kiran-kumar-k3 / mentor-mentee

Welcome to the Mentor-Mentee Matching App, a Streamlit-based application for managing mentorship relationships and student details.

Mentor-Mentee Matching App

Welcome to the Mentor-Mentee Matching App, a Streamlit-based application for managing mentorship relationships and student details.

Overview

This application allows mentors and students to interact through a centralized platform. It utilizes SQLite for data storage and provides functionalities such as:

• User Authentication: Secure login and signup for mentors and students.
• Student Details Management: Capture and store student information including test marks, certifications, projects, and academic issues.
• Mentor Feedback: Enable mentors to provide feedback to assigned students.
• Dynamic UI: Utilizes Streamlit's interactive components for seamless user interaction.

Features

• User Roles: Supports roles for both mentors and students.
• Database Integration: Uses SQLite to store user accounts, student data, and mentor feedback.
• Responsive Design: Includes UI styling for a visually appealing experience.

Installation

To run the application locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/KIRAN-KUMAR-K3/mentor-mentee
   cd mentor-mentee

2. Install dependencies:

   Ensure you have Python installed. Then install the required libraries:

   pip install -r requirements.txt

3. Run the application:

   Execute the following command to start the Streamlit app:

   streamlit run app.py

4. Access the app:

   Open your web browser and go to http://localhost:8501 to view the application.

Usage

• Login or Signup: Choose to login as a mentor or student, or create a new account.
• Student Details Form: Students can input their personal details, test marks, certifications, projects, and academic issues.
• Mentor Interaction: Mentors can select students, view their details, provide feedback, and manage mentorship relationships.

Screenshots

Technologies Used

• Python
• Streamlit
• SQLite
• Pandas
• hashlib (for password hashing)
• requests (for URL image fetching)
• base64 (for encoding images)

Contributing

Contributions are welcome! Please fork the repository and create a pull request for any suggested changes.

License

This project is licensed under the MIT License - see the LICENSE file for details.