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✨ feat!(llm): 重构并升级大语言模型服务为全新 AI 智能体框架 (#2146)
* ✨ feat!(llm): 重构并升级大语言模型服务为全新 AI 智能体框架 - 【重构】将原 services/llm 重构并迁移至全新的 services/ai 架构，提供向下兼容垫片 - 【新增】引入 Agent、Team、Workflow 三大智能体与工作流编排范式 - 【新增】引入基于 RAG 的长期向量记忆与中期槽位记忆系统 - 【新增】引入基于 Docker 的安全代码执行沙箱环境 - 【新增】支持 MCP 协议，允许动态管理和调用 MCP 服务 - 【新增】引入输入输出安全合规护栏与自愈反思机制 - 【优化】重构并优化多厂商 API 适配器 (Gemini, OpenAI, DeepSeek, GLM 等) - 【优化】优化日志脱敏与 Token 预估机制 - 【移除】移除旧版 llm default 和 llm reset-key 命令，新增 llm mcp 管理命令 * 🔧 chore(deps): 更新项目依赖与配置 - 添加 mcp、jieba 和 aiodocker 依赖到配置文件及 requirements.txt - 在 pyright 配置中设置 reportMissingImports 为 none - 调整 .gitignore 中 resources 目录的忽略规则 * ♻️ refactor(tools): 重构工具终止机制并清理知识库日志输出 - 统一使用 `context.state["__end_run__"]` 替代 `EndRunResult` 控制任务结束 - 移除文件系统和向量知识库检索工具中 `ToolResult` 的 `.with_log` 调用 - 调整指令处理器（Directive）的返回值为 `tool_res.output` - 修复部分类型检查警告并优化联合类型判断语法 * ♻️ refactor(tools): 重构工具副作用指令与控制流熔断机制 - 引入 `DirectivePayload` 及 `ToolResult` 的子类以结构化表达工具副作用 - 移除通过 `context.state` 传递魔术变量的隐式控制流设计 - 重构 `DirectiveManager` 处理器接口，直接在处理器中修改 `AgentState` 并构建 `AgentRunResult` - 在 `StandardAgentExecutor` 中统一通过 `directive_manager` 调度工具返回的副作用指令 - 补全 `MessageBuilder` 中部分核心方法的文档注释 * 🐛 fix(sandbox): 修复 Docker 沙箱容器状态检测与会话清理逻辑 -【修复】修正 `is_alive` 中直接读取私有属性的问题，改用 `show()` 返回值 -【修复】解决 `execute_code` 中缓存的执行器与当前会话不一致的问题 -【优化】在清理工作区前增加容器存活检测，避免向已死容器发送请求 -【优化】创建容器时增加运行状态校验，若已停止则自动从缓存中移除并重建 -【优化】优化容器销毁和清理逻辑，静默处理容器不存在 (404) 的异常 * 📝 docs(core): 补充核心模块初始化方法的文档注释 * 🚨 auto fix by pre-commit hooks --------- Co-authored-by: webjoin111 <455457521@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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parent
bdc1374848
commit
80fc5b86a7
@@ -1,120 +1,387 @@
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"""
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LLM 服务模块 - 公共 API 入口
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向下兼容门面 (Facade)
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提供统一的 AI 服务调用接口、核心类型定义和模型管理功能。
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利用 sys.modules 魔法，将对 zhenxun.services.llm 及其子模块的导入
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无缝重定向到 zhenxun.services.ai.llm 下，避免破坏任何第三方插件。
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同时在此提供最常用的类导出，作为 LLM 服务的统一入口。
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"""
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from .api import (
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chat,
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code,
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create_image,
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embed,
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embed_documents,
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embed_query,
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generate,
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generate_structured,
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search,
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)
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from .config import (
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CommonOverrides,
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GenConfigBuilder,
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LLMGenerationConfig,
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register_llm_configs,
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import sys
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from types import ModuleType
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from typing import Any
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from zhenxun.services import logger
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logger.warning(
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"zhenxun.services.llm 已被重构迁移至 zhenxun.services.ai.llm，"
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"为了更好的性能和兼容性，请及时更新您的插件导入路径。"
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)
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register_llm_configs()
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from .api import ModelName
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from .manager import (
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clear_model_cache,
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get_cache_stats,
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get_global_default_model_name,
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from pydantic import BaseModel, ConfigDict
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import zhenxun.services.ai.core
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import zhenxun.services.ai.core.exceptions
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import zhenxun.services.ai.core.messages
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from zhenxun.services.ai.core.messages import ChatResponse as LLMResponse
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from zhenxun.services.ai.core.messages import LLMContentPart, ToolCallPart
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import zhenxun.services.ai.core.models
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from zhenxun.services.ai.core.models import ToolDefinition
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import zhenxun.services.ai.core.options
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import zhenxun.services.ai.core.protocols
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from zhenxun.services.ai.core.protocols.tool import ToolExecutable
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import zhenxun.services.ai.llm
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import zhenxun.services.ai.llm.system.capabilities
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from zhenxun.services.ai.run import RunContext as RealRunContext
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import zhenxun.services.ai.tools
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from zhenxun.services.ai.tools.models import ToolResult
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_legacy_types_module = ModuleType("zhenxun.services.llm.types")
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for _mod in (
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zhenxun.services.ai.core.options,
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zhenxun.services.ai.core.exceptions,
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zhenxun.services.ai.core.messages,
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zhenxun.services.ai.core.models,
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):
