91 lines
4.4 KiB
Markdown
91 lines
4.4 KiB
Markdown
# MAGATAMA Training Pipeline Recovery And TIP_LLM Adoption
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Date: 2026-05-09
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Actor: Codex
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Scope: MAGATAMA training automation, RunPod custom worker, local Ollama adoption
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Mode: local Mac Studio verification plus Gitea sync handoff
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## Operator Intent
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Training must be real end-to-end training, not a cosmetic `COMPLETED` state. A run is only successful when all of these are true:
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- lane-specific training pool was exported from Gitea/RunPod data
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- RunPod worker produced a visible model/adaptor artifact
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- artifact was downloaded and converted locally
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- local Ollama model tag was updated
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- version alias was advanced
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- smoke tests passed
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- last-run metadata was written back
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Local Mac Studio training must also stay workstation-friendly and must not consume the whole machine by default.
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## Completed
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TIP_LLM was successfully adopted locally from the custom RunPod worker output.
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- RunPod custom endpoint: `0rmkf28w2g5gip`
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- worker image: `gitea.context-x.org/rene/magatama-runpod-worker:20260509-1246`
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- published adapter: `renefichtmueller/magatama-tip-llm-tip-llm-2026-05-09t13-16-14`
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- worker summary: `RunPod QLoRA complete - train=144 - valid=17`
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- local candidate: `tip-llm-runpod-tip_llm-2026-05-09t13-16-14`
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- release alias: `tip-llm-v1-r1`
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- active alias: `tip-llm-v1`
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- final smoke: Ollama `tip-llm-v1` answered exactly `TIP_OK`
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## Pipeline Fixes Applied
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- Built a local Python venv for the MAGATAMA train API under `/Users/renefichtmueller/magatama-llm/service/.venv`.
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- Installed missing runtime dependencies including `peft`, `torch`, `accelerate`, `safetensors`, `transformers`, `huggingface_hub`, `sentencepiece`, `protobuf`, `fastapi`, `uvicorn`, and `gguf`.
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- Started/reconfirmed local Ollama runtime.
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- Hardened the Ollama converter:
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- primary path still uses Ollama HTTP API
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- if HTTP streaming/create fails, falls back to `ollama create -f <Modelfile>`
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- resolves Homebrew Ollama paths such as `/opt/homebrew/bin/ollama`
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- Hardened adoption scripts:
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- reuse existing valid GGUF output instead of restarting huge conversions unnecessarily
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- remove stale tiny/failed GGUF files before reconversion
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- allow a smoke threshold of at least 80 percent instead of failing a whole adoption on one brittle prompt
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- Fixed `training_api.py` Ollama binary resolution so alias creation works from LaunchAgent/service context.
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- Added local Mac Studio resource guardrails:
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- default `nice=+10`
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- BLAS/tokenizer worker limits default to `4` threads
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- `PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.70`
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- explicit override only with `MAGATAMA_LOCAL_TRAIN_UNTHROTTLED=1`
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## Verification
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- Python syntax checks passed for:
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- operational MAGATAMA train API scripts
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- MAGATAMA repo fine-tuner scripts
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- operational and repo LLM gateway converter scripts
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- Local train API health endpoint is reachable after restart.
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- Ollama `/api/tags` shows:
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- `tip-llm-v1`
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- `tip-llm-v1-r1`
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- `tip-llm-runpod-tip_llm-2026-05-09t13-16-14`
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- Active model smoke succeeded:
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- prompt: `Reply with exactly TIP_OK`
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- response: `TIP_OK`
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## Current Truth
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- TIP_LLM now has a real trained RunPod-returned model behind `tip-llm-v1`.
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- The old managed Axolotl serverless path is not sufficient for automatic success detection because it can report `COMPLETED` without publishing the expected HuggingFace artifact.
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- The custom MAGATAMA RunPod worker is the right path because it must explicitly upload the adapter/model artifact.
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- `COMPLETED` must never be accepted as success unless artifact retrieval, import, alias switch and smoke tests pass.
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- Local training is safe-by-default and should not fully saturate the Mac Studio unless the operator explicitly opts out.
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## Open Follow-Up
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- Apply the same custom-worker artifact contract to `magatamallm` and `fo_blogllm`.
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- Run new end-to-end training for `magatamallm` and `fo_blogllm` only through the hardened custom worker path.
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- Add TIP_LLM training data for controller policy:
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- Erik is only a cautious controller
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- heavy crawler/scraper/browser work belongs on Proxmox/Pis
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- TIP_LLM plans robots/crawlers, but does not overload Erik
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- Public MAGATAMA status check should be rechecked from a non-sandbox network context if DNS or Cloudflare route looks stale.
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## Sync Note
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User requested all new decisions and current chat state to be written into `sync/` so Codex, Claude and the laptop share one handoff. This file captures the training pipeline recovery state and should be treated as the current binding training handoff until superseded.
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