sync: record magatama runpod adoption and lane truth
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@ -343,6 +343,87 @@ From 2026-04-29:
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- Last price observation: `2026-04-29 19:15:53 UTC`
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- Last stock observation: `2026-04-29 19:15:56 UTC`
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## Latest MAGATAMA Training / RunPod Truth
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Confirmed on `2026-05-06`:
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- Lane-specific training pools are now materially separated and no longer all fallback to `magatamallm`.
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- Live Erik dashboard API now reports:
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- `magatamallm`
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- `1367 train`
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- `152 eval`
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- `1519 total`
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- `newSinceLastTraining = 1367`
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- `fo_blogllm`
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- `17353 train`
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- `1929 eval`
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- `19282 total`
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- `newSinceLastTraining = 17353`
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- active local model resolves to `fo-blog-v7`
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- `tip_llm`
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- `6482 train`
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- `721 eval`
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- `7203 total`
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- `newSinceLastTraining = 6482`
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- target active model is `tip-llm-v1`, but this model is not yet present locally in Ollama
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- Result:
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- previous `1097` everywhere was stale / wrong.
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- selected lane now controls its own manifest, model label, and training counts.
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### Gitea-backed Pool Materialization
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- `magatamallm` Gitea pool remains canonical and populated.
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- `fo_blogllm` and `tip_llm` Gitea-backed pool folders were previously almost empty; they are now materialized from the local RunPod lane exports.
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- Lane manifests and JSONL exports now exist under:
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- `training-data/gitea-learning-pool/fo_blogllm/`
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- `training-data/gitea-learning-pool/tip_llm/`
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### RunPod Completion Hardening
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- MAGATAMA dashboard code now treats RunPod `COMPLETED` as success only after:
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1. target model artifact is referenced
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2. local Mac training API adopts/imports the artifact
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3. lane-specific smoke tests pass
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4. active Ollama alias is updated
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- New local adoption endpoint is:
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- `POST /adopt-runpod-model`
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### Mac Training API State
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- The old LaunchAgent on Mac Studio was still serving the legacy training API from:
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- `~/magatama-llm/service/training_api.py`
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- It has now been upgraded in place so Erik sees the new adoption-capable API.
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- Verified from Erik:
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- `http://192.168.178.213:3214/health` returns the new service
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- it now exposes `register_script` pointing into the MAGATAMA repo
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- `POST /adopt-runpod-model` exists and rejects unauthenticated requests with `401`, proving the route is live
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### Still Outstanding
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- A fully successful end-to-end RunPod fine-tune with:
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- real worker success
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- real artifact
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- successful local Ollama import
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- active alias switch
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- smoke-test proof
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has not yet been re-verified after the new adoption pipeline was wired in.
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- `tip_llm-v1` is still not installed locally in Ollama.
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### Pulso AI Recommendation
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- Keep a shared network/transceiver/switch core corpus with TIP.
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- Do not collapse `Pulso AI` into the same instruction lane as `TIP_LLM`.
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- Recommended split:
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- `TIP_LLM`
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- research
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- crawler / scraper / robot planning
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- vendor / firmware / issue extraction
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- `Pulso AI`
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- product responses
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- support
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- diagnostics
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- operator explanation layer
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## Safe Next Steps
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1. Clone or pull Gitea `origin` on laptop/Claude Code.
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@ -0,0 +1,161 @@
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# 2026-05-06 — MAGATAMA RunPod Adoption + Lane Truth
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## Scope
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Finalize the MAGATAMA training path so that:
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1. lane-specific pools are real and visible
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2. RunPod `COMPLETED` is not treated as success without a real adoptable artifact
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3. Mac Studio exposes a live adoption endpoint for post-RunPod import + smoke tests
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4. `fo_blogllm` / `tip_llm` stop inheriting stale `magatamallm` counts
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## What Changed
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### 1. Gitea-backed lane pools are now materialized
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The sync/build chain was extended so `fo_blogllm` and `tip_llm` are not “README-only” placeholders anymore.
