0d64d8e559
Tracked: morrowind agent (py/cfg), skills/, training-data/, research/, notes/, specs/, test-results/, metrics/, heartbeat/, briefings/, memories/, skins/, hooks/, decisions.md, OPERATIONS.md, SOUL.md Excluded: screenshots, PNGs, binaries, sessions, databases, secrets, audio cache, timmy-config/ and timmy-telemetry/ (separate repos)
42 lines
4.9 KiB
JSON
42 lines
4.9 KiB
JSON
[
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{
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"prompt": "There is something wrong happening every time I close out a session. I get a bunch of stack traces and I think I'm losing the message history in sessions.",
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"chosen": "Let me investigate this. I'll search for recent session issues and look at the relevant code simultaneously.",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "Ok can you triage these PRs? looks like we dont' have auto-review and auto-merge set up yet. http://143.198.27.163:3000/Timmy_Foundation/the-nexus/pulls\nAlso, please check our automation loops. Kimi doesn't seem to be actually doing anything. Unless I'm not seeing it. And, someone out there is using my gitea token for rockachopa. Please find out who and make it stop.",
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"chosen": "Got it \u2014 three separate concerns. Let me set up tracking and hit all three in parallel.",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "the rockachopa key is in ~/.config/gitea so someone might have done that. We have to infer from the AI generated comments who has it. Kimi, claude code, a script? Maybe you're using it for something somehow?",
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"chosen": "Good point \u2014 let me check the browser for PRs and dig into the token usage simultaneously.",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "The other thing, please give me the link to downlaod our hermes4 8b parameter model we can use for training. That's what we lost from my lost session. fortunately I saved the conversation manually. the MLX model quantized 36b. Check out out by finding the conversation I saved.",
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"chosen": "",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "Is this the one we should do? https://huggingface.co/k8smee/Hermes-4-14B-mlx-6Bit Is there a reason we should do a different one? Is there one that outclasses it?",
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"chosen": "Let me check that model and see what else is available in the Hermes 4 family.",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "Keep going with that, and I want you to do a backlog audit. We downloaded it on my vps and are doing rsync to get it over here over tailscale. Now here is my stupid question, if I have those 3 models for training, and I train them... why would I ever use a gguf model again?",
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"chosen": "Not a stupid question at all \u2014 it's the right question. Here's the answer:\n\n=======================================\nMLX SAFETENSORS vs GGUF \u2014 WHY BOTH?\n=======================================\n\nMLX safetensors = Apple Silicon native. Training AND inference.\nGGUF = universal. Runs on llama.cpp, Ollama, any CPU/GPU, any OS.\n\nAfter you train LoRA on MLX and fuse the adapters, you have a\ncustom MLX safetensors model. You CAN run inference on it directly\nwith mlx-lm. On your Mac, it's fast.\n\nSo why would you ever touch GGUF again?\n\n 1. YOUR VPS IS LINUX. No MLX there. If Timmy needs to think\n on the VPS (serving, kimi-loop, Ollama endpoints), it needs GGUF.\n\n 2. OTHER PEOPLE. If anyone else runs Timmy, they probably don't\n have Apple Silicon. GGUF is the universal format.\n\n 3. OLLAMA. Your local Ollama setup (hermes3 at 57t/s) uses GGUF.\n If you want your fine-tuned model in Ollama, you convert to GGUF.\n\n 4. MEMORY. GGUF Q4/Q5 quants are smaller than bf16 safetensors.\n For inference-only, GGUF lets you run bigger models in less RAM.\n\nTHE WORKFLOW:\n Train on MLX safetensors (bf16/8bit) \u2192 fuse LoRA adapters \u2192\n export to GGUF for deployment \u2192 keep MLX copy for further training\n\nIf your entire world is your Mac and you only use mlx-lm for\ninference too, you could skip GGUF entirely. But the moment Timmy\nneeds to run anywhere else, you need it.\n\nShort answer: GGUF is the deployment format. MLX is the training format.\nYou train in MLX, deploy in GGUF. Both matter.\n\nNow let me check the rsync status and kick off the backlog audit.",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "Lets add repo management to the nexus. You are in charge, follow the appropriate patterns I have set out.",
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"chosen": "Let me study the patterns you've established on Timmy-time-dashboard first, then replicate them on the-nexus.",
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"session": "session_20260323_212234_e8158e.json"
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},
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{
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"prompt": "Review the conversation above and consider saving or updating a skill if appropriate.\n\nFocus on: was a non-trivial approach used to complete a task that required trial and error, or changing course due to experiential findings along the way, or did the user expect or desire a different method or outcome?\n\nIf a relevant skill already exists, update it with what you learned. Otherwise, create a new skill if the approach is reusable.\nIf nothing is worth saving, just say 'Nothing to save.' and stop.",
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"chosen": "Let me review what happened in this session and check existing skills for relevance.",
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"session": "session_20260323_212234_e8158e.json"
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}
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] |