# Contributing to LiteLLM Thank you for your interest in contributing to LiteLLM! We welcome contributions of all kinds - from bug fixes and documentation improvements to new features and integrations. ## **Checklist before submitting a PR** Here are the core requirements for any PR submitted to LiteLLM: - [ ] **Sign the Contributor License Agreement (CLA)** - [see details](#contributor-license-agreement-cla) - [ ] **Keep scope isolated** - Your changes should address 1 specific problem at a time #### Proxy (Backend) PRs - [ ] **Add testing** - Adding at least 1 test is a hard requirement - [see details](#adding-testing) - [ ] **Ensure your PR passes all checks**: - [ ] [Linting / Formatting](#running-linting-and-formatting-checks) - `make lint` - [ ] [The tests covering your change](#running-unit-tests) pass, e.g. `uv run pytest tests/test_litellm/.py -v`. CI runs the full unit test matrix, so you don't need to run the whole suite locally #### UI PRs - [ ] **Ensure the UI builds successfully** - `npm run build` - [ ] **Ensure all UI unit tests pass** - `npm run test` - [ ] **Add tests for new components or logic** - If you are adding a new component or new logic, add corresponding tests ## **Contributor License Agreement (CLA)** Before contributing code to LiteLLM, you must sign our [Contributor License Agreement (CLA)](https://cla-assistant.io/BerriAI/litellm). This is a legal requirement for all contributions to be merged into the main repository. **Important:** We strongly recommend reviewing and signing the CLA before starting work on your contribution to avoid any delays in the PR process. ## Quick Start ### 1. Setup Your Local Development Environment ```bash # Fork the repository on GitHub (click the Fork button at https://github.com/BerriAI/litellm) # Then clone your fork locally git clone https://github.com/YOUR_USERNAME/litellm.git cd litellm # Create a new branch for your feature (see "Commit and Branch Conventions" below) git checkout -b feature/your-feature # Install development dependencies make install-dev # Install git hooks that enforce commit + branch conventions (one-time, opt-in) make install-hooks # Verify your setup works make help ``` That's it! Your local development environment is ready. ## Commit and Branch Conventions Commits follow [Conventional Commits](https://www.conventionalcommits.org/en/v1.0.0/) and branches follow [Conventional Branches](https://conventional-branch.github.io/). Run `make install-hooks` once per clone to enable the local git hooks that enforce these — see the [contributor docs](https://docs.litellm.ai/docs/extras/contributing_code#commit-and-branch-conventions) for the full type list, examples, the protected-branch bypass list, and how to opt out. ### 2. Development Workflow Here's the recommended workflow for making changes: ```bash # Make your changes to the code # ... # Format your code (auto-fixes formatting issues) make format # Run all linting checks (matches CI exactly) make lint # Run the tests covering your change (CI runs the full suite) uv run pytest tests/test_litellm/.py -v # Commit your changes (must follow Conventional Commits — see above) git add . git commit -m "feat(scope): your descriptive commit message" # Push and create a PR (branch must follow Conventional Branches — see above) git push origin feature/your-feature ``` ## Adding Testing **Adding at least 1 test is a hard requirement for all PRs.** ### Where to Add Tests Add your tests to the [`tests/test_litellm/` directory](https://github.com/BerriAI/litellm/tree/main/tests/test_litellm). - This directory mirrors the structure of the `litellm/` directory - **Only add mocked tests** - no real LLM API calls in this directory - For integration tests with real APIs, use the appropriate test directories ### File Naming Convention The `tests/test_litellm/` directory follows the same structure as `litellm/`: - `litellm/proxy/caching_routes.py` → `tests/test_litellm/proxy/test_caching_routes.py` - `litellm/utils.py` → `tests/test_litellm/test_utils.py` ### Example Test ```python import pytest from litellm import completion def test_your_feature(): """Test your feature with a descriptive docstring.""" # Arrange messages = [{"role": "user", "content": "Hello"}] # Act # Use mocked responses, not real API calls # Assert assert expected_result == actual_result ``` ## Running Tests and Checks ### Running Unit Tests Run the tests covering your change: ```bash uv run pytest tests/test_litellm/test_your_file.py -v ``` `tests/test_litellm` holds thousands of tests, so running all of it locally takes a long time. CI runs it as a parallel matrix (`make test-unit-llms`, `make test-unit-proxy-core`, and the other `test-unit-*` targets) on beefier boxes, so if, for whatever reason, you must run the whole suite, it's better to rely on CI to do that. If you're running broader test suites, proxy tests, or anything that touches PostgreSQL-backed fixtures/plugins, install the full local test environment first: ```bash make install-test-deps ``` This syncs the locked test environment used across the repo, including `psycopg` v3 plus `psycopg-binary` (used by `pytest-postgresql`), `psycopg2-binary` (used by some proxy E2E tests), and a generated Prisma client for DB-backed proxy tests, so pytest startup matches CI without manual package installs. ### Running Linting and Formatting Checks Run all linting checks (matches CI exactly): ```bash make lint ``` Individual linting commands: ```bash make format-check # Check Black formatting make lint-ruff # Run Ruff linting make lint-basedpyright # Run basedpyright type checking make check-circular-imports # Check for circular imports make check-import-safety # Check import safety ``` Apply formatting (auto-fixes issues): ```bash make format ``` > **Black formatting is enforced in CI.