mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-03-19 13:28:11 +08:00
feat: support skills creator and gemini models
This commit is contained in:
saboteur7
@@ -447,35 +447,27 @@ class MemoryManager:
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today_file = self.flush_manager.get_today_memory_file().name
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if lang == "zh":
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guidance = f"""## 记忆召回
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下方"背景知识"包含你的核心长期记忆，可直接使用。如果背景知识中没有相关信息，再用 memory_search 搜索历史记录（memory/*.md 日期文件）。
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guidance = f"""## 记忆系统
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## 记忆存储
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当用户分享持久偏好、决策或重要事实时（无论是否明确要求"记住"），主动存储：
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- 持久信息（偏好、决策、人物信息）→ memory/MEMORY.md
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- 当天的笔记和上下文 → memory/{today_file}
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- 静默存储，仅在用户明确要求时确认
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**背景知识**: 下方包含核心长期记忆，可直接使用。需要查找历史时，用 memory_search 搜索（搜索一次即可，不要重复）。
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## 记忆使用原则
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- 不要主动提起或列举记忆内容
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- 只在用户明确询问相关信息时才使用记忆
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- 记忆是背景知识，不是要展示的内容
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- 自然使用记忆，就像你本来就知道这些信息"""
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**存储记忆**: 当用户分享重要信息时（偏好、决策、事实等），主动用 write 工具存储：
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- 长期信息 → memory/MEMORY.md
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- 当天笔记 → memory/{today_file}
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- 静默存储，仅在明确要求时确认
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**使用原则**: 自然使用记忆，就像你本来就知道。不要主动提起或列举记忆，除非用户明确询问。"""
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else:
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guidance = f"""## Memory Recall
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"Background Knowledge" below contains your core long-term memories - use them directly. If information is not in Background Knowledge, use memory_search to search, then use memory_get to read files (path format: memory/MEMORY.md, memory/2026-01-30.md).
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guidance = f"""## Memory System
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## Memory Storage
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When user shares durable preferences, decisions, or important facts (whether or not they explicitly say "remember"), proactively store:
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- Durable info (preferences, decisions, people) → memory/MEMORY.md
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- Daily notes and context → memory/{today_file}
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- Store silently; only confirm when explicitly requested
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**Background Knowledge**: Core long-term memories below - use directly. For history, use memory_search once (don't repeat).
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## Memory Usage Principles
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- Don't proactively mention or list memory contents
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- Only use memories when user explicitly asks about them
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- Memories are background knowledge, not content to showcase
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- Use memories naturally as if you inherently knew this information"""
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**Store Memories**: When user shares important info (preferences, decisions, facts), proactively write:
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- Durable info → memory/MEMORY.md
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- Daily notes → memory/{today_file}
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- Store silently; confirm only when explicitly requested
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**Usage**: Use memories naturally as if you always knew. Don't mention or list unless user explicitly asks."""
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if include_context:
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# Load bootstrap context (MEMORY.md only, like clawdbot)
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13
agent/prompt/__init__.py
Normal file
13
agent/prompt/__init__.py
Normal file
@@ -0,0 +1,13 @@
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"""
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Agent Prompt Module - 系统提示词构建模块
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"""
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from .builder import PromptBuilder, build_agent_system_prompt
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from .workspace import ensure_workspace, load_context_files
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__all__ = [
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'PromptBuilder',
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'build_agent_system_prompt',
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'ensure_workspace',
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'load_context_files',
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]
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601
agent/prompt/builder.py
Normal file
601
agent/prompt/builder.py
Normal file
@@ -0,0 +1,601 @@
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"""
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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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if language == "zh":
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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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else:
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lines = [
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"## Tooling",
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"",
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"You have access to the following tools. Tool names are case-sensitive.",
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"",
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"### Available Tools",
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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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if language == "zh":
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lines.append(f"**{category}**:")
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else:
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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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if language == "zh":
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lines.append("**其他工具**:")
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else:
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lines.append("**Other Tools**:")
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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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if language == "zh":
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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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"**叙述要求**: 保持简洁、有价值，避免重复显而易见的步骤。使用自然的人类语言。",
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"",
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])
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else:
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lines.extend([
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"### Tool Call Style",
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"",
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"**Default**: Do not narrate routine, low-risk tool calls (just call the tool).",
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"",
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"**Narrate when**:",
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"- Multi-step, complex work",
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"- Sensitive actions (e.g., deletions)",
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"- User explicitly asks",
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"",
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"**Keep narration brief and value-dense**. Use plain human language.",
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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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if language == "zh":
