756 lines
25 KiB
Python
756 lines
25 KiB
Python
"""
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MACP 业务服务层模块。
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为平台各功能模块提供业务逻辑实现，基于内存假数据模拟完整业务流程。
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包含以下服务：
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- TemplateService: 文档模板管理服务
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- GjbValidatorService: GJB合规验证服务
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- DocumentService: 文档管理服务
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- SkillService: Skills编排服务
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- MemoryService: 智能体记忆管理服务
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- KnowledgeBaseService: 知识库交互服务
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- ModelService: 大模型接入管理服务
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- MultimodalService: 多模态处理服务
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- SandboxService: 安全沙箱执行服务
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- McpToolService: MCP工具管理服务
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"""
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from __future__ import annotations
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import uuid
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from datetime import datetime
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from typing import Any, Optional
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from app.models import (
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Document,
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DocumentStatus,
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FileType,
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GjbRule,
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GjbStandard,
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KnowledgeChunk,
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KnowledgeLevel,
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McpTool,
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MemoryEntry,
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MemoryType,
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ModelProfile,
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ModelStatus,
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MultimodalResult,
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Skill,
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Template,
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TemplateType,
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ValidationReport,
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Workflow,
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)
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# =============================================================================
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# 假数据初始化
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# =============================================================================
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def _init_mock_templates() -> dict[str, Template]:
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"""初始化假数据模板库"""
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templates = {}
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t1 = Template(
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id="TPL-001",
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name="GJB438C 软件需求规格说明书模板",
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template_type=TemplateType.SRS,
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gjb_standard=GjbStandard.GJB438C,
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version="2.0",
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content_structure={
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"sections": [
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{"id": "1", "title": "范围", "required": True},
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{"id": "2", "title": "引用文档", "required": True},
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{"id": "3", "title": "需求", "required": True},
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{"id": "3.1", "title": "功能需求", "required": True},
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{"id": "3.2", "title": "接口需求", "required": True},
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{"id": "4", "title": "合格性需求", "required": True},
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{"id": "5", "title": "需求可追踪性", "required": False},
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]
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},
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author="系统管理员",
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)
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t2 = Template(
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id="TPL-002",
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name="GJB438C 软件设计说明书模板",
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template_type=TemplateType.SDD,
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gjb_standard=GjbStandard.GJB438C,
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version="1.5",
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content_structure={
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"sections": [
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{"id": "1", "title": "范围", "required": True},
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{"id": "2", "title": "引用文档", "required": True},
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{"id": "3", "title": "软件体系结构设计", "required": True},
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{"id": "4", "title": "软件详细设计", "required": True},
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]
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},
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author="系统管理员",
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)
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templates[t1.id] = t1
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templates[t2.id] = t2
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return templates
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def _init_mock_rules() -> dict[str, GjbRule]:
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"""初始化假数据GJB规则库"""
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rules = {}
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rule_data = [
