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Vanna
Retrieval-augmented text-to-SQL: train on your schema and docs, then ask questions in English and get accurate, runnable SQL.
Vanna
Vanna is a Python framework for accurate text-to-SQL over your own database. You "train" it on your DDL, documentation, and example queries; it stores those in a vector store and uses RAG so an LLM generates SQL grounded in your actual schema. Ask a question in plain English and Vanna returns runnable SQL, executes it, and can render the result as a table or chart.
Key features
- RAG-based text-to-SQL that improves as you add training data
- Model-agnostic (OpenAI, Anthropic, and others) and DB-agnostic (Postgres, Snowflake, BigQuery, MySQL, SQLite, and more)
- Pluggable vector stores (ChromaDB, Qdrant, and others)
- Runs from a notebook, Streamlit/Flask app, or embedded in your own agent
- Self-hostable — your schema and data stay in your environment
Well suited to analytics copilots and agent tools that need reliable SQL grounded in a specific warehouse rather than generic guesses.
Curated mirror of the open-source Vanna (MIT). Get it from the source.