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Build an AI SQL Assistant with OpenAI and Streamlit

Build an AI SQL Assistant with OpenAI and Streamlit

44mIntermediate2026-01-26

Authors

Walter Shields

Walter Shields

Tech Educator and Best-Selling Author

Course details

Learn to build powerful AI-driven SQL assistants that allow users to query databases using natural language instead of complex SQL syntax. This hands-on course combines Streamlit's rapid web development capabilities with OpenAI's advanced language models to create intelligent database interfaces. You'll master the integration of AI APIs with SQL databases while implementing essential security measures to prevent SQL injection and ensure safe query execution. The course covers everything from initial setup and database connections to advanced customization, styling, and online deployment. By the end, you'll have created a production-ready SQL assistant that can be shared with others and adapted for various business use cases, making database querying accessible to non-technical users.

Learning objectives
After completing this course, you will be able to build a complete AI-powered SQL assistant web application using Streamlit and the OpenAI API.
After completing this course, you will be able to integrate OpenAI's language models with SQL databases to generate and execute database queries through natural language prompts.
After completing this course, you will be able to implement proper error handling and SQL safety measures to prevent injection attacks in AI database applications.
After completing this course, you will be able to deploy and share interactive Streamlit applications online with custom styling and user-friendly interfaces.
After completing this course, you will be able to customize AI behavior through prompt engineering to create domain-specific database assistants.

Concepts

Introduction

  • Build AI SQL Assistant - Overview and Environment setup

Build the SQL Assistant Interface

  • Build and design the SQL assistant interface in Streamlit
  • Build interactive Streamlit forms
  • Connect Python to SQL Database - Streamlit Database Integration

Add AI-Powered SQL Generation

  • Send a prompt to the OpenAI API
  • Display SQL query results in Streamlit

Improve and Personalize the App

  • SQL Injection Prevention - Error Handling in AI Database Apps

Sharing Your AI SQL Assistant

  • Deploy the Streamlit app online

Conclusion

  • Recognizing what you've built

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