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("R-001", "1", "文档必须包含'范围'章节，说明软件用途和背景", True, [TemplateType.SRS, TemplateType.SDD], "建议在文档开头添加'范围'章节"),
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("R-002", "2", "文档必须包含'引用文档'章节，列出所有参考文献", True, [TemplateType.SRS, TemplateType.SDD], "建议添加'引用文档'章节并列出参考文献"),
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("R-003", "3", "需求规格说明书必须包含功能需求和接口需求", True, [TemplateType.SRS], "请补充功能需求和接口需求章节"),
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("R-004", "3.1", "每项功能需求必须有唯一标识符", True, [TemplateType.SRS], "请为功能需求添加唯一标识符"),
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("R-005", "3.2", "接口需求应明确输入输出数据格式", True, [TemplateType.SRS], "请补充接口的数据格式说明"),
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("R-006", "4", "文档应包含合格性需求章节", False, [TemplateType.SRS], "建议添加合格性需求章节"),
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("R-007", "5", "需求应具备可追踪性", False, [TemplateType.SRS], "建议添加需求追踪矩阵"),
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]
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for rid, sec, req, man, types, sug in rule_data:
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rules[rid] = GjbRule(
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id=rid,
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section=sec,
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requirement=req,
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mandatory=man,
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applicable_types=types,
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suggestion=sug,
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)
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return rules
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def _init_mock_documents() -> dict[str, Document]:
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"""初始化假数据文档库"""
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docs = {}
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d1 = Document(
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id="DOC-001",
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title="某型雷达系统软件需求规格说明书",
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template_id="TPL-001",
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current_version="1.0",
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content="# 1. 范围\n\n本文档描述了某型雷达系统的软件需求。\n\n# 2. 引用文档\n\n- GJB438C-2021\n\n# 3. 需求\n\n## 3.1 功能需求\n\n- FR-001: 目标探测功能\n- FR-002: 目标跟踪功能\n\n## 3.2 接口需求\n\n...",
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edit_history=[
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{"version": "1.0", "editor": "张三", "timestamp": "2024-01-15T10:00:00Z"},
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],
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status=DocumentStatus.DRAFT,
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)
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d2 = Document(
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id="DOC-002",
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title="某型通信系统软件设计说明书",
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template_id="TPL-002",
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current_version="1.0",
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content="# 1. 范围\n\n本文档描述了某型通信系统的软件设计。\n\n# 2. 引用文档\n\n- GJB438C-2021\n\n# 3. 软件体系结构设计\n\n采用分层架构设计。",
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status=DocumentStatus.SUBMITTED,
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)
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docs[d1.id] = d1
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docs[d2.id] = d2
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return docs
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def _init_mock_skills() -> dict[str, Skill]:
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"""初始化假数据Skills库"""
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skills = {}
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s1 = Skill(
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id="SK-001",
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name="文档合规审查",
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prompt_template="请根据GJB标准对以下文档进行合规性审查：{document_content}",
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associated_tools=["gjb_validator", "llm_analyzer"],
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input_definition={"document_id": "string"},
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output_definition={"report": "object"},
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orchestration_order=1,
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)
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s2 = Skill(
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id="SK-002",
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name="文档智能生成",
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prompt_template="请根据模板{template_id}生成{title}文档初稿",
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associated_tools=["template_loader", "llm_generator"],
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input_definition={"template_id": "string", "title": "string"},
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output_definition={"document": "object"},
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orchestration_order=2,
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)
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skills[s1.id] = s1
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skills[s2.id] = s2
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return skills
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def _init_mock_memories() -> dict[str, MemoryEntry]:
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"""初始化假数据记忆库"""
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memories = {}
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m1 = MemoryEntry(
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id="MEM-001",
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session_id="SESS-001",
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summary="用户询问GJB438C标准要求",
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original_dialogue="用户：GJB438C标准对需求文档有什么要求？\n助手：GJB438C标准要求需求文档包含范围、引用文档、需求等章节。",
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memory_type=MemoryType.LONG_TERM,
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)
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m2 = MemoryEntry(
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id="MEM-002",