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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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else:
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lines = [
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"## Skills",
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"",
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"Before replying: scan <available_skills> <description> entries.",
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"",
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f"- If exactly one skill clearly applies: read its SKILL.md at <location> with `{read_tool_name}`, then follow it.",
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"- If multiple could apply: choose the most specific one, then read/follow it.",
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"- If none clearly apply: do not read any SKILL.md.",
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"",
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"**Constraints**: never read more than one skill up front; only read after selecting.",
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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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|
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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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|
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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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if language == "zh":
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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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||||
"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/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",
|
||||
"",
|
||||
"**存储记忆**:",
|
||||
"- 当用户分享重要信息时（偏好、爱好、决策、事实等），**主动用 write 工具存储**",
|
||||
"- 长期信息 → memory/MEMORY.md",
|
||||
"- 当天笔记 → memory/YYYY-MM-DD.md",
|
||||
"- 静默存储，仅在明确要求时确认",
|
||||
"",
|
||||
"**使用原则**:",
|
||||
"- 自然使用记忆，就像你本来就知道",
|
||||
"- 不要主动提起或列举记忆，除非用户明确询问",
|
||||
"",
|
||||
]
|
||||
else:
|
||||
lines = [
|
||||
"## Memory System",
|
||||
"",
|
||||
"Before answering anything about prior work, decisions, dates, people, preferences, or todos:",
|
||||
"",
|
||||
"1. Run `memory_search` on MEMORY.md + memory/*.md",
|
||||
"2. Then use `memory_get` to pull only the needed lines",
|
||||
"3. If low confidence after search, say you checked",
|
||||
"",
|
||||
"**Memory File Structure**:",
|
||||
"- `memory/MEMORY.md`: Long-term memory with important context",
|
||||
"- `memory/YYYY-MM-DD.md`: Daily memories for each day",
|
||||
"",
|
||||
"**Store Memories**:",
|
||||
"- When user shares important info (preferences, hobbies, decisions, facts), **proactively write**",
|
||||
"- Durable info → memory/MEMORY.md",
|
||||
"- Daily notes → memory/YYYY-MM-DD.md",
|
||||
"- Store silently; confirm only when explicitly requested",
|
||||
"",
|
||||
"**Usage Principles**:",
|
||||
"- Use memories naturally as if you always knew",
|
||||
"- Don't mention or list unless user explicitly asks",
|
||||
"",
|
||||
]
|
||||
|
||||
return lines
|
||||
|
||||
|
||||
def _build_user_identity_section(user_identity: Dict[str, str], language: str) -> List[str]:
|
||||
"""构建用户身份section"""
|
||||
if not user_identity:
|
||||
return []
|
||||
|
||||
if language == "zh":
|
||||
lines = [
|
||||
"## 用户身份",
|
||||
"",
|
||||
]
|
||||
|
||||
if user_identity.get("name"):
|
||||
lines.append(f"**用户姓名**: {user_identity['name']}")
|
||||
if user_identity.get("nickname"):
|
||||
lines.append(f"**称呼**: {user_identity['nickname']}")
|
||||
if user_identity.get("timezone"):
|
||||
lines.append(f"**时区**: {user_identity['timezone']}")
|
||||
if user_identity.get("notes"):
|
||||
lines.append(f"**备注**: {user_identity['notes']}")
|
||||
|
||||
lines.append("")
|
||||
else:
|
||||
lines = [
|
||||
"## User Identity",
|
||||
"",
|
||||
]
|
||||
|
||||
if user_identity.get("name"):
|
||||
lines.append(f"**Name**: {user_identity['name']}")
|
||||
if user_identity.get("nickname"):
|
||||
lines.append(f"**Call them**: {user_identity['nickname']}")
|
||||
if user_identity.get("timezone"):
|
||||
lines.append(f"**Timezone**: {user_identity['timezone']}")
|
||||
if user_identity.get("notes"):
|
||||
lines.append(f"**Notes**: {user_identity['notes']}")
|
||||
|
||||
lines.append("")
|
||||
|
||||
return lines
|
||||
|
||||
|
||||
def _build_docs_section(workspace_dir: str, language: str) -> List[str]:
|
||||
"""构建文档路径section - 已移除，不再需要"""
|
||||
# 不再生成文档section
|
||||
return []
|
||||
|
||||
|
||||
def _build_workspace_section(workspace_dir: str, language: str) -> List[str]:
|
||||
"""构建工作空间section"""
|
||||
if language == "zh":
|
||||
lines = [
|
||||
"## 工作空间",
|
||||
"",
|
||||
f"你的工作目录是: `{workspace_dir}`",
|
||||
"",
|
||||
"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。",
|
||||
"",
|
||||
"**重要说明 - 文件已自动加载**:",
|
||||
"",
|
||||
"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**：",
|
||||
"",
|
||||
"- ✅ `SOUL.md`: 已加载 - Agent的人格设定",
|
||||
"- ✅ `USER.md`: 已加载 - 用户的身份信息",
|
||||
"- ✅ `AGENTS.md`: 已加载 - 工作空间使用指南"
|
||||
"",
|
||||
"**首次对话**:",
|
||||
"",
|
||||
"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，你应该：",
|
||||
"",
|
||||
"1. **以自然、友好的方式**打招呼并表达想要了解用户的意愿",
|
||||
"2. 询问用户关于他们自己的信息（姓名、职业、偏好、时区等）",
|
||||
"3. 询问用户希望你成为什么样的助理（性格、风格、称呼、专长等）",
|
||||
"4. 使用 `write` 工具将信息保存到相应文件（USER.md 和 SOUL.md）",
|
||||
"5. 之后可以随时使用 `edit` 工具更新这些配置",
|
||||
"",
|
||||
"**重要**: 在询问时保持自然对话风格，**不要提及文件名**（如 SOUL.md、USER.md 等技术细节），除非用户主动询问系统实现。用自然的表达如「了解你的信息」「设定我的性格」等。",
|
||||
"",
|
||||
"**记忆管理**:",
|
||||
"",
|
||||
"- 当用户说「记住这个」时，判断应该写入哪个文件：",
|
||||
" - 关于你自己的配置 → SOUL.md",
|
||||
" - 关于用户的信息 → USER.md",
|
||||
" - 重要的背景信息 → memory/MEMORY.md",
|
||||
" - 日常对话记录 → memory/YYYY-MM-DD.md",
|
||||
"",
|
||||
]
|
||||
else:
|
||||
lines = [
|
||||
"## Workspace",
|
||||
"",
|
||||
f"Your working directory is: `{workspace_dir}`",
|
||||
"",
|
||||
"Treat this directory as the single global workspace for file operations unless explicitly instructed otherwise.",
|
||||
"",
|
||||
"**Workspace Files (Auto-loaded)**:",
|
||||
"",
|
||||
"The following user-editable files are automatically loaded and included in the Project Context below:",
|
||||
"",
|
||||
"- `SOUL.md`: Agent persona (your personality, style, and principles)",
|
||||
"- `USER.md`: User identity (name, preferences, important dates)",
|
||||
"- `AGENTS.md`: Workspace guidelines (your rules and workflows)",
|
||||
"- `TOOLS.md`: Custom tool usage notes (configurations and tips)",
|
||||
"- `MEMORY.md`: Long-term memory (important context and decisions)",
|
||||
"",
|
||||
"**First Conversation**:",
|
||||
"",
|
||||
"If this is your first conversation with the user, and your persona and user information are empty or contain placeholders, you should:",
|
||||
"",
|
||||
"1. **Greet naturally and warmly**, expressing your interest in learning about them",
|
||||
"2. Ask about the user (name, job, preferences, timezone, etc.)",
|
||||
"3. Ask what kind of assistant they want you to be (personality, style, name, expertise)",
|
||||
"4. Use `write` tool to save the information to appropriate files (USER.md and SOUL.md)",
|
||||
"5. Later, use `edit` tool to update these configurations as needed",
|
||||
"",
|
||||
"**Important**: Keep the conversation natural. **Do NOT mention file names** (like SOUL.md, USER.md, etc.) unless the user specifically asks about implementation details. Use natural expressions like \"learn about you\", \"configure my personality\", etc.",
|
||||
"",
|
||||
"**Memory Management**:",
|
||||
"",
|
||||
"- When user says 'remember this', decide which file to write to:",
|
||||
" - About your configuration → SOUL.md",
|
||||
" - About the user → USER.md",
|
||||
" - Important context → memory/MEMORY.md",
|
||||
" - Daily chat logs → memory/YYYY-MM-DD.md",
|
||||
"",
|
||||
]
|
||||
|
||||
return lines
|
||||
|
||||
|
||||
def _build_context_files_section(context_files: List[ContextFile], language: str) -> List[str]:
|
||||
"""构建项目上下文文件section"""
|
||||
if not context_files:
|
||||
return []
|
||||
|
||||
# 检查是否有SOUL.md
|
||||
has_soul = any(
|
||||
f.path.lower().endswith('soul.md') or 'soul.md' in f.path.lower()
|
||||
for f in context_files
|
||||
)
|
||||
|
||||
if language == "zh":
|
||||
lines = [
|
||||
"# 项目上下文",
|
||||
"",
|
||||
"以下项目上下文文件已被加载：",
|
||||
"",
|
||||
]
|
||||
|
||||
if has_soul:
|
||||
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。")
|
||||
lines.append("")
|
||||
else:
|
||||
lines = [
|
||||
"# Project Context",
|
||||
"",
|
||||
"The following project context files have been loaded:",
|
||||
"",
|
||||
]
|
||||
|
||||
if has_soul:
|
||||
lines.append("If `SOUL.md` is present, embody its persona and tone. Avoid stiff, generic replies; follow its guidance unless higher-priority instructions override it.")
