This app implements:
- Text generation providers: Free prompt, Summarize, Headline, Context write, Chat, and Reformulate (using any available large language model)
- A Translation provider (using any available language model)
- A SpeechToText provider (using Whisper)
- An image generation provider
Instead of connecting to the OpenAI API for these, you can also connect to a self-hosted LocalAI instance or to any service that implements an API similar to the OpenAI one, for example: Plusserver or MistralAI.
Negative:
- The software for training and inference of this model is proprietary, limiting running it locally or training by yourself
- The trained model is not freely available, so the model can not be run on-premises
- The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model's performance and CO2 usage.
Negative:
- The software for training and inference of this model is proprietary, limiting running it locally or training by yourself
- The trained model is not freely available, so the model can not be run on-premises
- The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model's performance and CO2 usage.
Negative:
- The software for training and inferencing of this model is proprietary, limiting running it locally or training by yourself
- The trained model is not freely available, so the model can not be ran on-premises
- The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.
Positive:
- The software for training and inferencing of this model is open source
- The trained model is freely available, and thus can run on-premise
Negative:
- The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.
Positive:
- The software for training and inferencing of this model is open source
- The trained model is freely available, and thus can be ran on-premises
- The training data is freely available, making it possible to check or correct for bias or optimise the performance and CO2 usage.
Positive:
- The software for training and inferencing of this model is open source
- The trained model is freely available, and thus can be ran on-premises
Negative:
- The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.
Positive:
- The software for training and inferencing of this model is open source
- The trained model is freely available, and thus can be ran on-premises
Negative:
- The training data is not freely available, limiting the ability of external parties to check and correct for bias or optimise the model’s performance and CO2 usage.
Learn more about the Nextcloud Ethical AI Rating in our blog.
There is a "Artificial intelligence" admin settings section where you can:
- Choose whether you use OpenAI, a LocalAI instance or another remote service
- Set a global API key (or basic auth credentials) for the Nextcloud instance
- Configure default models and quota settings
There is a "Artificial intelligence" personal settings section to let users set their personal API key or basic auth credentials. Users can also see their quota information there.