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for _name in dir(_mod):
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if not _name.startswith("_"):
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setattr(_legacy_types_module, _name, getattr(_mod, _name))
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sys.modules["zhenxun.services.llm.types"] = _legacy_types_module
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sys.modules["zhenxun.services.llm.types.models"] = zhenxun.services.ai.core.models
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sys.modules["zhenxun.services.llm.types.protocols"] = zhenxun.services.ai.core.protocols
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sys.modules["zhenxun.services.llm.types.exceptions"] = (
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zhenxun.services.ai.core.exceptions
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)
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sys.modules["zhenxun.services.llm.types.capabilities"] = (
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zhenxun.services.ai.llm.system.capabilities
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)
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prefix_old = "zhenxun.services.llm"
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prefix_new = "zhenxun.services.ai.llm"
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for module_name, module_obj in list(sys.modules.items()):
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if module_name.startswith(prefix_new):
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old_module_name = module_name.replace(prefix_new, prefix_old, 1)
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if old_module_name not in sys.modules:
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sys.modules[old_module_name] = module_obj
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sys.modules["zhenxun.services.llm.tools"] = zhenxun.services.ai.tools
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class LLMToolFunction(BaseModel):
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name: str
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arguments: str
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class LLMToolCall(BaseModel):
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id: str
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function: LLMToolFunction
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thought_signature: str | None = None
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type: str = "function"
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class _FakeFunction:
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def __init__(self, name, args):
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self.name = name
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self.arguments = (
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args
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if isinstance(args, str)
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else __import__("json").dumps(args, ensure_ascii=False)
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)
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@property
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def _legacy_function(self) -> _FakeFunction:
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return _FakeFunction(self.tool_name, self.args)
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setattr(ToolCallPart, "function", _legacy_function) # type: ignore
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@property
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def _legacy_thought_signature(self) -> Any:
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return self.metadata.get("thought_signature") if self.metadata else None
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@_legacy_thought_signature.setter
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def _legacy_thought_signature(self, value: Any) -> None:
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if self.metadata is None:
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self.metadata = {}
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self.metadata["thought_signature"] = value
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setattr(ToolCallPart, "thought_signature", _legacy_thought_signature) # type: ignore
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from zhenxun.services.ai.core.messages import LLMMessage
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_original_assistant_tool_calls = LLMMessage.assistant_tool_calls
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@classmethod
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def _shim_assistant_tool_calls(
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cls, tool_calls: Any, content: Any = "", scope: Any = None
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) -> Any:
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converted = []
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for tc in tool_calls:
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if hasattr(tc, "function") and not isinstance(tc, ToolCallPart):
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converted.append(
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ToolCallPart(
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id=tc.id, tool_name=tc.function.name, args=tc.function.arguments
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)
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)
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else:
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converted.append(tc)
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return _original_assistant_tool_calls(converted, content, scope) # type: ignore
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setattr(LLMMessage, "assistant_tool_calls", _shim_assistant_tool_calls) # type: ignore
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if not hasattr(LLMMessage, "name"):
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@property
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def _legacy_name(self) -> Any:
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return getattr(self, "source_name", None)
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@_legacy_name.setter
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def _legacy_name(self, value: Any) -> None:
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self.source_name = value
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setattr(LLMMessage, "name", _legacy_name) # type: ignore
