2009 lines
193 KiB
Plaintext
2009 lines
193 KiB
Plaintext
[2026-02-28 13:16:51,269] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 13:16:51,270] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 13:16:51,271] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 13:16:51,271] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 13:16:51,271] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 13:16:51,271] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 13:16:51,272] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: claude-sonnet-4-6
|
||
[2026-02-28 13:16:51,273] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 13:16:51,273] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 13:16:51,273] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 13:59:08,843] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 13:59:08,844] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 13:59:08,845] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 13:59:08,845] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 13:59:08,845] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 13:59:08,845] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 13:59:08,846] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: claude-sonnet-4-6
|
||
[2026-02-28 13:59:08,847] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 13:59:08,848] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 13:59:08,848] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 13:59:40,111] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 13:59:41,400] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:00:07,071] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:00:51,574] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:02:14,371] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:04:03,060] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:15:21,435] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:15:21,437] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:15:21,437] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:15:21,438] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:15:21,438] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:15:21,438] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:15:21,439] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: claude-sonnet-4-6
|
||
[2026-02-28 14:15:21,730] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:15:21,731] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:15:21,731] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:15:37,946] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:15:38,634] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1+1等于多少
|
||
[2026-02-28 14:15:39,212] [agent.MEMORY] DEBUG: 💬 [USER] 1+1等于多少...
|
||
[2026-02-28 14:15:40,563] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:15:47,714] [agent.LLM] INFO: 💭 分析意图: 1+1等于多少...
|
||
[2026-02-28 14:15:50,157] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:17:52,834] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:17:52,836] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:17:52,837] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:17:52,837] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:17:52,837] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:17:52,838] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:17:52,839] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: claude-sonnet-4-6
|
||
[2026-02-28 14:17:53,009] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:17:53,010] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:17:53,010] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:18:02,052] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:18:02,614] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:18:03,083] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:18:04,093] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:18:07,998] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:18:09,082] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:19:28,781] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:19:28,781] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:19:28,782] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:19:28,782] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:19:28,783] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:19:28,783] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:19:28,783] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:19:28,912] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:19:28,913] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:19:28,913] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:19:38,773] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:19:38,773] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:19:38,774] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:19:38,774] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:19:38,774] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:19:38,774] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:24:25,989] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:24:25,990] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:24:25,991] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:24:25,991] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:24:25,991] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:24:25,991] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:24:25,992] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:24:26,120] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:24:26,120] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:24:26,121] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:24:47,520] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:24:47,520] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:24:47,521] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:24:47,521] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:24:47,521] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:24:47,521] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:26:41,628] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:26:41,629] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:26:41,630] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:26:41,630] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:26:41,631] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:26:41,631] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:26:41,632] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:26:41,764] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:26:41,764] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:26:41,765] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:26:52,266] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:26:52,266] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:26:52,267] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:26:52,267] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:26:52,267] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:26:52,268] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:29:31,672] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:29:31,673] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:29:31,674] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:29:31,674] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:29:31,674] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:29:31,675] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:29:31,675] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:29:31,809] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:29:31,810] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:29:31,811] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:29:43,546] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:29:43,546] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:29:43,546] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:29:43,547] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:29:43,547] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:29:43,547] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:32:01,347] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:32:01,348] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:32:01,349] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:32:01,349] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:32:01,349] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:32:01,350] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:32:01,351] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:32:01,477] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:32:01,477] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:32:01,478] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:32:08,959] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:32:08,959] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:32:08,959] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:32:08,960] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:32:08,960] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:32:08,960] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:34:04,981] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:34:04,982] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:34:04,983] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:34:04,984] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:34:04,984] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:34:04,985] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:34:04,987] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:34:05,137] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:34:05,140] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:34:05,141] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:34:14,908] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:34:14,908] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:34:14,908] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:34:14,908] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:34:14,909] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:34:14,909] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:35:39,204] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:35:39,205] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:35:39,205] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:35:39,205] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:35:39,206] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:35:39,206] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:35:39,207] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:35:39,333] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:35:39,334] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:35:39,334] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:35:51,583] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:35:51,583] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:35:51,584] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:35:51,584] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:35:51,584] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:35:51,585] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:43:51,069] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 14:43:51,069] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 14:43:51,070] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 14:43:51,070] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 14:43:51,071] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 14:43:51,071] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 14:43:51,071] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 14:43:51,198] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 14:43:51,198] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 14:43:51,199] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 14:44:04,009] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 14:44:04,009] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 14:44:04,009] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 14:44:04,010] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 14:44:04,010] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 14:44:04,010] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 14:44:10,159] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [calculator]
|
||
[2026-02-28 14:44:10,159] [agent.LLM] DEBUG: 💡 推理: 用户询问数学计算问题，直接调用计算工具得到1+1的结果是最合适的。
|
||
[2026-02-28 14:44:21,419] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: calculator
|
||
参数: {'expression': '1+1'}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'e4d8732a', 'method': 'tools/call', 'params': {'name': 'calculator', 'arguments': {'expression': '1+1'}}}
|
||
[2026-02-28 14:44:36,340] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [calculator]...
|
||
[2026-02-28 14:44:40,181] [agent.MCP] INFO: 📨 收到请求 id=e4d8732a method=tools/call
|
||
[2026-02-28 14:46:24,701] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '1+1'}
|
||
[2026-02-28 14:46:50,239] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-02-28 16:05:27,152] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 1+1 = 2...
|
||
[2026-02-28 16:05:46,521] [agent.MEMORY] DEBUG: 💬 [TOOL] 1+1 = 2...
|
||
[2026-02-28 16:05:49,469] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合工具结果，生成最终回复...
|
||
[2026-02-28 16:05:53,270] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
|
||
[2026-02-28 16:05:53,271] [agent.LLM] INFO: 💬 回复已生成 (83 chars)
|
||
[2026-02-28 16:06:03,400] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [calculator] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
1+1 = 2
|
||
|
||
---
|
||
*由 gpt-...
|
||
[2026-02-28 16:06:05,167] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-02-28 22:29:24,671] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:29:24,672] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:29:24,672] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:29:24,672] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:29:24,672] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:29:24,672] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:29:24,672] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:29:56,971] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:29:56,971] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:29:56,971] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:29:56,971] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:29:56,971] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:29:56,971] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:29:56,972] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:30:46,017] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:30:46,017] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:30:46,017] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:30:46,018] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:30:46,018] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:30:46,018] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:30:46,018] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:30:53,901] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:30:53,902] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:30:53,902] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:30:53,902] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:30:53,902] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:30:53,902] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:30:53,902] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:47:31,295] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:47:31,296] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:47:31,296] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:47:31,296] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:47:31,296] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:47:31,296] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:47:31,296] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:51:08,506] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:51:08,507] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:51:08,507] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:51:08,507] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:51:08,507] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:51:08,507] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:51:08,507] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:51:43,854] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:51:43,855] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:51:43,855] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:51:43,855] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:51:43,855] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:51:43,855] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:51:43,855] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:51:43,891] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 22:51:43,891] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 22:51:43,891] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 22:51:58,206] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:51:58,206] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:51:58,206] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:51:58,206] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:51:58,207] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:51:58,207] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:51:58,207] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:51:58,232] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 22:51:58,232] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 22:51:58,232] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 22:52:08,077] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 22:52:08,077] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 22:52:08,077] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 22:52:08,078] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 22:52:08,078] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 22:52:08,078] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 22:54:48,518] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:54:48,518] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:54:48,518] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:54:48,519] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:54:48,519] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:54:48,519] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:54:48,519] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:54:48,543] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 22:54:48,544] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 22:54:48,544] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 22:55:14,173] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:55:14,173] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:55:14,173] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:55:14,174] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:55:14,174] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:55:14,174] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:55:14,174] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:55:54,637] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:55:54,637] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:55:54,637] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:55:54,638] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:55:54,638] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:55:54,638] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:55:54,638] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:55:54,675] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 22:55:54,676] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 22:55:54,676] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 22:56:03,477] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 22:56:03,478] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 1加1等于多少
|
||
[2026-02-28 22:56:03,478] [agent.MEMORY] DEBUG: 💬 [USER] 1加1等于多少...
|
||
[2026-02-28 22:56:03,478] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 22:56:03,478] [agent.LLM] INFO: 💭 分析意图: 1加1等于多少...
|
||
[2026-02-28 22:56:03,478] [agent.LLM] DEBUG: 📝 Prompt 已构造 (344 chars)
|
||
[2026-02-28 22:56:17,390] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [calculator]
|
||
[2026-02-28 22:56:17,391] [agent.LLM] DEBUG: 💡 推理: 用户提出了一个数学问题，需要计算 1 加 1 的值，用 calculator 工具进行计算是最合适的。
|
||
[2026-02-28 22:56:17,391] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: calculator
|
||
参数: {'expression': '1+1'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '2bcb050e', 'method': 'tools/call', 'params': {'name': 'calculator', 'arguments': {'expression': '1+1'}}}
|
||
[2026-02-28 22:56:17,392] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [calculator]...
|
||
[2026-02-28 22:56:17,392] [agent.MCP] INFO: 📨 收到请求 id=2bcb050e method=tools/call
|
||
[2026-02-28 22:56:17,392] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '1+1'}
|
||
[2026-02-28 22:56:17,392] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-02-28 22:56:17,393] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 1+1 = 2...
|
||
[2026-02-28 22:56:17,393] [agent.MEMORY] DEBUG: 💬 [TOOL] 1+1 = 2...
|
||
[2026-02-28 22:56:17,393] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合工具结果，生成最终回复...
|
||
[2026-02-28 22:56:17,393] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
|
||
[2026-02-28 22:56:17,394] [agent.LLM] INFO: 💬 回复已生成 (83 chars)
|
||
[2026-02-28 22:56:17,394] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [calculator] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
1+1 = 2
|
||
|
||
---
|
||
*由 gpt-...
|
||
[2026-02-28 22:56:17,394] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-02-28 22:56:35,957] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 22:56:35,958] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 34*67等于多少
|
||
[2026-02-28 22:56:35,958] [agent.MEMORY] DEBUG: 💬 [USER] 34*67等于多少...
|
||
[2026-02-28 22:56:35,959] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 22:56:35,959] [agent.LLM] INFO: 💭 分析意图: 34*67等于多少...
|
||
[2026-02-28 22:56:35,959] [agent.LLM] DEBUG: 📝 Prompt 已构造 (471 chars)
|
||
[2026-02-28 22:58:14,926] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 22:58:14,926] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 22:58:14,926] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 22:58:14,926] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 22:58:14,926] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 22:58:14,926] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 22:58:14,927] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 22:58:14,964] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 22:58:14,964] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 22:58:14,965] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 22:58:21,018] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 22:58:21,018] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 34*56等于多少
|
||
[2026-02-28 22:58:21,018] [agent.MEMORY] DEBUG: 💬 [USER] 34*56等于多少...
|
||
[2026-02-28 22:58:21,018] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 22:58:21,018] [agent.LLM] INFO: 💭 分析意图: 34*56等于多少...
|
||
[2026-02-28 22:58:21,019] [agent.LLM] DEBUG: 📝 Prompt 已构造 (348 chars)
|
||
[2026-02-28 22:58:23,409] [agent.Monica] INFO: {
|
||
"need_tool": true,
|
||
"tool_name": "calculator",
|
||
"arguments": {
|
||
"expression": "34*56"
|
||
},
|
||
"reasoning": "用户询问的数学问题需要计算具体结果，这可以通过调用 calculator 工具来完成。"
|
||
}
|
||
[2026-02-28 22:58:23,409] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [calculator]
|
||
[2026-02-28 22:58:23,409] [agent.LLM] DEBUG: 💡 推理: 用户询问的数学问题需要计算具体结果，这可以通过调用 calculator 工具来完成。
|
||
[2026-02-28 22:58:23,409] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: calculator
|
||
参数: {'expression': '34*56'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '6f404ceb', 'method': 'tools/call', 'params': {'name': 'calculator', 'arguments': {'expression': '34*56'}}}
|
||
[2026-02-28 22:58:23,409] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [calculator]...
|
||
[2026-02-28 22:58:23,410] [agent.MCP] INFO: 📨 收到请求 id=6f404ceb method=tools/call
|
||
[2026-02-28 22:58:23,410] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '34*56'}
|
||
[2026-02-28 22:58:23,410] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-02-28 22:58:23,410] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 34*56 = 1904...
|
||
[2026-02-28 22:58:23,410] [agent.MEMORY] DEBUG: 💬 [TOOL] 34*56 = 1904...
|
||
[2026-02-28 22:58:23,410] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合工具结果，生成最终回复...
|
||
[2026-02-28 22:58:23,410] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
|
||
[2026-02-28 22:58:23,410] [agent.LLM] INFO: 💬 回复已生成 (88 chars)
|
||
[2026-02-28 22:58:23,410] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [calculator] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
34*56 = 1904
|
||
|
||
---
|
||
*由...
|
||
[2026-02-28 22:58:23,410] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-02-28 22:58:37,709] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 22:58:37,710] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 23*45等于多少
|
||
[2026-02-28 22:58:37,710] [agent.MEMORY] DEBUG: 💬 [USER] 23*45等于多少...
|
||
[2026-02-28 22:58:37,710] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 22:58:37,711] [agent.LLM] INFO: 💭 分析意图: 23*45等于多少...
|
||
[2026-02-28 22:58:37,711] [agent.LLM] DEBUG: 📝 Prompt 已构造 (478 chars)
|
||
[2026-02-28 22:58:47,485] [agent.Monica] INFO: {"need_tool": true, "tool_name": "calculator", "arguments": {"expression": "23*45"}, "reasoning": "计算数学表达式需要调用 calculator 工具直接获得结果，以确保准确性。"}
|
||
[2026-02-28 22:58:47,486] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [calculator]
|
||
[2026-02-28 22:58:47,486] [agent.LLM] DEBUG: 💡 推理: 计算数学表达式需要调用 calculator 工具直接获得结果，以确保准确性。
|
||
[2026-02-28 22:58:47,487] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: calculator
|
||
参数: {'expression': '23*45'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '246d9a09', 'method': 'tools/call', 'params': {'name': 'calculator', 'arguments': {'expression': '23*45'}}}
|
||
[2026-02-28 22:58:47,487] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [calculator]...
