… tests (#12511)

## background

anthropic tests were partially migrated to the fixture-based pattern -
doStream and some doGenerate tests already used
`prepareJsonFixtureResponse` / `prepareChunksFixtureResponse`, but 3
`prepareJsonResponse` helper definitions (55 total calls) still remained

## summary

- record `anthropic-text.json` and `anthropic-text.chunks.txt` fixtures
from real API (`claude-sonnet-4-5-20250929`)
- replace 23 `prepareJsonResponse({})` calls (tests that only check
request body/headers) with
`prepareJsonFixtureResponse('anthropic-text')`
- inline `server.urls` assignments for 10 main doGenerate tests that
need specific response content (reasoning, usage, citations, tool calls,
etc.)
- inline `server.urls` assignments for 8 web search tests and delete the
scoped helper
- inline `server.urls` assignments for 4 code execution tests and delete
the scoped helper
- remove the main `prepareJsonResponse` function definition and unused
`Citation`/`JSONObject` imports

## background

openai provider tests used inline `prepareJsonResponse` /
`prepareStreamResponse` helpers that constructed fake API responses.
this made tests fragile and inconsistent with the fixture-based pattern
used by other migrated providers

## summary

- record real API fixtures for all 6 openai test files (chat, responses,
completion, embedding, transcription, image)
- replace all `prepareJsonResponse` / `prepareStreamResponse` helpers
with `prepareJsonFixtureResponse` / `prepareChunksFixtureResponse` that
read from `__fixtures__/` files
- inline `server.urls` for tests that check specific response content
(finish reasons, logprobs, usage overrides, etc.)
- trim large response data per conventions (embedding vectors to 5
values, image base64 to ~100 chars, transcription words to 5)
- fix missing `.filter(line => line.trim().length > 0)` in chat
`prepareChunksFixtureResponse` to match reference pattern
- zero `prepareJsonResponse` or `prepareStreamResponse` remaining in the
openai package

## background

xAI's token reporting is inconsistent across models. most models report
`prompt_tokens`/`input_tokens` inclusive of cached tokens (like OpenAI),
but some models (e.g. `grok-4-1-fast-non-reasoning`) report them
exclusive of cached tokens, where `cached_tokens > prompt_tokens`

## summary

- detect which reporting style xAI is using based on whether
`cached_tokens <= prompt_tokens`
- when inclusive (normal): subtract cached from prompt to get noCache
(OpenAI pattern)
- when exclusive (anomalous): prompt tokens already represent noCache,
add cached for total (Anthropic pattern)
- applies to both chat completions and responses APIs
- add unit tests for the non-inclusive reporting edge case
- add responses usage test file

## verification

<details>
<summary>gateway bug case (cached > prompt)</summary>

```
before: total=4142, noCache=-186, cacheRead=4328
after:  total=8470, noCache=4142, cacheRead=4328
```

</details>

<details>
<summary>normal case (cached <= prompt)</summary>

```
raw:   input_tokens: 12, cached_tokens: 3
sdk:   noCache: 9, cacheRead: 3, total: 12
```

</details>

## checklist

- [x] tests have been added / updated (for bug fixes / features)
- [ ] documentation has been added / updated (for bug fixes / features)
- [x] a _patch_ changeset for relevant packages has been added (run
`pnpm changeset` in root)
- [x] i have reviewed this pull request (self-review)

This PR was opened by the [Changesets
release](https://github.com/changesets/action) GitHub action. When
you're ready to do a release, you can merge this and the packages will
be published to npm automatically. If you're not ready to do a release
yet, that's fine, whenever you add more changesets to main, this PR will
be updated.


# Releases
## @ai-sdk/xai@3.0.56

### Patch Changes

- 7ccb902: fix(provider/xai): handle inconsistent cached token reporting

Co-authored-by: vercel-ai-sdk[bot] <225926702+vercel-ai-sdk[bot]@users.noreply.github.com>

## background

google-vertex embedding and image model tests used inline
`prepareJsonResponse` helpers with hand-constructed mock data. this
normalizes them to the fixture-based pattern per #12270.

