Query Language Manager (QLM)

QLM (Query Language Manager) is an AI-powered platform designed to simplify the process of generating and executing SQL queries using natural language. Leveraging the capabilities of Google’s Generative AI (GenAI), QLM empowers both technical and non-technical users to interact with databases effortlessly and gain actionable insights in real-time. The platform integrates seamlessly with MySQL and various APIs, providing personalized data insights across domains such as finance, healthcare, and more.

Introduction

In the realm of data management, SQL queries are fundamental for interacting with databases. However, constructing these queries often requires a solid understanding of SQL syntax, which can be a barrier for non-technical users. QLM addresses this challenge by integrating a powerful AI model that interprets plain English prompts and converts them into precise SQL commands.

Features

• AI-Powered Query Generation: Utilizes Google's generative AI model to translate natural language prompts into SQL queries.

• Database Management: Connects seamlessly to MySQL databases, executes generated queries, and displays results in real-time.

• User-Friendly Interface: Built with Streamlit, QLM provides an intuitive interface for users to input prompts, view generated SQL, and manage database interactions effortlessly.

• Logging and Monitoring: Comprehensive logging ensures transparency and allows users to track executed queries and system activities.

• Customizable Safety Settings: Includes safety settings to control content generation based on specific categories like dangerous content or hate speech.

Use Cases

QLM is designed to be adaptable across multiple industries:

• Finance: Provides financial analytics and predictions using APIs like Finitcity.
• Healthcare: Tracks health data and offers personalized insights via Google Fit.
• Education: Automates content creation and provides personalized learning recommendations using APIs like Google Calendar and News.
• Social Media: Analyzes posts and generates engagement suggestions using social media APIs.

Certainly! Here's the usage guide for the Query Language Manager (QLM) in Markdown format:

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Query Language Manager (QLM) Usage Guide

1. Installation

Clone the Repository

Clone the QLM repository from GitHub using the command:

git clone https://github.com/AyonSOMADDAR/QLM.git
cd QLM
cd Query-Language-Manager-QLM-

Install Dependencies

Navigate to the cloned repository folder and install the required Python dependencies using pip:

pip install -r requirements.txt

Set Up Environment Variables

Create a .env file in the root directory (where main.py is located). Define the following environment variables in the .env file:

GOOGLE_API_KEY=your_google_api_key

Replace your_google_api_key with your actual Google API key. This key is necessary for the generative AI model used in QLM.

2. Configuration

Database Configuration

Ensure you have a MySQL database set up where QLM will execute SQL queries. Make note of the database host, username, password, and database name. Inside the code add your username and password.

3. Running the Application

Launch QLM

Start the QLM application using Streamlit. Run the following command in the terminal:

streamlit run LLM.py

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-Developed by Team 3g "Genie"