|
||
[2026-02-28 22:58:47,487] [agent.MCP] INFO: 📨 收到请求 id=246d9a09 method=tools/call
|
||
[2026-02-28 22:58:47,487] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '23*45'}
|
||
[2026-02-28 22:58:47,488] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-02-28 22:58:47,488] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 23*45 = 1035...
|
||
[2026-02-28 22:58:47,488] [agent.MEMORY] DEBUG: 💬 [TOOL] 23*45 = 1035...
|
||
[2026-02-28 22:58:47,489] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合工具结果，生成最终回复...
|
||
[2026-02-28 22:58:47,489] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
|
||
[2026-02-28 22:58:47,489] [agent.LLM] INFO: 💬 回复已生成 (88 chars)
|
||
[2026-02-28 22:58:47,489] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [calculator] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
23*45 = 1035
|
||
|
||
---
|
||
*由...
|
||
[2026-02-28 22:58:47,489] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-02-28 23:01:29,790] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 23:01:29,790] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 搜索今日的天气如何
|
||
[2026-02-28 23:01:29,790] [agent.MEMORY] DEBUG: 💬 [USER] 搜索今日的天气如何...
|
||
[2026-02-28 23:01:29,791] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 23:01:29,791] [agent.LLM] INFO: 💭 分析意图: 搜索今日的天气如何...
|
||
[2026-02-28 23:01:29,791] [agent.LLM] DEBUG: 📝 Prompt 已构造 (591 chars)
|
||
[2026-02-28 23:02:40,057] [agent.Monica] INFO: ```json
|
||
{
|
||
"need_tool": true,
|
||
"tool_name": "web_search",
|
||
"arguments": {
|
||
"query": "今日的天气"
|
||
},
|
||
"reasoning": "获取当日天气信息需要实时数据，而我无法直接访问实时信息，因此需要调用 web_search 工具来搜索并获取最新的天气信息。"
|
||
}
|
||
```
|
||
[2026-02-28 23:11:18,766] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 23:11:18,766] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 23:11:18,766] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 23:11:18,766] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 23:11:18,766] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 23:11:18,766] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 23:11:18,767] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 23:11:18,821] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 23:11:18,822] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 23:11:18,822] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 23:11:23,918] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 23:11:23,918] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 查询今天的天气
|
||
[2026-02-28 23:11:23,918] [agent.MEMORY] DEBUG: 💬 [USER] 查询今天的天气...
|
||
[2026-02-28 23:11:23,918] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 23:11:23,918] [agent.LLM] INFO: 💭 分析意图: 查询今天的天气...
|
||
[2026-02-28 23:11:23,919] [agent.LLM] DEBUG: 📝 Prompt 已构造 (359 chars)
|
||
[2026-02-28 23:11:27,029] [agent.Monica] INFO: {"need_tool": true, "tool_name": "web_search", "arguments": {"query": "今天的天气"}, "reasoning": "查询天气需要访问实时信息，无法直接从内置数据中获取，因此需要调用网络搜索工具来获取当天的天气状况。"}
|
||
[2026-02-28 23:11:27,029] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [web_search]
|
||
[2026-02-28 23:11:27,029] [agent.LLM] DEBUG: 💡 推理: 查询天气需要访问实时信息，无法直接从内置数据中获取，因此需要调用网络搜索工具来获取当天的天气状况。
|
||
[2026-02-28 23:11:27,029] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: web_search
|
||
参数: {'query': '今天的天气'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '6b19ead1', 'method': 'tools/call', 'params': {'name': 'web_search', 'arguments': {'query': '今天的天气'}}}
|
||
[2026-02-28 23:11:27,030] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [web_search]...
|
||
[2026-02-28 23:11:27,030] [agent.MCP] INFO: 📨 收到请求 id=6b19ead1 method=tools/call
|
||
[2026-02-28 23:11:27,030] [agent.TOOL] INFO: ▶ 执行工具 [web_search]，参数: {'query': '今天的天气'}
|
||
[2026-02-28 23:11:27,130] [agent.TOOL] INFO: ✅ 工具 [web_search] 执行成功
|
||
[2026-02-28 23:11:27,130] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 搜索「今天的天气」，共 2 条结果:
|
||
[1] 今日天气预报
|
||
晴转多云，气温 15°C ~ 24°C，东南风 3 级
|
||
[2] 未来 7 天天气
|
||
本...
|
||
[2026-02-28 23:11:27,130] [agent.MEMORY] DEBUG: 💬 [TOOL] 搜索「今天的天气」，共 2 条结果:
|
||
[1] 今日天气预报
|
||
晴转多云，气温 15°C ~ 24°C，东南风 3 ...
|
||
[2026-02-28 23:11:27,130] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合工具结果，生成最终回复...
|
||
[2026-02-28 23:11:27,131] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
|
||
[2026-02-28 23:11:27,131] [agent.LLM] INFO: 💬 回复已生成 (167 chars)
|
||
[2026-02-28 23:11:27,131] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [web_search] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
搜索「今天的天气」，共 2 条结果:
|
||
[...
|
||
[2026-02-28 23:11:27,131] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-02-28 23:12:22,747] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-02-28 23:12:22,747] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-02-28 23:12:22,747] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-02-28 23:12:22,747] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-02-28 23:12:22,747] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-02-28 23:12:22,747] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-02-28 23:12:22,747] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-02-28 23:12:22,785] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-02-28 23:12:22,785] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-02-28 23:12:22,785] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-02-28 23:12:53,887] [agent.CLIENT] INFO: =======================================================
|
||
[2026-02-28 23:12:53,887] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 执行python代码：print('你好')
|
||
[2026-02-28 23:12:53,887] [agent.MEMORY] DEBUG: 💬 [USER] 执行python代码：print('你好')...
|
||
[2026-02-28 23:12:53,887] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-02-28 23:12:53,887] [agent.LLM] INFO: 💭 分析意图: 执行python代码：print('你好')...
|
||
[2026-02-28 23:12:53,887] [agent.LLM] DEBUG: 📝 Prompt 已构造 (389 chars)
|
||
[2026-02-28 23:12:57,254] [agent.Monica] INFO: {"need_tool": true, "tool_name": "code_executor", "arguments": {"code": "print('你好')"}, "reasoning": "用户明确要求执行一段Python代码，因此需要调用code_executor工具来执行该代码。"}
|
||
[2026-02-28 23:12:57,254] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [code_executor]
|
||
[2026-02-28 23:12:57,254] [agent.LLM] DEBUG: 💡 推理: 用户明确要求执行一段Python代码，因此需要调用code_executor工具来执行该代码。
|
||
[2026-02-28 23:12:57,254] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: code_executor
|
||
参数: {'code': "print('你好')"}
|
||
请求体: {'jsonrpc': '2.0', 'id': '49bf04da', 'method': 'tools/call', 'params': {'name': 'code_executor', 'arguments': {'code': "print('你好')"}}}
|
||
[2026-02-28 23:12:57,255] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [code_executor]...
|
||
[2026-02-28 23:12:57,255] [agent.MCP] INFO: 📨 收到请求 id=49bf04da method=tools/call
|
||
[2026-02-28 23:12:57,255] [agent.TOOL] INFO: ▶ 执行工具 [code_executor]，参数: {'code': "print('你好')"}
|
||
[2026-02-28 23:12:57,255] [agent.TOOL] INFO: ✅ 工具 [code_executor] 执行成功
|
||
[2026-02-28 23:12:57,255] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 执行成功 (0.1ms):
|
||
你好
|
||
...
|
||
[2026-02-28 23:12:57,255] [agent.MEMORY] DEBUG: 💬 [TOOL] 执行成功 (0.1ms):
|
||
你好
|
||
...
|
||
[2026-02-28 23:12:57,255] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合工具结果，生成最终回复...
|
||
[2026-02-28 23:12:57,255] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
|
||
[2026-02-28 23:12:57,255] [agent.LLM] INFO: 💬 回复已生成 (99 chars)
|
||
[2026-02-28 23:12:57,256] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [code_executor] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
执行成功 (0.1ms):
|
||
你好
|
||
...
|
||
[2026-02-28 23:12:57,256] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-03-02 10:49:15,081] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 10:49:15,081] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 10:49:15,081] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 10:49:15,081] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 10:49:15,081] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 10:49:15,081] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 10:49:15,081] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 10:49:15,081] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 10:49:15,119] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 10:49:15,119] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 10:49:15,119] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 10:59:16,161] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 10:59:16,162] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 10:59:16,162] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 10:59:16,162] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 10:59:16,162] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 10:59:16,162] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 10:59:16,162] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 10:59:16,162] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 10:59:16,200] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 10:59:16,201] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 10:59:16,201] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:00:03,211] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:00:03,211] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：
|
||
[2026-03-02 11:00:03,211] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：...
|
||
[2026-03-02 11:00:03,211] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:00:03,211] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：...
|
||
[2026-03-02 11:00:03,212] [agent.LLM] DEBUG: 📝 Prompt 已构造 (456 chars)
|
||
[2026-03-02 11:02:33,970] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:02:33,970] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:02:33,970] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:02:33,970] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:02:33,970] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:02:33,971] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:02:33,971] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:02:33,971] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:02:34,008] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:02:34,008] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:02:34,008] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:02:39,526] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:02:39,526] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(BaseTool):\n name = \"my demo tool\"\n description = \"this demo is used to show how to write a agent tool \"\n parameters = {\n \"parameter1\": {\n \"type\": \"string\",\n \"description\": \"the first parameter\"\n },\n \"parameter2\": {\n \"type\": \"integer\",\n \"description\": \"the second parameter\"\n }\n }\n def execute(parameter1: str, parameter2: int):\n ...\n"
|
||
[2026-03-02 11:02:39,526] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(Base...
|
||
[2026-03-02 11:02:39,526] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:02:39,526] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDem...
|
||
[2026-03-02 11:02:39,526] [agent.LLM] DEBUG: 📝 Prompt 已构造 (985 chars)
|
||
[2026-03-02 11:03:09,470] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:03:09,470] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:03:09,470] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:03:09,471] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:03:09,471] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:03:09,471] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:03:09,471] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:03:09,471] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:03:09,509] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:03:09,509] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:03:09,510] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:03:12,558] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:03:12,558] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(BaseTool):\n name = \"my demo tool\"\n description = \"this demo is used to show how to write a agent tool \"\n parameters = {\n \"parameter1\": {\n \"type\": \"string\",\n \"description\": \"the first parameter\"\n },\n \"parameter2\": {\n \"type\": \"integer\",\n \"description\": \"the second parameter\"\n }\n }\n def execute(parameter1: str, parameter2: int):\n ...\n"
|
||
[2026-03-02 11:03:12,558] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(Base...
|
||
[2026-03-02 11:03:12,558] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:03:12,558] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDem...
|
||
[2026-03-02 11:03:12,558] [agent.LLM] DEBUG: 📝 Prompt 已构造 (985 chars)
|
||
[2026-03-02 11:06:15,110] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:06:15,110] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:06:15,110] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:06:15,110] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:06:15,111] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:06:15,111] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:06:15,111] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:06:15,111] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:06:15,148] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:06:15,148] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:06:15,148] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:06:18,486] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:06:18,486] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(BaseTool):\n name = \"my demo tool\"\n description = \"this demo is used to show how to write a agent tool \"\n parameters = {\n \"parameter1\": {\n \"type\": \"string\",\n \"description\": \"the first parameter\"\n },\n \"parameter2\": {\n \"type\": \"integer\",\n \"description\": \"the second parameter\"\n }\n }\n def execute(parameter1: str, parameter2: int):\n ...\n"
|
||
[2026-03-02 11:06:18,486] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(Base...
|
||
[2026-03-02 11:06:18,486] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:06:18,486] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDem...
|
||
[2026-03-02 11:06:18,486] [agent.LLM] DEBUG: 📝 Prompt 已构造 (985 chars)
|
||
[2026-03-02 11:06:21,669] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"name": "process_status_query_tool", "description": "Tool for querying current system process status", "parameters": {"process_id": {"type": "integer", "description": "The ID of the process to query"}}, "execution_code": "def execute(process_id: int):\n import psutil\n process = psutil.Process(process_id)\n return {\n 'name': process.name(),\n 'status': process.status(),\n 'cpu_usage': process.cpu_percent(interval=1),\n 'memory_info': process.memory_info()._asdict()\n }"}, "reasoning": "The user requested code for an agent skill tool that queries system process status. The agent_skill_generator tool is necessary to generate the required skill code based on the provided input."}
|
||
[2026-03-02 11:06:21,669] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:06:21,669] [agent.LLM] DEBUG: 💡 推理: The user requested code for an agent skill tool that queries system process status. The agent_skill_generator tool is necessary to generate the required skill code based on the provided input.
|
||
[2026-03-02 11:06:21,669] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'name': 'process_status_query_tool', 'description': 'Tool for querying current system process status', 'parameters': {'process_id': {'type': 'integer', 'description': 'The ID of the process to query'}}, 'execution_code': "def execute(process_id: int):\n import psutil\n process = psutil.Process(process_id)\n return {\n 'name': process.name(),\n 'status': process.status(),\n 'cpu_usage': process.cpu_percent(interval=1),\n 'memory_info': process.memory_info()._asdict()\n }"}
|
||
请求体: {'jsonrpc': '2.0', 'id': '11f24daa', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'name': 'process_status_query_tool', 'description': 'Tool for querying current system process status', 'parameters': {'process_id': {'type': 'integer', 'description': 'The ID of the process to query'}}, 'execution_code': "def execute(process_id: int):\n import psutil\n process = psutil.Process(process_id)\n return {\n 'name': process.name(),\n 'status': process.status(),\n 'cpu_usage': process.cpu_percent(interval=1),\n 'memory_info': process.memory_info()._asdict()\n }"}}}
|
||
[2026-03-02 11:06:21,669] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:06:21,669] [agent.MCP] INFO: 📨 收到请求 id=11f24daa method=tools/call
|
||
[2026-03-02 11:06:21,669] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'name': 'process_status_query_tool', 'description': 'Tool for querying current system process status', 'parameters': {'process_id': {'type': 'integer', 'description': 'The ID of the process to query'}}, 'execution_code': "def execute(process_id: int):\n import psutil\n process = psutil.Process(process_id)\n return {\n 'name': process.name(),\n 'status': process.status(),\n 'cpu_usage': process.cpu_percent(interval=1),\n 'memory_info': process.memory_info()._asdict()\n }"}
|
||
[2026-03-02 11:06:21,669] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'name'
|
||
[2026-03-02 11:06:21,669] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'name'"}
|
||
[2026-03-02 11:13:52,278] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:13:52,278] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(BaseTool):\n name = \"my demo tool\"\n description = \"this demo is used to show how to write a agent tool \"\n parameters = {\n \"type\": \"string\",\n \"description\": \"the first parameter\"\n },\n \"parameter2\": {\n \"type\": \"integer\",\n \"description\": \"the second parameter\"\n }\n }\n def execute(self, parameter1: str, parameter2: int):\n ...\n"
|
||
[2026-03-02 11:13:52,278] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDemoTool(Base...
