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MuWinds
ac57ad0c18
LLM 层重构： - 将 LLM 调用层重构为 Provider 模式，支持多 API 类型 - 新增 Anthropic、OpenAI Chat、OpenAI Responses 三种 Provider - 新增 LLM 类型定义和工厂类 WebSocket 重连： - 添加指数退避自动重连机制（初始 1s，最大 30s，最多 10 次） - 区分手动关闭与意外断开，仅意外断开触发重连 - 在任务页面顶部添加连接状态指示灯（绿/黄/红） 图表字体跨平台兼容： - 在 backend/fonts/ 存放 SimHei 字体文件 - create_work_dir() 自动复制字体到任务工作目录 - 两个解释器从工作目录动态加载字体 - E2B 移除 apt-get install 依赖，改用上传字体文件 - 统一三处字体优先级配置 其他： - 重构注释规范、修复类型错误、添加 lint hook - 更新 CLAUDE.md 项目文档
140 lines
3.8 KiB
Python
140 lines
3.8 KiB
Python
"""响应数据模型定义，包括消息类型和代码执行结果。"""
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from typing import Literal, Union
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from app.schemas.enums import AgentType
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from pydantic import BaseModel, Field
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from uuid import uuid4
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class Message(BaseModel):
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"""消息基类。"""
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id: str = Field(default_factory=lambda: str(uuid4()))
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msg_type: str # system | agent | user | tool | approval
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content: str | None = None
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class ToolMessage(Message):
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msg_type: Literal["system", "agent", "user", "tool"] = "tool" # type: ignore[assignment]
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tool_name: Literal["execute_code", "search_scholar"]
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input: dict | None = None
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output: list | None = None
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class SystemMessage(Message):
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msg_type: Literal["system", "agent", "user", "tool"] = "system" # type: ignore[assignment]
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type: Literal["info", "warning", "success", "error"] = "info"
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class UserMessage(Message):
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msg_type: Literal["system", "agent", "user", "tool"] = "user" # type: ignore[assignment]
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class AgentMessage(Message):
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msg_type: Literal["system", "agent", "user", "tool"] = "agent" # type: ignore[assignment]
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agent_type: AgentType # CoordinatorAgent | ModelerAgent | CoderAgent | WriterAgent
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class ModelerMessage(AgentMessage):
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agent_type: AgentType = AgentType.MODELER
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class CoordinatorMessage(AgentMessage):
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agent_type: AgentType = AgentType.COORDINATOR
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class CodeExecution(BaseModel):
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"""代码执行结果基类。"""
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res_type: Literal["stdout", "stderr", "result", "error"]
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msg: str | None = None
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class StdOutModel(CodeExecution):
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res_type: Literal["stdout", "stderr", "result", "error"] = "stdout" # type: ignore[assignment]
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class StdErrModel(CodeExecution):
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res_type: Literal["stdout", "stderr", "result", "error"] = "stderr" # type: ignore[assignment]
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class ResultModel(CodeExecution):
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res_type: Literal["stdout", "stderr", "result", "error"] = "result" # type: ignore[assignment]
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format: Literal[
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"text",
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"html",
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"markdown",
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"png",
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"jpeg",
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"svg",
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"pdf",
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"latex",
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"json",
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"javascript",
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]
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class ErrorModel(CodeExecution):
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res_type: Literal["stdout", "stderr", "result", "error"] = "error" # type: ignore[assignment]
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name: str
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value: str
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traceback: str
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# 代码执行结果类型
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OutputItem = Union[StdOutModel, StdErrModel, ResultModel, ErrorModel]
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class ScholarMessage(ToolMessage):
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tool_name: Literal["execute_code", "search_scholar"] = "search_scholar" # type: ignore[assignment]
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input: dict | None = None # query
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output: list[str] | None = None # cites
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class InterpreterMessage(ToolMessage):
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tool_name: Literal["execute_code", "search_scholar"] = "execute_code" # type: ignore[assignment]
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input: dict | None = None # code
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output: list[OutputItem] | None = None # code_results
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# 1. 只带 code
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# 2. 只带 code result
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class CoderMessage(AgentMessage):
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agent_type: AgentType = AgentType.CODER
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class WriterMessage(AgentMessage):
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agent_type: AgentType = AgentType.WRITER
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sub_title: str | None = None
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class ApprovalMessage(Message):
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"""HIL 审批消息，发送到前端触发审批对话框。"""
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msg_type: Literal["system", "agent", "user", "tool", "approval"] = "approval" # type: ignore[assignment]
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checkpoint_id: str = ""
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prompt: dict = Field(default_factory=dict)
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options: list[str] = Field(
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default_factory=lambda: [
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"confirm",
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"edit",
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"regenerate",
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"ask",
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"skip",
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"abort",
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]
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)
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timeout: int = 300
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# 所有可能的消息类型
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MessageType = Union[
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SystemMessage,
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UserMessage,
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AgentMessage,
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ToolMessage,
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ScholarMessage,
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InterpreterMessage,
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CoderMessage,
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WriterMessage,
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ModelerMessage,
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CoordinatorMessage,
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]
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