transceiver-db/sync/history/2026-05-07-magatamallm-local-training-verification.md

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