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Vanna AI Build SQL AI Chatbots To Talk To Database! (Opensource)

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Vanna AI Build SQL AI Chatbots To Talk To Database! (Opensource)

AI Summary

Savannah AI Overview

  • Fully open-source app for chatting with SQL databases.
  • Unlimited access and highly accurate text-to-SQL generation using advanced models.

Features

  1. RAG Framework:
    • Handles complex text-to-SQL tasks.
    • Allows for training custom RAG models.
  2. User Interfaces:
    • Accessible via Jupyter Notebooks, Google Colab, Streamlit, Flask, and Slack.
  3. Database Support:
    • Supports various databases and models (OpenAI, Enthropic, Google Gemini).

Getting Started

  • Suggested to use the Quick Start template.
  • Can be set up locally or on Google Colab.

Setup Steps

  1. On Google Colab:
    • Save a copy of the notebook to your Google Drive.
    • Change runtime to best available hardware.
    • Install dependencies for Postgres.
    • Paste and configure your API key.
    • Configure database connection settings (host, name, user, password, port).
    • Train the RAG model once with your data.
    • Query the database by asking natural language questions.
  2. Local Setup:
    • Clone the repository using git clone <repository_link>.
    • Create and activate a Python virtual environment.
    • Install requirements and configure settings in the relevant files.
    • Run the Streamlit app using streamlit run app.py command.

Conclusion

  • Savannah AI provides a user-friendly interface for database interaction and is a powerful tool for data analysis. It’s an open-source solution ideal for users looking to engage with their databases effectively without limitations.

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