tanishqgandhi1908 opened a new pull request, #6869:
URL: https://github.com/apache/texera/pull/6869
### What changes were proposed in this PR?
Lets users create and manage ML models the same way they manage datasets:
make a model, rename it, describe it, make it public or private, share it with
specific people, and delete it. Uploading model files comes in a follow-up PR.
A model is a sibling of a dataset — its own table and its own LakeFS
repository (`model-{mid}`), on the same storage engine. Creating one provisions
its repository and grants the creator write access; deleting one removes the
repository, the stored files, and the row.
Two endpoints:
- **`/model`** — create, list, get, delete, rename, update description, and
toggle public / downloadable.
- **`/access/model`** — see the owner, see who a model is shared with, grant
and revoke access.
Both reuse the shared resource layer rather than repeating the dataset
rules, so the model-specific code is mostly the endpoints themselves.
### Any related issues, documentation, discussions?
Part of #6498, umbrella #6494.
**Depends on #7760**, which adds the shared access and naming layer this
builds on.
### How was this PR tested?
- `ModelResourceSpec` (22) — create (valid, duplicate name per owner,
invalid name, framework default), get / list / public-get with access
filtering, owner-only delete, rename and description updates, publicity and
downloadable toggles.
- `ModelAccessResourceSpec` (30) — privilege rules, grant / list / revoke,
and rejection of unknown or placeholder accounts.
- `sbt "FileService/test"` — 293/293 with #7760 applied, including the
existing dataset suites.
- `scalafmtCheckAll` and `scalafixAll --check` clean.
Also verified manually in a running Texera: create, rename, duplicate-name
rejection, sharing and revoking with a second account, public visibility, and
owner-only delete.
### Was this PR authored or co-authored using generative AI tooling?
Generated-by: Claude Code (Claude Opus 5)
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