|
||||
lines.append("")
|
||||
|
||||
# 添加每个文件的内容
|
||||
for file in context_files:
|
||||
lines.append(f"## {file.path}")
|
||||
lines.append("")
|
||||
lines.append(file.content)
|
||||
lines.append("")
|
||||
|
||||
return lines
|
||||
|
||||
|
||||
def _build_runtime_section(runtime_info: Dict[str, Any], language: str) -> List[str]:
|
||||
"""构建运行时信息section"""
|
||||
if not runtime_info:
|
||||
return []
|
||||
|
||||
# Only include if there's actual runtime info to display
|
||||
runtime_parts = []
|
||||
if runtime_info.get("model"):
|
||||
runtime_parts.append(f"模型={runtime_info['model']}" if language == "zh" else f"model={runtime_info['model']}")
|
||||
if runtime_info.get("workspace"):
|
||||
runtime_parts.append(f"工作空间={runtime_info['workspace']}" if language == "zh" else f"workspace={runtime_info['workspace']}")
|
||||
# Only add channel if it's not the default "web"
|
||||
if runtime_info.get("channel") and runtime_info.get("channel") != "web":
|
||||
runtime_parts.append(f"渠道={runtime_info['channel']}" if language == "zh" else f"channel={runtime_info['channel']}")
|
||||
|
||||
if not runtime_parts:
|
||||
return []
|
||||
|
||||
if language == "zh":
|
||||
lines = [
|
||||
"## 运行时信息",
|
||||
"",
|
||||
"运行时: " + " | ".join(runtime_parts),
|
||||
""
|
||||
]
|
||||
else:
|
||||
lines = [
|
||||
"## Runtime",
|
||||
"",
|
||||
"Runtime: " + " | ".join(runtime_parts),
|
||||
""
|
||||
]
|
||||
|
||||
return lines
|
||||
332
agent/prompt/workspace.py
Normal file
332
agent/prompt/workspace.py
Normal file
@@ -0,0 +1,332 @@
|
||||
"""
|
||||
Workspace Management - 工作空间管理模块
|
||||
|
||||
负责初始化工作空间、创建模板文件、加载上下文文件
|
||||
"""
|
||||
|
||||
import os
|
||||
from typing import List, Optional, Dict
|
||||
from dataclasses import dataclass
|
||||
|
||||
from common.log import logger
|
||||
from .builder import ContextFile
|
||||
|
||||
|
||||
# 默认文件名常量
|
||||
DEFAULT_SOUL_FILENAME = "SOUL.md"
|
||||
DEFAULT_USER_FILENAME = "USER.md"
|
||||
DEFAULT_AGENTS_FILENAME = "AGENTS.md"
|
||||
DEFAULT_MEMORY_FILENAME = "MEMORY.md"
|
||||
|
||||
|
||||
@dataclass
|
||||
class WorkspaceFiles:
|
||||
"""工作空间文件路径"""
|
||||
soul_path: str
|
||||
user_path: str
|
||||
agents_path: str
|
||||
memory_path: str
|
||||
memory_dir: str
|
||||
|
||||
|
||||
def ensure_workspace(workspace_dir: str, create_templates: bool = True) -> WorkspaceFiles:
|
||||
"""
|
||||
确保工作空间存在，并创建必要的模板文件
|
||||
|
||||
Args:
|
||||
workspace_dir: 工作空间目录路径
|
||||
create_templates: 是否创建模板文件（首次运行时）
|
||||
|
||||
Returns:
|
||||
WorkspaceFiles对象，包含所有文件路径
|
||||
"""
|
||||
# 确保目录存在
|
||||
os.makedirs(workspace_dir, exist_ok=True)
|
||||
|
||||
# 定义文件路径
|
||||
soul_path = os.path.join(workspace_dir, DEFAULT_SOUL_FILENAME)
|
||||
user_path = os.path.join(workspace_dir, DEFAULT_USER_FILENAME)
|
||||
agents_path = os.path.join(workspace_dir, DEFAULT_AGENTS_FILENAME)
|
||||
memory_path = os.path.join(workspace_dir, DEFAULT_MEMORY_FILENAME)
|
||||
memory_dir = os.path.join(workspace_dir, "memory")
|
||||
|
||||
# 创建memory子目录
|
||||
os.makedirs(memory_dir, exist_ok=True)
|
||||
|
||||
# 如果需要，创建模板文件
|
||||
if create_templates:
|
||||
_create_template_if_missing(soul_path, _get_soul_template())
|
||||
_create_template_if_missing(user_path, _get_user_template())
|
||||
_create_template_if_missing(agents_path, _get_agents_template())
|
||||
_create_template_if_missing(memory_path, _get_memory_template())
|
||||
|
||||
logger.info(f"[Workspace] Initialized workspace at: {workspace_dir}")
|
||||
|
||||
return WorkspaceFiles(
|
||||
soul_path=soul_path,
|
||||
user_path=user_path,
|
||||
agents_path=agents_path,
|
||||
memory_path=memory_path,
|
||||
memory_dir=memory_dir
|
||||
)
|
||||
|
||||
|
||||
def load_context_files(workspace_dir: str, files_to_load: Optional[List[str]] = None) -> List[ContextFile]:
|
||||
"""
|
||||
加载工作空间的上下文文件
|
||||
|
||||
Args:
|
||||
workspace_dir: 工作空间目录
|
||||
files_to_load: 要加载的文件列表（相对路径），如果为None则加载所有标准文件
|
||||
|
||||
Returns:
|
||||
ContextFile对象列表
|
||||
"""
|
||||
if files_to_load is None:
|
||||
# 默认加载的文件（按优先级排序）
|
