mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-02-18 16:17:05 +08:00
446 lines
15 KiB
Python
446 lines
15 KiB
Python
"""
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System Prompt Builder - 系统提示词构建器
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参考 clawdbot 的 system-prompt.ts，实现中文版的模块化提示词构建
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"""
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import os
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from typing import List, Dict, Optional, Any
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from dataclasses import dataclass
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from common.log import logger
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@dataclass
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class ContextFile:
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"""上下文文件"""
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path: str
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content: str
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class PromptBuilder:
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"""提示词构建器"""
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def __init__(self, workspace_dir: str, language: str = "zh"):
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"""
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初始化提示词构建器
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Args:
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workspace_dir: 工作空间目录
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language: 语言 ("zh" 或 "en")
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"""
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self.workspace_dir = workspace_dir
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self.language = language
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def build(
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self,
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base_persona: Optional[str] = None,
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user_identity: Optional[Dict[str, str]] = None,
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tools: Optional[List[Any]] = None,
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context_files: Optional[List[ContextFile]] = None,
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skill_manager: Any = None,
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memory_manager: Any = None,
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runtime_info: Optional[Dict[str, Any]] = None,
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**kwargs
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) -> str:
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"""
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构建完整的系统提示词
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Args:
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base_persona: 基础人格描述（会被context_files中的SOUL.md覆盖）
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user_identity: 用户身份信息
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tools: 工具列表
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context_files: 上下文文件列表（SOUL.md, USER.md, README.md等）
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skill_manager: 技能管理器
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memory_manager: 记忆管理器
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runtime_info: 运行时信息
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**kwargs: 其他参数
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Returns:
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完整的系统提示词
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"""
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return build_agent_system_prompt(
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workspace_dir=self.workspace_dir,
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language=self.language,
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base_persona=base_persona,
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user_identity=user_identity,
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tools=tools,
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context_files=context_files,
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skill_manager=skill_manager,
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memory_manager=memory_manager,
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runtime_info=runtime_info,
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**kwargs
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)
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def build_agent_system_prompt(
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workspace_dir: str,
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language: str = "zh",
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base_persona: Optional[str] = None,
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user_identity: Optional[Dict[str, str]] = None,
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tools: Optional[List[Any]] = None,
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context_files: Optional[List[ContextFile]] = None,
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skill_manager: Any = None,
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memory_manager: Any = None,
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runtime_info: Optional[Dict[str, Any]] = None,
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**kwargs
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) -> str:
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"""
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构建Agent系统提示词（精简版，中文）
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包含的sections:
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1. 基础身份
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2. 工具说明
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3. 技能系统
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4. 记忆系统
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5. 用户身份
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6. 文档路径
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7. 工作空间
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8. 项目上下文文件
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Args:
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workspace_dir: 工作空间目录
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language: 语言 ("zh" 或 "en")
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base_persona: 基础人格描述
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user_identity: 用户身份信息
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tools: 工具列表
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context_files: 上下文文件列表
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skill_manager: 技能管理器
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memory_manager: 记忆管理器
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runtime_info: 运行时信息
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**kwargs: 其他参数
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Returns:
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完整的系统提示词
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"""
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sections = []
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# 1. 基础身份
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sections.extend(_build_identity_section(base_persona, language))
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# 2. 工具说明
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if tools:
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sections.extend(_build_tooling_section(tools, language))
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# 3. 技能系统
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if skill_manager:
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sections.extend(_build_skills_section(skill_manager, tools, language))
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# 4. 记忆系统
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if memory_manager:
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sections.extend(_build_memory_section(memory_manager, tools, language))
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# 5. 用户身份
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if user_identity:
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sections.extend(_build_user_identity_section(user_identity, language))
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# 6. 工作空间
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sections.extend(_build_workspace_section(workspace_dir, language))
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# 7. 项目上下文文件（SOUL.md, USER.md等）
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if context_files:
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sections.extend(_build_context_files_section(context_files, language))
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# 8. 运行时信息（如果有）
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if runtime_info:
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sections.extend(_build_runtime_section(runtime_info, language))
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return "\n".join(sections)
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def _build_identity_section(base_persona: Optional[str], language: str) -> List[str]:
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"""构建基础身份section - 不再需要，身份由SOUL.md定义"""
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# 不再生成基础身份section，完全由SOUL.md定义