|
||
[2026-03-02 11:13:52,278] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:13:52,278] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询，技能工具代码示例如下：\nclass MyDem...
|
||
[2026-03-02 11:13:52,278] [agent.LLM] DEBUG: 📝 Prompt 已构造 (1047 chars)
|
||
[2026-03-02 11:13:55,354] [agent.Monica] INFO: {
|
||
"need_tool": true,
|
||
"tool_name": "agent_skill_generator",
|
||
"arguments": {
|
||
"tool_name": "System Process State Query",
|
||
"description": "A tool designed to retrieve the current state of system processes.",
|
||
"parameters": {
|
||
"query": {
|
||
"type": "string",
|
||
"description": "A keyword or query to filter specific system processes."
|
||
}
|
||
}
|
||
},
|
||
"reasoning": "The user has requested to generate an agent skill tool that can query the current system process states with specific parameters. The `agent_skill_generator` is the appropriate tool to generate the required agent tool code."
|
||
}
|
||
[2026-03-02 11:13:55,354] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:13:55,354] [agent.LLM] DEBUG: 💡 推理: The user has requested to generate an agent skill tool that can query the current system process states with specific parameters. The `agent_skill_generator` is the appropriate tool to generate the required agent tool code.
|
||
[2026-03-02 11:13:55,354] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'tool_name': 'System Process State Query', 'description': 'A tool designed to retrieve the current state of system processes.', 'parameters': {'query': {'type': 'string', 'description': 'A keyword or query to filter specific system processes.'}}}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'a37c6fb6', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'tool_name': 'System Process State Query', 'description': 'A tool designed to retrieve the current state of system processes.', 'parameters': {'query': {'type': 'string', 'description': 'A keyword or query to filter specific system processes.'}}}}}
|
||
[2026-03-02 11:13:55,354] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:13:55,354] [agent.MCP] INFO: 📨 收到请求 id=a37c6fb6 method=tools/call
|
||
[2026-03-02 11:13:55,354] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'tool_name': 'System Process State Query', 'description': 'A tool designed to retrieve the current state of system processes.', 'parameters': {'query': {'type': 'string', 'description': 'A keyword or query to filter specific system processes.'}}}
|
||
[2026-03-02 11:13:55,354] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'tool_name'
|
||
[2026-03-02 11:13:55,354] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'tool_name'"}
|
||
[2026-03-02 11:24:14,691] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:24:14,691] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:24:14,691] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:24:14,691] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:24:14,691] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:24:14,692] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:24:14,692] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:24:14,692] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:24:14,729] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:24:14,730] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:24:14,730] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:24:35,048] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:24:35,048] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询
|
||
[2026-03-02 11:24:35,048] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询...
|
||
[2026-03-02 11:24:35,048] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:24:35,048] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询...
|
||
[2026-03-02 11:24:35,048] [agent.LLM] DEBUG: 📝 Prompt 已构造 (432 chars)
|
||
[2026-03-02 11:24:37,629] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"description": "实现当前系统进程状态查询"}, "reasoning": "用户请求生成一个agent技能工具用于查询当前系统进程状态，这要求创建一个相关功能的工具，而agent_skill_generator正是为了生成这样的工具。"}
|
||
[2026-03-02 11:24:37,630] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:24:37,630] [agent.LLM] DEBUG: 💡 推理: 用户请求生成一个agent技能工具用于查询当前系统进程状态，这要求创建一个相关功能的工具，而agent_skill_generator正是为了生成这样的工具。
|
||
[2026-03-02 11:24:37,630] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'description': '实现当前系统进程状态查询'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '7aa01ed6', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'description': '实现当前系统进程状态查询'}}}
|
||
[2026-03-02 11:24:37,630] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:24:37,630] [agent.MCP] INFO: 📨 收到请求 id=7aa01ed6 method=tools/call
|
||
[2026-03-02 11:24:37,630] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'description': '实现当前系统进程状态查询'}
|
||
[2026-03-02 11:24:37,630] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'description'
|
||
[2026-03-02 11:24:37,630] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'description'"}
|
||
[2026-03-02 11:30:16,159] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:30:16,159] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:30:16,160] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:30:16,160] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:30:16,160] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:30:16,160] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:30:16,160] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:30:16,160] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:30:16,199] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:30:16,200] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:30:16,200] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:30:31,049] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:30:31,049] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 生成agent技能工具用于实现当前系统进程状态查询
|
||
[2026-03-02 11:30:31,049] [agent.MEMORY] DEBUG: 💬 [USER] 生成agent技能工具用于实现当前系统进程状态查询...
|
||
[2026-03-02 11:30:31,049] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:30:31,049] [agent.LLM] INFO: 💭 分析意图: 生成agent技能工具用于实现当前系统进程状态查询...
|
||
[2026-03-02 11:30:31,049] [agent.LLM] DEBUG: 📝 Prompt 已构造 (432 chars)
|
||
[2026-03-02 11:30:33,326] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"description": "实现当前系统进程状态查询的工具"}, "reasoning": "用户请求生成一个agent技能工具用于查询当前系统的进程状态，符合agent_skill_generator工具的功能需求。"}
|
||
[2026-03-02 11:30:33,327] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:30:33,327] [agent.LLM] DEBUG: 💡 推理: 用户请求生成一个agent技能工具用于查询当前系统的进程状态，符合agent_skill_generator工具的功能需求。
|
||
[2026-03-02 11:30:33,327] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'description': '实现当前系统进程状态查询的工具'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '2f435cb4', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'description': '实现当前系统进程状态查询的工具'}}}
|
||
[2026-03-02 11:30:33,327] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:30:33,327] [agent.MCP] INFO: 📨 收到请求 id=2f435cb4 method=tools/call
|
||
[2026-03-02 11:30:33,327] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'description': '实现当前系统进程状态查询的工具'}
|
||
[2026-03-02 11:30:33,327] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'description'
|
||
[2026-03-02 11:30:33,327] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'description'"}
|
||
[2026-03-02 11:30:54,686] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:30:54,686] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:30:54,686] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:30:54,686] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:30:54,686] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:30:54,687] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:30:54,687] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:30:54,687] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:30:54,725] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:30:54,725] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:30:54,725] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:31:54,249] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:31:54,249] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:31:54,249] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:31:54,249] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:31:54,249] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:31:54,249] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:31:54,249] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:31:54,250] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:31:54,291] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:31:54,291] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:31:54,292] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:32:03,024] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:32:03,024] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: create tool to get system name
|
||
[2026-03-02 11:32:03,025] [agent.MEMORY] DEBUG: 💬 [USER] create tool to get system name...
|
||
[2026-03-02 11:32:03,025] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:32:03,025] [agent.LLM] INFO: 💭 分析意图: create tool to get system name...
|
||
[2026-03-02 11:32:03,025] [agent.LLM] DEBUG: 📝 Prompt 已构造 (442 chars)
|
||
[2026-03-02 11:32:05,556] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"task_description": "Create a tool to retrieve the name of the system or operating system."}, "reasoning": "The user wants to create a tool capable of retrieving the system name. This requires generating code for the tool, which falls under the capabilities of the 'agent_skill_generator' tool."}
|
||
[2026-03-02 11:32:05,556] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:32:05,557] [agent.LLM] DEBUG: 💡 推理: The user wants to create a tool capable of retrieving the system name. This requires generating code for the tool, which falls under the capabilities of the 'agent_skill_generator' tool.
|
||
[2026-03-02 11:32:05,557] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'task_description': 'Create a tool to retrieve the name of the system or operating system.'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '40b58637', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'task_description': 'Create a tool to retrieve the name of the system or operating system.'}}}
|
||
[2026-03-02 11:32:05,557] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:32:05,557] [agent.MCP] INFO: 📨 收到请求 id=40b58637 method=tools/call
|
||
[2026-03-02 11:32:05,557] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'task_description': 'Create a tool to retrieve the name of the system or operating system.'}
|
||
[2026-03-02 11:32:05,557] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'task_description'
|
||
[2026-03-02 11:32:05,557] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'task_description'"}
|
||
[2026-03-02 11:34:15,429] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:34:15,430] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:34:15,430] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:34:15,430] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:34:15,430] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:34:15,430] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:34:15,430] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:34:15,430] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:34:15,468] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:34:15,468] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:34:15,468] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:34:22,464] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:34:22,465] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: create tool to get system name
|
||
[2026-03-02 11:34:22,465] [agent.MEMORY] DEBUG: 💬 [USER] create tool to get system name...
|
||
[2026-03-02 11:34:22,465] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:34:22,465] [agent.LLM] INFO: 💭 分析意图: create tool to get system name...
|
||
[2026-03-02 11:34:22,465] [agent.LLM] DEBUG: 📝 Prompt 已构造 (442 chars)
|
||
[2026-03-02 11:34:24,754] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"description": "A tool to retrieve the name of the operating system or system information."}, "reasoning": "The task involves creating a specialized tool, which aligns with the purpose of the 'agent_skill_generator' to generate agent tools based on user requirements."}
|
||
[2026-03-02 11:34:24,754] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:34:24,754] [agent.LLM] DEBUG: 💡 推理: The task involves creating a specialized tool, which aligns with the purpose of the 'agent_skill_generator' to generate agent tools based on user requirements.
|
||
[2026-03-02 11:34:24,755] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'description': 'A tool to retrieve the name of the operating system or system information.'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '29799203', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'description': 'A tool to retrieve the name of the operating system or system information.'}}}
|
||
[2026-03-02 11:34:24,755] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:34:24,755] [agent.MCP] INFO: 📨 收到请求 id=29799203 method=tools/call
|
||
[2026-03-02 11:34:24,755] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'description': 'A tool to retrieve the name of the operating system or system information.'}
|
||
[2026-03-02 11:34:24,755] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() missing 3 required positional arguments: 'name', 'parameters', and 'execution_code'
|
||
[2026-03-02 11:34:24,755] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() missing 3 required positional arguments: 'name', 'parameters', and 'execution_code'"}
|
||
[2026-03-02 11:35:56,812] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:35:56,812] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:35:56,813] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:35:56,813] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:35:56,813] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:35:56,813] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:35:56,813] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:35:56,813] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:35:56,850] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:35:56,850] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:35:56,851] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:36:13,470] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:36:13,470] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: create tool to get system name
|
||
[2026-03-02 11:36:13,470] [agent.MEMORY] DEBUG: 💬 [USER] create tool to get system name...
|
||
[2026-03-02 11:36:13,470] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:36:13,470] [agent.LLM] INFO: 💭 分析意图: create tool to get system name...
|
||
[2026-03-02 11:36:13,471] [agent.LLM] DEBUG: 📝 Prompt 已构造 (442 chars)
|
||
[2026-03-02 11:36:15,863] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"description": "Generate a tool to fetch the system name of the machine it is run on.", "input_format": "", "output_format": "The system name as a string."}, "reasoning": "The user requested to create a tool that retrieves the system name, which requires generating a specific agent skill to achieve this functionality."}
|
||
[2026-03-02 11:36:15,863] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:36:15,863] [agent.LLM] DEBUG: 💡 推理: The user requested to create a tool that retrieves the system name, which requires generating a specific agent skill to achieve this functionality.
|
||
[2026-03-02 11:36:15,863] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'description': 'Generate a tool to fetch the system name of the machine it is run on.', 'input_format': '', 'output_format': 'The system name as a string.'}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'c03b28f1', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'description': 'Generate a tool to fetch the system name of the machine it is run on.', 'input_format': '', 'output_format': 'The system name as a string.'}}}
|
||
[2026-03-02 11:36:15,863] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:36:15,863] [agent.MCP] INFO: 📨 收到请求 id=c03b28f1 method=tools/call
|
||
[2026-03-02 11:36:15,863] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'description': 'Generate a tool to fetch the system name of the machine it is run on.', 'input_format': '', 'output_format': 'The system name as a string.'}
|
||
[2026-03-02 11:36:15,864] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'input_format'
|
||
[2026-03-02 11:36:15,864] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'input_format'"}
|
||
[2026-03-02 11:36:54,380] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:36:54,380] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate python function to get system name
|
||
[2026-03-02 11:36:54,380] [agent.MEMORY] DEBUG: 💬 [USER] generate python function to get system name...
|
||
[2026-03-02 11:36:54,380] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:36:54,380] [agent.LLM] INFO: 💭 分析意图: generate python function to get system name...
|
||
[2026-03-02 11:36:54,380] [agent.LLM] DEBUG: 📝 Prompt 已构造 (506 chars)
|
||
[2026-03-02 11:36:56,964] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"request": "generate a Python function to get the system name"}, "reasoning": "The user has requested the generation of a Python function to get the system name, which can be fulfilled using the 'agent_skill_generator' tool that creates agent tools or code snippets."}
|
||
[2026-03-02 11:36:56,964] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:36:56,964] [agent.LLM] DEBUG: 💡 推理: The user has requested the generation of a Python function to get the system name, which can be fulfilled using the 'agent_skill_generator' tool that creates agent tools or code snippets.
|
||
[2026-03-02 11:36:56,965] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'request': 'generate a Python function to get the system name'}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'e985d57b', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'request': 'generate a Python function to get the system name'}}}
|
||
[2026-03-02 11:36:56,965] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:36:56,965] [agent.MCP] INFO: 📨 收到请求 id=e985d57b method=tools/call
|
||
[2026-03-02 11:36:56,965] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'request': 'generate a Python function to get the system name'}
|
||
[2026-03-02 11:36:56,965] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'request'
|
||
[2026-03-02 11:36:56,966] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() got an unexpected keyword argument 'request'"}
|
||
[2026-03-02 11:37:17,360] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:37:17,361] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:37:17,361] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:37:17,361] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:37:17,361] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:37:17,361] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:37:17,361] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:37:17,361] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:37:17,398] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:37:17,398] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:37:17,399] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:37:33,225] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:37:33,225] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate python tool to get system name
|
||
[2026-03-02 11:37:33,226] [agent.MEMORY] DEBUG: 💬 [USER] generate python tool to get system name...
|
||
[2026-03-02 11:37:33,226] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:37:33,226] [agent.LLM] INFO: 💭 分析意图: generate python tool to get system name...
|
||
[2026-03-02 11:37:33,226] [agent.LLM] DEBUG: 📝 Prompt 已构造 (460 chars)
|
||
[2026-03-02 11:37:35,615] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"description": "A python tool to get the system name"}, "reasoning": "The user is requesting a Python tool that retrieves the system name. To fulfill this request, the agent_skill_generator is the appropriate tool to generate this code."}
|
||
[2026-03-02 11:37:35,615] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:37:35,615] [agent.LLM] DEBUG: 💡 推理: The user is requesting a Python tool that retrieves the system name. To fulfill this request, the agent_skill_generator is the appropriate tool to generate this code.
|
||
[2026-03-02 11:37:35,615] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'description': 'A python tool to get the system name'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '1bbc8950', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'description': 'A python tool to get the system name'}}}
|
||
[2026-03-02 11:37:35,615] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:37:35,615] [agent.MCP] INFO: 📨 收到请求 id=1bbc8950 method=tools/call
|
||
[2026-03-02 11:37:35,615] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'description': 'A python tool to get the system name'}
|
||
[2026-03-02 11:37:35,615] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: AgentSkillGeneratorTool.execute() missing 3 required positional arguments: 'name', 'parameters', and 'code'
|
||
[2026-03-02 11:37:35,615] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: AgentSkillGeneratorTool.execute() missing 3 required positional arguments: 'name', 'parameters', and 'code'"}
|
||
[2026-03-02 11:40:22,719] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:40:22,719] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:40:22,720] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:40:22,720] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:40:22,720] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:40:22,720] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:40:22,720] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:40:22,720] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:40:22,757] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:40:22,758] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:40:22,758] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:41:21,329] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:41:21,330] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:41:21,330] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:41:21,330] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:41:21,330] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:41:21,330] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:41:21,330] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:41:21,330] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:41:21,368] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:41:21,369] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:41:21,369] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:41:26,744] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:41:26,745] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: create a tool to get system name
|
||
[2026-03-02 11:41:26,745] [agent.MEMORY] DEBUG: 💬 [USER] create a tool to get system name...
|
||
[2026-03-02 11:41:26,745] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:41:26,745] [agent.LLM] INFO: 💭 分析意图: create a tool to get system name...
|
||
[2026-03-02 11:41:26,745] [agent.LLM] DEBUG: 📝 Prompt 已构造 (446 chars)
|
||
[2026-03-02 11:41:28,904] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"prompt": "Create a tool to get the operating system name of the current system in Python"}, "reasoning": "To create a tool for retrieving the system name, I should use the 'agent_skill_generator' tool to define and construct this functionality."}
|
||
[2026-03-02 11:41:28,904] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:41:28,905] [agent.LLM] DEBUG: 💡 推理: To create a tool for retrieving the system name, I should use the 'agent_skill_generator' tool to define and construct this functionality.
|
||
[2026-03-02 11:41:28,905] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'prompt': 'Create a tool to get the operating system name of the current system in Python'}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'b4653973', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'prompt': 'Create a tool to get the operating system name of the current system in Python'}}}
|
||
[2026-03-02 11:41:28,905] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:41:28,905] [agent.MCP] INFO: 📨 收到请求 id=b4653973 method=tools/call
|
||
[2026-03-02 11:41:28,905] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'prompt': 'Create a tool to get the operating system name of the current system in Python'}
|
||
[2026-03-02 11:41:28,905] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: ToolGeneratorTool.execute() got an unexpected keyword argument 'prompt'
|
||
[2026-03-02 11:41:28,905] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: ToolGeneratorTool.execute() got an unexpected keyword argument 'prompt'"}
|
||
[2026-03-02 11:41:58,733] [agent.MEMORY] INFO: 🗑 对话历史已清空
|
||
[2026-03-02 11:41:58,733] [agent.CLIENT] INFO: 🗑 会话已清空
|
||
[2026-03-02 11:42:03,610] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 11:42:03,611] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 11:42:03,611] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 11:42:03,611] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 11:42:03,611] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 11:42:03,611] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 11:42:03,611] [agent.MCP] INFO: 📌 注册工具: [agent_skill_generator] — 生成agent工具代码
|
||
[2026-03-02 11:42:03,611] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 11:42:03,650] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 11:42:03,650] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 11:42:03,650] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'agent_skill_generator']
|
||
[2026-03-02 11:42:09,009] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 11:42:09,009] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: create tool to get system name
|
||
[2026-03-02 11:42:09,009] [agent.MEMORY] DEBUG: 💬 [USER] create tool to get system name...
|
||
[2026-03-02 11:42:09,009] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 11:42:09,009] [agent.LLM] INFO: 💭 分析意图: create tool to get system name...
|
||
[2026-03-02 11:42:09,009] [agent.LLM] DEBUG: 📝 Prompt 已构造 (442 chars)
|
||
[2026-03-02 11:42:11,109] [agent.Monica] INFO: {"need_tool": true, "tool_name": "agent_skill_generator", "arguments": {"description": "A tool to retrieve the system's name or hostname"}, "reasoning": "The user wants to create a tool to retrieve the system's name, which requires generating custom code for a new tool. The appropriate action is to use the 'agent_skill_generator' tool to create this functionality."}
|
||
[2026-03-02 11:42:11,109] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [agent_skill_generator]
|
||
[2026-03-02 11:42:11,109] [agent.LLM] DEBUG: 💡 推理: The user wants to create a tool to retrieve the system's name, which requires generating custom code for a new tool. The appropriate action is to use the 'agent_skill_generator' tool to create this functionality.
|
||
[2026-03-02 11:42:11,109] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: agent_skill_generator
|
||
参数: {'description': "A tool to retrieve the system's name or hostname"}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'da607239', 'method': 'tools/call', 'params': {'name': 'agent_skill_generator', 'arguments': {'description': "A tool to retrieve the system's name or hostname"}}}
|
||
[2026-03-02 11:42:11,109] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [agent_skill_generator]...
|
||
[2026-03-02 11:42:11,109] [agent.MCP] INFO: 📨 收到请求 id=da607239 method=tools/call
|
||
[2026-03-02 11:42:11,110] [agent.TOOL] INFO: ▶ 执行工具 [agent_skill_generator]，参数: {'description': "A tool to retrieve the system's name or hostname"}
|
||
[2026-03-02 11:42:11,110] [agent.TOOL] ERROR: ❌ 工具 [agent_skill_generator] 执行失败: ToolGeneratorTool.execute() missing 3 required positional arguments: 'name', 'parameters', and 'code'
|
||
[2026-03-02 11:42:11,110] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: ToolGeneratorTool.execute() missing 3 required positional arguments: 'name', 'parameters', and 'code'"}
|
||
[2026-03-02 13:46:40,526] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 13:46:40,527] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 13:46:40,527] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 13:46:40,527] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 13:46:40,527] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 13:46:40,527] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 13:46:40,527] [agent.MCP] INFO: 📌 注册工具: [tool_generator] — 生成agent工具代码
|
||
[2026-03-02 13:46:40,527] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 13:46:51,425] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 13:46:51,425] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 13:46:51,425] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 13:46:51,425] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 13:46:51,426] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 13:46:51,426] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 13:46:51,426] [agent.MCP] INFO: 📌 注册工具: [tool_generator] — 生成agent工具代码
|
||
[2026-03-02 13:46:51,426] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 13:46:51,468] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 13:46:51,468] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 13:46:51,469] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'tool_generator']
|
||
[2026-03-02 13:47:26,677] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 13:47:26,678] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 13:47:26,678] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 13:47:26,678] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 13:47:26,678] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 13:47:26,678] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 13:47:26,678] [agent.MCP] INFO: 📌 注册工具: [tool_generator] — 生成agent工具代码
|
||
[2026-03-02 13:47:26,678] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 13:47:26,718] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 13:47:26,718] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 13:47:26,719] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'tool_generator']
|
||
[2026-03-02 13:47:37,167] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 13:47:37,167] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate a python function to get system's name
|
||
[2026-03-02 13:47:37,167] [agent.MEMORY] DEBUG: 💬 [USER] generate a python function to get system's name...
|
||
[2026-03-02 13:47:37,167] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 13:47:37,167] [agent.LLM] INFO: 💭 分析意图: generate a python function to get system's name...
|
||
[2026-03-02 13:47:37,167] [agent.LLM] DEBUG: 📝 Prompt 已构造 (469 chars)
|
||
[2026-03-02 13:47:39,191] [agent.Monica] INFO: {"need_tool": false, "tool_name": "", "arguments": {}, "reasoning": "The task involves generating a Python function, which can be done directly without requiring the use of any tools."}
|
||
[2026-03-02 13:47:39,191] [agent.LLM] INFO: 🎯 决策结果: 直接回复
|
||
[2026-03-02 13:47:39,191] [agent.LLM] DEBUG: 💡 推理: The task involves generating a Python function, which can be done directly without requiring the use of any tools.
|
||
[2026-03-02 13:47:39,191] [agent.CLIENT] INFO: 💬 无需工具，直接生成回复
|
||
[2026-03-02 13:47:39,191] [agent.LLM] INFO: 💬 直接生成回复（无需工具）
|
||
[2026-03-02 13:47:39,191] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] [gpt-4o] 您好！关于「generate a python function to get system's na...
|
||
[2026-03-02 14:10:27,448] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 14:10:27,448] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 14:10:27,448] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 14:10:27,448] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 14:10:27,449] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 14:10:27,449] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 14:10:27,449] [agent.MCP] INFO: 📌 注册工具: [tool_generator] — 生成agent工具代码
|
||
[2026-03-02 14:10:27,449] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 14:10:27,487] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 14:10:27,487] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 14:10:27,488] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'tool_generator']
|
||
[2026-03-02 14:10:39,389] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 14:10:39,389] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate a python function to get system's name
|
||
[2026-03-02 14:10:39,389] [agent.MEMORY] DEBUG: 💬 [USER] generate a python function to get system's name...
|
||
[2026-03-02 14:10:39,389] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 14:10:39,389] [agent.LLM] INFO: 💭 分析意图: generate a python function to get system's name...
|
||
[2026-03-02 14:10:39,390] [agent.LLM] DEBUG: 📝 Prompt 已构造 (469 chars)
|
||
[2026-03-02 14:10:43,803] [agent.Monica] INFO: {"need_tool": false, "tool_name": "", "arguments": {}, "reasoning": "The task can be accomplished without any tools by providing a Python code snippet to get the system's name using the platform module."}
|
||
[2026-03-02 14:10:43,803] [agent.LLM] INFO: 🎯 决策结果: 直接回复
|
||
[2026-03-02 14:10:43,803] [agent.LLM] DEBUG: 💡 推理: The task can be accomplished without any tools by providing a Python code snippet to get the system's name using the platform module.
|
||
[2026-03-02 14:10:43,803] [agent.CLIENT] INFO: 💬 无需工具，直接生成回复
|
||
[2026-03-02 14:10:43,803] [agent.LLM] INFO: 💬 直接生成回复（无需工具）
|
||
[2026-03-02 14:10:45,852] [agent.Monica] INFO: Here is a Python function to get the system's name using the `platform` module:
|
||
|
||
```python
|
||
import platform
|
||
|
||
def get_system_name():
|
||
"""
|
||
Returns the name of the system/OS.
|
||
For example: 'Windows', 'Linux', 'Darwin' (for macOS)
|
||
"""
|
||
return platform.system()
|
||
|
||
# Example usage
|
||
if __name__ == "__main__":
|
||
print("System name:", get_system_name())
|
||
```
|
||
|
||
This function uses the `platform.system()` method, which retrieves the name of the operating system your script is running on. For example, it will return `'Windows'` for Windows systems, `'Linux'` for Linux systems, or `'Darwin'` for macOS.
|
||
[2026-03-02 14:12:22,700] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 14:12:22,700] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 14:12:22,701] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 14:12:22,701] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 14:12:22,701] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 14:12:22,701] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 14:12:22,701] [agent.MCP] INFO: 📌 注册工具: [tool_generator] — 生成agent工具代码
|
||
[2026-03-02 14:12:22,701] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 14:12:22,741] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 14:12:22,741] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 14:12:22,742] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'tool_generator']
|
||
[2026-03-02 14:12:33,611] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 14:12:33,611] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate a python function to get system's name
|
||
[2026-03-02 14:12:33,612] [agent.MEMORY] DEBUG: 💬 [USER] generate a python function to get system's name...
|
||
[2026-03-02 14:12:33,612] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 14:12:33,612] [agent.LLM] INFO: 💭 分析意图: generate a python function to get system's name...
|
||
[2026-03-02 14:12:33,612] [agent.LLM] DEBUG: 📝 Prompt 已构造 (469 chars)
|
||
[2026-03-02 14:12:35,773] [agent.Monica] INFO: {"need_tool": false, "tool_name": "", "arguments": {}, "reasoning": "To generate a Python function that retrieves a system's name, no tool needs to be invoked; providing the Python code directly is sufficient."}
|
||
[2026-03-02 14:12:35,773] [agent.LLM] INFO: 🎯 决策结果: 直接回复
|
||
[2026-03-02 14:12:35,773] [agent.LLM] DEBUG: 💡 推理: To generate a Python function that retrieves a system's name, no tool needs to be invoked; providing the Python code directly is sufficient.
|
||
[2026-03-02 14:12:35,773] [agent.CLIENT] INFO: 💬 无需工具，直接生成回复
|
||
[2026-03-02 14:12:35,773] [agent.LLM] INFO: 💬 直接生成回复（无需工具）
|
||
[2026-03-02 14:12:37,842] [agent.Monica] INFO: Here is a Python function to get the system's name using the `platform` module:
|
||
|
||
```python
|
||
import platform
|
||
|
||
def get_system_name():
|
||
"""
|
||
This function retrieves the system's name.
|
||
Returns:
|
||
str: The name of the operating system (e.g., 'Windows', 'Linux', 'Darwin').
|
||
"""
|
||
system_name = platform.system()
|
||
return system_name
|
||
|
||
# Example usage
|
||
if __name__ == "__main__":
|
||
print(f"System Name: {get_system_name()}")
|
||
```
|
||
|
||
The function `get_system_name()` uses `platform.system()` to determine the system's name. This will return values such as:
|
||
- `Windows` for Windows,
|
||
- `Linux` for Linux-based systems,
|
||
- `Darwin` for macOS systems.
|
||
[2026-03-02 14:12:37,842] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] Here is a Python function to get the system's name using the...
|
||
[2026-03-02 14:13:24,958] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 14:13:24,959] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 将生成的代码转换成本地工具用于调用
|
||
[2026-03-02 14:13:24,959] [agent.MEMORY] DEBUG: 💬 [USER] 将生成的代码转换成本地工具用于调用...
|
||
[2026-03-02 14:13:24,959] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 14:13:24,959] [agent.LLM] INFO: 💭 分析意图: 将生成的代码转换成本地工具用于调用...
|
||
[2026-03-02 14:13:24,959] [agent.LLM] DEBUG: 📝 Prompt 已构造 (557 chars)
|
||
[2026-03-02 14:13:29,677] [agent.Monica] INFO: {
|
||
"need_tool": true,
|
||
"tool_name": "tool_generator",
|
||
"arguments": {
|
||
"code": "import platform\ndef get_system_name():\n return platform.system()"
|
||
},
|
||
"reasoning": "The user wants to convert the previously generated code into a local tool for calling, which can be achieved using the tool_generator by providing the generated code."
|
||
}
|
||
[2026-03-02 14:13:29,678] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [tool_generator]
|
||
[2026-03-02 14:13:29,678] [agent.LLM] DEBUG: 💡 推理: The user wants to convert the previously generated code into a local tool for calling, which can be achieved using the tool_generator by providing the generated code.
|
||
[2026-03-02 14:13:29,678] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: tool_generator
|
||
参数: {'code': 'import platform\ndef get_system_name():\n return platform.system()'}
|
||
请求体: {'jsonrpc': '2.0', 'id': 'a7e1eee2', 'method': 'tools/call', 'params': {'name': 'tool_generator', 'arguments': {'code': 'import platform\ndef get_system_name():\n return platform.system()'}}}
|
||
[2026-03-02 14:13:29,679] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [tool_generator]...
|
||
[2026-03-02 14:13:29,679] [agent.MCP] INFO: 📨 收到请求 id=a7e1eee2 method=tools/call
|
||
[2026-03-02 14:13:29,679] [agent.TOOL] INFO: ▶ 执行工具 [tool_generator]，参数: {'code': 'import platform\ndef get_system_name():\n return platform.system()'}
|
||
[2026-03-02 14:13:29,679] [agent.TOOL] ERROR: ❌ 工具 [tool_generator] 执行失败: ToolGeneratorTool.execute() missing 3 required positional arguments: 'name', 'description', and 'parameters'
|
||
[2026-03-02 14:13:29,680] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: ToolGeneratorTool.execute() missing 3 required positional arguments: 'name', 'description', and 'parameters'"}
|
||
[2026-03-02 14:16:50,715] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
|
||
[2026-03-02 14:16:50,716] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-02 14:16:50,716] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-02 14:16:50,716] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-02 14:16:50,716] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限 workspace/ 目录下的文件
|
||
[2026-03-02 14:16:50,716] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-02 14:16:50,716] [agent.MCP] INFO: 📌 注册工具: [tool_generator] — 生成agent工具代码
|
||
[2026-03-02 14:16:50,716] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
|
||
[2026-03-02 14:16:50,754] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-02 14:16:50,754] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
|
||
[2026-03-02 14:16:50,754] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'tool_generator']
|
||
[2026-03-02 14:17:52,746] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 14:17:52,746] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate the python code to get system's name and generate a tool with the code
|
||
[2026-03-02 14:17:52,746] [agent.MEMORY] DEBUG: 💬 [USER] generate the python code to get system's name and generate a...
|
||
[2026-03-02 14:17:52,746] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 14:17:52,746] [agent.LLM] INFO: 💭 分析意图: generate the python code to get system's name and ...
|
||
[2026-03-02 14:17:52,746] [agent.LLM] DEBUG: 📝 Prompt 已构造 (533 chars)
|
||
[2026-03-02 14:17:55,200] [agent.Monica] INFO: {"need_tool": true, "tool_name": "tool_generator", "arguments": {"code": "import platform\n\ndef get_system_name():\n return platform.system()"}, "reasoning": "The user explicitly requested to generate a Python script that retrieves the system's name, and to create a tool based on that code. The provided tool_generator is appropriate for this task."}
|
||
[2026-03-02 14:17:55,200] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [tool_generator]
|
||
[2026-03-02 14:17:55,200] [agent.LLM] DEBUG: 💡 推理: The user explicitly requested to generate a Python script that retrieves the system's name, and to create a tool based on that code. The provided tool_generator is appropriate for this task.
|
||
[2026-03-02 14:17:55,200] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: tool_generator
|
||
参数: {'code': 'import platform\n\ndef get_system_name():\n return platform.system()'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '6adf8eba', 'method': 'tools/call', 'params': {'name': 'tool_generator', 'arguments': {'code': 'import platform\n\ndef get_system_name():\n return platform.system()'}}}
|
||
[2026-03-02 14:17:55,200] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [tool_generator]...
|
||
[2026-03-02 14:17:55,201] [agent.MCP] INFO: 📨 收到请求 id=6adf8eba method=tools/call
|
||
[2026-03-02 14:17:55,201] [agent.TOOL] INFO: ▶ 执行工具 [tool_generator]，参数: {'code': 'import platform\n\ndef get_system_name():\n return platform.system()'}
|
||
[2026-03-02 14:17:55,201] [agent.TOOL] ERROR: ❌ 工具 [tool_generator] 执行失败: ToolGeneratorTool.execute() missing 3 required positional arguments: 'name', 'description', and 'parameters'
|
||
[2026-03-02 14:17:55,201] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: ToolGeneratorTool.execute() missing 3 required positional arguments: 'name', 'description', and 'parameters'"}
|
||
[2026-03-02 14:21:07,265] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 14:21:07,266] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate the python function to get system's name and then generate the a tool with the code that includes tool name, tool description
|
||
[2026-03-02 14:21:07,266] [agent.MEMORY] DEBUG: 💬 [USER] generate the python function to get system's name and then g...
|
||
[2026-03-02 14:21:07,266] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 14:21:07,266] [agent.LLM] INFO: 💭 分析意图: generate the python function to get system's name ...
|
||
[2026-03-02 14:21:07,266] [agent.LLM] DEBUG: 📝 Prompt 已构造 (676 chars)
|
||
[2026-03-02 14:21:09,618] [agent.Monica] INFO: {"need_tool": true, "tool_name": "tool_generator", "arguments": {"code": "def get_system_name():\n import platform\n return platform.system()", "tool_name": "get_system_name_tool", "tool_description": "A tool to retrieve the name of the operating system."}, "reasoning": "User wants to generate a tool based on the Python function for retrieving the system's name. The tool_generator is appropriate for creating such a tool with the provided code, name, and description."}
|
||
[2026-03-02 14:21:09,618] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [tool_generator]
|
||
[2026-03-02 14:21:09,618] [agent.LLM] DEBUG: 💡 推理: User wants to generate a tool based on the Python function for retrieving the system's name. The tool_generator is appropriate for creating such a tool with the provided code, name, and description.
|
||
[2026-03-02 14:21:09,618] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: tool_generator
|
||
参数: {'code': 'def get_system_name():\n import platform\n return platform.system()', 'tool_name': 'get_system_name_tool', 'tool_description': 'A tool to retrieve the name of the operating system.'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '766f288c', 'method': 'tools/call', 'params': {'name': 'tool_generator', 'arguments': {'code': 'def get_system_name():\n import platform\n return platform.system()', 'tool_name': 'get_system_name_tool', 'tool_description': 'A tool to retrieve the name of the operating system.'}}}
|
||
[2026-03-02 14:21:09,618] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [tool_generator]...
|
||
[2026-03-02 14:21:09,618] [agent.MCP] INFO: 📨 收到请求 id=766f288c method=tools/call
|
||
[2026-03-02 14:21:09,618] [agent.TOOL] INFO: ▶ 执行工具 [tool_generator]，参数: {'code': 'def get_system_name():\n import platform\n return platform.system()', 'tool_name': 'get_system_name_tool', 'tool_description': 'A tool to retrieve the name of the operating system.'}
|
||
[2026-03-02 14:21:09,618] [agent.TOOL] ERROR: ❌ 工具 [tool_generator] 执行失败: ToolGeneratorTool.execute() got an unexpected keyword argument 'tool_name'
|
||
[2026-03-02 14:21:09,618] [agent.CLIENT] ERROR: ❌ 工具调用失败: {'code': -32000, 'message': "工具执行异常: ToolGeneratorTool.execute() got an unexpected keyword argument 'tool_name'"}
|
||
[2026-03-02 14:27:41,610] [agent.CLIENT] INFO: =======================================================
|
||
[2026-03-02 14:27:41,610] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: generate the python function to get system's name and then generate the a tool with the code that includes tool name, tool description, tool parameters and code.
|
||
[2026-03-02 14:27:41,611] [agent.MEMORY] DEBUG: 💬 [USER] generate the python function to get system's name and then g...
|
||
[2026-03-02 14:27:41,611] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
|
||
[2026-03-02 14:27:41,611] [agent.LLM] INFO: 💭 分析意图: generate the python function to get system's name ...
|
||
[2026-03-02 14:27:41,611] [agent.LLM] DEBUG: 📝 Prompt 已构造 (791 chars)
|
||
[2026-03-02 14:27:44,132] [agent.Monica] INFO: {
|
||
"need_tool": true,
|
||
"tool_name": "tool_generator",
|
||
"arguments": {
|
||
"name": "get_system_name",
|
||
"description": "Returns the name of the operating system of the machine.",
|
||
"parameters": {},
|
||
"code": "import platform\ndef get_system_name():\n return platform.system()"
|
||
},
|
||
"reasoning": "The user requested to generate a Python function that retrieves the system's name and then encapsulate it into a tool with specified attributes such as tool name, description, parameters, and code. To accomplish this task, the `tool_generator` utility can be used with the specified parameters."
|
||
}
|
||
[2026-03-02 14:27:44,133] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [tool_generator]
|
||
[2026-03-02 14:27:44,133] [agent.LLM] DEBUG: 💡 推理: The user requested to generate a Python function that retrieves the system's name and then encapsulate it into a tool with specified attributes such as tool name, description, parameters, and code. To accomplish this task, the `tool_generator` utility can be used with the specified parameters.
|
||
[2026-03-02 14:27:44,133] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
|
||
方法: tools/call
|
||
工具: tool_generator
|
||
参数: {'name': 'get_system_name', 'description': 'Returns the name of the operating system of the machine.', 'parameters': {}, 'code': 'import platform\ndef get_system_name():\n return platform.system()'}
|
||
请求体: {'jsonrpc': '2.0', 'id': '9118bd32', 'method': 'tools/call', 'params': {'name': 'tool_generator', 'arguments': {'name': 'get_system_name', 'description': 'Returns the name of the operating system of the machine.', 'parameters': {}, 'code': 'import platform\ndef get_system_name():\n return platform.system()'}}}
|
||
[2026-03-02 14:27:44,134] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [tool_generator]...
|
||
[2026-03-02 14:27:44,134] [agent.MCP] INFO: 📨 收到请求 id=9118bd32 method=tools/call
|
||
[2026-03-02 14:27:44,134] [agent.TOOL] INFO: ▶ 执行工具 [tool_generator]，参数: {'name': 'get_system_name', 'description': 'Returns the name of the operating system of the machine.', 'parameters': {}, 'code': 'import platform\ndef get_system_name():\n return platform.system()'}
|
||
[2026-03-02 14:27:44,134] [agent.TOOL] INFO: ✅ 工具 [tool_generator] 执行成功
|
||
[2026-03-09 13:11:25,019] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（配置文件驱动）...
|
||
[2026-03-09 13:11:25,019] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────
|
||
[LLM] provider = anthropic
|
||
[LLM] model_name = claude-sonnet-4-6
|
||
[LLM] model_path = (未设置)
|
||
[LLM] api_key = (未设置)
|
||
[LLM] temperature = 0.7
|
||
[MCP] server_name = DemoMCPServer
|
||
[MCP] transport = stdio
|
||
[MCP] tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[MEMORY] max_history = 20
|
||
[AGENT] multi_step = True
|
||
[AGENT] max_steps = 10
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────
|
||
[2026-03-09 13:11:25,020] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 13:11:25,020] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 13:11:25,020] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:11:25,021] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 13:11:25,021] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 13:11:25,021] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 13:11:25,022] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 13:11:25,022] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 13:11:25,022] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 13:11:25,022] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 13:11:25,022] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 13:11:25,023] [agent.LLM] INFO: 🧠 LLM 引擎初始化
|
||
[2026-03-09 13:11:25,024] [agent.LLM] INFO: provider = anthropic
|
||
[2026-03-09 13:11:25,024] [agent.LLM] INFO: model_name = claude-sonnet-4-6
|
||
[2026-03-09 13:11:25,024] [agent.LLM] INFO: model_path = (未设置)
|
||
[2026-03-09 13:11:25,025] [agent.LLM] INFO: api_base = (默认)
|
||
[2026-03-09 13:11:25,025] [agent.LLM] INFO: temperature= 0.7
|
||
[2026-03-09 13:11:25,025] [agent.LLM] INFO: max_tokens = 4096
|
||
[2026-03-09 13:11:25,026] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 13:11:25,027] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（支持多步串行调用）
|
||
[2026-03-09 13:11:25,027] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:14:47,765] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（配置文件驱动）...
|
||
[2026-03-09 13:14:47,768] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────
|
||
[LLM] provider = anthropic
|
||
[LLM] model_name = claude-sonnet-4-6
|
||
[LLM] model_path = (未设置)
|
||
[LLM] api_key = (未设置)
|
||
[LLM] temperature = 0.7
|
||
[MCP] server_name = DemoMCPServer
|
||
[MCP] transport = stdio
|
||
[MCP] tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[MEMORY] max_history = 20
|
||
[AGENT] multi_step = True
|
||
[AGENT] max_steps = 10
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────
|
||
[2026-03-09 13:14:47,769] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 13:14:47,769] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 13:14:47,769] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:14:47,770] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 13:14:47,770] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 13:14:47,770] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 13:14:47,770] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 13:14:47,771] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 13:14:47,771] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 13:14:47,771] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 13:14:47,771] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 13:14:47,772] [agent.LLM] INFO: 🧠 LLM 引擎初始化
|
||
[2026-03-09 13:14:47,773] [agent.LLM] INFO: provider = anthropic
|
||
[2026-03-09 13:14:47,773] [agent.LLM] INFO: model_name = claude-sonnet-4-6
|
||
[2026-03-09 13:14:47,773] [agent.LLM] INFO: model_path = (未设置)
|
||
[2026-03-09 13:14:47,773] [agent.LLM] INFO: api_base = (默认)
|
||
[2026-03-09 13:14:47,773] [agent.LLM] INFO: temperature= 0.7
|
||
[2026-03-09 13:14:47,774] [agent.LLM] INFO: max_tokens = 4096
|
||
[2026-03-09 13:14:47,775] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 13:14:47,776] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（支持多步串行调用）
|
||
[2026-03-09 13:14:47,777] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:15:29,737] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（配置文件驱动）...
|
||
[2026-03-09 13:15:29,739] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────
|
||
[LLM] provider = monica
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] model_path = (未设置)
|
||
[LLM] api_key = ***
|
||
[LLM] temperature = 0.7
|
||
[MCP] server_name = MCPServer
|
||
[MCP] transport = stdio
|
||
[MCP] tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[MEMORY] max_history = 20
|
||
[AGENT] multi_step = True
|
||
[AGENT] max_steps = 10
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────
|
||
[2026-03-09 13:15:29,742] [agent.MCP] INFO: 🚀 MCP Server [MCPServer] 启动
|
||
[2026-03-09 13:15:29,743] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 13:15:29,743] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:15:29,745] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 13:15:29,745] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 13:15:29,745] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 13:15:29,745] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 13:15:29,746] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 13:15:29,746] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 13:15:29,747] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 13:15:29,748] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 13:15:29,748] [agent.LLM] INFO: 🧠 LLM 引擎初始化
|
||
[2026-03-09 13:15:29,749] [agent.LLM] INFO: provider = monica
|
||
[2026-03-09 13:15:29,749] [agent.LLM] INFO: model_name = gpt-4o
|
||
[2026-03-09 13:15:29,749] [agent.LLM] INFO: model_path = (未设置)
|
||
[2026-03-09 13:15:29,749] [agent.LLM] INFO: api_base = https://openapi.monica.im/v1
|
||
[2026-03-09 13:15:29,750] [agent.LLM] INFO: temperature= 0.7
|
||
[2026-03-09 13:15:29,750] [agent.LLM] INFO: max_tokens = 4096
|
||
[2026-03-09 13:15:29,751] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 13:15:29,752] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（支持多步串行调用）
|
||
[2026-03-09 13:15:29,752] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:17:27,993] [agent.CLIENT] INFO: ══════════════════════════════════════════════════════════
|
||
[2026-03-09 13:17:27,995] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 从从网络搜索获取系统名称的python代码并进行执行
|
||
[2026-03-09 13:17:27,996] [agent.CLIENT] INFO: ══════════════════════════════════════════════════════════
|
||
[2026-03-09 13:17:27,996] [agent.MEMORY] DEBUG: 💬 [USER] 从从网络搜索获取系统名称的python代码并进行执行...
|
||
[2026-03-09 13:17:27,997] [agent.CLIENT] INFO: 🗺 Step 2 [LLM] 分析任务，规划工具调用链...
|
||
[2026-03-09 13:17:27,997] [agent.LLM] INFO: 🗺 规划工具调用链 [gpt-4o]: 从从网络搜索获取系统名称的python代码并进行执行...
|
||
[2026-03-09 13:17:27,998] [agent.LLM] DEBUG: 📝 Prompt 已构造 (436 chars)
|
||
[2026-03-09 13:17:27,998] [agent.LLM] INFO: 📋 规划完成: ChainPlan(goal='从从网络搜索获取系统名称的python代码并进行执行', chain=[1]web_search)
|
||
[2026-03-09 13:17:27,998] [agent.LLM] INFO: Step 1: [web_search] depends_on=[] — 网络搜索
|
||
[2026-03-09 13:17:27,998] [agent.CLIENT] INFO:
|
||
──────────────────────────────────────────────────────────
|
||
🔗 开始执行工具调用链
|
||
目标: 从从网络搜索获取系统名称的python代码并进行执行
|
||
步骤: 1 步
|
||
──────────────────────────────────────────────────────────
|
||
[2026-03-09 13:17:27,999] [agent.CLIENT] INFO:
|
||
▶ Step 1/1 执行中
|
||
工具: [web_search]
|
||
说明: 网络搜索
|
||
参数: {'query': '从从网络搜索获取系统名称的python代码并进行执行', 'max_results': 5}
|
||
[2026-03-09 13:17:28,002] [agent.CLIENT] INFO: 📡 [MCP] 发送请求: {'jsonrpc': '2.0', 'id': 'dc801fda', 'method': 'tools/call', 'params': {'name': 'web_search', 'arguments': {'query': '从从网络搜索获取系统名称的python代码并进行执行', 'max_results': 5}}}
|
||
[2026-03-09 13:17:28,003] [agent.MCP] INFO: 📨 收到请求 id=dc801fda method=tools/call transport=stdio
|
||
[2026-03-09 13:17:28,003] [agent.TOOL] INFO: ▶ 执行工具 [web_search]，参数: {'query': '从从网络搜索获取系统名称的python代码并进行执行', 'max_results': 5}
|
||
[2026-03-09 13:17:28,108] [agent.TOOL] INFO: ✅ 工具 [web_search] 执行成功
|
||
[2026-03-09 13:17:28,109] [agent.CLIENT] INFO: ✅ Step 1 成功: 搜索「从从网络搜索获取系统名称的python代码并进行执行」(mock)，共 2 条:
|
||
[1] Python 官方文档
|
||
Python 3.12 新特性：...
|
||
[2026-03-09 13:17:28,109] [agent.MEMORY] DEBUG: 💬 [TOOL] 搜索「从从网络搜索获取系统名称的python代码并进行执行」(mock)，共 2 条:
|
||
[1] Python 官方文档
|
||
...
|
||
[2026-03-09 13:17:28,111] [agent.CLIENT] INFO: ──────────────────────────────────────────────────────────
|
||
✅ 调用链执行完成
|
||
完成: 1/1 步
|
||
──────────────────────────────────────────────────────────
|
||
[2026-03-09 13:17:28,111] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合所有步骤结果，生成最终回复...
|
||
[2026-03-09 13:17:28,111] [agent.LLM] INFO: ✍️ 整合单步工具结果 [gpt-4o]...
|
||
[2026-03-09 13:17:28,111] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [web_search] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
搜索「从从网络搜索获取系统名称的pyth...
|
||
[2026-03-09 13:18:21,524] [agent.CLIENT] INFO: ══════════════════════════════════════════════════════════
|
||
[2026-03-09 13:18:21,524] [agent.CLIENT] INFO: 📨 Step 1 [CLIENT] 收到用户输入: 计算1+1等于多少
|
||
[2026-03-09 13:18:21,524] [agent.CLIENT] INFO: ══════════════════════════════════════════════════════════
|
||
[2026-03-09 13:18:21,525] [agent.MEMORY] DEBUG: 💬 [USER] 计算1+1等于多少...
|
||
[2026-03-09 13:18:21,525] [agent.CLIENT] INFO: 🗺 Step 2 [LLM] 分析任务，规划工具调用链...
|
||
[2026-03-09 13:18:21,526] [agent.LLM] INFO: 🗺 规划工具调用链 [gpt-4o]: 计算1+1等于多少...
|
||
[2026-03-09 13:18:21,526] [agent.LLM] DEBUG: 📝 Prompt 已构造 (617 chars)
|
||
[2026-03-09 13:18:21,528] [agent.LLM] INFO: 📋 规划完成: ChainPlan(goal='计算1+1等于多少', chain=[1]calculator)
|
||
[2026-03-09 13:18:21,528] [agent.LLM] INFO: Step 1: [calculator] depends_on=[] — 数学计算
|
||
[2026-03-09 13:18:21,529] [agent.CLIENT] INFO:
|
||
──────────────────────────────────────────────────────────
|
||
🔗 开始执行工具调用链
|
||
目标: 计算1+1等于多少
|
||
步骤: 1 步
|
||
──────────────────────────────────────────────────────────
|
||
[2026-03-09 13:18:21,529] [agent.CLIENT] INFO:
|
||
▶ Step 1/1 执行中
|
||
工具: [calculator]
|
||
说明: 数学计算
|
||
参数: {'expression': '1+1'}
|
||
[2026-03-09 13:18:21,530] [agent.CLIENT] INFO: 📡 [MCP] 发送请求: {'jsonrpc': '2.0', 'id': 'd6becfe5', 'method': 'tools/call', 'params': {'name': 'calculator', 'arguments': {'expression': '1+1'}}}
|
||
[2026-03-09 13:18:21,530] [agent.MCP] INFO: 📨 收到请求 id=d6becfe5 method=tools/call transport=stdio
|
||
[2026-03-09 13:18:21,530] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '1+1'}
|
||
[2026-03-09 13:18:21,532] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-03-09 13:18:21,533] [agent.CLIENT] INFO: ✅ Step 1 成功: 1+1 = 2...
|
||
[2026-03-09 13:18:21,533] [agent.MEMORY] DEBUG: 💬 [TOOL] 1+1 = 2...
|
||
[2026-03-09 13:18:21,533] [agent.CLIENT] INFO: ──────────────────────────────────────────────────────────
|
||
✅ 调用链执行完成
|
||
完成: 1/1 步
|
||
──────────────────────────────────────────────────────────
|
||
[2026-03-09 13:18:21,534] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 整合所有步骤结果，生成最终回复...
|
||
[2026-03-09 13:18:21,534] [agent.LLM] INFO: ✍️ 整合单步工具结果 [gpt-4o]...
|
||
[2026-03-09 13:18:21,534] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [calculator] 工具处理您的请求。
|
||
|
||
**执行结果:**
|
||
1+1 = 2
|
||
|
||
---
|
||
*由 gpt-...
|
||
[2026-03-09 13:29:29,657] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 13:29:29,659] [agent.SYSTEM] INFO: ────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = (未设置)
|
||
[LLM] api_base_url = (默认)
|
||
[LLM] temperature = 0.7
|
||
[LLM] max_tokens = 4096
|
||
[LLM] function_calling = True
|
||
[LLM] stream = False
|
||
[LLM] max_retries = 3
|
||
[MCP] server_name = DemoMCPServer
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[MEMORY] max_history = 20
|
||
[AGENT] multi_step = True
|
||
[AGENT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
────────────────────────────────────────────────────
|
||
[2026-03-09 13:29:29,661] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 13:29:29,662] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 13:29:29,662] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:29:29,663] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 13:29:29,663] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 13:29:29,664] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 13:29:29,664] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 13:29:29,664] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 13:29:29,664] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 13:29:29,665] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 13:29:29,665] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 13:29:29,665] [agent.LLM] INFO: 🏭 Provider 工厂: 创建 [openai] Provider
|
||
[2026-03-09 13:29:33,124] [agent.LLM] WARNING: ⚠️ LLM_API_KEY 未设置，OpenAI API 调用将失败。
|
||
请设置环境变量: export LLM_API_KEY=sk-...
|
||
[2026-03-09 13:29:33,315] [agent.LLM] INFO: ✅ OpenAI 客户端初始化完成
|
||
model = gpt-4o
|
||
base_url = https://api.openai.com/v1
|
||
max_retries= 3
|
||
[2026-03-09 13:29:33,315] [agent.LLM] INFO: 🧠 LLM 引擎初始化完成
|
||
[2026-03-09 13:29:33,315] [agent.LLM] INFO: provider = openai
|
||
[2026-03-09 13:29:33,315] [agent.LLM] INFO: model_name = gpt-4o
|
||
[2026-03-09 13:29:33,315] [agent.LLM] INFO: function_calling = True
|
||
[2026-03-09 13:29:33,315] [agent.LLM] INFO: temperature = 0.7
|
||
[2026-03-09 13:29:33,316] [agent.LLM] INFO: fallback_rules = True
|
||
[2026-03-09 13:29:33,316] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 13:29:33,317] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（OpenAI Function Calling 模式）
|
||
[2026-03-09 13:29:33,317] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:30:14,954] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 13:30:14,954] [agent.SYSTEM] INFO: ────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] temperature = 0.7
|
||
[LLM] max_tokens = 4096
|
||
[LLM] function_calling = True
|
||
[LLM] stream = False
|
||
[LLM] max_retries = 3
|
||
[MCP] server_name = DemoMCPServer
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[MEMORY] max_history = 20
|
||
[AGENT] multi_step = True
|
||
[AGENT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
────────────────────────────────────────────────────
|
||
[2026-03-09 13:30:14,955] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 13:30:14,956] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 13:30:14,956] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:30:14,957] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 13:30:14,957] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 13:30:14,957] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 13:30:14,958] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 13:30:14,958] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 13:30:14,959] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 13:30:14,960] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 13:30:14,960] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 13:30:14,961] [agent.LLM] INFO: 🏭 Provider 工厂: 创建 [openai] Provider
|
||
[2026-03-09 13:30:17,075] [agent.LLM] INFO: 🔗 使用自定义 API 地址: https://openapi.monica.im/v1
|
||
[2026-03-09 13:30:17,245] [agent.LLM] INFO: ✅ OpenAI 客户端初始化完成
|
||
model = gpt-4o
|
||
base_url = https://openapi.monica.im/v1
|
||
max_retries= 3
|
||
[2026-03-09 13:30:17,246] [agent.LLM] INFO: 🧠 LLM 引擎初始化完成
|
||
[2026-03-09 13:30:17,246] [agent.LLM] INFO: provider = openai
|
||
[2026-03-09 13:30:17,246] [agent.LLM] INFO: model_name = gpt-4o
|
||
[2026-03-09 13:30:17,246] [agent.LLM] INFO: function_calling = True
|
||
[2026-03-09 13:30:17,247] [agent.LLM] INFO: temperature = 0.7
|
||
[2026-03-09 13:30:17,247] [agent.LLM] INFO: fallback_rules = True
|
||
[2026-03-09 13:30:17,248] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 13:30:17,249] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（OpenAI Function Calling 模式）
|
||
[2026-03-09 13:30:17,249] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:30:39,084] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:30:39,085] [agent.CLIENT] INFO: 📨 收到用户输入: 234乘以123等于多少
|
||
[2026-03-09 13:30:39,085] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:30:39,086] [agent.MEMORY] DEBUG: 💬 [USER] 234乘以123等于多少...
|
||
[2026-03-09 13:30:39,086] [agent.CLIENT] INFO: 🗺 Step 2 [LLM] 规划工具调用链...
|
||
[2026-03-09 13:30:39,086] [agent.LLM] INFO: 🗺 规划工具调用链: 234乘以123等于多少...
|
||
[2026-03-09 13:30:39,087] [agent.LLM] DEBUG: 📤 发送规划请求，tools 数量: 4
|
||
[2026-03-09 13:30:39,087] [agent.LLM] DEBUG: 📤 消息历史长度: 3
|
||
[2026-03-09 13:30:42,294] [agent.LLM] INFO: 📊 Token 用量: prompt=395, completion=17
|
||
[2026-03-09 13:30:42,294] [agent.LLM] INFO: 📋 解析到 1 个工具调用步骤
|
||
[2026-03-09 13:30:42,294] [agent.LLM] INFO: 📋 OpenAI 规划完成: 1 步
|
||
[2026-03-09 13:30:42,294] [agent.LLM] INFO: Step 1: [calculator] args={'expression': '234*123'}
|
||
[2026-03-09 13:30:42,294] [agent.CLIENT] INFO:
|
||
────────────────────────────────────────────────────────────
|
||
🔗 开始执行工具调用链
|
||
目标: calculator
|
||
步骤: 1 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:30:42,295] [agent.CLIENT] INFO:
|
||
▶ Step 1 执行中
|
||
工具: [calculator]
|
||
说明: 调用 calculator（由 OpenAI Function Calling 规划）
|
||
参数: {'expression': '234*123'}
|
||
call_id: call_6b8b5745
|
||
[2026-03-09 13:30:42,295] [agent.MCP] INFO: 📨 收到请求 id=11862afa method=tools/call transport=stdio
|
||
[2026-03-09 13:30:42,295] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '234*123'}
|
||
[2026-03-09 13:30:42,297] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-03-09 13:30:42,297] [agent.CLIENT] INFO: ✅ Step 1 成功: 234*123 = 28782...
|
||
[2026-03-09 13:30:42,297] [agent.MEMORY] DEBUG: 💬 [TOOL] 234*123 = 28782...
|
||
[2026-03-09 13:30:42,297] [agent.CLIENT] INFO: ────────────────────────────────────────────────────────────
|
||
✅ 调用链执行完成
|
||
完成: 1/1 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:30:42,297] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 调用 OpenAI 生成最终回复...
|
||
[2026-03-09 13:30:42,298] [agent.LLM] INFO: ✍️ 整合单步工具结果 [calculator]...
|
||
[2026-03-09 13:30:42,298] [agent.LLM] INFO: ✍️ 生成最终回复...
|
||
[2026-03-09 13:30:42,298] [agent.LLM] DEBUG: 📤 发送回复生成请求，消息长度: 3
|
||
[2026-03-09 13:30:42,924] [agent.LLM] WARNING: ⚠️ OpenAI 回复生成失败: 生成回复失败: Error code: 400 - {'error': {'code': '11111', 'message': "StatusCode: 400: API returned unexpected status code: 400: Invalid parameter: messages with role 'tool' must be a response to a preceeding message with 'tool_calls'.", 'type': 'invalid_request_error'}}
|
||
[2026-03-09 13:30:42,924] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ **任务已完成**
|
||
|
||
针对您的需求「234乘以123等于多少」，执行结果如下：
|
||
|
||
234*123 = 28782...
|
||
[2026-03-09 13:30:42,924] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-03-09 13:34:35,843] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:34:35,845] [agent.CLIENT] INFO: 📨 收到用户输入: 先计算34乘以45，再计算12乘以23
|
||
[2026-03-09 13:34:35,845] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:34:35,846] [agent.MEMORY] DEBUG: 💬 [USER] 先计算34乘以45，再计算12乘以23...
|
||
[2026-03-09 13:34:35,846] [agent.CLIENT] INFO: 🗺 Step 2 [LLM] 规划工具调用链...
|
||
[2026-03-09 13:34:35,846] [agent.LLM] INFO: 🗺 规划工具调用链: 先计算34乘以45，再计算12乘以23...
|
||
[2026-03-09 13:34:35,846] [agent.LLM] DEBUG: 📤 发送规划请求，tools 数量: 4
|
||
[2026-03-09 13:34:35,847] [agent.LLM] DEBUG: 📤 消息历史长度: 4
|
||
[2026-03-09 13:34:37,936] [agent.LLM] INFO: 📊 Token 用量: prompt=424, completion=49
|
||
[2026-03-09 13:34:37,936] [agent.LLM] INFO: 📋 解析到 2 个工具调用步骤
|
||
[2026-03-09 13:34:37,937] [agent.LLM] INFO: 📋 OpenAI 规划完成: 2 步
|
||
[2026-03-09 13:34:37,937] [agent.LLM] INFO: Step 1: [calculator] args={'expression': '34*45'}
|
||
[2026-03-09 13:34:37,937] [agent.LLM] INFO: Step 2: [calculator] args={'expression': '12*23'}
|
||
[2026-03-09 13:34:37,937] [agent.CLIENT] INFO:
|
||
────────────────────────────────────────────────────────────
|
||
🔗 开始执行工具调用链
|
||
目标: calculator → calculator
|
||
步骤: 2 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:34:37,938] [agent.CLIENT] INFO:
|
||
▶ Step 1 执行中
|
||
工具: [calculator]
|
||
说明: 调用 calculator（由 OpenAI Function Calling 规划）
|
||
参数: {'expression': '34*45'}
|
||
call_id: call_78edf968
|
||
[2026-03-09 13:34:37,938] [agent.MCP] INFO: 📨 收到请求 id=ec8a2d23 method=tools/call transport=stdio
|
||
[2026-03-09 13:34:37,938] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '34*45'}
|
||
[2026-03-09 13:34:37,938] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-03-09 13:34:37,938] [agent.CLIENT] INFO: ✅ Step 1 成功: 34*45 = 1530...
|
||
[2026-03-09 13:34:37,938] [agent.MEMORY] DEBUG: 💬 [TOOL] 34*45 = 1530...
|
||
[2026-03-09 13:34:37,939] [agent.CLIENT] INFO:
|
||
▶ Step 2 执行中
|
||
工具: [calculator]
|
||
说明: 调用 calculator（由 OpenAI Function Calling 规划）
|
||
参数: {'expression': '12*23'}
|
||
call_id: call_f3174090
|
||
[2026-03-09 13:34:37,939] [agent.MCP] INFO: 📨 收到请求 id=ce5f9e24 method=tools/call transport=stdio
|
||
[2026-03-09 13:34:37,939] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '12*23'}
|
||
[2026-03-09 13:34:37,939] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-03-09 13:34:37,939] [agent.CLIENT] INFO: ✅ Step 2 成功: 12*23 = 276...
|
||
[2026-03-09 13:34:37,940] [agent.MEMORY] DEBUG: 💬 [TOOL] 12*23 = 276...
|
||
[2026-03-09 13:34:37,940] [agent.CLIENT] INFO: ────────────────────────────────────────────────────────────
|
||
✅ 调用链执行完成
|
||
完成: 2/2 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:34:37,940] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 调用 OpenAI 生成最终回复...
|
||
[2026-03-09 13:34:37,940] [agent.LLM] INFO: ✍️ 生成最终回复...
|
||
[2026-03-09 13:34:37,940] [agent.LLM] DEBUG: 📤 发送回复生成请求，消息长度: 5
|
||
[2026-03-09 13:34:39,468] [agent.LLM] INFO: ✅ 回复生成成功，长度: 25 chars，Token: 18
|
||
[2026-03-09 13:34:39,469] [agent.LLM] INFO: ✅ OpenAI 回复生成成功 (25 chars)
|
||
[2026-03-09 13:34:39,469] [agent.MEMORY] DEBUG: 💬 [CHAIN] 34乘以45等于1530，12乘以23等于276。...
|
||
[2026-03-09 13:34:39,469] [agent.MEMORY] INFO: 🔗 调用链已记录: 2/2 步成功
|
||
[2026-03-09 13:34:39,470] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-03-09 13:35:13,266] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:35:13,267] [agent.CLIENT] INFO: 📨 收到用户输入: 先计算34乘以56，再将结果乘以12
|
||
[2026-03-09 13:35:13,268] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:35:13,268] [agent.MEMORY] DEBUG: 💬 [USER] 先计算34乘以56，再将结果乘以12...
|
||
[2026-03-09 13:35:13,269] [agent.CLIENT] INFO: 🗺 Step 2 [LLM] 规划工具调用链...
|
||
[2026-03-09 13:35:13,269] [agent.LLM] INFO: 🗺 规划工具调用链: 先计算34乘以56，再将结果乘以12...
|
||
[2026-03-09 13:35:13,269] [agent.LLM] DEBUG: 📤 发送规划请求，tools 数量: 4
|
||
[2026-03-09 13:35:13,270] [agent.LLM] DEBUG: 📤 消息历史长度: 6
|
||
[2026-03-09 13:35:15,298] [agent.LLM] INFO: 📊 Token 用量: prompt=461, completion=17
|
||
[2026-03-09 13:35:15,299] [agent.LLM] INFO: 📋 解析到 1 个工具调用步骤
|
||
[2026-03-09 13:35:15,299] [agent.LLM] INFO: 📋 OpenAI 规划完成: 1 步
|
||
[2026-03-09 13:35:15,299] [agent.LLM] INFO: Step 1: [calculator] args={'expression': '34*56'}
|
||
[2026-03-09 13:35:15,299] [agent.CLIENT] INFO:
|
||
────────────────────────────────────────────────────────────
|
||
🔗 开始执行工具调用链
|
||
目标: calculator
|
||
步骤: 1 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:35:15,300] [agent.CLIENT] INFO:
|
||
▶ Step 1 执行中
|
||
工具: [calculator]
|
||
说明: 调用 calculator（由 OpenAI Function Calling 规划）
|
||
参数: {'expression': '34*56'}
|
||
call_id: call_6e1cc584
|
||
[2026-03-09 13:35:15,300] [agent.MCP] INFO: 📨 收到请求 id=a2b93b20 method=tools/call transport=stdio
|
||
[2026-03-09 13:35:15,300] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '34*56'}
|
||
[2026-03-09 13:35:15,300] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-03-09 13:35:15,301] [agent.CLIENT] INFO: ✅ Step 1 成功: 34*56 = 1904...
|
||
[2026-03-09 13:35:15,301] [agent.MEMORY] DEBUG: 💬 [TOOL] 34*56 = 1904...
|
||
[2026-03-09 13:35:15,301] [agent.CLIENT] INFO: ────────────────────────────────────────────────────────────
|
||
✅ 调用链执行完成
|
||
完成: 1/1 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:35:15,301] [agent.CLIENT] INFO: ✍️ Step 5 [LLM] 调用 OpenAI 生成最终回复...
|
||
[2026-03-09 13:35:15,301] [agent.LLM] INFO: ✍️ 整合单步工具结果 [calculator]...
|
||
[2026-03-09 13:35:15,302] [agent.LLM] INFO: ✍️ 生成最终回复...
|
||
[2026-03-09 13:35:15,302] [agent.LLM] DEBUG: 📤 发送回复生成请求，消息长度: 3
|
||
[2026-03-09 13:35:15,929] [agent.LLM] WARNING: ⚠️ OpenAI 回复生成失败: 生成回复失败: Error code: 400 - {'error': {'code': '11111', 'message': "StatusCode: 400: API returned unexpected status code: 400: Invalid parameter: messages with role 'tool' must be a response to a preceeding message with 'tool_calls'.", 'type': 'invalid_request_error'}}
|
||
[2026-03-09 13:35:15,929] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ **任务已完成**
|
||
|
||
针对您的需求「先计算34乘以56，再将结果乘以12」，执行结果如下：
|
||
|
||
34*56 = 190...
