vanna

Very cool. Would the license allow for use with Vanna? https://github.com/vanna-ai/vanna

I’m trying to solve for this with my project using RAG and (at least based on what people say in Discord), it’s working really well for them: https://github.com/vanna-ai/vanna

This is a good idea. I think what you'd want to do is override the generate_sql function and store the question with the "related" metadata and the generated sql somewhere: https://github.com/vanna-ai/vanna/blob/main/src/vanna/base/b... We're going to be adding a generic logging function soon and fairly soon what you're talking about could just be a custom logger.

Author of the package here. That's pretty much what this package does just with optimization around what context gets sent to the LLM about the database: https://github.com/vanna-ai/vanna/blob/main/src/vanna/base/b... And then of course once you have the SQL, you can put it in an interface where you the SQL can be run automatically and then get a chart etc.

Prompts are quite straightforward. - OpenAI: https://github.com/vanna-ai/vanna/blob/a4cdf7593ac0c584f7d74... - Mistral: https://github.com/vanna-ai/vanna/blob/a4cdf7593ac0c584f7d74...

Hello HN! We’ve been working hard on Vanna, our RAG framework for SQL generation and we’ve been updating our documentation. Please have a look — we have a ton of Jupyter notebooks for any combination of desired use cases. At it’s heart, we have abstractions that help you: - “train” a RAG “model” i.e. add metadata for the retrieval augmentation system to reference when constructing the LLM prompt (yes, we know that the terms “train” and “model” are somewhat confusing and we’re open to changing those terms if you can suggest better ones) - “ask” questions, which will generate SQL, run it, produce charts, etc You can use this in: - Jupyter notebooks - Streamlit (open-source code provided) - Flask (open-source code provided) - Slack (open-source code provided) One key thing to note is that in most of the user interfaces, there’s an opportunit

Oh man, I would love to compare notes. I pivoted in the reverse direction from: https://github.com/pycob/pyvibe To https://github.com/vanna-ai/vanna

Hey there HN! We've just open-sourced Vanna – a Python package that allows you to transform questions into SQL. We've leveraged LLMs to enable you to "ask" databases what you need, bypassing the need to "write" complex SQL. Quick Overview: - "Train" using DDL statements, documentation, or known correct SQL statements. - "Ask" questions in natural language and receive SQL, tables, and charts in return. - Open Source Flexibility: Swap storage mechanisms, customize LLMs, and choose your databases. - Local or Hosted: Operate everything locally or use our hosted version for free (including complimentary LLM calls). - Use it wherever Python is applicable. We provide code examples for integration in Jupyter, Streamlit, Slack, and more. We would greatly appreciate your feedback, insights on issues, and contributions: https://github.com/vanna-ai/v

Hey HN, We are Zain and Ashish, founders of Vanna AI. We recently embarked on an experiment to see if large language models (specifically LLMs) could help in generating SQL queries for real-world datasets. We initially started this project as a web app but realized that it was most useful and had broadest applicability as a Python package since you can then incorporate it into an existing workflow (Jupyter notebook, Slackbot, etc). We've had some good success with customer datasets but we've generally heard a lot of skepticism so we decided to write a paper about the methodology we're using and how various LLMs compare. Let us know if you have any questions or requests. The underlying Python package is open source. There is a server component to store and retrieve metadata but by next week there will be a fully open-source and locally run

Vanna: A Python package to generate SQL using LLMs Package: https://github.com/vanna-ai/vanna A paper we're just finished: https://github.com/vanna-ai/vanna/blob/main/papers/ai-sql-ac...