diff options
Diffstat (limited to 'app/docs')
| -rw-r--r-- | app/docs/backend-audiocpp.md | 2 | ||||
| -rw-r--r-- | app/docs/backend-faster.md | 2 | ||||
| -rw-r--r-- | app/docs/backend-qwen.md | 2 |
3 files changed, 3 insertions, 3 deletions
diff --git a/app/docs/backend-audiocpp.md b/app/docs/backend-audiocpp.md index 5ce7f49..db35c81 100644 --- a/app/docs/backend-audiocpp.md +++ b/app/docs/backend-audiocpp.md @@ -2,7 +2,7 @@ `--backend audiocpp` talks to `audiocpp_server` from [audio.cpp](https://github.com/0xShug0/audio.cpp), which hosts numerous TTS model families. -The easiest way is the TUI: run `python audiobook.py`, choose **Set up a backend… → audio.cpp**, and it clones `audio.cpp` into `app/audio.cpp` (or reuses an existing checkout), builds `audiocpp_server`, lets you pick model families/packages from an expandable checkbox tree (reading the checkout's `model_specs/`), transcribes `.wav` voices with `whisper`, writes `server.json` into the checkout, syncs `app/converter/config.py`, and prints the launch command (the hub can also start the server for you via the **Start/Stop Backend Servers** menu or automatically when converting). Run it directly with `python app/backends/audiocpp.py` (flags like `--wavs`, `--families`, `--build-backend`, `--clone` skip the corresponding screens for scripting). The TUI runs in the managed `app/envs/tts` venv, which includes `whisper` via `requirements.txt`; for a manual setup, make sure `whisper` (or `faster_whisper`) is installed in the environment you run the wizard from. The Qwen3-TTS model tree also offers hosting the VoiceDesign package as a `vdes` entry. +The easiest way is the TUI: run `python audiobook.py`, choose **Configure backends… → Install Backend → audio.cpp**, and it clones `audio.cpp` into `app/audio.cpp` (or reuses an existing checkout), builds `audiocpp_server`, lets you pick model families/packages from an expandable checkbox tree (reading the checkout's `model_specs/`), transcribes `.wav` voices with `whisper`, writes `server.json` into the checkout, syncs `app/converter/config.py`, and prints the launch command (the hub can also start the server for you via the **Start/Stop Backend Servers** menu or automatically when converting). Run it directly with `python app/backends/audiocpp.py` (flags like `--wavs`, `--families`, `--build-backend`, `--clone` skip the corresponding screens for scripting). The TUI runs in the managed `app/envs/tts` venv, which includes `whisper` via `requirements.txt`; for a manual setup, make sure `whisper` (or `faster_whisper`) is installed in the environment you run the wizard from. The Qwen3-TTS model tree also offers hosting the VoiceDesign package as a `vdes` entry. 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. diff --git a/app/docs/backend-faster.md b/app/docs/backend-faster.md index d4b5b40..3036ca7 100644 --- a/app/docs/backend-faster.md +++ b/app/docs/backend-faster.md @@ -2,7 +2,7 @@ `--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` → **Set up a 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`, and writes `voices.json` for you. 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 managed venv (`app/envs/tts`), clones the repo, transcribes the `.wav` files with `whisper`, and writes `voices.json` for you. 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. diff --git a/app/docs/backend-qwen.md b/app/docs/backend-qwen.md index 0cc2e5a..800c7ae 100644 --- a/app/docs/backend-qwen.md +++ b/app/docs/backend-qwen.md @@ -1,6 +1,6 @@ # Backend Option 2: Qwen3-TTS -The easiest way is to run `python audiobook.py` → **Set up a backend… → qwen-tts** (or `python app/backends/qwen.py`): the TUI pip-installs `qwen-tts` into its managed venv (`app/envs/tts`), configures the two ports and the built-in speaker in `app/converter/config.py`, and prints the launch commands. 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 → qwen-tts** (or `python app/backends/qwen.py`): the TUI pip-installs `qwen-tts` into its managed venv (`app/envs/tts`), configures the two ports and the built-in speaker in `app/converter/config.py`, and prints the launch commands. 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 demo servers on another machine, set `QWEN_REMOTE_URL`/`CLONE_REMOTE_URL` in `app/converter/config.py` to their `host:port` (defaults `127.0.0.1:7860`/`:7861`) — the hub probes each and offers the matching `qwen-tts [remote]` mode — or pass `--api-url` on the CLI. |