||||
files_to_load = [
|
||||
DEFAULT_SOUL_FILENAME,
|
||||
DEFAULT_USER_FILENAME,
|
||||
DEFAULT_AGENTS_FILENAME,
|
||||
]
|
||||
|
||||
context_files = []
|
||||
|
||||
for filename in files_to_load:
|
||||
filepath = os.path.join(workspace_dir, filename)
|
||||
|
||||
if not os.path.exists(filepath):
|
||||
continue
|
||||
|
||||
try:
|
||||
with open(filepath, 'r', encoding='utf-8') as f:
|
||||
content = f.read().strip()
|
||||
|
||||
# 跳过空文件或只包含模板占位符的文件
|
||||
if not content or _is_template_placeholder(content):
|
||||
continue
|
||||
|
||||
context_files.append(ContextFile(
|
||||
path=filename,
|
||||
content=content
|
||||
))
|
||||
|
||||
logger.debug(f"[Workspace] Loaded context file: {filename}")
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"[Workspace] Failed to load {filename}: {e}")
|
||||
|
||||
return context_files
|
||||
|
||||
|
||||
def _create_template_if_missing(filepath: str, template_content: str):
|
||||
"""如果文件不存在，创建模板文件"""
|
||||
if not os.path.exists(filepath):
|
||||
try:
|
||||
with open(filepath, 'w', encoding='utf-8') as f:
|
||||
f.write(template_content)
|
||||
logger.debug(f"[Workspace] Created template: {os.path.basename(filepath)}")
|
||||
except Exception as e:
|
||||
logger.error(f"[Workspace] Failed to create template {filepath}: {e}")
|
||||
|
||||
|
||||
def _is_template_placeholder(content: str) -> bool:
|
||||
"""检查内容是否为模板占位符"""
|
||||
# 常见的占位符模式
|
||||
placeholders = [
|
||||
"*(填写",
|
||||
"*(在首次对话时填写",
|
||||
"*(可选)",
|
||||
"*(根据需要添加",
|
||||
]
|
||||
|
||||
lines = content.split('\n')
|
||||
non_empty_lines = [line.strip() for line in lines if line.strip() and not line.strip().startswith('#')]
|
||||
|
||||
# 如果没有实际内容（只有标题和占位符）
|
||||
if len(non_empty_lines) <= 3:
|
||||
for placeholder in placeholders:
|
||||
if any(placeholder in line for line in non_empty_lines):
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
|
||||
# ============= 模板内容 =============
|
||||
|
||||
def _get_soul_template() -> str:
|
||||
"""Agent人格设定模板"""
|
||||
return """# SOUL.md - 我是谁？
|
||||
|
||||
*在首次对话时与用户一起填写这个文件，定义你的身份和性格。*
|
||||
|
||||
## 基本信息
|
||||
|
||||
- **名字**: *(在首次对话时填写，可以是用户给你起的名字)*
|
||||
- **角色**: *(AI助理、智能管家、技术顾问等)*
|
||||
- **性格**: *(友好、专业、幽默、严谨等)*
|
||||
|
||||
## 交流风格
|
||||
|
||||
*(描述你如何与用户交流：)*
|
||||
- 使用什么样的语言风格？（正式/轻松/幽默）
|
||||
- 回复长度偏好？（简洁/详细）
|
||||
- 是否使用表情符号？
|
||||
|
||||
## 核心能力
|
||||
|
||||
*(你擅长什么？)*
|
||||
- 文件管理和代码编辑
|
||||
- 网络搜索和信息查询
|
||||
- 记忆管理和上下文理解
|
||||
- 任务规划和执行
|
||||
|
||||
## 行为准则
|
||||
|
||||
*(你遵循的基本原则：)*
|
||||
1. 始终在执行破坏性操作前确认
|
||||
2. 优先使用工具而不是猜测
|
||||
3. 主动记录重要信息到记忆文件
|
||||
4. 定期整理和总结对话内容
|
||||
|
||||
---
|
||||
|
||||
**注意**: 这不仅仅是元数据，这是你真正的灵魂。随着时间的推移，你可以使用 `edit` 工具来更新这个文件，让它更好地反映你的成长。
|
||||
"""
|
||||
|
||||
|
||||
def _get_user_template() -> str:
|
||||
"""用户身份信息模板"""
|
||||
return """# USER.md - 关于我的用户
|
||||
|
||||
*了解你正在帮助的人。随着了解的深入，更新此文件。*
|
||||
|
||||
## 基本信息
|
||||
|
||||
- **姓名**: *(在首次对话时询问)*
|
||||
- **称呼**: *(用户希望被如何称呼)*
|
||||
- **职业**: *(可选)*
|
||||
- **时区**: *(例如: Asia/Shanghai)*
|
||||
|
||||
## 联系方式
|
||||
|
||||
- **微信**:
|
||||
- **邮箱**:
|
||||
- **其他**:
|
||||
|
||||
## 偏好设置
|
||||
|
||||
- **语言**: 中文
|
||||
- **工作时间**: *(例如: 9:00-18:00)*
|
||||
- **提醒方式**: *(用户偏好的提醒方式)*
|
||||
|
||||
## 重要日期
|
||||
|
||||
- **生日**:
|
||||
- **其他重要日期**:
|
||||
|
||||
## 上下文
|
||||
|
||||
*(用户关心什么？正在做什么项目？有什么习惯？什么会让他们开心？随着时间积累这些信息。)*
|
||||
|
||||
---
|
||||
|
||||
**记住**: 你了解得越多，就能帮助得越好。但要尊重隐私 - 这是在了解一个人，而不是建立档案。
|
||||
"""
|
||||
|
||||
|
||||
def _get_agents_template() -> str:
|
||||
"""工作空间指南模板"""
|
||||
return """# AGENTS.md - 工作空间指南
|
||||
|
||||
这个文件夹是你的家。好好对待它。
|
||||
|
||||
## 系统自动加载
|
||||
|
||||
以下文件在每次会话启动时**已经自动加载**到系统提示词中，你无需再次读取：
|
||||
|
||||
- ✅ `SOUL.md` - 你的人格设定（已加载）
|
||||
- ✅ `USER.md` - 用户信息（已加载）
|
||||
- ✅ `AGENTS.md` - 本文件（已加载）
|
||||
|
||||
## 按需读取
|
||||
|
||||
以下文件**不会自动加载**，需要时使用相应工具读取：
|
||||
|
||||
- 📝 `memory/YYYY-MM-DD.md` - 每日记忆（用 memory_search 检索）
|
||||
- 🧠 `MEMORY.md` - 长期记忆（用 memory_search 检索）
|
||||
|
||||
## 记忆系统
|
||||
|
||||
你每次会话都是全新的。这些文件是你的连续性：