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if not hasattr(LLMMessage, "tool_call_id"):
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@property
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def _legacy_tool_call_id(self) -> Any:
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return None
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@_legacy_tool_call_id.setter
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def _legacy_tool_call_id(self, value: Any) -> None:
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pass
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setattr(LLMMessage, "tool_call_id", _legacy_tool_call_id) # type: ignore
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from zhenxun.services.ai.core.options import GenerationConfig, ReasoningEffort
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mod_config_gen = ModuleType("zhenxun.services.llm.config.generation")
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sys.modules["zhenxun.services.llm.config"] = ModuleType("zhenxun.services.llm.config")
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sys.modules["zhenxun.services.llm.config.generation"] = mod_config_gen
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class ReasoningConfig(BaseModel):
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model_config = ConfigDict(extra="allow") # type: ignore
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class ToolConfig(BaseModel):
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model_config = ConfigDict(extra="allow") # type: ignore
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setattr(mod_config_gen, "LLMGenerationConfig", GenerationConfig) # type: ignore
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setattr(mod_config_gen, "ReasoningConfig", ReasoningConfig) # type: ignore
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setattr(mod_config_gen, "ToolConfig", ToolConfig) # type: ignore
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setattr(mod_config_gen, "ReasoningEffort", ReasoningEffort) # type: ignore
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_target_models_mod = sys.modules["zhenxun.services.llm.types.models"]
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setattr(_target_models_mod, "ToolResult", ToolResult) # type: ignore
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setattr(_target_models_mod, "LLMToolCall", LLMToolCall) # type: ignore
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setattr(_target_models_mod, "LLMToolFunction", LLMToolFunction) # type: ignore
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setattr(_target_models_mod, "LLMContentPart", LLMContentPart) # type: ignore
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setattr(_target_models_mod, "ToolDefinition", ToolDefinition) # type: ignore
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setattr(_target_models_mod, "LLMResponse", LLMResponse) # type: ignore
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setattr(_target_models_mod, "LLMMessage", LLMMessage) # type: ignore
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setattr(
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sys.modules["zhenxun.services.llm.types.protocols"],
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"ToolExecutable",
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ToolExecutable,
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) # type: ignore
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class LegacyRunContextShim:
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"""拦截旧版 RunContext(extra={...}) 的调用，转化为新版支持的 state"""
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def __new__(cls, session_id=None, extra=None, scope=None, **kwargs):
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state = kwargs.get("state", {})
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if extra:
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state.update(extra)
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if scope:
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state.update(scope)
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ctx = RealRunContext(session_id=session_id, state=state)
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ctx.extra = ctx.state # type: ignore
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ctx.scope = ctx.state # type: ignore
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return ctx
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setattr(sys.modules["zhenxun.services.llm.tools"], "RunContext", LegacyRunContextShim) # type: ignore
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class ToolInvoker:
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"""向下兼容垫片：代替被重构移除的旧版 ToolInvoker"""
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def __init__(self, callbacks=None):
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self.callbacks = callbacks or []
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async def execute_tool_call(self, tool_call, available_tools, context=None):
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import json
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if hasattr(tool_call, "function") and hasattr(tool_call.function, "name"):
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tool_name = tool_call.function.name
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args_raw = tool_call.function.arguments
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else:
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tool_name = getattr(tool_call, "tool_name", "unknown")
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args_raw = getattr(tool_call, "args", "{}")
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arguments = {}
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if args_raw:
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if isinstance(args_raw, str):
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try:
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arguments = json.loads(args_raw)
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except Exception:
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pass
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elif isinstance(args_raw, dict):
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arguments = args_raw
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executable = available_tools.get(tool_name)
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if not executable:
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return tool_call, ToolResult(output=f"Error: Tool '{tool_name}' not found.")
