# Whisper Hugging Face Inference API bug

**URL:** <https://discuss.huggingface.co/t/whisper-hugging-face-inference-api-bug/173122>\
**Category:** Models\
**Created:** [February 5, 2026, 9:34pm UTC](https://discuss.huggingface.co/t/whisper-hugging-face-inference-api-bug/173122 "2026-02-05T21:34:57Z")\
**Posts on this page:** 1\
**Showing post:** 4

<div class="post-metadata">

**Author:** ![John6666](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/john6666/32/27664_2.png) [@John6666](https://discuss.huggingface.co/u/John6666)\
**Post date:** [February 10, 2026, 2:38am UTC](https://discuss.huggingface.co/t/whisper-hugging-face-inference-api-bug/173122/4 "2026-02-10T02:38:22Z")

</div>

Oh… There are discrepancies in the document’s claims…😱

* * *

## What the `File name too long: 'AAAAGGZ0eXBtcDQy...'` error means

That string (`AAAAGGZ0eXBtcDQy...`) is the **base64** of your `.m4a` file header (MP4 container). The server is **not decoding it as base64 audio**. Instead, it is treating the `inputs` string as a **file path** and trying to open it as a filename; because it’s thousands of characters long, the OS raises “file name too long”.

This is a known failure mode for ASR requests where a base64 string is accidentally interpreted as a path. ([Hugging Face Forums](https://discuss.huggingface.co/t/automatic-speech-recognition-endpoint-not-working/29331 "Automatic Speech Recognition endpoint not working - Beginners - Hugging Face Forums"))

So: your audio length (15 seconds) is not the issue. The request is being interpreted incorrectly on the server side.

* * *

## Why this happens on this endpoint

### 1) The ASR schema says `inputs` is a base64 string (but some backends still treat strings as paths)

Hugging Face’s Inference Providers ASR documentation states:

- `inputs`: base64-encoded audio string
- or **raw bytes** if you don’t send `parameters` ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))

However, some ASR serving wrappers (and older endpoint implementations) handle a string `inputs` as “path/URL to an audio file” first, and only decode bytes in other branches. When that happens, base64 gets misread as a path → “file name too long”. ([Hugging Face Forums](https://discuss.huggingface.co/t/automatic-speech-recognition-endpoint-not-working/29331 "Automatic Speech Recognition endpoint not working - Beginners - Hugging Face Forums"))

### 2) `.m4a` decoding and content-type handling can be brittle

For binary-audio tasks, HF has historically relied on “content-type guessing” or backend-specific decoding paths; inconsistencies between serverless inference and other deployments are documented as a practical pitfall. ([Hugging Face](https://huggingface.co/docs/huggingface_hub/en/package_reference/inference_client "Inference"))

* * *

## Fixes (choose based on whether you must send parameters)

### Fix A — Most reliable: send **raw audio bytes** (no JSON, no parameters)

Per the ASR docs, if you omit `parameters`, you can send raw bytes directly. ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))

**Dart (raw bytes)**

```dart
final url = Uri.parse(
  'https://router.huggingface.co/hf-inference/models/openai/whisper-large-v3-turbo',
);

final req = http.Request('POST', url)
  ..headers['Authorization'] = 'Bearer $_hfToken'
  ..headers['Accept'] = 'application/json'
  // For .m4a in an MP4 container, audio/mp4 is generally safer than audio/m4a.
  ..headers['Content-Type'] = 'audio/mp4'
  ..bodyBytes = audioBytes;

final streamed = await req.send();
final body = await streamed.stream.bytesToString();

if (streamed.statusCode != 200) {
  throw Exception('HTTP ${streamed.statusCode}: $body');
}

```

**Why this works:** the server receives bytes and can’t misinterpret them as a filename. ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))

**Tradeoff:** you can’t pass `generation_parameters` in this “raw bytes” mode (the docs only describe raw bytes when no `parameters` are provided). ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))

* * *

### Fix B — If you need `generation_parameters`: pass a **URL** as `inputs` (JSON)

If your backend is treating string `inputs` as a path, then **use that intentionally** : provide an HTTPS URL to the audio file (ideally a short-lived signed URL), and keep your JSON parameters.