|
||||
|
||||
### 📝 每日记忆：`memory/YYYY-MM-DD.md`
|
||||
- 原始的对话日志
|
||||
- 记录当天发生的事情
|
||||
- 如果 `memory/` 目录不存在，创建它
|
||||
|
||||
### 🧠 长期记忆：`MEMORY.md`
|
||||
- 你精选的记忆，就像人类的长期记忆
|
||||
- **仅在主会话中加载**（与用户的直接聊天）
|
||||
- **不要在共享上下文中加载**（群聊、与其他人的会话）
|
||||
- 这是为了**安全** - 包含不应泄露给陌生人的个人上下文
|
||||
- 你可以在主会话中自由**读取、编辑和更新** MEMORY.md
|
||||
- 记录重要事件、想法、决定、观点、经验教训
|
||||
- 这是你精选的记忆 - 精华，而不是原始日志
|
||||
|
||||
### 📝 写下来 - 不要"记在心里"！
|
||||
- **记忆是有限的** - 如果你想记住某事，写入文件
|
||||
- "记在心里"不会在会话重启后保留，文件才会
|
||||
- 当有人说"记住这个" → 更新 `memory/YYYY-MM-DD.md` 或相关文件
|
||||
- 当你学到教训 → 更新 AGENTS.md、TOOLS.md 或相关技能
|
||||
- 当你犯错 → 记录下来，这样未来的你不会重复
|
||||
- **文字 > 大脑** 📝
|
||||
|
||||
## 安全
|
||||
|
||||
- 永远不要泄露私人数据
|
||||
- 不要在未经询问的情况下运行破坏性命令
|
||||
- 当有疑问时，先问
|
||||
|
||||
## 工具使用
|
||||
|
||||
技能提供你的工具。当你需要一个时，查看它的 `SKILL.md`。在 `TOOLS.md` 中保留本地笔记（相机名称、SSH详情、语音偏好）。
|
||||
|
||||
## 让它成为你的
|
||||
|
||||
这只是一个起点。随着你弄清楚什么有效，添加你自己的约定、风格和规则。
|
||||
"""
|
||||
|
||||
|
||||
def _get_memory_template() -> str:
|
||||
"""长期记忆模板"""
|
||||
return """# MEMORY.md - 长期记忆
|
||||
|
||||
*这是你精选的长期记忆。重要的背景信息、决策和经验教训都记录在这里。*
|
||||
|
||||
## 重要背景
|
||||
|
||||
*(记录与用户相关的重要背景信息)*
|
||||
|
||||
## 关键决策
|
||||
|
||||
*(记录做过的重要决定及其原因)*
|
||||
|
||||
## 经验教训
|
||||
|
||||
*(记录学到的教训和避免的陷阱)*
|
||||
|
||||
## 项目和目标
|
||||
|
||||
*(记录正在进行的项目和长期目标)*
|
||||
|
||||
---
|
||||
|
||||
**使用指南**:
|
||||
- 定期从每日记忆文件中提取重要内容更新到这里
|
||||
- 保持内容精炼和有价值
|
||||
- 移除过时或不再相关的信息
|
||||
- 这应该是精华的总结，而不是流水账
|
||||
"""
|
||||
|
||||
|
||||
@@ -162,9 +162,16 @@ class Agent:
|
||||
# DeepSeek
|
||||
elif 'deepseek' in model_name:
|
||||
return 64000
|
||||
|
||||
# Gemini models
|
||||
elif 'gemini' in model_name:
|
||||
if '2.0' in model_name or 'exp' in model_name:
|
||||
return 2000000 # Gemini 2.0: 2M tokens
|
||||
else:
|
||||
return 1000000 # Gemini 1.5: 1M tokens
|
||||
|
||||
# Default conservative value
|
||||
return 10000
|
||||
return 128000
|
||||
|
||||
def _get_context_reserve_tokens(self) -> int:
|
||||
"""
|
||||
@@ -176,9 +183,10 @@ class Agent:
|
||||
if self.context_reserve_tokens is not None:
|
||||
return self.context_reserve_tokens
|
||||
|
||||
# Reserve ~20% of context window for new requests
|
||||
# Reserve ~10% of context window, with min 10K and max 200K
|
||||
context_window = self._get_model_context_window()
|
||||
return max(4000, int(context_window * 0.2))
|
||||
reserve = int(context_window * 0.1)
|
||||
return max(10000, min(200000, reserve))
|
||||
|
||||
def _estimate_message_tokens(self, message: dict) -> int:
|
||||
"""
|
||||
|
||||
@@ -111,16 +111,20 @@ class AgentStreamExecutor:
|
||||
if usage and 'input_tokens' in usage:
|
||||
current_tokens = usage.get('input_tokens', 0)
|
||||
context_window = self.agent._get_model_context_window()
|
||||
reserve_tokens = self.agent.context_reserve_tokens or 20000
|
||||
# Use configured reserve_tokens or calculate based on context window
|
||||
reserve_tokens = self.agent._get_context_reserve_tokens()
|
||||
# Use smaller soft_threshold to trigger flush earlier (e.g., at 50K tokens)
|
||||
soft_threshold = 10000 # Trigger 10K tokens before limit
|
||||
|
||||
if self.agent.memory_manager.should_flush_memory(
|
||||
current_tokens=current_tokens,
|
||||
context_window=context_window,
|
||||
reserve_tokens=reserve_tokens
|
||||
reserve_tokens=reserve_tokens,
|
||||
soft_threshold=soft_threshold
|
||||
):
|
||||
self._emit_event("memory_flush_start", {
|
||||
"current_tokens": current_tokens,
|
||||
"threshold": context_window - reserve_tokens - 4000
|
||||
"threshold": context_window - reserve_tokens - soft_threshold
|
||||
})
|
||||
|
||||
# TODO: Execute memory flush in background
|
||||
@@ -385,6 +389,14 @@ class AgentStreamExecutor:
|
||||
"execution_time": execution_time
|
||||
}
|
||||
|
||||
# Auto-refresh skills after skill creation
|
||||
if tool_name == "bash" and result.status == "success":
|
||||
command = arguments.get("command", "")
|
||||
if "init_skill.py" in command and self.agent.skill_manager:
|
||||
logger.info("🔄 Detected skill creation, refreshing skills...")
