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openclaw/agents/knowledge-base/sessions/c0f375bd-41d0-49d4-a33a-97444d792a5c.jsonl.deleted.2026-02-14T11-10-54.205Z
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starmen1265 bce284f7c6 Initial commit
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{"type":"session","version":3,"id":"c0f375bd-41d0-49d4-a33a-97444d792a5c","timestamp":"2026-02-14T10:10:22.057Z","cwd":"/home/starmen1265/.openclaw/agents/knowledge-base/workspace"}
{"type":"model_change","id":"53ce54f0","parentId":null,"timestamp":"2026-02-14T10:10:22.057Z","provider":"zhipu","modelId":"glm-5"}
{"type":"thinking_level_change","id":"60de8aea","parentId":"53ce54f0","timestamp":"2026-02-14T10:10:22.057Z","thinkingLevel":"off"}
{"type":"custom","customType":"model-snapshot","data":{"timestamp":1771063822058,"provider":"zhipu","modelApi":"openai-completions","modelId":"glm-5"},"id":"77ffe90b","parentId":"60de8aea","timestamp":"2026-02-14T10:10:22.058Z"}
{"type":"message","id":"e5200c4c","parentId":"77ffe90b","timestamp":"2026-02-14T10:10:22.061Z","message":{"role":"user","content":[{"type":"text","text":"[Sat 2026-02-14 18:10 GMT+8] 执行 kb-whisper 技能，进行语音识别。\n\n输入视频: /home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4\n模型: base\n输出目录: /home/starmen1265/work/knowledge-base/content\n\n请调用：\n```bash\nsource ~/.kb_env && python3 /home/starmen1265/.openclaw/skills/kb-whisper/whisper.py --input \"/home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4\" --model base --output \"/home/starmen1265/work/knowledge-base/content\"\n```\n\n返回结果（success, output_files）。注意：这个步骤可能需要较长时间。"}],"timestamp":1771063822060}}
{"type":"message","id":"321c97c1","parentId":"e5200c4c","timestamp":"2026-02-14T10:10:37.560Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to execute the kb-whisper skill for speech recognition on a video file. I need to run the provided command which will process the video and extract text from the audio.\n\nThis is a subagent task - I was spawned specifically to run this command. Let me execute it and report back the results.\n\nThe command is:\n```bash\nsource ~/.kb_env && python3 /home/starmen1265/.openclaw/skills/kb-whisper/whisper.py --input \"/home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4\" --model base --output \"/home/starmen1265/work/knowledge-base/content\"\n```\n\nThis may take a long time, so I should run it and wait for completion.","thinkingSignature":"reasoning_content"},{"type":"text","text":"正在执行语音识别任务..."},{"type":"toolCall","id":"call_5edcaf25071840b8b6fdfd7d","name":"exec","arguments":{"command":"source ~/.kb_env && python3 /home/starmen1265/.openclaw/skills/kb-whisper/whisper.py --input \"/home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4\" --model base --output \"/home/starmen1265/work/knowledge-base/content\"","timeout":600}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":5626,"output":310,"cacheRead":4672,"cacheWrite":0,"totalTokens":10608,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063822061}}
{"type":"message","id":"1ff89acc","parentId":"321c97c1","timestamp":"2026-02-14T10:10:47.584Z","message":{"role":"toolResult","toolCallId":"call_5edcaf25071840b8b6fdfd7d","toolName":"exec","content":[{"type":"text","text":"Command still running (session marine-harbor, pid 3386542). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"marine-harbor","pid":3386542,"startedAt":1771063837560,"cwd":"/home/starmen1265/.openclaw/agents/knowledge-base/workspace","tail":""},"isError":false,"timestamp":1771063847576}}
{"type":"message","id":"03c32e68","parentId":"1ff89acc","timestamp":"2026-02-14T10:10:53.721Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The command is still running. Let me poll for the output.","thinkingSignature":"reasoning_content"},{"type":"text","text":"命令仍在执行中，等待语音识别完成..."},{"type":"toolCall","id":"call_3cf3f939c83f4d9db01cf70d","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":3352,"output":43,"cacheRead":7296,"cacheWrite":0,"totalTokens":10691,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063847584}}
{"type":"message","id":"d57a8517","parentId":"03c32e68","timestamp":"2026-02-14T10:10:53.729Z","message":{"role":"toolResult","toolCallId":"call_3cf3f939c83f4d9db01cf70d","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063853728}}
{"type":"message","id":"9e1e6a78","parentId":"d57a8517","timestamp":"2026-02-14T10:10:56.741Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running, let me wait a bit more.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_509e76b4a78c40d180632eb1","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":463,"output":30,"cacheRead":10240,"cacheWrite":0,"totalTokens":10733,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063853729}}
{"type":"message","id":"7f9f1fac","parentId":"9e1e6a78","timestamp":"2026-02-14T10:10:56.749Z","message":{"role":"toolResult","toolCallId":"call_509e76b4a78c40d180632eb1","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063856748}}
{"type":"message","id":"f5df1e07","parentId":"7f9f1fac","timestamp":"2026-02-14T10:11:03.395Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. This is a video transcription task which can take a while. Let me wait more.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_ce24e43be0d84805bed05eb4","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":3449,"output":40,"cacheRead":7296,"cacheWrite":0,"totalTokens":10785,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063856749}}
