Ce référentiel contient des composants permettant d'exécuter SUSI.AI sur le bureau ou sur un haut-parleur intelligent sans tête avec le serveur SUSI.AI. Les fonctionnalités implémentées ici incluent l'utilisation du microphone pour collecter des commandes vocales, la conversion de la parole en texte (STT) à l'aide de composants tels que Deep Speech, Flite, Pocket Sphinx, IBM Watson ou autres, le contrôle du volume avec des commandes vocales et la fourniture d'une interface GTK simple. Afin d'utiliser la sortie JSON du serveur SUSI.AI (écrite en Java), nous utilisons un Wrapper Python de l'API SUSI.AI. L'objectif ultime du projet est de permettre aux utilisateurs d'installer SUSI.AI n'importe où, en dehors des ordinateurs de bureau et des haut-parleurs intelligents sur les appareils IoT, les systèmes automobiles, les machines à laver et bien plus encore.
Les fonctionnalités du projet sont fournies comme suit :
L'écosystème SUSI.AI se compose des parties suivantes :
* Web Client and Content Management System for the SUSI.AI Skills - Home of the SUSI.AI community
|_ susi.ai (React Application, User Account Management for the CMS, a client for the susi_server at https://api.susi.ai the content management system for susi skills)
* server back-end
|_ susi_server (the brain of the infrastructure, a server which computes answers from queries)
|_ susi_skill_data (the knowledge of the brain, a large collection of skills provided by the SUSI.AI community)
* android front-end
|_ susi_android (Android application which is a client for the susi_server at https://api.susi.ai)
* iOS front-end
|_ susi_iOS (iOS application which is a client for the susi_server at https://api.susi.ai)
* Smart Speaker - Software to turn a Raspberry Pi into a Personal Assistant
| Several sub-projects come together in this device
|_ susi_installer (Framework which can install all parts on a RPi and Desktops, and also is able to create SUSIbian disk images)
|_ susi_python (Python API for the susi_server at https://api.susi.ai or local instance)
|_ susi_server (The same server as on api.susi.ai, hosted locally for maximum privacy. No cloud needed)
|_ susi_skill_data (The skills as provided by susi_server on api.susi.ai; pulled from the git repository automatically)
|_ susi_linux (a state machine in python which uses susi_python, Speech-to-text and Text-to-speech functions)
|_ susi.ai (React Application, the local web front-end with User Account Management, a client for the local deployment of the susi_server, the content management system for susi skills)
susi_linux
est normalement installé via le programme d'installation SUSI. Dans ce cas, il existe des binaires pour la configuration et le démarrage et d'autres disponibles dans $HOME/SUSI.AI/bin
(sous les paramètres d'installation par défaut).
En cas d'installations manuelles, les wrappers du répertoire wrapper
doivent être configurés pour pointer vers les répertoires d'installation respectifs et l'emplacement du fichier config.json
.
La configuration se fait via le fichier config.json qui réside normalement dans $HOME/.config/SUSI.AI/config.json
.
Le script $HOME/SUSI.AI/bin/susi-config
est mieux utilisé pour interroger, définir et modifier la configuration de susi_linux
. Il existe également une interface graphique pour la configuration dans $HOME/SUSI.AI/bin/susi-linux-configure
.
Les clés et valeurs possibles sont données en exécutant $HOME/SUSI.AI/bin/susi-config keys
Quelques clés importantes et valeurs possibles :
- `stt` is the speech to text service, one of the following choices:
- `google` - use Google STT service
- `watson` - IBM/Watson STT
- `bing` - MS Bing STT
- `pocketsphinx` - PocketSphinx STT system, working offline
- `deepspeech-local` - DeepSpeech STT system, offline, WORK IN PROGRESS
- `tts` is the text to speech service, one of the following choices:
- `google` - use Google TTS
- `watson` - IBM/Watson TTS (login credential necessary)
- `flite` - flite TTS service working offline
- `hotword.engine` is the choice if you want to use snowboy detector as the hotword detection or not
- `Snowboy` to use snowboy
- `PocketSphinx` to use Pocket Sphinx
- `wakebutton` is the choice if you want to use an external wake button or not
- `enabled` to use an external wake button
- `disabled` to disable the external wake button
- `not available` for systems without dedicated wake button
Other interfaces for configuration are available for Android and iOS.
