susi_linux
1.0.0
Dieses Repository enthält Komponenten zum Ausführen von SUSI.AI auf dem Desktop oder einem Headless Smart Speaker zusammen mit dem SUSI.AI-Server. Zu den hier implementierten Funktionalitäten gehören die Verwendung des Mikrofons zum Sammeln von Sprachbefehlen, die Umwandlung von Sprache in Text (STT) mithilfe von Komponenten wie Deep Speech, Flite, Pocket Sphinx, IBM Watson oder anderen, die Steuerung der Lautstärke mit Sprachbefehlen und die Bereitstellung einer einfachen GTK-Schnittstelle. Um die JSON-Ausgabe des SUSI.AI-Servers (in Java geschrieben) zu verwenden, verwenden wir einen SUSI.AI-API-Python-Wrapper. Das ultimative Ziel des Projekts besteht darin, Benutzern die Installation von SUSI.AI überall zu ermöglichen, abgesehen von Desktops und intelligenten Lautsprechern auf IoT-Geräten, Autosystemen, Waschmaschinen und mehr.
Die Funktionalitäten des Projekts werden wie folgt bereitgestellt:
Das SUSI.AI-Ökosystem besteht aus folgenden Teilen:
* 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 wird normalerweise über den SUSI Installer installiert. In diesem Fall stehen Binärdateien zum Konfigurieren und Starten sowie weitere in $HOME/SUSI.AI/bin (unter den Standardinstallationseinstellungen) zur Verfügung.
Bei manuellen Installationen müssen die Wrapper im wrapper -Verzeichnis so konfiguriert werden, dass sie auf die entsprechenden Installationsverzeichnisse und den Speicherort der Datei config.json verweisen.
Die Konfiguration erfolgt über die Datei config.json, die sich normalerweise in $HOME/.config/SUSI.AI/config.json befindet.
Das Skript $HOME/SUSI.AI/bin/susi-config wird am besten zum Abfragen, Festlegen und Ändern der Konfiguration von susi_linux verwendet. Es gibt auch eine GUI-Schnittstelle zur Konfiguration in $HOME/SUSI.AI/bin/susi-linux-configure .
Die möglichen Schlüssel und Werte werden durch Ausführen von $HOME/SUSI.AI/bin/susi-config keys angegeben
Einige wichtige Schlüssel und mögliche Werte:
- `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
Systemd-Daemon neu laden: sudo systemctl daemon-reload
Starten Sie den Dienst neu: sudo systemctl restart ss-susi-linux
Jetzt können Sie das Protokoll über journalctl lesen:
journalctl -u ss-susi-linuxjournalctl -fu ss-susi-linux um aktualisiert zu werden, wenn das Protokoll kontinuierlich erstellt wird. Die Option -v ist eigentlich dieselbe wie die erste Methode. Die Option --short-log dient dazu, einige Informationen auszuschließen, die bereits von journalctl bereitgestellt werden. Weitere Informationen zur logging finden Sie in diesem GitHub-Problem.