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{"type":"message","id":"54c881d2","parentId":"a63afae8","timestamp":"2026-02-14T10:11:11.012Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me continue waiting.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_dbcecbe996c645df811ba07e","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":109,"output":28,"cacheRead":10688,"cacheWrite":0,"totalTokens":10825,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063863420}}
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{"type":"message","id":"9a875ab4","parentId":"8d9c4221","timestamp":"2026-02-14T10:11:35.415Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me wait a bit more.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_131ff78372c44dcdb24e05bb","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":6165,"output":30,"cacheRead":4672,"cacheWrite":0,"totalTokens":10867,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063871022}}
{"type":"message","id":"5bc942b3","parentId":"9a875ab4","timestamp":"2026-02-14T10:11:35.427Z","message":{"role":"toolResult","toolCallId":"call_131ff78372c44dcdb24e05bb","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063895425}}
{"type":"message","id":"48220d0c","parentId":"5bc942b3","timestamp":"2026-02-14T10:11:39.982Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me keep waiting.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_0ba03152479a4e26b2e0470e","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":191,"output":28,"cacheRead":10688,"cacheWrite":0,"totalTokens":10907,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063895427}}
{"type":"message","id":"ebc23d8f","parentId":"48220d0c","timestamp":"2026-02-14T10:11:39.989Z","message":{"role":"toolResult","toolCallId":"call_0ba03152479a4e26b2e0470e","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063899988}}
{"type":"message","id":"690226c9","parentId":"ebc23d8f","timestamp":"2026-02-14T10:11:44.878Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. This is a long video processing task. Let me wait a bit more.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_9e1d9a3bac3248dcad9ac91d","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":103,"output":38,"cacheRead":10816,"cacheWrite":0,"totalTokens":10957,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063899989}}
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{"type":"message","id":"c3d6badc","parentId":"1b705045","timestamp":"2026-02-14T10:11:48.134Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. This video processing takes a while. Let me continue waiting.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_af62b092e7284e068f447f62","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":217,"output":35,"cacheRead":10752,"cacheWrite":0,"totalTokens":11004,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063904887}}
{"type":"message","id":"07d8b8cd","parentId":"c3d6badc","timestamp":"2026-02-14T10:11:48.141Z","message":{"role":"toolResult","toolCallId":"call_af62b092e7284e068f447f62","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063908140}}
{"type":"message","id":"fcdd2f07","parentId":"07d8b8cd","timestamp":"2026-02-14T10:11:52.947Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me continue to wait.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_9071354144db43e598c43d95","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":72,"output":29,"cacheRead":10944,"cacheWrite":0,"totalTokens":11045,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063908141}}
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{"type":"message","id":"395756cd","parentId":"36a166ee","timestamp":"2026-02-14T10:11:54.505Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me keep waiting.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_3b5e346355404b0e822607ae","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":433,"output":28,"cacheRead":10624,"cacheWrite":0,"totalTokens":11085,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063912953}}
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{"type":"message","id":"e13704da","parentId":"74e2a32a","timestamp":"2026-02-14T10:11:58.100Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me continue waiting.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_ddf3feb4f10e490eb7661706","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":89,"output":28,"cacheRead":11008,"cacheWrite":0,"totalTokens":11125,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063914514}}
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{"type":"message","id":"3b460b93","parentId":"d2bd5295","timestamp":"2026-02-14T10:12:02.483Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me wait a bit more.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_fd5d5b8af63d4f7a8932aac5","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":65,"output":30,"cacheRead":11072,"cacheWrite":0,"totalTokens":11167,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063918107}}
{"type":"message","id":"324a490e","parentId":"3b460b93","timestamp":"2026-02-14T10:12:02.493Z","message":{"role":"toolResult","toolCallId":"call_fd5d5b8af63d4f7a8932aac5","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063922491}}
{"type":"message","id":"ae7ee5b5","parentId":"324a490e","timestamp":"2026-02-14T10:12:08.036Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me continue waiting.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_f29d775b8b56454c93e691ab","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":363,"output":28,"cacheRead":10816,"cacheWrite":0,"totalTokens":11207,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063922493}}
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{"type":"message","id":"8628529c","parentId":"25b382df","timestamp":"2026-02-14T10:12:16.116Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me continue.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_cea829d44daf46a8852c9f68","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":250,"output":27,"cacheRead":11008,"cacheWrite":0,"totalTokens":11285,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063931494}}
