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Thorsten Sommer 2024-12-27 13:13:04 +01:00
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GPG Key ID: 371BBA77A02C0108
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app/MindWork AI Studio/Assistants/ERI/AssistantERI.razor
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@ -201,10 +201,23 @@
Data retrieval settings
</MudText>
<MudText Typo="Typo.body1" Class="mb-1">
You can integrate additional libraries. Perhaps you want to evaluate the prompts in advance using a machine learning method or analyze them with a text
mining approach? Or maybe you want to preprocess images in the prompts? For such advanced scenarios, you can specify which libraries you want to use here.
It's best to describe which library you want to integrate for which purpose. This way, the LLM that writes the ERI server for you can try to use these
libraries effectively. This should result in less rework being necessary. If you don't know the necessary libraries, you can instead attempt to describe
the intended use. The LLM can then attempt to choose suitable libraries. However, hallucinations can occur, and fictional libraries might be selected.
</MudText>
<MudTextField T="string" @bind-Text="@this.additionalLibraries" Label="(Optional) Additional libraries" HelperText="Do you want to include additional libraries? Then name them and briefly describe what you want to achieve with them." Variant="Variant.Outlined" Margin="Margin.Normal" Lines="3" AutoGrow="@true" MaxLines="12" UserAttributes="@USER_INPUT_ATTRIBUTES" Class="mb-3"/>
<MudText Typo="Typo.h4" Class="mt-9 mb-1">
Provider selection for generation
</MudText>
<MudText Typo="Typo.body1" Class="mb-1">
The task of writing the ERI server for you is very complex. Therefore, a very powerful LLM is needed to successfully accomplish this task.
Small local models will probably not be sufficient. Instead, try using a large cloud-based or a large self-hosted model.
</MudText>
<ProviderSelection @bind-ProviderSettings="@this.providerSettings" ValidateProvider="@this.ValidatingProvider"/>