API Development

An API is a contract between separately evolving components. An HTTP inference endpoint may validate structured input and return predictions, while gRPC uses service definitions and typed messages for remote procedure calls. Server-sent events can carry incremental server output over an HTTP connection. These mechanisms have different transport and client requirements; streaming is not simply a faster ordinary response. AI APIs also need to express model versions, asynchronous jobs, cancellation and usage limits without requiring clients to understand the serving implementation or infer success from generated text.

The practitioner chooses interaction patterns from the workload: a short prediction may fit request-response, while a long document analysis may require a job identifier and status endpoint. They specify schemas, authorization boundaries, stable error categories and retry rules. They define how clients detect stream termination and how partial results are represented. Contract tests exercise valid, invalid and unauthorized requests, alongside slow consumers and disconnected clients. The result is an interface clients can integrate with and operate under realistic failure conditions.

A schema validates shape, not the factual quality of a model response. Retrying a request can duplicate work or charges unless operation semantics support it. Long-lived streams can consume connection capacity and fail through proxies. gRPC, REST and event streams do not share identical error or compatibility rules. Check client behavior, deadlines, authorization and backward compatibility rather than relying only on generated API documentation.