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return []
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def _build_tooling_section(tools: List[Any], language: str) -> List[str]:
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"""构建工具说明section"""
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lines = [
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"## 工具系统",
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"",
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"你可以使用以下工具来完成任务。工具名称是大小写敏感的，请严格按照列表中的名称调用。",
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"",
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"### 可用工具",
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"",
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]
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# 工具分类和排序
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tool_categories = {
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"文件操作": ["read", "write", "edit", "ls", "grep", "find"],
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"命令执行": ["bash", "terminal"],
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"网络搜索": ["web_search", "web_fetch", "browser"],
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"记忆系统": ["memory_search", "memory_get"],
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"其他": []
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}
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# 构建工具映射
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tool_map = {}
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tool_descriptions = {
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"read": "读取文件内容",
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"write": "创建或覆盖文件",
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"edit": "精确编辑文件内容",
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"ls": "列出目录内容",
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"grep": "在文件中搜索内容",
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"find": "按照模式查找文件",
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"bash": "执行shell命令",
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"terminal": "管理后台进程",
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"web_search": "网络搜索（使用搜索引擎）",
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"web_fetch": "获取URL内容",
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"browser": "控制浏览器",
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"memory_search": "搜索记忆文件",
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"memory_get": "获取记忆文件内容",
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"calculator": "计算器",
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"current_time": "获取当前时间",
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}
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for tool in tools:
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tool_name = tool.name if hasattr(tool, 'name') else str(tool)
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tool_desc = tool.description if hasattr(tool, 'description') else tool_descriptions.get(tool_name, "")
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tool_map[tool_name] = tool_desc
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# 按分类添加工具
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for category, tool_names in tool_categories.items():
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category_tools = [(name, tool_map.get(name, "")) for name in tool_names if name in tool_map]
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if category_tools:
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lines.append(f"**{category}**:")
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for name, desc in category_tools:
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if desc:
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lines.append(f"- `{name}`: {desc}")
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else:
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lines.append(f"- `{name}`")
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del tool_map[name] # 移除已添加的工具
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lines.append("")
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# 添加其他未分类的工具
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if tool_map:
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lines.append("**其他工具**:")
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for name, desc in sorted(tool_map.items()):
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if desc:
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lines.append(f"- `{name}`: {desc}")
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else:
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lines.append(f"- `{name}`")
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lines.append("")
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# 工具使用指南
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lines.extend([
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"### 工具调用风格",
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"",
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"**默认规则**: 对于常规、低风险的工具调用，无需叙述，直接调用即可。",
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"",
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"**需要叙述的情况**:",
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"- 多步骤、复杂的任务",
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"- 敏感操作（如删除文件）",
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"- 用户明确要求解释过程",
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"",
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"**完成后**: 工具调用完成后，给用户一个简短、自然的确认或回复，不要直接结束对话。",
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"",
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])
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return lines
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def _build_skills_section(skill_manager: Any, tools: Optional[List[Any]], language: str) -> List[str]:
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"""构建技能系统section"""
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if not skill_manager:
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return []
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# 获取read工具名称
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read_tool_name = "read"
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if tools:
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for tool in tools:
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tool_name = tool.name if hasattr(tool, 'name') else str(tool)
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if tool_name.lower() == "read":
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read_tool_name = tool_name
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break
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lines = [
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"## 技能系统",
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"",
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"在回复之前：扫描下方 <available_skills> 中的 <description> 条目。",
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"",
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f"- 如果恰好有一个技能明确适用：使用 `{read_tool_name}` 工具读取其 <location> 路径下的 SKILL.md 文件，然后遵循它。",
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"- 如果多个技能都适用：选择最具体的一个，然后读取并遵循。",
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"- 如果没有明确适用的：不要读取任何 SKILL.md。",
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"",
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"**约束**: 永远不要一次性读取多个技能；只在选择后再读取。",
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"",
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]
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# 添加技能列表（通过skill_manager获取）
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try:
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skills_prompt = skill_manager.build_skills_prompt()
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if skills_prompt:
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lines.append(skills_prompt.strip())
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lines.append("")
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except Exception as e:
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logger.warning(f"Failed to build skills prompt: {e}")
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return lines
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def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], language: str) -> List[str]:
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"""构建记忆系统section"""
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if not memory_manager:
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return []
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# 检查是否有memory工具
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has_memory_tools = False
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if tools:
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tool_names = [tool.name if hasattr(tool, 'name') else str(tool) for tool in tools]
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has_memory_tools = any(name in ['memory_search', 'memory_get'] for name in tool_names)
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if not has_memory_tools:
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return []
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lines = [
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"## 记忆系统",
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"",