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Current local lane export truth:
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- `magatamallm`
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- `1367 train`
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- `152 eval`
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- `1519 total`
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- `fo_blogllm`
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- `17353 train`
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- `1929 eval`
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- `19282 total`
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- `tip_llm`
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- `6482 train`
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- `721 eval`
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- `7203 total`
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`sync_gitea_training_pool.ts` now writes lane-specific manifests and JSONL exports back into the Gitea-backed learning-pool tree.
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### 2. RunPod completion gating was hardened
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The dashboard/server path was updated so RunPod `COMPLETED` is no longer enough by itself.
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The intended success chain is now:
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1. RunPod reports terminal state
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2. target model artifact is identified
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3. Mac Studio `/adopt-runpod-model` is called
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4. local candidate model is imported into Ollama
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5. lane-specific smoke suite passes
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6. active alias is switched
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7. only then is the run treated as truly successful
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Registry status extensions added:
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- `completed_and_adopted`
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- `completed_seed_preparation`
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- `completed_not_adopted`
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### 3. Mac Studio training API was upgraded in place
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Critical discovery:
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- Erik already used `http://192.168.178.213:3214`
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- but the Mac LaunchAgent still served the **old** training API from:
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- `~/magatama-llm/service/training_api.py`
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This old service had no `/adopt-runpod-model`.
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Action taken:
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- upgraded the LaunchAgent-targeted file in place
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- made the training API portable enough to find `register_runpod_ollama_model.py` from either:
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- the MAGATAMA repo
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- or fallback candidate paths
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Verified from Erik:
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- `GET /health` works
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- response now contains:
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- `register_script: /Users/renefichtmueller/Desktop/Claude Code/magatama/scripts/register_runpod_ollama_model.py`
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- `POST /adopt-runpod-model` exists and returns `401` without auth, which proves the new route is live
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### 4. Lane status is now honest
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The live Erik dashboard API now reports lane-specific values instead of silently reusing `magatamallm`.
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Also fixed:
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- `fo_blogllm` and `tip_llm` no longer inherit a false “last successful run” from the global Mac training state
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- lane-specific active model labels are now used:
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- `fo_blogllm` -> `fo-blog-v7`
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- `tip_llm` -> `tip-llm-v1`
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## Verified Live State on Erik
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### `magatamallm`
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- available: `true`
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- activeProvider: `ollama:magatama-coder:latest`
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- `newSinceLastTraining = 1367`
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### `fo_blogllm`
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- available: `true`
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- activeProvider: `ollama:fo-blog-v7`
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- `newSinceLastTraining = 17353`
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- `lastTrainingAt = null`
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- `neverTrained = true`
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### `tip_llm`
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- available: `false`
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- activeProvider falls back to `claude-bridge`
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- target model shown as `tip-llm-v1`
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- `newSinceLastTraining = 6482`
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- `lastTrainingAt = null`
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- `neverTrained = true`
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Interpretation:
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- `tip_llm` corpus is real, but the active Ollama alias is not installed locally yet.
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## Pulso AI Decision
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Recommended architecture:
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- shared network / transceiver / switch knowledge core with TIP
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- separate behavior lane
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Meaning:
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- `TIP_LLM`
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- research
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- crawler planning
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- issue extraction
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- vendor / firmware / compatibility search
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- `Pulso AI`
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- support
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- diagnostics
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- operational explanation
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- customer/product answer layer
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Do **not** blindly reuse the exact same instruction lane for both.
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## Still Open
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1. A fresh real RunPod run still needs full end-to-end proof after the new adoption path:
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- successful worker execution
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- artifact exists
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- local import succeeds
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- smoke suite passes
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- alias switches
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2. `tip_llm-v1` still needs local Ollama adoption/installation.
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3. Further corpus enrichment is still desirable from:
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- local transceiver/TIP/blog pools
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- Susan/Fearghas if accessible
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- GitHub / universities / security research sources
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## Operator Notes
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- TIP policy remains:
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- TIPLLM-only for robot/crawler planning
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- Erik is light controller only
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- heavy crawling runs on Proxmox / Pis
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- Push only `sync/` to Gitea from this handoff update.
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