This aligns with HF’s client documentation: ASR inputs can be raw bytes, a local file, or a URL. ([Hugging Face](https://huggingface.co/docs/huggingface_hub/en/package_reference/inference_client "Inference"))

**JSON body**

```json
{
  "inputs": "https://<signed-url>/audio.m4a",
  "parameters": {
    "generation_parameters": {
      "do_sample": false,
      "temperature": 0,
      "top_p": 1,
      "num_beams": 1,
      "max_new_tokens": 448
    }
  }
}

```

**Dart (URL input + parameters)**

```dart
final payload = jsonEncode({
  "inputs": signedAudioUrl, // https://...
  "parameters": {
    "generation_parameters": {
      "do_sample": false,
      "temperature": 0,
      "top_p": 1,
      "num_beams": 1,
      "max_new_tokens": 448,
    }
  }
});

final req = http.Request('POST', url)
  ..headers['Authorization'] = 'Bearer $_hfToken'
  ..headers['Content-Type'] = 'application/json'
  ..headers['Accept'] = 'application/json'
  ..body = payload;

```

**Why this works:** it avoids base64 entirely, and it matches the “string interpreted as path/URL” behavior that is causing your error. ([Hugging Face Forums](https://discuss.huggingface.co/t/automatic-speech-recognition-endpoint-not-working/29331 "Automatic Speech Recognition endpoint not working - Beginners - Hugging Face Forums"))

* * *

### Fix C — If you need to force “transcribe” vs “translate” reliably: use a deployment that exposes Whisper’s task/language controls

Whisper supports explicit generation controls:

- `task`: `"transcribe"` or `"translate"`
- `language`: tokens like `"en"` / `"english"` ([Hugging Face](https://huggingface.co/docs/transformers/en/model_doc/whisper "Whisper"))

But the serverless ASR interface you’re calling is a generic ASR wrapper; even when `generation_parameters` is supported, Whisper-specific `task/language` may not be exposed the way Transformers exposes them. ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))

If you must **guarantee** “never translate, always transcribe (and optionally force English)”, the robust approach is to run Whisper behind an endpoint where you control the inference code (so you can set `task="transcribe"` and `language="english"` explicitly). ([Hugging Face](https://huggingface.co/docs/transformers/en/model_doc/whisper "Whisper"))

* * *

## Practical stability tips (to reduce “random languages”)

Even after you fix the request shape, “random language” output is often caused by audio decoding / language-ID instability. The highest-impact change is:

- Convert to **WAV PCM, mono, 16 kHz** before sending (then use `Content-Type: audio/wav`).
- If you keep `.m4a`, use `audio/mp4` rather than `audio/m4a` (some stacks handle it more consistently).
- Make decoding deterministic (`temperature: 0`, `do_sample: false`) — but that requires Fix B (URL input) or an endpoint that accepts parameters with bytes. ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))

* * *

## Recommendation for your exact situation

1. First, switch to **Fix A (raw bytes)** and confirm transcription works consistently (this isolates request-format issues). ([Hugging Face](https://huggingface.co/docs/inference-providers/en/tasks/automatic-speech-recognition "Automatic Speech Recognition"))
2. If you need deterministic decoding knobs, move to **Fix B (URL input)** and keep `generation_parameters`. ([Hugging Face](https://huggingface.co/docs/huggingface_hub/en/package_reference/inference_client "Inference"))
3. If you need a hard guarantee on transcribe vs translate, use a setup that exposes Whisper’s `task/language` controls directly. ([Hugging Face](https://huggingface.co/docs/transformers/en/model_doc/whisper "Whisper"))

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_[View the full topic](https://discuss.huggingface.co/t/whisper-hugging-face-inference-api-bug/173122)._