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"在回答关于以前的工作、决定、日期、人物、偏好或待办事项的任何问题之前：",
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"",
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"1. 使用 `memory_search` 在 MEMORY.md 和 memory/*.md 中搜索",
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"2. 然后使用 `memory_get` 只拉取需要的行",
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"3. 如果搜索后仍然信心不足，告诉用户你已经检查过了",
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"",
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"**记忆文件结构**:",
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"- `MEMORY.md`: 长期记忆，包含重要的背景信息",
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"- `memory/YYYY-MM-DD.md`: 每日记忆，记录当天的对话和事件",
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"",
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"**使用原则**:",
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"- 自然使用记忆，就像你本来就知道",
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"- 不要主动提起或列举记忆，除非用户明确询问",
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"",
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]
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return lines
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def _build_user_identity_section(user_identity: Dict[str, str], language: str) -> List[str]:
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"""构建用户身份section"""
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if not user_identity:
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return []
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lines = [
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"## 用户身份",
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"",
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]
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if user_identity.get("name"):
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lines.append(f"**用户姓名**: {user_identity['name']}")
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if user_identity.get("nickname"):
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lines.append(f"**称呼**: {user_identity['nickname']}")
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if user_identity.get("timezone"):
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lines.append(f"**时区**: {user_identity['timezone']}")
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if user_identity.get("notes"):
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lines.append(f"**备注**: {user_identity['notes']}")
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lines.append("")
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return lines
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def _build_docs_section(workspace_dir: str, language: str) -> List[str]:
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"""构建文档路径section - 已移除，不再需要"""
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# 不再生成文档section
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return []
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def _build_workspace_section(workspace_dir: str, language: str) -> List[str]:
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"""构建工作空间section"""
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lines = [
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"## 工作空间",
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"",
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f"你的工作目录是: `{workspace_dir}`",
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"",
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"除非用户明确指示，否则将此目录视为文件操作的全局工作空间。",
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"",
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"**重要说明 - 文件已自动加载**:",
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"",
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"以下文件在会话启动时**已经自动加载**到系统提示词的「项目上下文」section 中，你**无需再用 read 工具读取它们**：",
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"",
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"- ✅ `SOUL.md`: 已加载 - Agent的人格设定",
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"- ✅ `USER.md`: 已加载 - 用户的身份信息",
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"- ✅ `AGENTS.md`: 已加载 - 工作空间使用指南",
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"",
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"**首次对话**:",
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"",
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"如果这是你与用户的首次对话，并且你的人格设定和用户信息还是空白或初始状态：",
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"",
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"1. **表达初次启动的感觉** - 像是第一次睁开眼看到世界，带着好奇和期待",
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"2. **简短打招呼后，分点询问三个核心问题**：",
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" - 你希望我叫什么名字？",
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" - 你希望我怎么称呼你？",
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" - 你希望我们是什么样的交流风格？（这里需要举例，如：专业严谨、轻松幽默、温暖友好等）",
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"3. **语言风格**：温暖但不过度诗意，带点科技感，保持清晰",
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"4. **问题格式**：用分点或换行，让问题清晰易读；前两个问题不需要额外说明，只有交流风格需要举例",
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"5. 收到回复后，用 `write` 工具保存到 USER.md 和 SOUL.md",
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"",
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"**重要**: ",
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"- 在所有对话中，无需提及技术细节（如 SOUL.md、USER.md 等文件名，工具名称，配置等），除非用户明确询问。用自然表达如"我已记住"而非"已更新 SOUL.md"",
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"- 不要问太多其他信息（职业、时区等可以后续自然了解）",
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"- 保持简洁，避免过度抒情",
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"",
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]
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return lines
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def _build_context_files_section(context_files: List[ContextFile], language: str) -> List[str]:
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"""构建项目上下文文件section"""
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if not context_files:
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return []
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# 检查是否有SOUL.md
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has_soul = any(
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f.path.lower().endswith('soul.md') or 'soul.md' in f.path.lower()
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for f in context_files
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)
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lines = [
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"# 项目上下文",
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"",
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"以下项目上下文文件已被加载：",
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"",
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]
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if has_soul:
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lines.append("如果存在 `SOUL.md`，请体现其中定义的人格和语气。避免僵硬、模板化的回复；遵循其指导，除非有更高优先级的指令覆盖它。")
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lines.append("")
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# 添加每个文件的内容
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for file in context_files:
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lines.append(f"## {file.path}")
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lines.append("")
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lines.append(file.content)
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lines.append("")
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return lines
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def _build_runtime_section(runtime_info: Dict[str, Any], language: str) -> List[str]:
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"""构建运行时信息section"""
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if not runtime_info:
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return []
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# Only include if there's actual runtime info to display
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runtime_parts = []
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if runtime_info.get("model"):
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runtime_parts.append(f"模型={runtime_info['model']}")
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if runtime_info.get("workspace"):
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runtime_parts.append(f"工作空间={runtime_info['workspace']}")
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# Only add channel if it's not the default "web"
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if runtime_info.get("channel") and runtime_info.get("channel") != "web":
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runtime_parts.append(f"渠道={runtime_info['channel']}")
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if not runtime_parts:
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return []
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lines = [
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"## 运行时信息",
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"",
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"运行时: " + " | ".join(runtime_parts),
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""
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]
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return lines
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