Keep provider-specific behavior at a narrow integration boundary, define explicitly what your application expects from each API, and test both contract compatibility and model behavior. Then version deliberately, retry only when repeating an operation is safe, and capture enough diagnostic context to investigate failures.
Put each provider behind an integration boundary
Your application should depend on an interface describing the AI capability it needs, not on a provider’s endpoint paths, authentication headers, request format, response shape, or error conventions. Keep those provider-specific details in an adapter that translates between the application’s internal interface and the provider’s API.
This separation limits the places that must change when a provider changes its contract or when you add or replace a provider. It also gives you one place to normalize responses and errors before the rest of the application handles them.
Describe and maintain the external contract
OpenAPI is a language-agnostic way to describe an HTTP API. An OpenAPI description can support generated documentation, clients, and tests. Treat it as a maintained representation of the provider contract you integrate with, rather than as proof that the integration is resilient by itself: generated code reflects a particular description and toolchain, and application-specific behavior still needs checking.
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Make compatibility assumptions explicit
“Backward compatible” is not a universal promise that every existing client will keep working. It depends on the API’s stated compatibility policy and on what a client assumes. Microsoft’s API guidance identifies removals, renames, behavioral changes, and changes to error contracts as examples of breaking changes. It also notes that API teams may disagree about whether adding a JSON response field is compatible.
Write down the assumptions your adapter makes, so a provider change can be assessed against actual client behavior rather than a vague claim of compatibility.
- Which response fields are required, and which may be absent or null?
- Can the parser ignore unfamiliar optional fields, or does the contract require strict rejection?
- Which event types does a streaming client recognize, and what should it do with an unfamiliar type?
- Which error codes or categories trigger special handling?
- Which semantic conditions must hold before application code uses a response?
At the parsing boundary, tolerate an unfamiliar optional field when the API’s contract allows it; do not reject an otherwise usable response just because it contains extra data. Conversely, validate required fields and semantic invariants before downstream code relies on them. This balances tolerance for permitted additions with protection against incomplete or unusable responses.
Choose API versions deliberately and plan migrations
When an addition fits the existing contract and preserves client behavior under the provider’s compatibility policy, an additive change can avoid an unnecessary version break. When the structure or behavior does break the contract, make the version your client requests explicit and plan the move before an older version is retired.
Microsoft’s Azure API design guidance describes several places to select a version. The choice affects how clients express their contract and raises routing and caching considerations; there is no universally best mechanism.
| Versioning approach | Where the client selects the version | Design question to settle |
|---|---|---|
| URI | In the request URI | How will routes and caches distinguish the versioned resource? |
| Query parameter | In a query parameter | Will routing and cache behavior account for the version parameter? |
| Header | In a request header | Will clients, routing, and caches consistently honor the version header? |
| Media type | In the request’s media type | How will clients and the server negotiate and route the requested representation? |
The table describes the selection mechanism and questions to resolve, not a ranking. For any approach, document the selected version and ensure caches do not serve a response for a different contract. Kubernetes API lifecycle guidance illustrates another necessary part of versioning: serving multiple versions while clients move from a deprecated version to its replacement. Set a migration window, communicate the replacement, and give clients clear examples before retiring the old version.
Retry according to operation semantics, not just status codes
A timeout tells the client it did not receive a timely result; it does not prove the server failed to apply the request. Automatically repeating a non-idempotent operation can therefore perform the operation twice. RFC 9110 says: “A client SHOULD NOT automatically retry a request with a non-idempotent method unless it has some means to know that the request semantics are actually idempotent, regardless of the method, or some means to detect that the original request was never applied.”
For a POST-based AI operation, decide whether repeating it is safe based on its actual semantics. Consider duplicate computation as well as any external side effects the operation may trigger. Do not enable automatic retries merely because a request timed out or returned a particular status code. Retry only when the operation is known to be idempotent or the client can establish that the original request was not applied.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test model behavior separately from API compatibility
A response can still match the API schema while the model behaves differently. OpenAI’s API documentation warns that prompting behavior can change between model snapshots and recommends pinned model versions and evaluations for consistency: “The best way to ensure consistent prompting behavior and model output is to use pinned model versions, and to implement evals for your applications.” This is provider-specific guidance; it does not establish that every provider offers the same snapshot controls or guarantees.
Keep the selected model identifier separate from general application logic and record it with the relevant configuration. When a provider offers pinned snapshots, evaluate a proposed snapshot change against representative application cases before rollout.
Test the behaviors your application depends on
Build evaluation cases around the integration’s actual requirements, rather than relying on a generic quality score. Depending on the application, check structured fields, tool selection, refusal handling, and streaming assembly. An evaluation can reveal regressions in tested cases, but there is no universal test set and it cannot guarantee that every change will be caught.
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Make production failures diagnosable
When an API call fails, collect enough metadata to connect the application’s view of the failure with the provider’s. Capture a provider request identifier when one is returned, along with your own trace identifier, provider and model selection, endpoint, timing, and a normalized error category. Follow your application’s data-handling requirements when logging; redact credentials and sensitive prompt or response content.
OpenAI recommends logging request IDs for production troubleshooting and documents a client-supplied request ID for network failures where a server-generated ID may not reach the client. That distinction matters during a timeout: the absence of a provider-generated identifier in the client’s logs does not by itself show that the request never reached the server.
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