mirror of
https://github.com/tiennm99/litellm.git
synced 2026-07-30 20:23:32 +00:00
Yuneng Jiang
3d55afe38b
The 12 core `[project.dependencies]` entries in pyproject.toml were exact `==` pins, a side effect of the Poetry → uv migration. This forces every downstream package that lists litellm as a dependency to downgrade common runtime libraries (openai, pydantic, aiohttp, click, jsonschema, ...) to the exact versions we ship. Customers have flagged this as a coexistence blocker. Switch to lower-bounded ranges with upper bounds where the upstream package is pre-1.0 or has a known breaking-major-version policy. Reproducibility for our Docker proxy and CI continues to come from `uv.lock`, which is regenerated here as a metadata-only diff (no resolved versions or hashes change). Inspired by #26157 (which got stranded on `litellm_oss_staging_04_21_2026` when the forward-merge to internal staging in #26216 was closed). Floors in this PR are tighter than #26157's: they were validated by installing litellm at `--resolution=lowest-direct` and importing the openai-namespace symbols the codebase actually uses. Floor highlights vs #26157: - openai >= 2.20 (was 2.0) — Responses API symbols + `Omit` need a 2.x mid-range floor - httpx >= 0.28, < 1.0 (was no upper) — pre-1.0 - importlib-metadata >= 8.0 (was 6.0) — stay in tested major - tokenizers >= 0.20, < 1.0 (was 0.19, no upper) — pre-1.0 - aiohttp >= 3.10, < 4.0 (was no upper) — bound major - pydantic >= 2.5, < 3.0 — kept - All other floors: keep tested major, add upper bound Adds a `check-dependency-floors.yml` GitHub Actions workflow that installs litellm at `--resolution=lowest-direct` on Python 3.10 and 3.13 and import-checks every openai symbol the codebase uses, so a future floor regression fails fast in CI rather than silently in the field.
Simple PyPI Publishing
A GitHub workflow to manually publish LiteLLM packages to PyPI with a specified version.
How to Use
- Go to the Actions tab in the GitHub repository
- Select Simple PyPI Publish from the workflow list
- Click Run workflow
- Enter the version to publish (e.g.,
1.74.10)
What the Workflow Does
- Updates the version in
pyproject.toml - Copies the model prices backup file
- Builds the Python package
- Publishes to PyPI
Prerequisites
Make sure the following secret is configured in the repository:
PYPI_PUBLISH_PASSWORD: PyPI API token for authentication
Example Usage
- Version:
1.74.11→ Publishes as v1.74.11 - Version:
1.74.10-hotfix1→ Publishes as v1.74.10-hotfix1
Features
- ✅ Manual trigger with version input
- ✅ Automatic version updates in
pyproject.toml - ✅ Repository safety check (only runs on official repo)
- ✅ Clean package building and publishing
- ✅ Success confirmation with PyPI package link