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try:
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result = await executable.execute(context=context, **arguments)
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if not hasattr(result, "output"):
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result = ToolResult(output=result)
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return tool_call, result
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except Exception as e:
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return tool_call, ToolResult(output=f"System Execution Error: {e!s}")
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import zhenxun.services.ai.tools
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setattr(zhenxun.services.ai.tools, "ToolInvoker", ToolInvoker) # type: ignore
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setattr(sys.modules["zhenxun.services.llm.tools"], "ToolInvoker", ToolInvoker) # type: ignore
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class CommonOverrides:
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"""向下兼容垫片：由于该类已被废弃，此处提供空实现以防止旧插件导入报错。"""
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@staticmethod
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def _fallback(*args, **kwargs):
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from zhenxun.services.ai.llm.builder import IntentBuilder
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return IntentBuilder().build()
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gemini_json = _fallback
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gemini_2_5_thinking = _fallback
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gemini_3_thinking = _fallback
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gemini_structured = _fallback
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gemini_safe = _fallback
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gemini_code_execution = _fallback
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gemini_grounding = _fallback
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gemini_nano_banana = _fallback
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gemini_high_res = _fallback
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from zhenxun.services.ai.core.options import GenerationConfig, OutputFormatConfig
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class OutputConfig(OutputFormatConfig):
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"""向下兼容垫片：旧版 OutputConfig 等价于 OutputFormatConfig。"""
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AIConfig = GenerationConfig
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LLMGenerationConfig = GenerationConfig
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from zhenxun.services.ai.llm import * # noqa: F403
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from zhenxun.services.ai.llm.manager import (
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get_default_model,
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get_model_instance,
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list_available_models,
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list_embedding_models,
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list_model_identifiers,
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set_global_default_model_name,
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)
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from .memory import (
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AIConfig,
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BaseMemory,
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MemoryProcessor,
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set_default_memory_backend,
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)
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from .session import AI
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from .tools import RunContext, ToolInvoker, function_tool, tool_provider_manager
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from .types import (
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EmbeddingTaskType,
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LLMContentPart,
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LLMErrorCode,
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LLMException,
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LLMMessage,
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LLMResponse,
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ModelDetail,
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ModelInfo,
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ModelProvider,
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ResponseFormat,
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TaskType,
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ToolCategory,
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ToolMetadata,
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UsageInfo,
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)
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from .types.models import (