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session_id="SESS-001",
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summary="用户创建了新文档模板",
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original_dialogue="用户：请创建一个新的SRS模板。\n助手：已创建完成，模板ID为TPL-003。",
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memory_type=MemoryType.SHORT_TERM,
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)
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memories[m1.id] = m1
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memories[m2.id] = m2
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return memories
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def _init_mock_knowledge() -> dict[str, KnowledgeChunk]:
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"""初始化假数据知识库"""
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chunks = {}
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c1 = KnowledgeChunk(
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id="KC-001",
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source_document="GJB438C-2021 军用软件文档编制要求",
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level=KnowledgeLevel.DOCUMENT,
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content="本标准规定了军用软件文档的编制要求，适用于军用软件的研制全过程。",
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metadata_tags=["GJB438C", "标准", "文档编制"],
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)
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c2 = KnowledgeChunk(
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id="KC-002",
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source_document="GJB438C-2021 军用软件文档编制要求",
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level=KnowledgeLevel.CHAPTER,
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content="第4章 软件需求规格说明书编制要求：应包括范围、引用文档、需求等章节。",
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metadata_tags=["GJB438C", "SRS", "需求规格说明书"],
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)
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c3 = KnowledgeChunk(
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id="KC-003",
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source_document="某型雷达系统软件需求规格说明书",
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level=KnowledgeLevel.PARAGRAPH,
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content="功能需求FR-001：系统应具备对空中目标的探测能力，探测距离不小于300km。",
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metadata_tags=["雷达系统", "功能需求", "FR-001"],
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)
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chunks[c1.id] = c1
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chunks[c2.id] = c2
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chunks[c3.id] = c3
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return chunks
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def _init_mock_models() -> dict[str, ModelProfile]:
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"""初始化假数据模型配置"""
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models = {}
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mp1 = ModelProfile(
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id="MDL-001",
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vendor="华为",
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api_url="https://api.huawei.com/v1/chat",
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is_primary=True,
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weight=2,
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)
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mp2 = ModelProfile(
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id="MDL-002",
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vendor="百度",
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api_url="https://api.baidu.com/v1/chat",
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is_primary=False,
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weight=1,
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)
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models[mp1.id] = mp1
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models[mp2.id] = mp2
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return models
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def _init_mock_mcp_tools() -> dict[str, McpTool]:
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"""初始化假数据MCP工具"""
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tools = {}
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t1 = McpTool(
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id="MCP-001",
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name="gjb_validator",
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description="GJB规则合规验证工具",
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json_schema={
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"type": "object",
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"properties": {
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"document_id": {"type": "string", "description": "待验证文档ID"},
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},
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"required": ["document_id"],
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},
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enabled=True,
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)
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t2 = McpTool(
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id="MCP-002",
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name="llm_analyzer",
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description="大模型智能分析工具",
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json_schema={
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"type": "object",
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"properties": {
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"prompt": {"type": "string", "description": "分析提示词"},
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"model_id": {"type": "string", "description": "模型ID"},
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},
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"required": ["prompt"],
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},
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enabled=True,
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)
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tools[t1.id] = t1
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tools[t2.id] = t2
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return tools
