You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
For international user, for voice interaction with assist we can use wyoming-faster-whisper STT with translation capability.
When I speak in my native language I get English in response, and this text goes to the model.
next part - text to voice for international, If I send a request in English, I will receive an answer in English, which should be promptly translated and transmitted to the TTS\assist.
Could you add an option to use deepl api for translation, specifying 3 params : base url , token , target_lang. API is: curl -X POST 'https://api-free.deepl.com/v2/translate' \ --header 'Authorization: DeepL-Auth-Key [yourAuthKey]' \ --data-urlencode 'text=Hello, world!' \ --data-urlencode 'target_lang=DE' EXAMPLE RESPONSE { "translations": [ { "detected_source_language": "EN", "text": "Hallo, Welt!" } ] }
For my part, I would prepare a short guide on how to launch the assistant in any language.
I have tried installing almost all kinds of APIs in order to execute functions\tools locally but have not succeeded.
Small models cant multilingual inference.
The text was updated successfully, but these errors were encountered:
Apart from the fact that I would advise against making important and security-relevant information / functions of your smart home dependent on online services (which may not even be from your own country)..
I don't think its even a good choice to translate prompts or responses for the use with english models (in smarthome scenarios) - because theres a million different ways, different models would interpret your translation.. It would rather make your responses not usable for smart homes (thats what I experienced)
BUT - I have had very good experience with the following German models so far:
Needs a little more prompt engineering in your language than in english but generally works with a lot of integrations (thanks to methods like In Context Learning to change your Prompt for better usage with those models) - as long as they do not rely on function_calling, which many open-source models / APIs (like ollama) don't support yet..
For international user, for voice interaction with assist we can use wyoming-faster-whisper STT with translation capability.
When I speak in my native language I get English in response, and this text goes to the model.
next part - text to voice for international, If I send a request in English, I will receive an answer in English, which should be promptly translated and transmitted to the TTS\assist.
Could you add an option to use deepl api for translation, specifying 3 params : base url , token , target_lang.
API is:
curl -X POST 'https://api-free.deepl.com/v2/translate' \ --header 'Authorization: DeepL-Auth-Key [yourAuthKey]' \ --data-urlencode 'text=Hello, world!' \ --data-urlencode 'target_lang=DE' EXAMPLE RESPONSE { "translations": [ { "detected_source_language": "EN", "text": "Hallo, Welt!" } ] }
For my part, I would prepare a short guide on how to launch the assistant in any language.
I have tried installing almost all kinds of APIs in order to execute functions\tools locally but have not succeeded.
Small models cant multilingual inference.
The text was updated successfully, but these errors were encountered: