QuerySense: Natural Language to SQL Converter & Database Query Tool

End-to-end LLM application enables seamless conversion of natural language queries into SQL (Structured Query Language) queries, along with querying an SQLite database. Leveraging the Gemini-pro API for language model capabilities, it offers a user-friendly interface for interacting with databases using plain English queries.

Features:

• Natural Language Interface: Easily input queries in everyday language and let the application handle translation into SQL.
• End-To-End Solution: From inputting text queries to fetching results from the database, this app provides a comprehensive solution.
• Database Compatibility: Compatible with SQLite databases, ensuring easy integration and demonstration.
• User-Friendly Interface: Intuitive design for smooth navigation and interaction.
• Fast and Efficient: Utilizes efficient algorithms for quick conversion and retrieval of results.

How to Use:

1. Run the Application: Execute the following command in your terminal to run the application locally:

   streamlit run app.py

2. Input Text Query: Enter your query in natural language format into the provided text input field.

3. Translate: Click on the 'Translate' button to convert your text query into SQL.

4. Execute Query: Once the translation is complete, execute the SQL query to retrieve results from the connected SQLite database.

5. View Results: The results will be displayed within the application interface for easy access.

Technologies Used:

• Python: Backend server environment and application logic.
• Streamlit: Web application framework for building interactive web applications.
• Gemini-pro API: Leveraged for language model capabilities.
• SQLite: SQL database for demonstration purposes.

Installation:

To install and run the application locally, follow these steps:

1. Clone this repository to your local machine.

   git clone https://github.com/pareekshitreddy/QuerySense-Natural-Language-to-SQL-Converter-Database-Query-Tool

2. Install dependencies.

   pip install -r requirements.txt

3. Start the application.

   streamlit run app.py

Future Improvements:

• Enhanced Language Support: Incorporate support for multiple languages for broader user accessibility.
• Advanced Query Optimization: Implement optimizations for complex queries to improve efficiency.
• User Authentication: Introduce user authentication for secure access to databases.
• Integration with External APIs: Allow integration with external APIs for data enrichment and expansion of query capabilities.