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def _init_mock_workflows() -> dict[str, Workflow]:
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"""初始化假数据工作流"""
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workflows = {}
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w1 = Workflow(
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id="WF-001",
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name="文档合规审查工作流",
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skill_ids=["SK-001", "SK-002"],
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logic={
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"type": "sequential",
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"steps": [
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{"skill_id": "SK-001", "on_success": "SK-002", "on_failure": "end"},
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],
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},
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)
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workflows[w1.id] = w1
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return workflows
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# =============================================================================
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# 服务类
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# =============================================================================
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class TemplateService:
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"""文档模板管理服务（SRS-MACP_F-001）"""
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def __init__(self):
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self._templates = _init_mock_templates()
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def list_templates(self) -> list[Template]:
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"""获取所有模板列表
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Returns:
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list[Template]: 模板列表
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"""
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return list(self._templates.values())
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def get_template(self, template_id: str) -> Optional[Template]:
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"""根据ID获取模板详情
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Args:
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template_id: 模板ID
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Returns:
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Optional[Template]: 模板对象，不存在时返回None
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"""
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return self._templates.get(template_id)
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def create_template(self, template: Template) -> Template:
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"""创建新模板
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Args:
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template: 模板对象（不含ID时自动生成）
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Returns:
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Template: 创建后的模板
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"""
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if not template.id:
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template.id = f"TPL-{uuid.uuid4().hex[:6].upper()}"
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template.created_at = datetime.now()
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self._templates[template.id] = template
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return template
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def delete_template(self, template_id: str) -> bool:
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"""删除模板
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Args:
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template_id: 模板ID
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Returns:
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bool: 是否删除成功
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"""
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if template_id in self._templates:
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del self._templates[template_id]
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return True
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return False
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class DocumentService:
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"""文档管理服务"""
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def __init__(self):
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self._documents = _init_mock_documents()
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def list_documents(self) -> list[Document]:
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"""获取所有文档列表"""
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return list(self._documents.values())
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def get_document(self, doc_id: str) -> Optional[Document]:
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"""根据ID获取文档详情"""
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return self._documents.get(doc_id)
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def create_document(self, document: Document) -> Document:
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"""创建新文档"""
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if not document.id:
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document.id = f"DOC-{uuid.uuid4().hex[:6].upper()}"
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document.created_at = datetime.now()
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document.updated_at = datetime.now()
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document.status = DocumentStatus.DRAFT
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self._documents[document.id] = document
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return document
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class GjbValidatorService:
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"""GJB合规验证服务（SRS-MACP_F-002）"""
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def __init__(self):
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self._rules = _init_mock_rules()
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self._reports: dict[str, ValidationReport] = {}
