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Release: datasette-enrichments-llm 0.2a0
S Simon Willison's Weblog @Simon Willison
One Sentence Summary
Release of datasette-enrichments-llm 0.2a0, introducing model management via datasette-llm and configurable model availability for data enrichment tasks.
Summary
This release note announces version 0.2a0 of the datasette-enrichments-llm plugin. The primary update is the integration with datasette-llm for centralized model configuration and management. This change allows users to explicitly define which LLMs are available for data enrichment purposes within Datasette, enhancing control over model selection and usage in data processing workflows.
Main Points
* 1. Integration with datasette-llm for unified model management.The plugin now leverages a centralized system to handle LLM configurations, ensuring a consistent way to access and manage models across the Datasette ecosystem. * 2. Granular control over model availability for enrichments.Users can now specify exactly which models should be made available for the 'enrichments' purpose, providing better governance over AI-driven data tasks.
Metadata
AI Score
82
Website simonwillison.net
Published At Today
Length 41 words (about 1 min)
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1st April 2026
Releasedatasette-enrichments-llm 0.2a0— Enrich data by prompting LLMs
> * This plugin now uses datasette-llm to configure and manage models. This means it's possible to specify which models should be made available for enrichments, using the new enrichments purpose.
S Simon Willison's Weblog @Simon Willison
One Sentence Summary
Release of datasette-enrichments-llm 0.2a0, introducing model management via datasette-llm and configurable model availability for data enrichment tasks.
Summary
This release note announces version 0.2a0 of the datasette-enrichments-llm plugin. The primary update is the integration with datasette-llm for centralized model configuration and management. This change allows users to explicitly define which LLMs are available for data enrichment purposes within Datasette, enhancing control over model selection and usage in data processing workflows.
Main Points
* 1. Integration with datasette-llm for unified model management.
The plugin now leverages a centralized system to handle LLM configurations, ensuring a consistent way to access and manage models across the Datasette ecosystem.
* 2. Granular control over model availability for enrichments.
Users can now specify exactly which models should be made available for the 'enrichments' purpose, providing better governance over AI-driven data tasks.
Key Quotes
* This plugin now uses datasette-llm to configure and manage models. * This means it's possible to specify which models should be made available for enrichments, using the new enrichments purpose.
AI Score
82
Website simonwillison.net
Published At Today
Length 41 words (about 1 min)
Tags
Datasette
LLM
Data Enrichment
Open Source
Plugin Release
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