README.md

metadata

title: Chat With Database
emoji: 😻
colorFrom: red
colorTo: purple
sdk: streamlit
sdk_version: 1.41.0
app_file: app.py
pinned: false
license: mit

🚀 Chat with Database 🚀

Overview

"Chat with Database" is an innovative tool that bridges the gap between natural language and SQL. It allows users to query databases simply by typing in everyday language, with the system translating it into SQL queries and displaying the results. This project empowers non-technical users to access and manipulate data with ease, making data insights accessible to everyone.

Features

• Natural Language Querying: Users can type queries in plain language, and the tool translates them into SQL commands.
• Intent Understanding: The system interprets the user’s intent, converting it into the right SQL syntax.
• Data Retrieval & Display: Retrieves data from the database and presents it in an easy-to-read format.
• User-Friendly: Makes database interaction accessible to users with minimal technical skills.

Why This Matters

"Chat with Database" saves time and unlocks new insights by making data retrieval as simple as sending a text. No SQL knowledge is needed, making it ideal for analysts, business users, and teams seeking data-driven decisions.

Installation

1. Clone the repository:

   git clone https://github.com/username/chat-with-database.git
   

2. Navigate into the project directory:

   cd chat-with-database
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

4. Configure Database Credentials and API Key:

   • Open config.py.
   • Add your database credentials and Gemini API key in the format below:

   # config.py
   db_configuration = {
       "USER": "your_database_user",
       "PASSWORD": "your_database_password",
       "PORT": "your_database_port",
       "DB": "your_database_name",
       "HOST": "your_database_host"
   }
   
   API_KEY = "your_gemini_api_key"
   

Usage

1. Start the application:

   streamlit run app.py
   

2. Type in your data queries in natural language, and the system will automatically generate and execute SQL queries, returning results in a user-friendly format.

Contributing

Contributions are welcome! Feel free to fork the repository and submit a pull request with your improvements.

License

This project is licensed under the MIT License.

👉 Check it out on GitHub: Chat with Database