In-App Chatbot Code Reviews — A Beginner's Portable API Contract

When considering an in-app chatbot for reviewing logistics code changes, the choice between an OpenAI-compatible endpoint and an Anthropic-specific contract depends on the organization's priorities. A beginner should opt for the OpenAI-compatible contract, as it offers broader developer experience benefits such as examples, SDK support, middleware, and migration paths. Anthropic's native API should only be chosen when its distinct contract is a requirement that the team is prepared to own.

The key concern is preventing any changes in the provider from altering the application's review request, finding schema, or retry policy. The remote chat protocol should be treated as an adapter, with the focus on keeping the review request, finding schema, and retry policy invariant. The application should consistently send the repository path, diff, and policy version, regardless of the underlying model. It should also receive findings with stable fields like severity, file, line, and explanation.

The OpenAI-compatible contract presents a practical advantage, as existing chatbot samples and middleware can often be reused, and the same conversation structure can grow from a single user message to a system prompt, chat history, and JSON output. However, an adapter is still required, and compatibility only reduces the adapter's surface area rather than eliminating it entirely.

When dealing with potential production failures, such as a worker timing out before the application stores review findings, the focus should be on maintaining a stable review ID. This ID should be derived from repository, commit SHA, policy version, and diff digest, and stored before calling the model. The final database write should be conditional on the same ID. This approach ensures idempotency and prevents duplicates when retries occur.

To make the decision, compare the contracts based on operational ownership. The OpenAI-compatible contract offers a baseline for the compatible ecosystem, making it ideal for teams wanting direct reference implementation. Anthropic-native messages require an explicit adapter to leave the native contract, introducing potential provider-specific dependencies. The choice ultimately depends on the organization's priorities and existing governance and operations infrastructure.