| # Contributing to H2O LLM STUDIO | |
| H2O LLM Studio is an open source project released under the Apache Software Licence v2. Open Source projects live by | |
| their user and developer communities. We welcome and encourage your contributions of any kind! | |
| ## Bug Reports and Feature Requests | |
| Found a bug or have an idea for a new feature? Your feedback is invaluable! To ensure a smooth and collaborative | |
| process, please follow these steps: | |
| 1. Provide the full error message and stack trace, if applicable. | |
| 2. Attach the model configuration yaml file if the error is related to model training. | |
| 3. Specify the commit hash of the version you are using (running `git rev-parse HEAD`) in your report. If you are | |
| pasting the UI error message, the commit hash will also be included in the error message. | |
| 4. If the error is reproducible, kindly include the steps to reproduce it. | |
| 5. If possible, attempt to reproduce the error using the default dataset. | |
| 6. Please mention any other details that might be useful, e.g. if you are using LLM Studio in a Docker container, etc. | |
| ## Pull Requests | |
| You can contribute to the project by fixing bugs, adding new features, refactoring code, or enhancing documentation. | |
| To ensure a smooth and collaborative process for everyone, please follow these guidelines: | |
| 1. Check if the issue you plan to address is already [reported](https://github.com/h2oai/h2o-llmstudio/issues). If not, | |
| please open a new issue | |
| to discuss your proposed changes. | |
| 2. Avoid duplicating work by commenting on the issue you're working on and feel free to seek assistance or ask | |
| questions; our team is happy to help. | |
| 3. Fork the repository and create a new branch from `main`. To develop, please follow the setup instructions below. | |
| 4. Implement your changes and commit them to your branch. | |
| 5. When you feel ready, open a pull request with your changes. You can also open the PR as a draft to receive early | |
| feedback. To facilitate the review process, we have provided a PR checklist below. | |
| 6. Our team will review your pull request and provide feedback. Once everything looks good, we will proceed to merge | |
| your contribution. | |
| ## Setting up your development environment | |
| Follow the instructions in [README](https://github.com/h2oai/h2o-llmstudio/blob/main/README.md) to set up your | |
| environment. Run `make setup-dev` instead of `make setup` to install the development dependencies. | |
| ## Running linters and tests | |
| Before submitting your pull request, ensure that your code passes the linters and tests. | |
| To format your code, run `make format`. You can check for any style issues by running `make style`. To run the tests, | |
| run `make test`. | |
| ## PR checklist | |
| Please make sure your pull request fulfills the following checklist: | |
| ☐ The PR title should provide a clear summary of your contribution. | |
| ☐ Link the related issue (e.g., closes #123) in your PR description. | |
| ☐ If your contribution is still a work in progress, change the PR to draft mode. | |
| ☐ Ensure that the existing tests pass by running `make test`. | |
| ☐ Make sure `make style` passes to maintain consistent code style. | |
| ## Installing custom packages | |
| If you need to install additional Python packages into the environment, you can do so using pip after activating your virtual environment via ```make shell```. For example, to install flash-attention, you would use the following commands: | |
| ```bash | |
| make shell | |
| pip install flash-attn --no-build-isolation | |
| pip install git+https://github.com/HazyResearch/flash-attention.git#subdirectory=csrc/rotary | |
| ``` | |
| For a PR, update the Pipfile and the Pipfile.lock via ```pipenv install package_name```. | |