# 2026-05-07 – MagatamaLLM Local Training Verification

## Question

Did the recent local / MAGATAMA-side MagatamaLLM training actually succeed and increase the active model’s knowledge?

## Answer

No. The dataset refresh succeeded, but a newer locally adopted MagatamaLLM model was **not** verified.

## Evidence

### 1. Public MAGATAMA status

`GET https://magatama.fichtmueller.org/api/llm/status`

Observed:
- `activeProvider = ollama:magatama-coder:latest`
- `autoFixProvider = ollama:magatama-coder:latest`
- `training.lastTrainingAt = 2026-05-06T22:43:20Z`
- `training.modelVersion = magatama-coder:latest`
- `training.activeRun = null`

Interpretation:
- the dashboard timestamp reflects the latest dataset/training-state update
- it does **not** prove that a new local model was imported and activated

### 2. Local Ollama state on the Mac

`ollama list`

Relevant entries:
- `magatama-coder:latest` → modified `3 weeks ago`
- `magatama-llm-v2-0:latest` → modified `11 days ago`

Interpretation:
- no newly imported Magatama candidate/adopted model is visible locally
- the active alias still points to an older model image

### 3. Dataset/lane export did work

Fresh Erik manifest exists:
- `/opt/magatama/training-data/runpod/magatamallm/manifest.json`

Observed:
- `generatedAt = 2026-05-06T22:45:15.944Z`
- `train = 15679`
- `eval = 1743`
- `total = 17422`

Interpretation:
- the lane export / pool sync is healthy
- training input exists and was rebuilt

### 4. Adoption/registry proof is missing

On Erik, these expected local state files were absent:
- `/opt/magatama/training-data/model-registry/models.json`
- `/opt/magatama/training-data/model-registry/runs.json`
- `/opt/magatama/training-data/model-registry/active.json`
- `/opt/magatama/data/llm-status.json`

Interpretation:
- no trustworthy proof that a new model artifact was imported, registered, and activated

### 5. Historical run records still show failed/non-adopted outcomes

Local `training-data/model-registry/training-runs.json` still contains recent `magatamallm` runs such as:
- `submitted`
- `not_found_after_submit`

There is still no verified “completed_and_adopted” proof for a new MagatamaLLM local model.

## Conclusion

Current state:
- pool refresh works
- lane export works
- active alias/version switching after training is still not proven

Therefore:
- MagatamaLLM did **not** yet gain a verified newer local knowledge state from the recent run attempts
- MAGATAMA is still operating on the older active alias `magatama-coder:latest`

## Next Required Fix

The remaining training-automation gap is still:

1. run completes
2. artifact existence is verified
3. artifact is adopted/imported locally
4. smoke tests pass
5. active alias + model version are updated
6. only then mark training as successful