|
||
[2026-03-09 13:35:15,930] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
|
||
[2026-03-09 13:39:06,494] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 13:39:06,494] [agent.SYSTEM] INFO: ────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] temperature = 0.7
|
||
[LLM] max_tokens = 4096
|
||
[LLM] function_calling = True
|
||
[LLM] stream = False
|
||
[LLM] max_retries = 3
|
||
[MCP] server_name = DemoMCPServer
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[MEMORY] max_history = 20
|
||
[AGENT] multi_step = True
|
||
[AGENT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
────────────────────────────────────────────────────
|
||
[2026-03-09 13:39:06,495] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 13:39:06,495] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 13:39:06,496] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:39:06,497] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 13:39:06,498] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 13:39:06,498] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 13:39:06,498] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 13:39:06,498] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 13:39:06,498] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 13:39:06,499] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 13:39:06,499] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 13:39:06,499] [agent.LLM] INFO: 🏭 Provider 工厂: 创建 [openai] Provider
|
||
[2026-03-09 13:39:08,884] [agent.LLM] INFO: 🔗 使用自定义 API 地址: https://openapi.monica.im/v1
|
||
[2026-03-09 13:39:09,057] [agent.LLM] INFO: ✅ OpenAI 客户端初始化完成
|
||
model = gpt-4o
|
||
base_url = https://openapi.monica.im/v1
|
||
max_retries= 3
|
||
[2026-03-09 13:39:09,058] [agent.LLM] INFO: 🧠 LLM 引擎初始化完成
|
||
[2026-03-09 13:39:09,058] [agent.LLM] INFO: provider = openai
|
||
[2026-03-09 13:39:09,058] [agent.LLM] INFO: model_name = gpt-4o
|
||
[2026-03-09 13:39:09,058] [agent.LLM] INFO: function_calling = True
|
||
[2026-03-09 13:39:09,058] [agent.LLM] INFO: temperature = 0.7
|
||
[2026-03-09 13:39:09,059] [agent.LLM] INFO: fallback_rules = True
|
||
[2026-03-09 13:39:09,059] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 13:39:09,060] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（OpenAI Function Calling 模式）
|
||
[2026-03-09 13:39:09,061] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor']
|
||
[2026-03-09 13:39:25,884] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:39:25,884] [agent.CLIENT] INFO: 📨 收到用户输入: 先计算34乘以12，再将结果乘以56
|
||
[2026-03-09 13:39:25,884] [agent.CLIENT] INFO: ════════════════════════════════════════════════════════════
|
||
[2026-03-09 13:39:25,885] [agent.MEMORY] DEBUG: 💬 [USER] 先计算34乘以12，再将结果乘以56...
|
||
[2026-03-09 13:39:25,885] [agent.CLIENT] INFO: 🗺 [LLM] 规划工具调用链...
|
||
[2026-03-09 13:39:25,885] [agent.LLM] INFO: 🗺 规划工具调用链: 先计算34乘以12，再将结果乘以56...
|
||
[2026-03-09 13:39:25,886] [agent.LLM] DEBUG: 📤 发送规划请求，tools 数量: 4
|
||
[2026-03-09 13:39:25,886] [agent.LLM] DEBUG: 📤 消息历史长度: 3
|
||
[2026-03-09 13:39:28,752] [agent.LLM] INFO: 📊 Token 用量: prompt=405, completion=17
|
||
[2026-03-09 13:39:28,752] [agent.LLM] INFO: 📋 解析到 1 个工具调用步骤
|
||
[2026-03-09 13:39:28,753] [agent.LLM] INFO: 📋 OpenAI 规划完成: 1 步
|
||
[2026-03-09 13:39:28,753] [agent.LLM] INFO: Step 1: [calculator] args={'expression': '34*12'}
|
||
[2026-03-09 13:39:28,753] [agent.CLIENT] INFO:
|
||
────────────────────────────────────────────────────────────
|
||
🔗 开始执行工具调用链
|
||
目标: calculator
|
||
步骤: 1 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:39:28,753] [agent.CLIENT] DEBUG: 🔑 预生成 tool_call_ids: {1: 'call_d656a0cfe9ab'}
|
||
[2026-03-09 13:39:28,753] [agent.CLIENT] INFO:
|
||
▶ Step 1 执行中
|
||
工具 : [calculator]
|
||
说明 : 调用 calculator（由 OpenAI Function Calling 规划）
|
||
参数 : {'expression': '34*12'}
|
||
call_id : call_d656a0cfe9ab
|
||
[2026-03-09 13:39:28,754] [agent.MCP] INFO: 📨 收到请求 id=df72b664 method=tools/call transport=stdio
|
||
[2026-03-09 13:39:28,754] [agent.TOOL] INFO: ▶ 执行工具 [calculator]，参数: {'expression': '34*12'}
|
||
[2026-03-09 13:39:28,754] [agent.TOOL] INFO: ✅ 工具 [calculator] 执行成功
|
||
[2026-03-09 13:39:28,754] [agent.CLIENT] INFO: ✅ Step 1 成功: 34*12 = 408...
|
||
[2026-03-09 13:39:28,754] [agent.MEMORY] DEBUG: 💬 [TOOL] 34*12 = 408...
|
||
[2026-03-09 13:39:28,754] [agent.CLIENT] DEBUG: 📦 OpenAI 消息块结构:
|
||
[2026-03-09 13:39:28,754] [agent.CLIENT] DEBUG: [0] assistant tool_calls.ids = ['call_d656a0cfe9ab']
|
||
[2026-03-09 13:39:28,755] [agent.CLIENT] DEBUG: [1] tool tool_call_id = call_d656a0cfe9ab content = 34*12 = 408...
|
||
[2026-03-09 13:39:28,755] [agent.CLIENT] INFO: ────────────────────────────────────────────────────────────
|
||
✅ 调用链执行完成
|
||
完成: 1/1 步
|
||
────────────────────────────────────────────────────────────
|
||
[2026-03-09 13:39:28,755] [agent.CLIENT] INFO: ✍️ [LLM] 调用 OpenAI 生成最终回复...
|
||
[2026-03-09 13:39:28,755] [agent.LLM] INFO: ✍️ 生成最终回复（工具调用链模式）...
|
||
[2026-03-09 13:39:28,755] [agent.LLM] DEBUG: 📤 发送回复请求，消息数: 4
|
||
[2026-03-09 13:39:28,755] [agent.LLM] DEBUG: 📋 消息序列结构:
|
||
[2026-03-09 13:39:28,755] [agent.LLM] DEBUG: [0] system 你是一个友好、专业的 AI 助手。
|
||
请基于已执行的工具调用结果，用清晰、自然的语言回答用户的问题。
|
||
...
|
||
[2026-03-09 13:39:28,755] [agent.LLM] DEBUG: [1] user 先计算34乘以12，再将结果乘以56...
|
||
[2026-03-09 13:39:28,755] [agent.LLM] DEBUG: [2] assistant tool_calls=['calculator'] ids=['call_d656a0cfe9ab']
|
||
[2026-03-09 13:39:28,755] [agent.LLM] DEBUG: [3] tool tool_call_id=call_d656a0cfe9ab content=34*12 = 408...
|
||
[2026-03-09 13:39:28,756] [agent.LLM] DEBUG: 📤 发送回复生成请求，消息长度: 4
|
||
[2026-03-09 13:39:30,293] [agent.LLM] INFO: ✅ 回复生成成功，长度: 27 chars，Token: 18
|
||
[2026-03-09 13:39:30,294] [agent.LLM] INFO: ✅ OpenAI 回复生成成功 (27 chars)
|
||
[2026-03-09 13:39:30,294] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] 34乘以12的结果是408。接下来计算408乘以56。...
|
||
[2026-03-09 13:39:30,294] [agent.CLIENT] INFO: 🎉 流程完成，回复已返回
|
||
[2026-03-09 14:03:41,261] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:03:41,271] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:03:41,271] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:03:41,276] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:03:41,278] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:03:41,278] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:05:16,524] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:05:16,529] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:05:16,529] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:05:16,530] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:05:16,530] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:05:16,531] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:06:01,148] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:06:01,156] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:06:01,157] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:06:01,161] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:06:01,161] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:06:01,161] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:06:11,760] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:06:11,766] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:06:11,766] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:06:11,767] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:06:11,767] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:06:11,768] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:06:11,768] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 14:06:11,769] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 14:06:22,925] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:06:22,939] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:06:22,940] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:06:22,942] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:06:22,942] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:06:22,942] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:06:22,943] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 14:06:22,943] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 14:06:44,043] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:06:44,046] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:06:44,046] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:06:44,048] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:06:44,048] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:06:44,048] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:06:44,049] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 14:06:44,049] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 14:06:44,049] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 14:06:44,050] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 14:07:04,527] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:07:04,531] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:07:04,532] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:07:04,532] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:07:04,533] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:07:04,533] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:07:04,533] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 14:07:04,533] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 14:07:04,533] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 14:07:04,533] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 14:07:04,534] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 14:07:04,534] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 14:07:40,023] [agent.TOOL.SSHDocker] WARNING: ⚠️ paramiko 未安装，请执行: pip install paramiko>=3.0.0
|
||
[2026-03-09 14:07:40,029] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统（OpenAI Function Calling 模式）...
|
||
[2026-03-09 14:07:40,029] [agent.SYSTEM] INFO: ──────────────────────────────────────────────────────────────
|
||
📋 当前配置
|
||
──────────────────────────────────────────────────────────────
|
||
[LLM] provider = openai
|
||
[LLM] model_name = gpt-4o
|
||
[LLM] api_key = ***ACjR
|
||
[LLM] api_base_url = https://openapi.monica.im/v1
|
||
[LLM] function_calling = True
|
||
[LLM] temperature = 0.7
|
||
[MCP] enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[TOOL] calculator.precision= 10
|
||
[TOOL] web_search.engine = mock
|
||
[TOOL] web_search.timeout = 10s
|
||
[TOOL] file_reader.root = ./workspace
|
||
[TOOL] code_executor.timeout=5s
|
||
[TOOL] static_analyzer.tool = cppcheck
|
||
[TOOL] static_analyzer.std = c++17
|
||
[TOOL] static_analyzer.timeout = 120s
|
||
[TOOL] static_analyzer.jobs = 4
|
||
[TOOL] static_analyzer.roots = (不限制)
|
||
[TOOL] ssh_docker.port = 22
|
||
[TOOL] ssh_docker.user = root
|
||
[TOOL] ssh_docker.conn_timeout = 30s
|
||
[TOOL] ssh_docker.deploy_timeout= 300s
|
||
[TOOL] ssh_docker.allowed_hosts = (不限制)
|
||
[TOOL] ssh_docker.servers = (无预设)
|
||
[MEM] max_history = 20
|
||
[AGT] fallback_rules = True
|
||
[LOG] level = DEBUG
|
||
──────────────────────────────────────────────────────────────
|
||
[2026-03-09 14:07:40,032] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
|
||
[2026-03-09 14:07:40,032] [agent.MCP] INFO: transport = stdio
|
||
[2026-03-09 14:07:40,032] [agent.MCP] INFO: enabled_tools = ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|
||
[2026-03-09 14:07:40,033] [agent.TOOL] DEBUG: ⚙️ Calculator 精度: 10
|
||
[2026-03-09 14:07:40,034] [agent.MCP] INFO: 📌 注册工具: [calculator] — 计算数学表达式，支持加减乘除、幂运算、括号等
|
||
[2026-03-09 14:07:40,034] [agent.TOOL] DEBUG: ⚙️ WebSearch engine=mock, max_results=5, api_key=(未设置)
|
||
[2026-03-09 14:07:40,035] [agent.MCP] INFO: 📌 注册工具: [web_search] — 在互联网上搜索信息，返回相关网页摘要
|
||
[2026-03-09 14:07:40,035] [agent.TOOL] DEBUG: ⚙️ FileReader root=workspace, max_size=512KB
|
||
[2026-03-09 14:07:40,035] [agent.MCP] INFO: 📌 注册工具: [file_reader] — 读取本地文件内容，仅限配置的 allowed_root 目录
|
||
[2026-03-09 14:07:40,036] [agent.TOOL] DEBUG: ⚙️ CodeExecutor timeout=5s, sandbox=True
|
||
[2026-03-09 14:07:40,036] [agent.MCP] INFO: 📌 注册工具: [code_executor] — 在沙箱环境中执行 Python 代码片段，返回标准输出
|
||
[2026-03-09 14:07:40,036] [agent.MCP] INFO: 📌 注册工具: [static_analyzer] — 对指定目录下的 C/C++ 工程调用外部静态分析工具（cppcheck/clang-tidy/infer）进行代码质量检查，返回错误、警告及代码风格问题
|
||
[2026-03-09 14:07:40,036] [agent.MCP] INFO: 📌 注册工具: [ssh_docker] — 通过 SSH 连接到远程服务器，使用 Docker 部署和管理容器应用。支持: deploy | start | stop | restart | status | logs | remove | compose_up | compose_down | compose_ps | pull | inspect | stats
|
||
[2026-03-09 14:07:40,037] [agent.LLM] INFO: 🏭 Provider 工厂: 创建 [openai] Provider
|
||
[2026-03-09 14:07:42,643] [agent.LLM] INFO: 🔗 使用自定义 API 地址: https://openapi.monica.im/v1
|
||
[2026-03-09 14:07:42,832] [agent.LLM] INFO: ✅ OpenAI 客户端初始化完成
|
||
model = gpt-4o
|
||
base_url = https://openapi.monica.im/v1
|
||
max_retries= 3
|
||
[2026-03-09 14:07:42,833] [agent.LLM] INFO: 🧠 LLM 引擎初始化完成
|
||
[2026-03-09 14:07:42,833] [agent.LLM] INFO: provider = openai
|
||
[2026-03-09 14:07:42,833] [agent.LLM] INFO: model_name = gpt-4o
|
||
[2026-03-09 14:07:42,833] [agent.LLM] INFO: function_calling = True
|
||
[2026-03-09 14:07:42,834] [agent.LLM] INFO: temperature = 0.7
|
||
[2026-03-09 14:07:42,834] [agent.LLM] INFO: fallback_rules = True
|
||
[2026-03-09 14:07:42,834] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
|
||
[2026-03-09 14:07:42,834] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成（OpenAI Function Calling 模式）
|
||
[2026-03-09 14:07:42,835] [agent.SYSTEM] INFO: ✅ Agent 组装完成，已注册工具: ['calculator', 'web_search', 'file_reader', 'code_executor', 'static_analyzer', 'ssh_docker']
|