Simon Willison’s Weblog

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Items tagged sqlite, generativeai

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Building and testing C extensions for SQLite with ChatGPT Code Interpreter

I wrote yesterday about how I used Claude and ChatGPT Code Interpreter for simple ad-hoc side quests—in that case, for converting a shapefile to GeoJSON and merging it into a single polygon.

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Weeknotes: the Datasette Cloud API, a podcast appearance and more

Datasette Cloud now has a documented API, plus a podcast appearance, some LLM plugins work and some geospatial excitement.

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LLM now provides tools for working with embeddings

LLM is my Python library and command-line tool for working with language models. I just released LLM 0.9 with a new set of features that extend LLM to provide tools for working with embeddings.

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Enriching data with GPT3.5 and SQLite SQL functions

I shipped openai-to-sqlite 0.3 yesterday with a fun new feature: you can now use the command-line tool to enrich data in a SQLite database by running values through an OpenAI model and saving the results, all in a single SQL query.

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Running Python micro-benchmarks using the ChatGPT Code Interpreter alpha

Today I wanted to understand the performance difference between two Python implementations of a mechanism to detect changes to a SQLite database schema. I rendered the difference between the two as this chart:

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apple-notes-to-sqlite (via) With the help of ChatGPT I finally figured out just enough AppleScript to automate the export of my notes to a SQLite database. AppleScript is a notoriously read-only language, which is turns out makes it a killer app for LLM-assisted coding. # 9th March 2023, 6:04 am

Weeknotes: A bunch of things I learned this week, plus datasette-explain

The Datasette table view refactor, JSON redesign and ?_extra= continues this week, mainly in this ongoing pull request and this tracking issue.

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How to implement Q&A against your documentation with GPT3, embeddings and Datasette

If you’ve spent any time with GPT-3 or ChatGPT, you’ve likely thought about how useful it would be if you could point them at a specific, current collection of text or documentation and have it use that as part of its input for answering questions.

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