diff options
Diffstat (limited to 'app/docs/backend-faster.md')
| -rw-r--r-- | app/docs/backend-faster.md | 12 |
1 files changed, 7 insertions, 5 deletions
diff --git a/app/docs/backend-faster.md b/app/docs/backend-faster.md index 37d0f23..9aa297e 100644 --- a/app/docs/backend-faster.md +++ b/app/docs/backend-faster.md @@ -2,16 +2,18 @@ `--backend faster` talks to the OpenAI-compatible server from [faster-qwen3-tts](https://github.com/andimarafioti/faster-qwen3-tts), which uses CUDA graph capture for roughly 5-10x faster inference with the same models. **It requires an NVIDIA GPU**. -The easiest way is to run `python audiobook.py` → **Configure backends… → Install Backend → faster-qwen3-tts** (or `python app/backends/faster.py path/to/clone/wavs`): the TUI pip-installs `faster-qwen3-tts[demo]` into its managed venv (`app/envs/tts`), clones the repo, transcribes the `.wav` files with whisper (faster-whisper, installed when wheels exist for your platform — otherwise you type the transcripts), and writes `voices.json` for you — all on one options screen (voices directory, language, whisper model, and what to re-transcribe on a modify run). The server port is not asked: it lives in `FASTER_API_URL` (edit it in **Settings**). You can also start the server from the hub's **Start/Stop Backend Servers** menu, or let a conversion start it automatically. +The easiest way is to run `python audiobook.py` → **Configure backends… → Install Backend → faster-qwen3-tts** (or `python app/backends/faster.py path/to/clone/wavs`): the TUI pip-installs `faster-qwen3-tts[demo]` into its own managed venv (`app/envs/faster`, separate from the app's venv and from the qwen backend's — both TTS stacks ship conflicting versions of a shared `qwen_tts` module; the faster wheel pulls its own `qwen-tts-hf` build of it automatically), clones the repo, transcribes the `.wav` files with whisper (faster-whisper, installed when wheels exist for your platform — otherwise you type the transcripts), and writes `voices.json` for you — all on one options screen (voices directory, language, whisper model, and what to re-transcribe on a modify run). The server port is not asked: it lives in `FASTER_API_URL` (edit it in **Settings**). You can also start the server from the hub's **Start/Stop Backend Servers** menu, or let a conversion start it automatically. If you prefer to install the backend yourself (in your own environment, not the managed venv), the manual steps are below. Either way the hub detects a running server by its port, so a manually-installed backend works once its server is up. To use a server on another machine, set `FASTER_REMOTE_URL` in `app/converter/config.py` to its `host:port` (default `127.0.0.1:8000`) — the hub probes it and offers a `faster-qwen3-tts [remote]` entry — or pass `--api-url` on the CLI. -Install into your environment (the same one used for qwen-tts is fine): +Install into your environment (this backend does **not** need the `qwen-tts` +pip package — the wheel pulls the compatible `qwen-tts-hf` build of the +`qwen_tts` library automatically, so keep it out of any venv that also has +upstream `qwen-tts` installed): ```bash -python -m venv audiobook -source audiobook/bin/activate -pip install -U qwen-tts +python -m venv audiobook-faster +source audiobook-faster/bin/activate pip install "faster-qwen3-tts[demo]" ``` |