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{"type":"message","id":"244d688f","parentId":"b0182f48","timestamp":"2026-02-14T10:12:27.966Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me continue.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_80c2777544a5413094fe4e07","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":137,"output":27,"cacheRead":11200,"cacheWrite":0,"totalTokens":11364,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063941545}}
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{"type":"message","id":"bf9fd420","parentId":"ab3fb945","timestamp":"2026-02-14T10:13:07.727Z","message":{"role":"toolResult","toolCallId":"call_541eea01a4364f87b1bbc4fc","toolName":"process","content":[{"type":"text","text":"(no new output)\n\nProcess still running."}],"details":{"status":"running","sessionId":"marine-harbor","aggregated":"","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063987726}}
{"type":"message","id":"684c1779","parentId":"bf9fd420","timestamp":"2026-02-14T10:13:10.763Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Still running. Let me wait.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_995dcc972be04e6297ac48c2","name":"process","arguments":{"action":"poll","sessionId":"marine-harbor"}}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":84,"output":27,"cacheRead":11648,"cacheWrite":0,"totalTokens":11759,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1771063987727}}
{"type":"message","id":"c4b7992e","parentId":"684c1779","timestamp":"2026-02-14T10:13:10.770Z","message":{"role":"toolResult","toolCallId":"call_995dcc972be04e6297ac48c2","toolName":"process","content":[{"type":"text","text":"✓ Whisper.cpp 路径: /home/starmen1265/whisper.cpp\n✓ 使用模型: base\n\n📁 处理文件: /home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4\n📁 输出目录: /home/starmen1265/work/knowledge-base/content\n\n🔄 步骤1: 转换音频格式...\n转换音频格式: /home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4 -> /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！_audio.wav\n音频转换完成\n\n🎙️ 步骤2: 语音识别 (语言: zh)...\n执行命令: /home/starmen1265/whisper.cpp/whisper-cli -m /home/starmen1265/whisper.cpp/models/ggml-base.bin -f /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！_audio.wav -of /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！ -l zh --output-txt --output-srt --output-json\n✓ 清理临时文件\n\n📝 步骤3: 生成输出文件...\n\n✅ 处理完成!\n 时长: 1780 秒\n 分段数: 600\n\n📄 输出文件:\n • TXT: /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.txt (25,189 bytes)\n • SRT: /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.srt (46,081 bytes)\n • JSON: /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.json (104,934 bytes)\n\n📋 Workflow JSON:\n{\n \"success\": true,\n \"tool\": \"whisper\",\n \"text_length\": 9268,\n \"segments_count\": 600\n}\n\n\nProcess exited with code 0."}],"details":{"status":"completed","sessionId":"marine-harbor","exitCode":0,"aggregated":"✓ Whisper.cpp 路径: /home/starmen1265/whisper.cpp\n✓ 使用模型: base\n\n📁 处理文件: /home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4\n📁 输出目录: /home/starmen1265/work/knowledge-base/content\n\n🔄 步骤1: 转换音频格式...\n转换音频格式: /home/starmen1265/work/knowledge-base/content/downloads/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.mp4 -> /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！_audio.wav\n音频转换完成\n\n🎙️ 步骤2: 语音识别 (语言: zh)...\n执行命令: /home/starmen1265/whisper.cpp/whisper-cli -m /home/starmen1265/whisper.cpp/models/ggml-base.bin -f /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！_audio.wav -of /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！ -l zh --output-txt --output-srt --output-json\n✓ 清理临时文件\n\n📝 步骤3: 生成输出文件...\n\n✅ 处理完成!\n 时长: 1780 秒\n 分段数: 600\n\n📄 输出文件:\n • TXT: /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.txt (25,189 bytes)\n • SRT: /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.srt (46,081 bytes)\n • JSON: /home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.json (104,934 bytes)\n\n📋 Workflow JSON:\n{\n \"success\": true,\n \"tool\": \"whisper\",\n \"text_length\": 9268,\n \"segments_count\": 600\n}\n","name":"source ~/.kb_env"},"isError":false,"timestamp":1771063990769}}
{"type":"message","id":"f2e26db2","parentId":"c4b7992e","timestamp":"2026-02-14T10:13:22.582Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The whisper transcription completed successfully. Let me summarize the results for the main agent.","thinkingSignature":"reasoning_content"},{"type":"text","text":"## ✅ 语音识别完成\n\n**执行结果：**\n\n| 项目 | 值 |\n|------|-----|\n| success | `true` |\n| 时长 | 1780 秒 (约 29.7 分钟) |\n| 分段数 | 600 |\n| 文本长度 | 9,268 字符 |\n\n**输出文件：**\n\n1. **TXT**: `/home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.txt` (25,189 bytes)\n2. **SRT**: `/home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.srt` (46,081 bytes)\n3. **JSON**: `/home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.json` (104,934 bytes)\n\n**返回结果：**\n```json\n{\n \"success\": true,\n \"output_files\": [\n \"/home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.txt\",\n \"/home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.srt\",\n \"/home/starmen1265/work/knowledge-base/content/千问QWQ VS 谷歌Gemma 3！本地T0模型巅峰对决！六大维度深度测评！清晰了解模型性能边界！.json\"\n ],\n \"text_length\": 9268,\n \"segments_count\": 600\n}\n```"}],"api":"openai-completions","provider":"zhipu","model":"glm-5","usage":{"input":715,"output":472,"cacheRead":11712,"cacheWrite":0,"totalTokens":12899,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1771063990770}}
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