** All PRs must pass the Black formatting check. > > - **AI coding agents** (Claude Code, Copilot, Cursor, etc.): `AGENTS.md` and `CLAUDE.md` instruct agents to run `poetry run black .` before committing. > - **VS Code users**: Install the [Black Formatter extension](https://marketplace.visualstudio.com/items?itemName=ms-python.black-formatter) and enable format-on-save: > ```json > { > "[python]": { > "editor.defaultFormatter": "ms-python.black-formatter", > "editor.formatOnSave": true > } > } > ``` ### CI Compatibility To ensure your changes will pass CI, run the exact same checks locally: ```bash # This runs the same checks as the GitHub workflows make lint make test-unit ``` For exact CI compatibility (pins OpenAI version like CI): ```bash make install-dev-ci # Installs exact CI dependencies ``` ## Available Make Commands Run `make help` to see all available commands: ```bash make help # Show all available commands make install-dev # Install development dependencies make install-proxy-dev # Install proxy development dependencies make install-test-deps # Install the full local test environment make format # Apply Black code formatting make format-check # Check Black formatting (matches CI) make lint # Run all linting checks make test-unit # Run unit tests make test-integration # Run integration tests make test-unit-helm # Run Helm unit tests ``` ## Code Quality Standards LiteLLM follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html). Our automated quality checks include: - **Black** for consistent code formatting - **Ruff** for linting and code quality - **basedpyright** for static type checking - **Circular import detection** - **Import safety validation** All checks must pass before your PR can be merged. ## Common Issues and Solutions ### 1. Linting Failures If `make lint` fails: 1. **Formatting issues**: Run `make format` to auto-fix 2. **Ruff issues**: Check the output and fix manually 3. **basedpyright issues**: Add proper type hints 4. **Circular imports**: Refactor import dependencies 5. **Import safety**: Fix any unprotected imports ### 2. Test Failures If `make test-unit` fails: 1. Check if you broke existing functionality 2. Add tests for your new code 3. Ensure tests use mocks, not real API calls 4. Check test file naming conventions ### 3. Common Development Tips - **Use type hints**: basedpyright requires proper type annotations - **Write descriptive commit messages**: Help reviewers understand your changes - **Keep PRs focused**: One feature/fix per PR - **Test edge cases**: Don't just test the happy path - **Update documentation**: If you change APIs, update docs ## Building and Running Locally ### LiteLLM Proxy Server To run the proxy server locally: ```bash # Install proxy dependencies make install-proxy-dev # Start the proxy server uv run litellm --config your_config.yaml ``` ### Docker Development If you want to build the Docker image yourself: ```bash # Build using the non-root Dockerfile docker build -f docker/Dockerfile.non_root -t litellm_dev . # Run with your config docker run \ -v $(pwd)/proxy_config.yaml:/app/config.yaml \ -e LITELLM_MASTER_KEY="sk-1234" \ -p 4000:4000 \ litellm_dev \ --config /app/config.yaml --detailed_debug ``` ## UI Development ### 1. Setup Your Local UI Development Environment ```bash # Clone the repo (if you haven't already) git clone https://github.com/YOUR_USERNAME/litellm.git cd litellm # Navigate to the UI dashboard directory cd ui/litellm-dashboard # Install dependencies npm install # Start the development server npm run dev ``` ### 2. Adding UI Tests If you are adding a **new component** or **new logic**, you must add corresponding tests. ### 3. Running UI Unit Tests ```bash npm run test ``` ### 4. Building the UI Ensure the UI builds successfully before submitting your PR: ```bash npm run build ``` ## Submitting Your PR 1. **Push your branch**: `git push origin your-feature-branch` 2. **Create a PR**: Go to GitHub and open a pull request against [`litellm_internal_staging`](https://github.com/BerriAI/litellm/tree/litellm_internal_staging), which is the default base branch. Do not target `main`. 3. **Fill out the PR template**: Provide clear description of changes 4. **Wait for review**: Maintainers will review and provide feedback 5. **Address feedback**: Make requested changes and push updates 6. **Merge**: Once approved, your PR will be merged! ## Getting Help If you need help: - 💬 [Join our Discord](https://discord.gg/wuPM9dRgDw) - 💬 [Join our Slack](https://www.litellm.ai/support) - 📧 Email us: ishaan@berri.ai / krrish@berri.ai - 🐛 [Create an issue](https://github.com/BerriAI/litellm/issues/new) ## What to Contribute Looking for ideas? Check out: - 🐛 [Good first issues](https://github.com/BerriAI/litellm/labels/good%20first%20issue) - 🚀 [Feature requests](https://github.com/BerriAI/litellm/labels/enhancement) - 📚 Documentation improvements - 🧪 Test coverage improvements - 🔌 New LLM provider integrations Thank you for contributing to LiteLLM! 🚀