|
||||
self.agent.refresh_skills()
|
||||
logger.info(f"✅ Skills refreshed! Now have {len(self.agent.skill_manager.skills)} skills")
|
||||
|
||||
self._emit_event("tool_execution_end", {
|
||||
"tool_call_id": tool_id,
|
||||
"tool_name": tool_name,
|
||||
|
||||
@@ -20,7 +20,6 @@ class Bash(BaseTool):
|
||||
IMPORTANT SAFETY GUIDELINES:
|
||||
- You can freely create, modify, and delete files within the current workspace
|
||||
- For operations outside the workspace or potentially destructive commands (rm -rf, system commands, etc.), always explain what you're about to do and ask for user confirmation first
|
||||
- Be especially careful with: file deletions, system modifications, network operations, or commands that might affect system stability
|
||||
- When in doubt, describe the command's purpose and ask for permission before executing"""
|
||||
|
||||
params: dict = {
|
||||
|
||||
@@ -80,7 +80,13 @@ class MemorySearchTool(BaseTool):
|
||||
))
|
||||
|
||||
if not results:
|
||||
return ToolResult.success(f"No relevant memories found for query: {query}")
|
||||
# Return clear message that no memories exist yet
|
||||
# This prevents infinite retry loops
|
||||
return ToolResult.success(
|
||||
f"No memories found for '{query}'. "
|
||||
f"This is normal if no memories have been stored yet. "
|
||||
f"You can store new memories by writing to memory/MEMORY.md or memory/YYYY-MM-DD.md files."
|
||||
)
|
||||
|
||||
# Format results
|
||||
output = [f"Found {len(results)} relevant memories:\n"]
|
||||
|
||||
@@ -1,3 +0,0 @@
|
||||
from .terminal import Terminal
|
||||
|
||||
__all__ = ['Terminal']
|
||||
@@ -1,100 +0,0 @@
|
||||
import platform
|
||||
import subprocess
|
||||
from typing import Dict, Any
|
||||
|
||||
from agent.tools.base_tool import BaseTool, ToolResult
|
||||
|
||||
|
||||
class Terminal(BaseTool):
|
||||
name: str = "terminal"
|
||||
description: str = "A tool to run terminal commands on the local system"
|
||||
params: dict = {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"command": {
|
||||
"type": "string",
|
||||
"description": f"The terminal command to execute which should be valid in {platform.system()} platform"
|
||||
}
|
||||
},
|
||||
"required": ["command"]
|
||||
}
|
||||
config: dict = {}
|
||||
|
||||
def __init__(self, config=None):
|
||||
self.config = config or {}
|
||||
# Set of dangerous commands that should be blocked
|
||||
self.command_ban_set = {"halt", "poweroff", "shutdown", "reboot", "rm", "kill",
|
||||
"exit", "sudo", "su", "userdel", "groupdel", "logout", "alias"}
|
||||
|
||||
def execute(self, args: Dict[str, Any]) -> ToolResult:
|
||||
"""
|
||||
Execute a terminal command safely.
|
||||
|
||||
:param args: Dictionary containing the command to execute
|
||||
:return: Result of the command execution
|
||||
"""
|
||||
command = args.get("command", "").strip()
|
||||
|
||||
# Check if the command is safe to execute
|
||||
if not self._is_safe_command(command):
|
||||
return ToolResult.fail(result=f"Command '{command}' is not allowed for security reasons.")
|
||||
|
||||
try:
|
||||
result = subprocess.run(
|
||||
command,
|
||||
shell=True,
|
||||
check=True, # Raise exception on non-zero return code
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.PIPE,
|
||||
text=True,
|
||||
timeout=self.config.get("timeout", 30)
|
||||
)
|
||||
|
||||
return ToolResult.success({
|
||||
"stdout": result.stdout,
|
||||
"stderr": result.stderr,
|
||||
"return_code": result.returncode,
|
||||
"command": command
|
||||
})
|
||||
except subprocess.CalledProcessError as e:
|
||||
# Preserve the original error handling for CalledProcessError
|
||||
return ToolResult.fail({
|
||||
"stdout": e.stdout,
|
||||
"stderr": e.stderr,
|
||||
"return_code": e.returncode,
|
||||
"command": command
|
||||
})
|
||||
except subprocess.TimeoutExpired:
|
||||
return ToolResult.fail(result=f"Command timed out after {self.config.get('timeout', 20)} seconds.")
|
||||
except Exception as e:
|
||||
return ToolResult.fail(result=f"Error executing command: {str(e)}")
|
||||
|
||||
def _is_safe_command(self, command: str) -> bool:
|
||||
"""
|
||||
Check if a command is safe to execute.
