Source URL: https://simonwillison.net/2024/Dec/5/datasette-enrichments-llm/#atom-everything
Source: Simon Willison’s Weblog
Title: datasette-enrichments-llm
Feedly Summary: datasette-enrichments-llm
Today’s new alpha release is datasette-enrichments-llm, a plugin for Datasette 1.0a+ that provides an enrichment that lets you run prompts against data from one or more column and store the result in another column.
So far it’s a light re-implementation of the existing datasette-enrichments-gpt plugin, now using the new llm.get_async_models() method to allow users to select any async-enabled model that has been registered by a plugin – so currently any of the models from OpenAI, Anthropic, Gemini or Mistral via their respective plugins.
Still plenty to do on this one. Next step is to integrate it with datasette-llm-usage and use it to drive a design-complete stable version of that.
Tags: llm, plugins, ai, llms, enrichments, releases, datasette, generative-ai, projects
AI Summary and Description: Yes
Summary: The text introduces a new alpha release of the “datasette-enrichments-llm” plugin for Datasette, which enables users to run LLM-based prompts against data and store results within the same dataset. It signifies the integration of various LLM models and highlights potential future enhancements, which are pivotal for professionals in AI security and data management.
Detailed Description: The release of the “datasette-enrichments-llm” plugin brings several noteworthy advancements, particularly relevant in the fields of AI and cloud computing. This plugin extends the capabilities of the Datasette platform, allowing for enhanced data interaction through LLM functionalities.
– **Plugin Overview**:
– The “datasette-enrichments-llm” serves as an enrichment tool within Datasette 1.0a+, utilizing LLM technology.
– It facilitates the execution of prompts against data from specific columns, with results being saved into a designated output column.
– **Integration with LLMs**:
– It is a re-implementation of the previous “datasette-enrichments-gpt”, now utilizing the llm.get_async_models() method.
– Users can select from any async-enabled LLMs registered through various plugins. Currently, this includes models from reputable AI developers such as OpenAI, Anthropic, Gemini, and Mistral.
– **Future Development**:
– The plugin’s future steps include integration with “datasette-llm-usage” for driving extensive improvements and developing a stable version.
– **Practical Implications**:
– This innovation enhances data management processes by allowing dynamic interactions with data using AI-driven prompts, which can improve data-driven decision-making.
– Professionals in AI, data analytics, and cloud computing may find this development particularly relevant for integrating advanced AI capabilities into their data workflows and can leverage these tools for enhanced security and compliance considerations.
This plugin’s development represents a significant step forward in merging AI with data management, facilitating innovative use cases across sectors, including information security and compliance.