review · segments
Read /tmp/legit-embedding-bakein-task.md in full — it's your complete spec. Goal: bake the default models (EVA02 + e5 + clip) into the worker image at BUILD time so a spawned pod's cold-start is just the image pull (no runtime model download), withou
codex 172 events 1 segments runpod-container-runtime
segment 1 of 1
Bake default models (EVA02, e5, CLIP) into the worker image at build time
The assistant read the task spec, examined the existing Dockerfile, model loaders, and config. Created scripts/prefetch_models.py that forces CPU, sets cache dirs, and reuses worker loaders to download EVA02, CLIP, and e5 models. Modified Dockerfile to add ARG HF_TOKEN and a RUN step after pip install to run the prefetch script and chown /models. Verified via AST parsing and identifier matching. Committed locally on runpod-container-runtime branch. Wrote /tmp/legit-embedding-bakein-findings.md with handoff instructions.
outcome
Local commit 846c3e5 on branch runpod-container-runtime with Dockerfile and scripts/prefetch_models.py; findings file ready for review.
next steps
—
key decisions
- Reuse worker's own load code (init_model, SingletonTextEmbeddingModel) to guarantee cache paths match exactly.
- Force CPU at build time by setting CUDA_VISIBLE_DEVICES='' before importing torch.
- Add HF_TOKEN as a Docker build arg, passed only to the prefetch command, not persisted as an ENV.
- Use explicit git add paths (Dockerfile and scripts/prefetch_models.py) to avoid staging unintended files.
- Do not push; leave coordination to Mike.
open questions
—
2 weeks ago → 2 weeks ago