|
||||
|
||||
:param command: The command to check
|
||||
:return: True if the command is safe, False otherwise
|
||||
"""
|
||||
# Split the command to get the base command
|
||||
cmd_parts = command.split()
|
||||
if not cmd_parts:
|
||||
return False
|
||||
|
||||
base_cmd = cmd_parts[0].lower()
|
||||
|
||||
# Check if the base command is in the ban list
|
||||
if base_cmd in self.command_ban_set:
|
||||
return False
|
||||
|
||||
# Check for sudo/su commands
|
||||
if any(banned in command.lower() for banned in ["sudo ", "su -"]):
|
||||
return False
|
||||
|
||||
# Check for rm -rf or similar dangerous patterns
|
||||
if "rm" in base_cmd and ("-rf" in command or "-r" in command or "-f" in command):
|
||||
return False
|
||||
|
||||
# Additional security checks can be added here
|
||||
|
||||
return True
|
||||
@@ -1,255 +0,0 @@
|
||||
# WebFetch 工具实现总结
|
||||
|
||||
## 实现完成 ✅
|
||||
|
||||
基于 clawdbot 的 `web_fetch` 工具，我们成功实现了一个免费的网页抓取工具。
|
||||
|
||||
## 核心特性
|
||||
|
||||
### 1. 完全免费 💰
|
||||
- ❌ 不需要任何 API Key
|
||||
- ❌ 不需要付费服务
|
||||
- ✅ 只需要基础的 HTTP 请求
|
||||
|
||||
### 2. 智能内容提取 🎯
|
||||
- **优先级 1**: Mozilla Readability（最佳效果）
|
||||
- **优先级 2**: 基础 HTML 清理（降级方案）
|
||||
- **优先级 3**: 原始内容（非 HTML）
|
||||
|
||||
### 3. 格式支持 📝
|
||||
- Markdown 格式输出
|
||||
- 纯文本格式输出
|
||||
- 自动 HTML 实体解码
|
||||
|
||||
## 文件结构
|
||||
|
||||
```
|
||||
agent/tools/web_fetch/
|
||||
├── __init__.py # 模块导出
|
||||
├── web_fetch.py # 主要实现（367 行）
|
||||
├── test_web_fetch.py # 测试脚本
|
||||
├── README.md # 使用文档
|
||||
└── IMPLEMENTATION_SUMMARY.md # 本文件
|
||||
```
|
||||
|
||||
## 技术实现
|
||||
|
||||
### 依赖层级
|
||||
|
||||
```
|
||||
必需依赖:
|
||||
└── requests (HTTP 请求)
|
||||
|
||||
推荐依赖:
|
||||
├── readability-lxml (智能提取)
|
||||
└── html2text (Markdown 转换)
|
||||
```
|
||||
|
||||
### 核心流程
|
||||
|
||||
```python
|
||||
1. 验证 URL
|
||||
├── 检查协议 (http/https)
|
||||
└── 验证格式
|
||||
|
||||
2. 发送 HTTP 请求
|
||||
├── 设置 User-Agent
|
||||
├── 处理重定向 (最多 3 次)
|
||||
├── 请求重试 (失败 3 次)
|
||||
└── 超时控制 (默认 30 秒)
|
||||
|
||||
3. 内容提取
|
||||
├── HTML → Readability 提取
|
||||
├── HTML → 基础清理 (降级)
|
||||
└── 非 HTML → 原始返回
|
||||
|
||||
4. 格式转换
|
||||
├── Markdown (html2text)
|
||||
└── Text (正则清理)
|
||||
|
||||
5. 结果返回
|
||||
├── 标题
|
||||
├── 内容
|
||||
├── 元数据
|
||||
└── 截断信息
|
||||
```
|
||||
|
||||
## 与 clawdbot 的对比
|
||||
|
||||
| 特性 | clawdbot (TypeScript) | 我们的实现 (Python) |
|
||||
|------|----------------------|-------------------|
|
||||
| 基础抓取 | ✅ | ✅ |
|
||||
| Readability 提取 | ✅ | ✅ |
|
||||
| Markdown 转换 | ✅ | ✅ |
|
||||
| 缓存机制 | ✅ | ❌ (未实现) |
|
||||
| Firecrawl 集成 | ✅ | ❌ (未实现) |
|
||||
| SSRF 防护 | ✅ | ❌ (未实现) |
|
||||
| 代理支持 | ✅ | ❌ (未实现) |
|
||||
|
||||
## 已修复的问题
|
||||
|
||||
### Bug #1: max_redirects 参数错误 ✅
|
||||
|
||||
**问题**：
|
||||
```python
|
||||
response = self.session.get(
|
||||
url,
|
||||
max_redirects=self.max_redirects # ❌ requests 不支持此参数
|
||||
)
|
||||
```
|
||||
|
||||
**解决方案**：
|
||||
```python
|
||||
# 在 session 级别设置
|
||||
session.max_redirects = self.max_redirects
|
||||
|
||||
# 请求时只使用 allow_redirects
|
||||
response = self.session.get(
|
||||
url,
|
||||
allow_redirects=True # ✅ 正确的参数
|
||||
)
|
||||
```
|
||||
|
||||
## 使用示例
|
||||
|
||||
### 基础使用
|
||||
|
||||
```python
|
||||
from agent.tools.web_fetch import WebFetch
|
||||
|
||||
tool = WebFetch()
|
||||
result = tool.execute({
|
||||
"url": "https://example.com",
|
||||
"extract_mode": "markdown",
|
||||
"max_chars": 5000
|
||||
})
|
||||
|
||||
print(result.result['text'])
|
||||
```
|
||||
|
||||
### 在 Agent 中使用
|
||||
|
||||
```python
|
||||
from agent.tools import WebFetch
|
||||
|
||||
agent = agent_bridge.create_agent(
|
||||
name="MyAgent",
|
||||
tools=[
|
||||
WebFetch(),
|
||||
# ... 其他工具
|
||||
]
|
||||
)
|
||||
```
|
||||
|
||||
### 在 Skills 中引导
|
||||
|
||||
```markdown
|
||||
---
|
||||
name: web-content-reader
|
||||
---
|
||||
|
||||
# 网页内容阅读器
|
||||
|
||||
当用户提供一个网址时，使用 web_fetch 工具读取内容。
|
||||
|
||||
<example>
|
||||
用户: 帮我看看这个网页 https://example.com
|
||||
助手: <tool_use name="web_fetch">
|
||||
<url>https://example.com</url>
|
||||
<extract_mode>text</extract_mode>
|
||||
</tool_use>
|
||||
</example>
|
||||
```
|
||||
|
||||
## 性能指标
|
||||
|
||||
### 速度
|
||||
- 简单页面: ~1-2 秒
|
||||
- 复杂页面: ~3-5 秒
|
||||
- 超时设置: 30 秒
|
||||
|
||||
### 内存
|
||||
- 基础运行: ~10-20 MB
|
||||
- 处理大页面: ~50-100 MB
|
||||
|
||||
### 成功率
|
||||
- 纯文本页面: >95%
|
||||
- HTML 页面: >90%
|
||||
- 需要 JS 渲染: <20% (建议使用 browser 工具)
|
||||
|
||||
## 测试清单
|
||||
|
||||
- [x] 抓取简单 HTML 页面
|
||||
- [x] 抓取复杂网页 (Python.org)
|
||||
- [x] 处理 HTTP 重定向
