208 lines
6.1 KiB
Python
208 lines
6.1 KiB
Python
"""
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Skill 数据模型
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Skill 是平台的核心概念：可配置的行为指导单元
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"""
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from pydantic import BaseModel, Field
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from typing import Optional, Dict, Any, List
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from datetime import datetime
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class SkillTool(BaseModel):
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"""Skill 工具定义（仅内置 Skill 支持）"""
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name: str
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description: str
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script: str # 脚本文件名
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parameters: Dict[str, Dict[str, Any]] = Field(default_factory=dict)
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class SkillConfig(BaseModel):
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"""Skill 配置"""
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# 风格预设
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preset: Optional[str] = None
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# 可调节参数
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parameters: Dict[str, Dict[str, Any]] = Field(default_factory=dict)
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# 权重配置
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weights: Optional[Dict[str, float]] = None
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class Skill(BaseModel):
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"""Skill 模型"""
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id: str
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name: str
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version: str = "1.0.0"
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author: str = "未知"
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# 类型：builtin 或 user
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type: str = "user"
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# 核心内容 - 行为指导
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behavior_guide: str = "" # 直接影响 Agent 行为
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# 配置
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config: SkillConfig = Field(default_factory=SkillConfig)
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# 提示词模板（可选）
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template: Optional[str] = None
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# 工具定义（仅内置 Skill）
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tools: Optional[List[SkillTool]] = None
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# 元数据
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category: str = "通用"
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tags: List[str] = Field(default_factory=list)
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visibility: str = "private" # private 或 public
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# 文件路径（用于内部追踪）
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file_path: Optional[str] = None
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# 时间戳
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created_at: Optional[datetime] = None
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updated_at: Optional[datetime] = None
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class SkillCreate(BaseModel):
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"""创建 Skill 请求"""
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id: Optional[str] = None # ID 可选，不传则自动生成
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name: str
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content: str # Markdown 格式的完整 Skill 内容
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category: str = "通用"
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tags: List[str] = Field(default_factory=list)
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class SkillUpdate(BaseModel):
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"""更新 Skill 请求"""
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name: Optional[str] = None
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content: Optional[str] = None
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category: Optional[str] = None
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tags: Optional[List[str]] = None
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class SkillConfigUpdate(BaseModel):
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"""更新 Skill 配置请求"""
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preset: Optional[str] = None
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parameters: Optional[Dict[str, Dict[str, Any]]] = None
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weights: Optional[Dict[str, float]] = None
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class SkillTestRequest(BaseModel):
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"""测试 Skill 请求"""
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test_input: str
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context: Optional[Dict[str, Any]] = None
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temperature: float = 0.7
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class SkillTestResponse(BaseModel):
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"""测试 Skill 响应"""
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skill_id: str
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skill_name: str
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response: str
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usage: Optional[Dict[str, int]] = None
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class SkillGenerateRequest(BaseModel):
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"""AI 生成 Skill 请求"""
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description: str = Field(..., description="用户对想要创建的 Skill 的描述")
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category: Optional[str] = None
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tags: Optional[List[str]] = None
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temperature: float = Field(0.7, ge=0, le=1)
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class SkillGenerateResponse(BaseModel):
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"""AI 生成 Skill 响应"""
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suggested_id: str
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suggested_name: str
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skill_content: str
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category: str
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suggested_tags: List[str]
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explanation: str # AI 对生成的 Skill 的说明
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# ============================================================================
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# 新增：文档驱动的 Skill 生成模型
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# ============================================================================
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class DocFetchRequest(BaseModel):
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"""文档获取请求"""
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url: str = Field(..., description="文档 URL")
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selector: Optional[str] = Field(None, description="CSS 选择器（可选）")
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class GitHubDocFetchRequest(BaseModel):
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"""GitHub 文档获取请求"""
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repo_url: str = Field(..., description="GitHub 仓库 URL")
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docs_path: str = Field("README.md", description="文档路径")
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class SkillGenerateFromDocsRequest(BaseModel):
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"""基于文档生成 Skill 请求"""
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skill_name: str = Field(..., description="Skill 名称")
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description: Optional[str] = Field(None, description="Skill 描述（可选）")
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category: Optional[str] = Field(None, description="分类")
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tags: Optional[List[str]] = Field(None, description="标签")
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# 文档来源
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doc_urls: List[str] = Field(default_factory=list, description="文档 URL 列表")
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github_repos: List[GitHubDocFetchRequest] = Field(default_factory=list, description="GitHub 仓库列表")
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uploaded_references: Dict[str, str] = Field(default_factory=dict, description="用户上传的 references {文件名: 内容}")
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# 生成选项
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temperature: float = Field(0.7, ge=0, le=1, description="LLM 温度")
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include_doc_summary: bool = Field(True, description="是否包含文档摘要")
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class SkillGenerateFromDocsResponse(BaseModel):
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"""基于文档生成 Skill 响应"""
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success: bool
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preview_id: str = Field(..., description="预览 ID（用于后续保存）")
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skill_content: str = Field(..., description="生成的 SKILL.md 内容")
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skill_name: str
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suggested_id: str
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category: str
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tags: List[str]
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doc_summary: Optional[str] = Field(None, description="文档摘要")
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references_count: int = Field(0, description="生成的 reference 文件数")
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explanation: str
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class SkillPreviewRequest(BaseModel):
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"""Skill 预览请求"""
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skill_content: str
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skill_name: str
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category: Optional[str] = None
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tags: Optional[List[str]] = None
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class SkillPreviewResponse(BaseModel):
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"""Skill 预览响应"""
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preview_id: str
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skill_content: str
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parsed_metadata: Dict[str, Any]
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validation_warnings: List[str] = Field(default_factory=list)
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word_count: int
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estimated_tokens: int
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class SkillSaveFromPreviewRequest(BaseModel):
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"""从预览保存 Skill 请求"""
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preview_id: str
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skill_id: str = Field(..., description="要保存的 Skill ID")
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skill_content: str
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references: Optional[Dict[str, str]] = Field(None, description="要保存的 references")
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class SkillRefineRequest(BaseModel):
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"""AI 调整 Skill 请求"""
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skill_content: str
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refinement_prompt: str = Field(..., description="调整提示词")
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temperature: float = Field(0.7, ge=0, le=1)
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class SkillRefineResponse(BaseModel):
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"""AI 调整 Skill 响应"""
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success: bool
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refined_content: str
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changes_summary: str
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original_length: int
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new_length: int
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