langchain4j--langchain4j/CONTRIBUTING.md

Thank you for investing your time and effort in contributing to our project, we appreciate it a lot! 🤗

General guidelines

• For new integrations, please consider adding it in community repo first.
• If you want to contribute a bug fix or a new feature that isn't listed in the issues yet, please open a new issue for it. We will triage it shortly.
• Follow Google's Best Practices for Java Libraries
• Keep the code compatible with Java 17.
• When integrating third-party services, use the official SDK whenever possible. If no official SDK is available, implement the client using langchain4j-http-client and Jackson.
• Avoid adding new dependencies as much as possible (new dependencies with test scope are OK). If absolutely necessary, try to use the same libraries which are already used in the project. Make sure you run mvn dependency:analyze to identify unnecessary dependencies.
• Write unit and/or integration tests for your code. This is critical: no tests, no review!
• The tests should cover both positive and negative cases.
• Make sure you run all unit tests on all modules with mvn clean test. Some integration tests need the API token (key) to be set up as an environment variable in order to communicate with the configured model provider (look for "EnabledIfEnvironmentVariable" annotation to find out the name of this token).
• Avoid making breaking changes. Always keep backward compatibility in mind. For example, instead of removing fields/methods/etc, mark them @Deprecated and make sure they still work as before.
• Follow existing naming conventions.
• Add Javadoc where necessary. There's no need to duplicate Javadoc from the implemented interfaces.
• Follow existing code style present in the project. Run make lint and make format before commit.
• Large features should be discussed with maintainers before implementation.

Opening an issue

• Please fill in all sections of the issue template.

Opening a PR

• Please open the PR as ready for review, not as a draft.
• Before opening the PR, please make sure it is complete:
  • Add unit and/or integration tests for your change (see the testing guidelines above). This is critical: no tests, no review!
  • Add documentation (if required).
  • Run ./mvnw spotless:check and ./mvnw spotless:apply to ensure compliance with the source code formatting of the project.
• Fill in all the sections of the PR template.
• Please make it easier to review your PR:
  • Keep changes as small as possible.
  • Do not combine refactoring with changes in a single PR.
  • Avoid reformatting existing code.

Please note that we do not have the capacity to review PRs immediately. We ask for your patience. We are doing our best to review your PR as quickly as possible.

Guidelines on adding a new model integration

• Please open PRs with new model integrations in the langchain4j-community repository
• Integration with OpenAI is a good example.
• Create integration test classes that extend from AbstractChatModelIT, AbstractStreamingChatModelIT, AbstractChatModelListenerIT, AbstractStreamingChatModelListenerIT and AbstractStreamingAiServiceIT. There are many examples in existing modules.
• If the model provider supports embeddings, implement EmbeddingModel using the request/response API (embed(EmbeddingRequest), supportedParameters(), supportedContentTypes(), listeners()), and create an integration test class that extends from AbstractEmbeddingModelIT. Override the supports*() methods to declare the model's capabilities (per-call parameters such as input_type/dimensions, image/multimodal inputs); the base test then verifies embed(EmbeddingRequest), the convenience methods, listeners, and the fail-fast behavior for unsupported parameters/modalities. See the OpenAI module for an example.
• If model provider supports tools, create an integration test class that extends from AbstractAiServiceWithToolsIT. There are many examples in existing modules.
• If model provider supports structured outputs, create an integration test class that extends from AbstractAiServiceWithJsonSchemaIT. There are many examples in existing modules.
• Document the new integration here, here and here.
• Add an example to the examples repository, similar to this.
• Add a new module to the appropriate section of the BOM.
• It would be great if you could add a Spring Boot starter.

Guidelines on adding a new embedding store integration

• Please open PRs with new embedding store integrations in the langchain4j-community repository
• Integration with Chroma is a good example.
• Add a {IntegrationName}EmbeddingStoreIT. It should extend from EmbeddingStoreWithFilteringIT (when store supports metadata filtering) or EmbeddingStoreIT and pass all tests.
• Add a {IntegrationName}EmbeddingStoreRemovalIT. It should extend from EmbeddingStoreWithRemovalIT and pass all tests.
• Document the new integration here, here and here.
• Add an example to the examples repository, similar to this.
• Add a new module to the appropriate section of the BOM.
• It would be great if you could add a Spring Boot starter. (after

Guidelines on changing an existing embedding store integration

• Ensure that your changes are backwards compatible. Embeddings and TextSegments persisted with the latest released version of LangChain4j should still work.