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FurtherAI
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## Summary Trying to add megatron dependencies in uv. This makes CI expensive, so I am trying to build a cached image with megatron related dependencies which does the heavy lifting. This can be updated by a dedicated workflow when megatron dependencies are modified. This PR is to add that workflow to main so #560 can test the workflow and CI.
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- Replace prebuilt-image bootstrap with uv-cache release-asset workflow and fingerprint gating. - Use compute/build helpers (`compute_uv_fingerprint.py`, `build_and_push_uv_cache.sh`) and document cache refresh in CONTRIBUTING. - Harden containerized Prek workflow for deterministic execution (git installed before checkout, explicit safe.directory, POSIX-safe shell checks). - Enforce fingerprint-only cache restore by removing moving `*-current.tar.zst` fallback from restore and publish paths. - Keep Prek dependency scope at `--all-extras --group dev` to preserve megatron coverage in CI. - Store full uv cache as fingerprinted chunked release assets (`.tar.zst.part-###`) so CI reuses wheel/build payloads without GH single-asset size limits. - Download cache parts with parallelism 8 in CI restore path, then reassemble in deterministic order. - Bump cache fingerprint schema/layout contract for the chunked-asset format. - Keep immutable cache retention policy (latest 4 fingerprints).
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Big problem with the initial version, CI takes forever and lots of memory. But mostly solved. After a number of iterations, the solution I have arrived at is as following:
This does increase the total CI time from ~2 min -> ~6 min (added installing the docker container and the uv cache). The benefit is keeping our dependencies in line (note we found an issue with conflicting required versions of numpy already) and ensuring reproducibility for our environments. |
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projects/art/src/art/megatron/setup.shto uv. This makes it cleaner to set up a venv for dev.