devel
This commit is contained in:
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488b9fd22e
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@ -184,7 +184,7 @@ class LLMEngine:
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f"## 对话历史\n{context or '（无）'}\n\n"
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f"## 用户输入\n{user_input}\n\n"
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f"## 指令\n"
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f"以 JSON 格式回复：\n"
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f"以纯 JSON 格式回复，不要嵌入到其他对象中，如下：\n"
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f'{{"need_tool": true/false, "tool_name": "...", "arguments": {{...}}, "reasoning": "..."}}'
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)
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105
logs/agent.log
105
logs/agent.log
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@ -418,3 +418,108 @@
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---
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*由...
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[2026-02-28 22:58:47,489] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
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[2026-02-28 23:01:29,790] [agent.CLIENT] INFO: =======================================================
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[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
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[2026-02-28 23:01:29,790] [agent.MEMORY] DEBUG: 💬 [USER] 搜索今日的天气如何...
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[2026-02-28 23:01:29,791] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
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[2026-02-28 23:01:29,791] [agent.LLM] INFO: 💭 分析意图: 搜索今日的天气如何...
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[2026-02-28 23:01:29,791] [agent.LLM] DEBUG: 📝 Prompt 已构造 (591 chars)
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[2026-02-28 23:02:40,057] [agent.Monica] INFO: ```json
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{
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"need_tool": true,
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"tool_name": "web_search",
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"arguments": {
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"query": "今日的天气"
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},
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"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。"
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}
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```
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[2026-02-28 23:11:18,766] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
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[2026-02-28 23:11:18,766] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
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[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
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[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
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[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
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[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
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[2026-02-28 23:11:18,767] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
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[2026-02-28 23:11:18,821] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
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[2026-02-28 23:11:18,822] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
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[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']
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[2026-02-28 23:11:23,918] [agent.CLIENT] INFO: =======================================================
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[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
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[2026-02-28 23:11:23,918] [agent.MEMORY] DEBUG: 💬 [USER] 查询今天的天气...
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[2026-02-28 23:11:23,918] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
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[2026-02-28 23:11:23,918] [agent.LLM] INFO: 💭 分析意图: 查询今天的天气...
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[2026-02-28 23:11:23,919] [agent.LLM] DEBUG: 📝 Prompt 已构造 (359 chars)
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[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。"}
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[2026-02-28 23:11:27,029] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [web_search]
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[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。
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[2026-02-28 23:11:27,029] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
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方法: tools/call
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工具: web_search
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参数: {'query': '今天的天气'}
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请求体: {'jsonrpc': '2.0', 'id': '6b19ead1', 'method': 'tools/call', 'params': {'name': 'web_search', 'arguments': {'query': '今天的天气'}}}
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[2026-02-28 23:11:27,030] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [web_search]...
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[2026-02-28 23:11:27,030] [agent.MCP] INFO: 📨 收到请求 id=6b19ead1 method=tools/call
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[2026-02-28 23:11:27,030] [agent.TOOL] INFO: ▶ 执行工具 [web_search]，参数: {'query': '今天的天气'}
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[2026-02-28 23:11:27,130] [agent.TOOL] INFO: ✅ 工具 [web_search] 执行成功
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[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:
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[1] 今日天气预报
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晴转多云，气温 15°C ~ 24°C，东南风 3 级
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[2] 未来 7 天天气
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本...
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[2026-02-28 23:11:27,130] [agent.MEMORY] DEBUG: 💬 [TOOL] 搜索「今天的天气」，共 2 条结果:
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[1] 今日天气预报
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晴转多云，气温 15°C ~ 24°C，东南风 3 ...
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[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...
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[2026-02-28 23:11:27,131] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
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[2026-02-28 23:11:27,131] [agent.LLM] INFO: 💬 回复已生成 (167 chars)
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[2026-02-28 23:11:27,131] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [web_search] 工具处理您的请求。
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**执行结果:**
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搜索「今天的天气」，共 2 条结果:
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[...
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[2026-02-28 23:11:27,131] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
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[2026-02-28 23:12:22,747] [agent.SYSTEM] INFO: 🔧 开始组装 Agent 系统...
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[2026-02-28 23:12:22,747] [agent.MCP] INFO: 🚀 MCP Server [DemoMCPServer] 启动
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[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
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[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
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[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
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[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
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[2026-02-28 23:12:22,747] [agent.LLM] INFO: 🧠 LLM 引擎初始化，模型: gpt-4o
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[2026-02-28 23:12:22,785] [agent.MEMORY] INFO: 💾 Memory 初始化，最大历史: 20 条
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[2026-02-28 23:12:22,785] [agent.CLIENT] INFO: 💻 Agent Client 初始化完成
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[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']
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[2026-02-28 23:12:53,887] [agent.CLIENT] INFO: =======================================================
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[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')
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[2026-02-28 23:12:53,887] [agent.MEMORY] DEBUG: 💬 [USER] 执行python代码：print('你好')...
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[2026-02-28 23:12:53,887] [agent.CLIENT] INFO: 🧠 Step 2 [LLM] 开始推理，分析意图...
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[2026-02-28 23:12:53,887] [agent.LLM] INFO: 💭 分析意图: 执行python代码：print('你好')...
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[2026-02-28 23:12:53,887] [agent.LLM] DEBUG: 📝 Prompt 已构造 (389 chars)
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[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。"}
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[2026-02-28 23:12:57,254] [agent.LLM] INFO: 🎯 决策结果: 调用工具 [code_executor]
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[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。
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[2026-02-28 23:12:57,254] [agent.CLIENT] INFO: 📡 Step 3 [MCP] 发送工具调用请求
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方法: tools/call
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工具: code_executor
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参数: {'code': "print('你好')"}
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请求体: {'jsonrpc': '2.0', 'id': '49bf04da', 'method': 'tools/call', 'params': {'name': 'code_executor', 'arguments': {'code': "print('你好')"}}}
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[2026-02-28 23:12:57,255] [agent.CLIENT] INFO: 🔧 Step 4 [TOOL] MCP Server 执行工具 [code_executor]...
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[2026-02-28 23:12:57,255] [agent.MCP] INFO: 📨 收到请求 id=49bf04da method=tools/call
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[2026-02-28 23:12:57,255] [agent.TOOL] INFO: ▶ 执行工具 [code_executor]，参数: {'code': "print('你好')"}
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[2026-02-28 23:12:57,255] [agent.TOOL] INFO: ✅ 工具 [code_executor] 执行成功
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[2026-02-28 23:12:57,255] [agent.CLIENT] INFO: ✅ 工具执行成功，输出: 执行成功 (0.1ms):
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你好
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...
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[2026-02-28 23:12:57,255] [agent.MEMORY] DEBUG: 💬 [TOOL] 执行成功 (0.1ms):
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你好
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...
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[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...
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[2026-02-28 23:12:57,255] [agent.LLM] INFO: ✍️ 整合工具结果，生成最终回复...
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[2026-02-28 23:12:57,255] [agent.LLM] INFO: 💬 回复已生成 (99 chars)
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[2026-02-28 23:12:57,256] [agent.MEMORY] DEBUG: 💬 [ASSISTANT] ✅ 已通过 [code_executor] 工具处理您的请求。
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**执行结果:**
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执行成功 (0.1ms):
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你好
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...
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[2026-02-28 23:12:57,256] [agent.CLIENT] INFO: 🎉 [CLIENT] 流程完成，回复已返回
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