Local STT Workflow

Use this skill to debug the full transcription path, not just the model.

Default assumption: the local STT server lives at http://127.0.0.1:8000/v1.

Current local model-path fallback worth remembering: if the server did not pull a model by name, it may be loading directly from a local path such as ./models/Qwen3-ASR-0.6B-bf16.

When exact route shape matters, the local OpenAPI document is available at:

• http://localhost:8000/openapi.json

Use this OpenAPI doc as a schema/reference source to compare this local mlx-audio server against OpenAI’s API. Do not treat it as a health check.

Workflow

1. Verify the server before blaming OpenClaw

Check the basics first:

curl http://127.0.0.1:8000/health
curl http://127.0.0.1:8000/v1/models

Confirm that the intended STT model exists, usually qwen3-asr.

If the model does not appear by pulled registry name, do not assume STT is broken — this server may be running a local-path model such as ./models/Qwen3-ASR-0.6B-bf16.

If the server is task-gated, ensure STT is enabled:

MLX_AUDIO_SERVER_TASKS=stt uv run python server.py

If the model is missing, register it before testing clients — but first check whether the server is intentionally loading from a local path and verify the exact accepted model IDs through /v1/models or http://localhost:8000/openapi.json.

2. Prove the raw STT endpoint works

Always isolate the server from the client stack.

Minimal direct transcription test:

curl -X POST http://127.0.0.1:8000/v1/audio/transcriptions \
  -F [email protected] \
  -F model=qwen3-asr \
  -F response_format=json

Useful richer test:

curl -X POST http://127.0.0.1:8000/v1/audio/transcriptions \
  -F [email protected] \
  -F model=qwen3-asr \
  -F response_format=verbose_json \
  -F 'timestamp_granularities[]=segment' \
  -F 'timestamp_granularities[]=word'

If direct curl works but OpenClaw does not, the bug is probably in the message ingestion or routing layer, not the STT backend.

3. Distinguish server failure from routing failure

Use this rule hard:

• Direct curl fails → fix the local STT server first
• Direct curl works, but OpenClaw shows no transcript → inspect OpenClaw audio pipeline / attachment routing
• OpenClaw sends requests, but fields are wrong → inspect request shape compatibility

This distinction saves a shitload of time.

4. Check the request shape

This server is designed around OpenAI-style multipart form upload.

Expected core fields for /v1/audio/transcriptions from the current local OpenAPI schema:

• required: file, model
• optional: language, verbose, max_tokens, chunk_duration, frame_threshold, stream, context, prefill_step_size, text

This means the local server is not exposing the same form shape as OpenAI Whisper-style docs. Do not blindly assume response_format, prompt, or timestamp_granularities[] exist just because OpenAI supports them.

If a client is suspected of sending the wrong shape, inspect traffic with a temporary dump proxy or server logs.

5. Use the reference doc when exact fields matter

Read references/stt-api.md when you need exact behavior for:

• response_format=json|text|verbose_json|srt|vtt
• stream=true SSE events
• timestamp_granularities[]
• include[]
• translation endpoint semantics
• error envelope shape
• current compatibility limits

Do not guess field support from generic OpenAI docs when this local server may intentionally differ.

Current notable mismatch: the local schema exposes context and text, plus chunking/prefill controls like chunk_duration, frame_threshold, and prefill_step_size, which are not the usual OpenAI STT field set.

6. OpenClaw-specific debugging pattern

When OpenClaw STT appears broken:

1. Confirm tools.media.audio is configured, not messages.stt
2. Confirm base URL points at http://127.0.0.1:8000/v1
3. Confirm the chosen model exists in /v1/models
4. Send the exact inbound audio file directly to /v1/audio/transcriptions
5. Inspect gateway logs for any sign of transcription dispatch
6. If there is no /audio/transcriptions request at all, the problem is upstream of STT

If OpenClaw never hits the server, stop tweaking model params. That would be cargo-cult debugging.

7. Preferred test ladder

Use this order:

1. GET /health
2. GET /v1/models
3. direct curl transcription with the same audio file
4. compare request fields against http://localhost:8000/openapi.json
5. OpenAI client compatibility test
6. OpenClaw integration test
7. dump-proxy / log inspection only if still ambiguous

8. Common conclusions

Niche input container bug

Typical signs:

• direct upload of a less-common container like .m4a returns 500
• server logs mention unsupported format handling during temp write or normalization
• converting the same source audio to mp3 or wav makes transcription succeed immediately

Conclusion: treat this as an input-container compatibility bug, not an ASR-quality failure. For now, transcode niche formats to mp3 or wav before testing recognition quality.

Server good, client bad

Typical signs:

• manual curl returns { "text": ... }
• OpenClaw logs show no transcription request
• changing model/language does nothing

Conclusion: fix routing, not inference.

Multipart mismatch

Typical signs:

• server is up
• model exists
• client gets 400 errors
• direct curl works but app client does not

Conclusion: compare multipart field names and values.

Feature mismatch

Typical signs:

• client expects diarization, logprobs, or richer streaming fields
• local server only implements a smaller compatible subset

Conclusion: align expectations with references/stt-api.md.

Resources

references/

• references/stt-api.md — exact local API behavior, schema, response formats, SSE events, limits, and compatibility notes