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NVIDIA NeMo Agent Toolkit Vanna

Vanna-based Text-to-SQL integration for NeMo Agent toolkit.

Overview

This package provides production-ready text-to-SQL capabilities using the Vanna framework with Databricks support.

Features

  • AI-Powered SQL Generation: Convert natural language to SQL using LLMs
  • Databricks Support: Optimized for Databricks SQL warehouses
  • Vector-Based Similarity Search: Milvus integration for few-shot learning
  • Streaming Support: Real-time progress updates
  • Query Execution: Optional database execution with formatted results
  • Highly Configurable: Customizable prompts, examples, and connections

Quick Start

Install the package:

pip install nvidia-nat-vanna

Create a workflow configuration:

functions:
  text2sql:
    _type: text2sql
    llm_name: my_llm
    embedder_name: my_embedder
    milvus_retriever: my_retriever
    database_type: databricks
    connection_url: "${CONNECTION_URL}"
    execute_sql: false

  execute_db_query:
    _type: execute_db_query
    database_type: databricks
    connection_url: "${CONNECTION_URL}"
    max_rows: 100

llms:
  my_llm:
    _type: nim
    model_name: meta/llama-3.1-70b-instruct
    api_key: "${NVIDIA_API_KEY}"

embedders:
  my_embedder:
    _type: nim
    model_name: nvidia/llama-3.2-nv-embedqa-1b-v2
    api_key: "${NVIDIA_API_KEY}"

retrievers:
  my_retriever:
    _type: milvus_retriever
    uri: "${MILVUS_URI}"
    connection_args:
      user: "developer"
      password: "${MILVUS_PASSWORD}"
      db_name: "default"
    embedding_model: my_embedder
    content_field: text
    use_async_client: true

workflow:
  _type: rewoo_agent
  tool_names: [text2sql, execute_db_query]
  llm_name: my_llm

Run the workflow:

nat run --config config.yml --input "How many customers do we have?"

Components

text2sql Function

Generates SQL queries from natural language using:

  • Few-shot learning with similar examples
  • DDL (schema) information
  • Custom documentation
  • LLM-powered query generation

execute_db_query Function

Executes SQL queries and returns formatted results:

  • Databricks SQL execution
  • Result limiting and pagination
  • Structured output format
  • SQLAlchemy Object Relational Mapper (ORM)-based connection

Use Cases

  • Business Intelligence: Enable non-technical users to query data
  • Data Exploration: Rapid prototyping and analysis
  • Conversational Analytics: Multi-turn Q&A about your data
  • SQL Assistance: Help analysts write complex queries

Documentation

Full documentation: https://docs.nvidia.com/nemo/agent-toolkit/latest/

License

Part of NVIDIA NeMo Agent toolkit. See repository for license details.

Metadata

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