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GeminiCodeExecution,
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GeminiGoogleSearch,
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GeminiUrlContext,
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)
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from .utils import create_multimodal_message, message_to_unimessage, unimsg_to_llm_parts
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from zhenxun.services.ai.message_builder import MessageBuilder
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message_to_unimessage = MessageBuilder.message_to_unimessage
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unimsg_to_llm_parts = MessageBuilder.unimsg_to_llm_parts
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from zhenxun.services.ai.core.exceptions import LLMException
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from zhenxun.services.ai.core.messages import ChatRequest
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from zhenxun.services.ai.core.messages import ChatResponse as LLMResponse
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from zhenxun.services.ai.llm.api import generate_structured as _new_generate_structured
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from zhenxun.services.ai.llm.engine.router import LLMOrchestrator
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from zhenxun.services.ai.tools import tool as function_tool
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class AI:
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"""向下兼容垫片：代替被彻底删除的旧版 AI 类"""
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def __init__(self, session_id=None, **kwargs):
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self.session_id = session_id
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async def generate_internal(
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self,
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messages,
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model=None,
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config=None,
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tools=None,
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tool_choice=None,
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timeout=None,
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):
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req = ChatRequest(
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messages=messages,
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config=config,
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tools=tools,
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tool_choice=tool_choice,
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timeout=timeout,
|
||||
)
|
||||
if self.session_id:
|
||||
req.extra["session_id"] = self.session_id
|
||||
return await LLMOrchestrator.invoke(req, model_name=model, task="chat")
|
||||
|
||||
async def generate_structured(
|
||||
self,
|
||||
message,
|
||||
response_model,
|
||||
model=None,
|
||||
tools=None,
|
||||
tool_choice=None,
|
||||
instruction=None,
|
||||
timeout=None,
|
||||
template_vars=None,
|
||||
config=None,
|
||||
max_validation_retries=None,
|
||||
validation_callback=None,
|
||||
error_prompt_template=None,
|
||||
auto_thinking=False,
|
||||
):
|
||||
return await _new_generate_structured(
|
||||
message=message,
|
||||
response_model=response_model,
|
||||
model=model,
|
||||
instruction=instruction,
|
||||
timeout=timeout,
|
||||
config=config,
|
||||
max_retries=max_validation_retries,
|
||||
error_prompt_template=error_prompt_template,
|
||||
)
|
||||
|
||||
|
||||
__all__ = [
|
||||
"AI",
|
||||
"AIConfig",
|
||||
"BaseMemory",
|
||||
"CommonOverrides",
|
||||
"EmbeddingTaskType",
|
||||
"GeminiCodeExecution",
|
||||
"GeminiGoogleSearch",
|
||||
"GeminiUrlContext",
|
||||
"GenConfigBuilder",
|
||||
"GenerationConfig",
|
||||
"LLMContentPart",
|
||||
"LLMErrorCode",
|
||||
"LLMException",
|
||||
"LLMGenerationConfig",
|
||||
"LLMMessage",
|
||||
"LLMResponse",
|
||||
"MemoryProcessor",
|
||||
"ModelDetail",
|
||||
"ModelInfo",
|
||||
"ModelName",
|
||||
"ModelProvider",
|
||||
"ResponseFormat",
|
||||
"RunContext",
|
||||
"TaskType",
|
||||
"ToolCategory",
|
||||
"LLMToolCall",
|
||||
"LLMToolFunction",
|
||||
"OutputConfig",
|
||||
"ToolDefinition",
|
||||
"ToolExecutable",
|
||||
"ToolInvoker",
|
||||
"ToolMetadata",
|
||||
"UsageInfo",
|
||||
"chat",
|
||||
"clear_model_cache",
|
||||
"code",
|
||||
"create_image",
|
||||
"create_multimodal_message",
|
||||
"embed",
|
||||
"embed_documents",
|
||||
"embed_query",
|
||||
"ToolResult",
|
||||
"function_tool",
|
||||
"generate",
|
||||
"generate_structured",
|
||||
"get_cache_stats",
|
||||
"get_global_default_model_name",
|
||||
"get_default_model",
|
||||
"get_model_instance",
|
||||
"list_available_models",
|
||||
"list_embedding_models",
|
||||
"list_model_identifiers",
|
||||
"message_to_unimessage",
|
||||
"register_llm_configs",
|
||||
"search",
|
||||
"set_default_memory_backend",
|
||||
"set_global_default_model_name",
|
||||
"tool_provider_manager",
|
||||
"unimsg_to_llm_parts",
|
||||
]
|
||||
|
||||
Reference in New Issue
Block a user