_manager: 配置管理器实例
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provider: Provider 标识符(如 'zhipu', 'ollama' 等)
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返回:
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Provider 配置字典,如果未找到则返回 None
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"""
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llm_config = config_manager.get_llm_config()
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if 'providers' in llm_config and provider in llm_config['providers']:
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return llm_config['providers'][provider]
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return None
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@classmethod
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def _run_llm_task(
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cls,
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llm_service_func: Callable,
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provider: str,
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*args,
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**kwargs
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) -> Dict[str, Any]:
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"""
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执行 LLM 任务(扩写/翻译)的统一方法
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封装了:
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1. 异步任务的线程执行
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2. 中断异常的捕获和处理
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3. API 异常的格式化
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参数:
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llm_service_func: LLMService 的异步方法
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provider: Provider 名称(用于错误格式化)
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*args, **kwargs: 传递给 llm_service_func 的参数
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返回:
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{"success": bool, "data": dict, "error": str} 格式的结果
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"""
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def thread_task(result_container, cancel_event):
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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try:
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# 将 cancel_event 传递给服务函数
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kwargs['cancel_event'] = cancel_event
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result = loop.run_until_complete(llm_service_func(*args, **kwargs))
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result_container['result'] = result
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except (asyncio.CancelledError, KeyboardInterrupt):
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print(f"{cls.LOG_PREFIX} 异步任务被取消")
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result_container['result'] = {"success": False, "error": "任务被中断"}
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except Exception as e:
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# 捕获其他异常,格式化错误信息
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error_message = format_api_error(e, provider)
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result_container['result'] = {"success": False, "error": error_message}
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finally:
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# 清理所有未完成的任务,消除 "Task was destroyed but it is pending" 警告
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try:
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pending = asyncio.all_tasks(loop)
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if pending:
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for task in pending:
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task.cancel()
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# 等待任务取消完成,忽略取消错误
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loop.run_until_complete(asyncio.gather(*pending, return_exceptions=True))
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except Exception:
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pass
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finally:
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loop.close()
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# 创建取消事件
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import threading
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cancel_event = threading.Event()
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return cls._execute_with_interrupt(thread_task, (), cancel_event)
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