Manual configuration is possible, the allowed keys in [`config.json`](config.json) are currently
- `device`: the name of the current device
- `wakebutton`: whether a wake button is available or not
- `stt`: see above for possible settings
- `tts`: see above for possible settings
- `language': language for STT and TTS processing
- `path.base`: directory where support files are installed
- `path.sound.detection`: sound file that is played when detection starts, relative to `data_base_dir`
- `path.sound.problem`: sound file that is played on general errors, relative to `data_base_dir`
- `path.sound.error.recognition`: sound file that is played on detection errors, relative to `data_base_dir`
- `path.sound.error.timeout`: sound file that is played when timing out waiting for spoken commands
- `path.flite_speech`: flitevox speech file, relative to `data_base_dir`
- `hotword.engine`: see above for possible settings
- `hotword.model`: (if hotword.engine = Snowboy) selects the model file for the hotword
- `susi.mode`: access mode to `accounts.susi.ai`, either `anonymous` or `authenticated`
- `susi.user`: (if susi.mode = authenticated) the user name (email) to be used
- `susi.pass`: (if susi.mode = authenticated) the password to be used
- `roomname`: free form description of the room
- `watson.stt.user`, `watson.stt.pass`, `watson.tts.user`, `watson.tts.pass`: credentials for IBM/Watson server for TTS and STT
- `watson.tts.voice`: voice name selected for IBM/Watson TTS
- `bing.api`: Bing STT API key
For details concerning installation, setup, and operation on RaspberryPi, see
the documentation at [SUSI Installer](https://github.com/fossasia/susi_installer).
## Information for developers
This section is intended for developer.
### **Important:** Tests before making a new release
1. The hotword detection should have a decent accuracy
2. SUSI Linux shouldn't crash when switching from online to offline and vice versa (failing as of now)
3. SUSI Linux should be able to boot offline when no internet connection available (failing as of now)
### Roadmap
- Offline Voice Detection (if possible with satisfactory results)
### General working of SUSI
- SUSI.AI follows a finite state system for the code architecture.
- Google TTS and STT services are used as default services but if the internet fails, a switch to offline services PocketSphinx (STT) and Flite (TTS) is made automatically
### Run SUSI Linux for development purposes
If installed via the SUSI Installer, systemd unit files are installed:
- `ss-susi-linux.service` for the user bus, use as user with `systemctl --user start/enable ss-susi-linux`
- `[email protected]` for the system bus, use as `root` user to start a job for a specific user,
independent from whether the user is logged in or not: `sudo systemctl start/enable ss-susi-linux@USER`
By default, it is ran in _production_ mode, where log messages are limited to _error_ and _warning_ only.
In development, you may want to see more logs, to help debugging. You can switch it to "verbose" mode by 2 ways:
1. Run it manually
- Stop systemd service by `sudo systemctl stop ss-susi-linux`
- Use Terminal, _cd_ to `susi_linux` directory and run
python3 -m susi_linux -v
or repeat `v` to increase verbosity:
python3 -m susi_linux -vv
2. Change command run by `systemd`
- Edit the _/lib/systemd/system/ss-susi-linux.service_ and change the command in `ExecStart` parameter:
```ini
ExecStart=/usr/bin/python3 -m susi_linux -v --short-log
Recharger le démon systemd : sudo systemctl daemon-reload
Redémarrez le service : sudo systemctl restart ss-susi-linux
Vous pouvez maintenant lire le journal via journalctl
:
journalctl -u ss-susi-linux
journalctl -fu ss-susi-linux
pour être mis à jour lorsque le journal est produit en continu. L'option -v
est en fait la même que la 1ère méthode. L'option --short-log
consiste à exclure certaines informations déjà fournies par journalctl
. Pour plus d'informations sur la fonctionnalité logging
, consultez ce problème GitHub.