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def list_rules(self) -> list[GjbRule]:
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"""获取所有GJB规则"""
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return list(self._rules.values())
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def validate_document(self, document: Document) -> ValidationReport:
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"""对文档执行GJB合规验证
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模拟校验文档结构、章节完整性与格式规范。
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Args:
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document: 待验证文档
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Returns:
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ValidationReport: 验证报告
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"""
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report_id = f"VR-{uuid.uuid4().hex[:6].upper()}"
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non_compliant = []
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compliant_count = 0
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for rule in self._rules.values():
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# 模拟校验逻辑：检查模板章节是否在文档内容中
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found = rule.section in document.content or rule.requirement[:10] in document.content
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if found:
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compliant_count += 1
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else:
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non_compliant.append({
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"rule_id": rule.id,
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"section": rule.section,
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"requirement": rule.requirement,
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"severity": "critical" if rule.mandatory else "warning",
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"suggestion": rule.suggestion,
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})
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report = ValidationReport(
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id=report_id,
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document_id=document.id,
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validated_at=datetime.now(),
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total_rules=len(self._rules),
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compliant_count=compliant_count,
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non_compliant_items=non_compliant,
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)
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self._reports[report_id] = report
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return report
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def get_report(self, report_id: str) -> Optional[ValidationReport]:
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"""获取验证报告"""
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return self._reports.get(report_id)
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class SkillService:
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"""Skills流程编排服务（SRS-MACP_F-005）"""
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def __init__(self):
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self._skills = _init_mock_skills()
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self._workflows = _init_mock_workflows()
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def list_skills(self) -> list[Skill]:
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"""获取所有Skill"""
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return list(self._skills.values())
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def get_skill(self, skill_id: str) -> Optional[Skill]:
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"""获取Skill详情"""
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return self._skills.get(skill_id)
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def create_skill(self, skill: Skill) -> Skill:
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"""创建新Skill"""
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if not skill.id:
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skill.id = f"SK-{uuid.uuid4().hex[:6].upper()}"
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self._skills[skill.id] = skill
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return skill
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def execute_skill(self, skill_id: str, context: dict[str, Any]) -> dict[str, Any]:
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"""模拟执行Skill
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Args:
|
||
skill_id: Skill ID
|
||
context: 执行上下文参数
|
||
|
||
Returns:
|
||
dict: 执行结果
|
||
"""
|
||
skill = self._skills.get(skill_id)
|
||
if not skill:
|
||
return {"success": False, "error": f"Skill {skill_id} not found"}
|
||
|
||
return {
|
||
"success": True,
|
||
"skill_id": skill_id,
|
||
"skill_name": skill.name,
|
||
"result": f"已模拟执行Skill: {skill.name}，输入上下文: {context}",
|
||
"executed_at": datetime.now().isoformat(),
|
||
}
|
||
|
||
def list_workflows(self) -> list[Workflow]:
|
||
"""获取所有工作流"""
|
||
return list(self._workflows.values())
|
||
|
||
def create_workflow(self, workflow: Workflow) -> Workflow:
|
||
"""创建工作流"""
|
||
if not workflow.id:
|
||
workflow.id = f"WF-{uuid.uuid4().hex[:6].upper()}"
|
||
self._workflows[workflow.id] = workflow
|
||
return workflow
|
||
|
||
|
||
class MemoryService:
|
||
"""智能体记忆管理服务（SRS-MACP_F-006）"""
|
||
|
||
def __init__(self):
|
||
self._memories = _init_mock_memories()
|
||
|
||
def list_memories(self, session_id: Optional[str] = None) -> list[MemoryEntry]:
|
||
"""获取记忆列表，可按会话ID过滤"""
|
||
if session_id:
|
||
return [m for m in self._memories.values() if m.session_id == session_id]
|
||
return list(self._memories.values())
|
||
|
||
def get_memory(self, memory_id: str) -> Optional[MemoryEntry]:
|
||
"""获取记忆详情"""
|
||
return self._memories.get(memory_id)
|
||
|
||
def create_memory(self, memory: MemoryEntry) -> MemoryEntry:
|
||
"""创建记忆条目"""
|
||
if not memory.id:
|
||
memory.id = f"MEM-{uuid.uuid4().hex[:6].upper()}"
|
||
memory.created_at = datetime.now()
|
||
self._memories[memory.id] = memory
|
||
return memory
|
||
|
||
def delete_memory(self, memory_id: str) -> bool:
|
||
"""删除记忆"""
|
||
if memory_id in self._memories:
|
||
del self._memories[memory_id]
|
||
return True
|
||
return False
|
||
|
||
def search_memories(self, query: str) -> list[MemoryEntry]:
|
||
"""基于语义相似度检索相关记忆（模拟实现）"""
|
||
results = []
|
||
for mem in self._memories.values():
|
||
if query.lower() in mem.summary.lower() or query.lower() in mem.original_dialogue.lower():
|
||
results.append(mem)
|
||
return results
|
||
|
||
|
||
class KnowledgeBaseService:
|
||
"""知识库交互服务（SRS-MACP_F-008）"""
|
||
|
||
def __init__(self):
|
||
self._chunks = _init_mock_knowledge()
|
||
|
||
def list_chunks(self, level: Optional[KnowledgeLevel] = None) -> list[KnowledgeChunk]:
|
||
"""获取知识库片段列表，可按层级过滤"""
|
||
if level:
|
||
return [c for c in self._chunks.values() if c.level == level]
|
||
return list(self._chunks.values())
|
||
|
||
def get_chunk(self, chunk_id: str) -> Optional[KnowledgeChunk]:
|
||
"""获取知识库片段详情"""
|
||
return self._chunks.get(chunk_id)
|
||
|
||
def search_chunks(self, query: str, top_k: int = 5) -> list[KnowledgeChunk]:
|
||
"""搜索知识库片段（模拟向量检索）"""
|
||
ranked = []
|
||
for chunk in self._chunks.values():
|
||
score = 0
|
||
if query.lower() in chunk.content.lower():
|
||
score += 3
|
||
for tag in chunk.metadata_tags:
|
||
if query.lower() in tag.lower():
|
||
score += 2
|
||
if query.lower() in chunk.source_document.lower():
|
||
score += 1
|
||
if score > 0:
|
||
ranked.append((score, chunk))
|
||
ranked.sort(key=lambda x: -x[0])
|
||
return [item[1] for item in ranked[:top_k]]
|
||
|
||
|
||
class ModelService:
|
||
"""统一大模型接入服务（SRS-MACP_F-009）"""
|
||
|
||
def __init__(self):
|
||
self._models = _init_mock_models()
|
||
|
||
def list_models(self) -> list[ModelProfile]:
|
||
"""获取所有模型配置"""
|
||
return list(self._models.values())
|
||
|
||
def get_primary_model(self) -> Optional[ModelProfile]:
|
||
"""获取主用模型"""
|
||
for model in self._models.values():
|
||
if model.is_primary:
|
||
return model
|
||
return None
|
||
|
||
def health_check(self, model_id: str) -> dict[str, Any]:
|
||
"""模拟模型健康检查"""
|
||
model = self._models.get(model_id)
|
||
if not model:
|
||
return {"status": "unknown", "error": "Model not found"}
|
||
return {
|
||
"model_id": model_id,
|
||
"vendor": model.vendor,
|
||
"status": model.health_status.value,
|
||
"healthy": model.health_status == ModelStatus.ACTIVE,
|
||
"checked_at": datetime.now().isoformat(),
|
||
}
|
||
|
||
def failover(self, failed_model_id: str) -> Optional[ModelProfile]:
|
||
"""模拟故障转移"""
|
||
failed = self._models.get(failed_model_id)
|
||
if failed:
|
||
failed.health_status = ModelStatus.FAILOVER
|
||
failed.is_primary = False
|
||
# 找下一个可用模型
|
||
for model in self._models.values():
|
||
if model.id != failed_model_id and model.health_status == ModelStatus.ACTIVE:
|
||
model.is_primary = True
|
||
return model
|
||
return None
|
||
|
||
|
||
class MultimodalService:
|
||
"""多模态输入处理服务（SRS-MACP_F-010）"""
|
||
|
||
def __init__(self):
|
||
self._results: dict[str, MultimodalResult] = {}
|
||
|
||
def process_file(self, file_name: str, file_type: FileType) -> MultimodalResult:
|
||
"""模拟多模态文件处理
|
||
|
||
根据文件类型模拟OCR识别、语音转写、关键帧提取等处理。
|
||
|
||
Args:
|
||
file_name: 文件名
|
||
file_type: 文件类型
|
||
|
||
Returns:
|
||
MultimodalResult: 处理结果
|
||
"""
|
||
result_id = f"MTR-{uuid.uuid4().hex[:6].upper()}"
|
||
result = MultimodalResult(
|
||
id=result_id,
|
||
file_type=file_type,
|
||
file_name=file_name,
|
||
extracted_at=datetime.now(),
|
||
)
|
||
|
||
if file_type == FileType.IMAGE:
|
||
result.ocr_text = f"[模拟OCR识别结果] 从图片 {file_name} 中识别到文本内容。"
|
||
elif file_type == FileType.AUDIO:
|
||
result.asr_transcript = f"[模拟ASR转写结果] 从音频 {file_name} 中转写出语音文本。"
|
||
elif file_type == FileType.VIDEO:
|
||
result.ocr_text = f"[模拟视频OCR] 从视频 {file_name} 中提取到字幕文本。"
|
||
result.asr_transcript = f"[模拟视频ASR] 从视频 {file_name} 中转写出语音文本。"
|
||
result.key_frames = [f"{file_name}_frame_001.jpg", f"{file_name}_frame_002.jpg"]
|
||
|
||
self._results[result_id] = result
|
||
return result
|
||
|
||
def get_result(self, result_id: str) -> Optional[MultimodalResult]:
|
||
"""获取处理结果"""
|
||
return self._results.get(result_id)
|
||
|
||
|
||
class SandboxService:
|
||
"""安全沙箱执行服务（SRS-MACP_F-007）"""
|
||
|
||
def __init__(self):
|
||
self._execution_logs: list[dict[str, Any]] = []
|
||
|
||
def execute_code(self, code: str, language: str = "python") -> dict[str, Any]:
|
||
"""模拟沙箱环境执行代码
|
||
|
||
Args:
|
||
code: 待执行代码
|
||
language: 编程语言
|
||
|
||
Returns:
|
||
dict: 执行结果，包含输出、日志、执行时间等
|
||
"""
|
||
execution_id = f"SBX-{uuid.uuid4().hex[:6].upper()}"
|
||
log_entry = {
|
||
"execution_id": execution_id,
|
||
"language": language,
|
||
"code_length": len(code),
|
||
"started_at": datetime.now().isoformat(),
|
||
"status": "completed",
|
||
}
|
||
|
||
# 模拟执行结果（沙箱内真实执行有安全风险，此处仅模拟）
|
||
result = {
|
||
"execution_id": execution_id,
|
||
"language": language,
|
||
"status": "completed",
|
||
"stdout": f"[模拟沙箱执行] 已安全执行{language}代码，长度{len(code)}字符。\n资源限制：CPU 1核，内存 512MB，网络隔离。",
|
||
"stderr": "",
|
||
"execution_time_ms": 120,
|
||
"resource_usage": {
|
||
"cpu_percent": 45.0,
|
||
"memory_mb": 128.0,
|
||
},
|
||
"executed_at": datetime.now().isoformat(),
|
||
}
|
||
|
||
log_entry["status"] = "completed"
|
||
log_entry["finished_at"] = datetime.now().isoformat()
|
||
self._execution_logs.append(log_entry)
|
||
|
||
return result
|
||
|
||
def get_execution_logs(self) -> list[dict[str, Any]]:
|
||
"""获取沙箱执行日志"""
|
||
return self._execution_logs
|
||
|
||
|
||
class McpToolService:
|
||
"""MCP工具接入服务（SRS-MACP_F-004）"""
|
||
|
||
def __init__(self):
|
||
self._tools = _init_mock_mcp_tools()
|
||
|
||
def list_tools(self) -> list[McpTool]:
|
||
"""获取所有MCP工具"""
|
||
return list(self._tools.values())
|
||
|
||
def get_tool(self, tool_id: str) -> Optional[McpTool]:
|
||
"""获取MCP工具详情"""
|
||
return self._tools.get(tool_id)
|
||
|
||
def register_tool(self, tool: McpTool) -> McpTool:
|
||
"""注册MCP工具"""
|
||
if not tool.id:
|
||
tool.id = f"MCP-{uuid.uuid4().hex[:6].upper()}"
|
||
tool.created_at = datetime.now()
|
||
self._tools[tool.id] = tool
|
||
return tool
|
||
|
||
def delete_tool(self, tool_id: str) -> bool:
|
||
"""删除MCP工具"""
|
||
if tool_id in self._tools:
|
||
del self._tools[tool_id]
|
||
return True
|
||
return False
|
||
|
||
def debug_tool(self, tool_id: str, input_data: dict[str, Any]) -> dict[str, Any]:
|
||
"""沙箱调试MCP工具
|
||
|
||
Args:
|
||
tool_id: 工具ID
|
||
input_data: 调试输入数据
|
||
|
||
Returns:
|
||
dict: 调试结果
|
||
"""
|
||
tool = self._tools.get(tool_id)
|
||
if not tool:
|
||
return {"success": False, "error": f"Tool {tool_id} not found"}
|
||
|
||
return {
|
||
"success": True,
|
||
"tool_id": tool_id,
|
||
"tool_name": tool.name,
|
||
"input": input_data,
|
||
"output": {"result": f"[模拟MCP工具调试] 工具 '{tool.name}' 执行成功"},
|
||
"debug_log": ["初始化工具上下文...", f"验证JSON Schema...", "执行工具逻辑...", "返回结果"],
|
||
}
|