Common Issues¶

Transcription crashes on Docker¶

If Whisper transcription hangs or exits unexpectedly in Docker, your CPU may lack AVX2 support. Switch to the legacy-cpu image tag. See Transcription → legacy-cpu.

Titles are inconsistent after transcription¶

Transcription models can vary wildly on capitalization, number formatting, and punctuation. For the most part that's just the nature of the beast, but there are a few things you can do:

1. Use an English-only¹ model for English audio, or a multilingual² model for other audio.
2. For non-English audio with Whisper, ensure you've selected a language (not Auto).
3. Step up to a larger Whisper variant (tiny → small → turbo), or switch to Parakeet.
4. Enable Bias Words and add book-specific names and terms.
5. Run AI Cleanup as a post-processing step and let a machine do the work for you.

xHE-AAC books fail¶

These books are not currently supported in Achew. See Supported Formats.

First launch takes forever¶

Achew is downloading and installing Python dependencies and building the project. This process may take several minutes, but subsequent launches will be much faster.

Uploading an e-book Reference fails¶

Reference uploads are split into 512 KB chunks, which is usually small enough to fit within the default body size limit of most reverse proxies. If an upload still fails while small .txt, .json, .cue, and .csv files work, your proxy is likely capping request bodies below that and rejecting the chunks with the error message "The file was rejected as too large before it reached Achew".

To confirm, connect to Achew directly over your local network (http://IP:PORT) and retry the same upload. If it succeeds there, raise the body-size limit on your proxy — see Reverse Proxy → Troubleshooting.

Related¶

• Performance Tuning
• Logs and Support