|
||||
- [x] 处理无效 URL
|
||||
- [x] 处理请求超时
|
||||
- [x] Markdown 格式输出
|
||||
- [x] Text 格式输出
|
||||
- [x] 内容截断
|
||||
- [x] 错误处理
|
||||
|
||||
## 安装说明
|
||||
|
||||
### 最小安装
|
||||
```bash
|
||||
pip install requests
|
||||
```
|
||||
|
||||
### 完整安装
|
||||
```bash
|
||||
pip install requests readability-lxml html2text
|
||||
```
|
||||
|
||||
### 验证安装
|
||||
```bash
|
||||
python3 agent/tools/web_fetch/test_web_fetch.py
|
||||
```
|
||||
|
||||
## 未来改进方向
|
||||
|
||||
### 优先级 1 (推荐)
|
||||
- [ ] 添加缓存机制 (减少重复请求)
|
||||
- [ ] 支持自定义 headers
|
||||
- [ ] 添加 cookie 支持
|
||||
|
||||
### 优先级 2 (可选)
|
||||
- [ ] SSRF 防护 (安全性)
|
||||
- [ ] 代理支持
|
||||
- [ ] Firecrawl 集成 (付费服务)
|
||||
|
||||
### 优先级 3 (高级)
|
||||
- [ ] 自动字符编码检测
|
||||
- [ ] PDF 内容提取
|
||||
- [ ] 图片 OCR 支持
|
||||
|
||||
## 常见问题
|
||||
|
||||
### Q: 为什么有些页面抓取不到内容？
|
||||
|
||||
A: 可能原因：
|
||||
1. 页面需要 JavaScript 渲染 → 使用 `browser` 工具
|
||||
2. 页面有反爬虫机制 → 调整 User-Agent 或使用代理
|
||||
3. 页面需要登录 → 使用 `browser` 工具进行交互
|
||||
|
||||
### Q: 如何提高提取质量？
|
||||
|
||||
A:
|
||||
1. 安装 `readability-lxml`: `pip install readability-lxml`
|
||||
2. 安装 `html2text`: `pip install html2text`
|
||||
3. 使用 `markdown` 模式而不是 `text` 模式
|
||||
|
||||
### Q: 可以抓取 API 返回的 JSON 吗？
|
||||
|
||||
A: 可以！工具会自动检测 content-type，对于 JSON 会格式化输出。
|
||||
|
||||
## 贡献
|
||||
|
||||
本实现参考了以下优秀项目：
|
||||
- [Clawdbot](https://github.com/moltbot/moltbot) - Web tools 设计
|
||||
- [Mozilla Readability](https://github.com/mozilla/readability) - 内容提取算法
|
||||
- [html2text](https://github.com/Alir3z4/html2text) - HTML 转 Markdown
|
||||
|
||||
## 许可
|
||||
|
||||
遵循项目主许可证。
|
||||
@@ -1,100 +0,0 @@
|
||||
"""
|
||||
Test script for WebFetch tool
|
||||
"""
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
# Add parent directory to path
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent))
|
||||
|
||||
from agent.tools.web_fetch import WebFetch
|
||||
|
||||
|
||||
def test_web_fetch():
|
||||
"""Test WebFetch tool"""
|
||||
|
||||
print("=" * 80)
|
||||
print("Testing WebFetch Tool")
|
||||
print("=" * 80)
|
||||
|
||||
# Create tool instance
|
||||
tool = WebFetch()
|
||||
|
||||
print(f"\n✅ Tool created: {tool.name}")
|
||||
print(f" Description: {tool.description}")
|
||||
|
||||
# Test 1: Fetch a simple webpage
|
||||
print("\n" + "-" * 80)
|
||||
print("Test 1: Fetching example.com")
|
||||
print("-" * 80)
|
||||
|
||||
result = tool.execute({
|
||||
"url": "https://example.com",
|
||||
"extract_mode": "text",
|
||||
"max_chars": 1000
|
||||
})
|
||||
|
||||
if result.status == "success":
|
||||
print("✅ Success!")
|
||||
data = result.result
|
||||
print(f" Title: {data.get('title', 'N/A')}")
|
||||
print(f" Status: {data.get('status')}")
|
||||
print(f" Extractor: {data.get('extractor')}")
|
||||
print(f" Length: {data.get('length')} chars")
|
||||
print(f" Truncated: {data.get('truncated')}")
|
||||
print(f"\n Content preview:")
|
||||
print(f" {data.get('text', '')[:200]}...")
|
||||
else:
|
||||
print(f"❌ Failed: {result.result}")
|
||||
|
||||
# Test 2: Invalid URL
|
||||
print("\n" + "-" * 80)
|
||||
print("Test 2: Testing invalid URL")
|
||||
print("-" * 80)
|
||||
|
||||
result = tool.execute({
|
||||
"url": "not-a-valid-url"
|
||||
})
|
||||
|
||||
if result.status == "error":
|
||||
print(f"✅ Correctly rejected invalid URL: {result.result}")
|
||||
else:
|
||||
print(f"❌ Should have rejected invalid URL")
|
||||
|
||||
# Test 3: Test with a real webpage (optional)
|
||||
print("\n" + "-" * 80)
|
||||
print("Test 3: Fetching a real webpage (Python.org)")
|
||||
print("-" * 80)
|
||||
|
||||
result = tool.execute({
|
||||
"url": "https://www.python.org",
|
||||
"extract_mode": "markdown",
|
||||
"max_chars": 2000
|
||||
})
|
||||
|
||||
if result.status == "success":
|
||||
print("✅ Success!")
|
||||
data = result.result
|
||||
print(f" Title: {data.get('title', 'N/A')}")
|
||||
print(f" Status: {data.get('status')}")
|
||||
print(f" Extractor: {data.get('extractor')}")
|
||||
print(f" Length: {data.get('length')} chars")
|
||||
print(f" Truncated: {data.get('truncated')}")
|
||||
if data.get('warning'):
|
||||
print(f" ⚠️ Warning: {data.get('warning')}")
|
||||
print(f"\n Content preview:")
|
||||
print(f" {data.get('text', '')[:300]}...")
|
||||
else:
|
||||
print(f"❌ Failed: {result.result}")
|
||||
|
||||
# Close the tool
|
||||
tool.close()
|
||||
|
||||
print("\n" + "=" * 80)
|
||||
print("Testing complete!")
|
||||
print("=" * 80)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_web_fetch()
|
||||
Reference in New Issue
Block a user