Miau Labs / Insight
Using DSPy to Evaluate and Improve Datasette Agent's SQL System Prompts
Simon Willison used the DSPy framework to evaluate and improve Datasette Agent's SQL system prompts. This project aims to refine the core production system prompts used by Datasette Agent's read-only SQL question answerer.
Simon Willison used the DSPy framework to evaluate and improve Datasette Agent's SQL system prompts. This project aims to refine the core production system prompts used by Datasette Agent's read-only SQL question answerer. Using DSPy can help improve the effectiveness and accuracy of Datasette Agent's responses.
Simon Willison used the DSPy framework to evaluate and improve Datasette Agent's SQL system prompts. This project aims to refine the core production system prompts used by Datasette Agent's read-only SQL question answerer.
- Simon Willison used DSPy to evaluate and improve Datasette Agent's SQL system prompts.
- This project leverages the DSPy framework to refine the core production system prompts used by Datasette Agent's read-only SQL question answerer.
- The methodology involves a harness where DSPy agents invoke Datasette Agent's actual tool implementations and prompts against a live in-process Datasette, and a gold-standard, auto
Miau Labs takeUsing DSPy can help improve the effectiveness and accuracy of Datasette Agent's responses.