## summary

- record real API fixtures from Vertex AI (text-embedding-005 for
embeddings, imagen-4.0-generate-001 for images)
- trim embedding vectors to 5 values per vector, trim image base64 to
100 chars
- replace all `prepareJsonResponse` with `prepareJsonFixtureResponse`
loading from `__fixtures__/`
- convert all `toStrictEqual` assertions to `toMatchInlineSnapshot()`
- add full result snapshot tests for both embedding and image models
- add standalone response headers and response metadata tests
- no tests lost (embedding: 11 -> 13, image: 22 -> 23)

…attern (#12517)

## background

part of the ongoing effort to normalize provider tests to use real API
response fixtures instead of inline mock data (#12270)

## summary

- record real transcription fixture from deepgram nova-3 API with
language detection enabled
- replace inline `prepareJsonResponse` helper with
`prepareJsonFixtureResponse` that reads from
`__fixtures__/deepgram-transcription.json`
- use `beforeEach` with fixture for standard tests, inline `server.urls`
for edge cases (custom detected language, undefined language)
- speech model test unchanged (uses `prepareAudioResponse` for binary
audio data, not part of fixture migration scope)

… pattern (#12526)

## background

part of the test fixture migration effort (#12270) - replacing inline
`prepareJsonResponse` helpers with real API response fixtures

## summary

- record real transcription fixture from elevenlabs `scribe_v1` API
- replace inline `prepareJsonResponse` with `prepareJsonFixtureResponse`
reading from `__fixtures__/`
- organize tests into describe blocks (transcription, response headers,
response metadata, no additional formats)
- use `toMatchSnapshot()` for response assertions,
`toMatchInlineSnapshot()` for other assertions
- speech tests left as-is (binary `prepareAudioResponse` is not part of
fixture migration scope)

…pattern (#12535)

## background

fal transcription tests used an inline `prepareJsonResponse` helper that
constructed fake response data directly in the test file - this makes
tests harder to maintain and doesn't reflect real API responses

## summary

- record 2 real API response fixtures from fal wizper model (queue
submit, transcription result)
- replace `prepareJsonResponse` with `prepareJsonFixtureResponse` that
reads from fixture files
- organize tests into describe blocks (`transcription`, `response
headers`, `response metadata`)
- use `toMatchSnapshot()` for response assertions

)

## background

revai tests used an inline `prepareJsonResponse` helper that constructed
fake response data directly in the test file - this makes tests harder
to maintain and doesn't reflect real API responses

## summary

- record 3 real API response fixtures from rev.ai (job submit, job
status, transcript)
- replace `prepareJsonResponse` with `prepareJsonFixtureResponse` that
reads from fixture files
- organize tests into describe blocks (`transcription`, `response
headers`, `response metadata`)
- use `toMatchSnapshot()` for response assertions

# Add Gateway Timeout Error Handling Examples

## Background

Proper error handling for timeout scenarios is crucial for applications
using the AI Gateway. This PR improves the error handling for timeout
situations and adds examples demonstrating how these errors are handled.

## Summary

- Fixed error handling in Gateway models by making `asGatewayError`
async in both image and video model implementations
- Added three new examples demonstrating timeout error handling for:
  - Image generation (`generate-image/gateway-timeout.ts`)
  - Video generation (`generate-video/gateway-timeout.ts`) 
  - Text streaming (`stream-text/gateway-timeout.ts`)

Each example uses undici with an extremely short timeout (1ms) to
deliberately trigger timeout errors, showing how the Gateway SDK catches
and provides helpful error messages with troubleshooting guidance.

## Manual Verification

Tested each example by running them with the AI Gateway API key set.
Confirmed that they properly trigger timeout errors and display the
expected error information including the original error cause.

## Checklist

- [ ] Tests have been added / updated (for bug fixes / features)
- [ ] Documentation has been added / updated (for bug fixes / features)
- [ ] A _patch_ changeset for relevant packages has been added (for bug
fixes / features - run `pnpm changeset` in the project root)
- [ ] I have reviewed this pull request (self-review)

This PR was opened by the [Changesets
release](https://github.com/changesets/action) GitHub action. When
you're ready to do a release, you can merge this and the packages will
be published to npm automatically. If you're not ready to do a release
yet, that's fine, whenever you add more changesets to main, this PR will
be updated.


# Releases
## ai@6.0.85

### Patch Changes

-   Updated dependencies [e858654]
    -   @ai-sdk/gateway@3.0.45

## @ai-sdk/angular@2.0.86

### Patch Changes

-   ai@6.0.85

## @ai-sdk/gateway@3.0.45

### Patch Changes

- e858654: fix (provider/gateway): Fixed error handling in Gateway
models by making asGatewayError async in both image and video model
implementations.

## @ai-sdk/langchain@2.0.91

### Patch Changes

-   ai@6.0.85

## @ai-sdk/llamaindex@2.0.85

### Patch Changes

-   ai@6.0.85

## @ai-sdk/react@3.0.87

### Patch Changes

-   ai@6.0.85

## @ai-sdk/rsc@2.0.85

### Patch Changes

-   ai@6.0.85

## @ai-sdk/svelte@4.0.85

### Patch Changes

-   ai@6.0.85

## @ai-sdk/vue@3.0.85

### Patch Changes

-   ai@6.0.85

Co-authored-by: vercel-ai-sdk[bot] <225926702+vercel-ai-sdk[bot]@users.noreply.github.com>