8 lines
2.8 KiB
JSON
8 lines
2.8 KiB
JSON
{"type":"session","version":3,"id":"fbb25a23-77e7-413d-97d0-64b834902f67","timestamp":"2026-02-13T04:41:35.180Z","cwd":"/home/starmen1265/.openclaw/workspace"}
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{"type":"model_change","id":"649213cf","parentId":null,"timestamp":"2026-02-13T04:41:35.183Z","provider":"mm","modelId":"MiniMax-M2.1"}
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{"type":"thinking_level_change","id":"290ed4fc","parentId":"649213cf","timestamp":"2026-02-13T04:41:35.183Z","thinkingLevel":"off"}
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{"type":"custom","customType":"model-snapshot","data":{"timestamp":1770957695184,"provider":"mm","modelApi":"anthropic-messages","modelId":"MiniMax-M2.1"},"id":"d3d7f611","parentId":"290ed4fc","timestamp":"2026-02-13T04:41:35.184Z"}
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{"type":"message","id":"af0c78e3","parentId":"d3d7f611","timestamp":"2026-02-13T04:41:35.191Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-02-13 12:41 GMT+8] 你好\n[message_id: a81fc8a5-8cc8-472b-a4f9-748a2346e6da]"}],"timestamp":1770957695187}}
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{"type":"message","id":"fc55f5cf","parentId":"af0c78e3","timestamp":"2026-02-13T04:41:39.061Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"用户用中文打招呼，说\"你好\"。根据我的设置，我应该：\n1. 用中文回复\n2. 收到消息立刻先回复\"浩南收到，蒋先生！\"，再继续安排工作\n\n所以我应该先回复\"浩南收到，蒋先生！\"然后等待用户继续说明他们需要什么帮助。","thinkingSignature":"08d0157e1cd440b9d7895f9b46b6728e3dc0d62c710670e1b97b6765aa89c6b3"},{"type":"text","text":"浩南收到，蒋先生！🧙♂️\n\n有什么可以帮您的？"}],"api":"anthropic-messages","provider":"mm","model":"MiniMax-M2.1","usage":{"input":32,"output":83,"cacheRead":0,"cacheWrite":16846,"totalTokens":16961,"cost":{"input":0.00048,"output":0.00498,"cacheRead":0,"cacheWrite":0.16846000000000003,"total":0.17392000000000002}},"stopReason":"stop","timestamp":1770957695189}}
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{"type":"message","id":"0e19f40b","parentId":"fc55f5cf","timestamp":"2026-02-13T04:46:29.104Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-02-13 12:46 GMT+8] 我们来处理kb-workflow系列技能的优化。现在进行到kb-deep-analyzer步骤，前面的步骤为我们提供了srt文件，我们从srt文件中简化了格式，变成每一行前面一个简短的开始时间，然后跟说话内容。之后检查这个内容的大小，在3000字符前后根据语音找个合适的时间拆分，将整段内容拆分成多段。在每一段前面加上一个概述，用元数据中的标题和描述。然后丢给AI处理提炼，拿到多段返回内容，组合起来，输出到最终的md文件。现在检查一下这个技能的逻辑是否符合我们上面的需求。然后检查一下技能需要的环境变量有哪些？是否都设置了\n[message_id: b4affc51-62e5-42f9-9bae-a4a340afd9e1]"}],"timestamp":1770957989102}}
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