Changes between Version 3 and Version 4 of Public/DjAi

Timestamp:

Jun 28, 2023, 5:19:00 PM (17 months ago)

Author:

Boris Horner

Comment:

—

Public/DjAi

@@ -18 +18 @@
 * The current status of a training in the editor can be immediately applied and tested. This shortens turnaround cycles and speeds up development. Realistic trainings with some examples that produce good results can be created in less than half a day.
 * The training format is abstract and is translated to the specific LLM's syntax only when it's applied. This allows trying the same training on different models, or different versions of the same model. This way, it is also easy to determine which operations can run on simpler, cheaper versions of a model and which ones require more reasoning and linguistic capabilities.
-* The AI request handling runs behind a web service. It is restricted to the functions defined by the training builders and is linked to a specific AI model such as {{{openAI GPT3.5}}} or {{{AlephAlpha luminous-extended}}}. Regular users can't change this.
 * The interface supports single-request operations, chat operations (with context management) and single-request operations with dynamically generated trainings. This allows ontology, terminology or other knowledge injection into the request or automatic attachment of examples chosen by keywords in the source.
+* The inference functionality with defined transforms (as called from the client software) can be easily integrated into your own software. Any environment able to send HTTP requests can access //dj//**AI** server by passing a local secret, the source data and the transform name. The service responds with the AI query result.
+* The AI request handling runs behind a web service. It is restricted to the functions defined by the training builders and is linked to a specific AI model such as {{{openAI GPT3.5}}} or {{{AlephAlpha luminous-extended}}}. Regular users can't change this. This way, transforms handling data to be protected can use a service like AlephAlpha with servers in Germany for such tasks, and openAI models for tasks with less sensitive data, where they perform better or well enough for less money.
 * Plugins for GPT3.5 and GPT4 and AlephAlpha are included. Other plugins will follow as required and can be added by implementing a simple software interface.
-* The inference functionality with defined transforms (as called from the client software) can be easily integrated into your own software. Any environment able to send HTTP requests can access //dj//**AI** server by passing a local secret, the source data and the transform name. The service responds with the AI query result.
 
 The client is a .net 7 applications and runs on all recent Windows versions. HTTP access is possible from any environment (supporting HTTP requests).