NLP2SQL

NLP2SQL is a project that aims to generate SQL queries from natural language text. It involves converting text input into a structured format to create a semantically correct SQL query for database execution.

🧐 Features

Here are some of the project's best features:

• Natural Language to SQL: Convert natural language text to SQL queries.
• Dynamic Database Handling: Adapt to different database schemas dynamically.
• Data Display and Visualization: Present data in an intuitive and interactive manner.
• Report Generation: Generate comprehensive reports based on SQL queries.
• Performance Optimization: Optimized for efficiency and speed.

🛠️ Installation Steps

1. Clone the Repository:

   git clone https://github.com/lohitkolluri/NLP2SQL.git
   cd NLP2SQL

2. Create and Activate a Virtual Environment:

   • On macOS/Linux:

     python3 -m venv venv
     source venv/bin/activate

   • On Windows:

     python -m venv venv
     .\venv\Scripts\activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Set Up Environment Variables:

   Create a .env file in the root directory and add the necessary environment variables such as your Azure OpenAI endpoint and API key.

   OPENAI_ENDPOINT=https://your-azure-openai-endpoint
   OPENAI_API_KEY=your-azure-openai-api-key

5. Running the App:

   streamlit run NLP2SQL.py

6. Access the App:

   Open your web browser and go to:

   http://localhost:8501
   

💻 Built With

Technologies used in the project:

• Streamlit: For building the interactive web application.
• Altair: For data visualization.
• Python: The core programming language.
• SQLite: For the database.
• Pandas: For data manipulation.
• Azure OpenAI: For generating SQL queries from natural language input.
• GPT 3.5 Turbo: Model Used to Transcribe NLT to Sematic SQL.