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A routine test run can spend API credits whenever the code path under test sends real requests to a provider. The dependable fix is to make ordinary tests offline: put a replaceable client or HTTP boundary around those calls, then inject scripted responses, intercept requests, or replay fixtures. Keep live provider checks in a separate, deliberately run integration test. Prompt caching may lower the cost of eligible repeated inputs, but it does not stop tests from making requests.
Find which test requests are reaching a provider
Start at the boundary between your application and the network. Search the test setup and code paths it exercises for SDK construction, HTTP client creation, dependency-injection bindings, and environment variables such as API keys. A test may use a live service because it constructs the production client by default, inherits credentials from a developer machine or CI environment, or reaches a network call through a workflow it was meant to test.
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Trace what happens when the test runs: identify the request-producing code, the client or transport it uses, and any other external services it contacts. The goal is not merely to hide or ignore the response. It is to ensure routine tests do not send the request in the first place.
Choose an offline substitute for the boundary you need to test
Use the narrowest substitute that still exercises the behavior you care about. A unit or workflow test usually needs predictable outputs and a way to inspect how your application called the provider; a browser test may need a controlled HTTP response; tests focused on provider-shaped payloads may benefit from recorded fixtures.
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| Approach | Best fit | Key trade-off |
|---|---|---|
| Injected client or in-process test double | Application logic, workflow branches, request construction, and deterministic errors | Fast and local, but only as representative as the interface and behaviors you model |
| Request interception | Browser or HTTP behavior that needs a known response without contacting the API | Tests a request at the interception boundary; it does not establish that the live provider currently accepts it |
| Recorded response fixtures | Tests that need realistic, provider-shaped response payloads | Requires explicit recording, review, matching, and refresh; fixtures can become stale |
Inject a client or use deterministic test doubles
Make the provider client replaceable, then inject a fake or scripted implementation in tests. OpenAI’s Agents SDK testing guide describes deterministic in-memory doubles for agent workflows, sandbox sessions, and Realtime sessions; it says these tests make no model, sandbox-provider, or Realtime API requests. The guide also supports scripted outputs, call inspection, and injected errors: OpenAI Agents SDK testing documentation.
Use those capabilities to check the parts of the request that belong to your application: the arguments sent, the order of calls, and how the returned data affects the result. If your application retries or falls back, script failures such as timeouts, rate limits, or provider errors and assert the expected behavior. These tests should not depend on variable model output.
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Intercept browser or HTTP requests
For browser tests, register the interception before the page action that triggers the request, then fulfill it with known JSON. Playwright documents this as a way to mock API requests without contacting the API: Playwright: Mock APIs. If a test needs recorded traffic, Playwright can also record and replay a HAR file.
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Replay recorded fixtures when payload shape matters
Fixtures are useful when a hand-written response would omit details your code depends on. Record responses intentionally, review what is stored, and replay those files during routine runs. The llm-mock project documentation describes matching requests to recorded fixtures and reporting missing fixtures rather than silently calling the provider. That is one project’s documented implementation, not an independent assessment of its behavior.
A missing fixture should be visible and fail the test; it should not cause an automatic live fallback. Refresh fixtures through an explicit recording step or a separate scheduled or manual provider check, then review changes before relying on them.
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Check for other network activity in an “offline” test
Replacing the model or HTTP call does not necessarily make the whole test process offline. The Agents SDK testing guide notes that tracing is a separate boundary: tracing may still export data even when provider calls are replaced. Disable tracing in tests that must make no outbound requests, and check for other telemetry, logging, or service integrations your test setup enables.
If offline behavior is a hard requirement, make it observable rather than assuming a mock covers everything. For example, configure the test environment so unexpected outbound requests fail, while keeping intentional live integration tests in their own job or command.
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Keep live integration checks separate and deliberate
Mocks verify your application’s behavior against a controlled boundary; they cannot prove that a real provider currently accepts your request format or that your integration still works end to end. Keep a small live check for that purpose, but run it separately from the routine suite so its cost and timing are intentional.
- Separate the command or CI job. Routine unit, workflow, and browser tests should use doubles, intercepted responses, or fixtures. Give live checks a distinct name and trigger.
- Control credentials and outbound access. Supply narrowly scoped credentials only to the live check, rather than allowing ordinary tests to inherit a production key. Where practical, make unexpected network calls fail in routine test jobs.
- Choose a deliberate cadence. Run the integration check manually or on a schedule that matches how often you need provider compatibility confidence. Avoid running it on every local test iteration unless that is an explicit choice.
- Make the result useful. Check the provider boundary—such as request serialization and a minimal successful response—without turning the integration check into a duplicate of the broader offline suite.
Why prompt caching is not the fix for test-suite calls
Prompt caching can reduce the input cost of eligible repeated prefixes, but the test still sends an API request. OpenAI’s prompt-caching guide says cache reuse depends on matching prefixes and compatible settings. It currently lists 1,024 tokens as the minimum cacheable prompt length for GPT-5.6 and later; thresholds differ for earlier models. Eligibility and rates are model-specific and can change.
For GPT-5.6 and later, the guide currently describes cache writes at 1.25× the ordinary input rate and subsequent reads at 0.1× for most models, or 0.05× for GPT-6.1 Sol. Its illustrative ten-request example—one write followed by nine full reads—totals 2.15× the uncached cost of one request, versus 10× for ten uncached repetitions. Those figures describe the guide’s stated model-specific assumptions, not guaranteed savings for a test suite. They do not change the fact that each test request still reaches the API.
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To see whether caching is helping, inspect cached tokens, cache-write tokens, and total cost across several representative requests. OpenAI’s cache diagnostics guidance describes diagnostics for Responses API requests on GPT-5.6 and later supported models. Do not infer a cache hit just because prompts look similar.
Quick Recap
A practical order of work
- Locate every external client and transport used by the tests, including tracing and other telemetry.
- Make the provider boundary replaceable through dependency injection or an equivalent test seam.
- Convert routine application tests to scripted outputs and assert request shape, call order, and application behavior.
- Intercept browser requests or replay reviewed fixtures where those better match the behavior under test.
- Make missing fixtures and unexpected network calls fail visibly instead of falling through to a live service.
- Disable tracing and check for any other outbound activity that remains in the offline test environment.
- Run a small live provider check separately, with deliberate credentials and cadence.
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