Powering your Copilot for Data – with Artem Keydunov of Cube.dev
t on LLMs and SQL highlighting why they don’t consistently work :
- “LLMs can write SQL, but they are often prone to making up tables, making up field”
- “LLMs have some context window which limits the amount of text they can operate over”
- “The SQL it writes may be incorrect for whatever reason, or it could be correct but just return an unexpected result.
Artyom Keydunov • Powering your Copilot for Data – with Artem Keydunov of Cube.dev
Cube is an open source semantic layer which recently integrated with LangChain to solve these issues in a different way. You can use YAML, Javascript, or Python to create definitions of different metrics, measures and dimensions for your data:
Artyom Keydunov • Powering your Copilot for Data – with Artem Keydunov of Cube.dev
For example, if you ask a model to “return all active users in the last 7 days” it might hallucinate a `is_active` column, join to an `activity` table that doesn’t exist, or potentially get the wrong date (especially in leap years!).
We previously talked to Shreya Rajpal at Guardrails AI, which also supports Text2SQL enforcement. Their approach was ... See more
We previously talked to Shreya Rajpal at Guardrails AI, which also supports Text2SQL enforcement. Their approach was ... See more