SCHOLARSHIP RECCOMENDATION SYSTEM WITH A CHATBOT USING STREAMLIT

🎓 Scholarship Assistant System – Project Overview

🔍 Objective

The Scholarship Assistant System is a user-friendly web application built with Streamlit that helps students:

• Check eligibility for scholarships based on academic and personal criteria.
• Interact with a chatbot to get answers to common scholarship-related questions.

🧰 Technologies Used

• Python: Core programming language.
• Streamlit: For building the interactive web interface.
• Pandas: For data manipulation and analysis.
• Scikit-learn: For implementing TF-IDF and cosine similarity in the chatbot.
• CSV Files: Used to store scholarship and student data.

📁 Data Files

• scholarships.csv: Contains scholarship details including:
• Scholarship ID
• Minimum GPA
• Maximum Family Income
• Minimum Extracurricular Activities
• students.csv: (Optional) Contains student profiles (not actively used in current logic).

🧠 Features

✅ Eligibility Checker

• Inputs:
• GPA
• Annual Family Income
• Number of Extracurricular Activities
• Logic:
• Compares user input against each scholarship’s criteria.
• Returns a list of eligible scholarships.
• Output:
• Displays eligible scholarships.
• Offers downloadable eligibility report (.txt format).
• Shows sample scholarship data in a table.

💬 Chatbot

• Purpose:
• Answers frequently asked questions about scholarships.
• Method:
• Uses TF-IDF vectorization and cosine similarity to match user queries with predefined responses.
• Response Threshold:
• If similarity score > 0.3, returns best-matched answer.
• Otherwise, returns a fallback message with guidance.

🗂️ Chatbot Q&A Bank

Includes responses to questions like:

• What scholarships are available?
• How do I apply?
• What GPA is required?
• Can I get multiple scholarships?
• What documents are needed?

📊 Sidebar Features

• Navigation between:
• Eligibility Checker
• Chatbot
• Scholarship Stats:
• Total scholarships
• Minimum GPA required
• Maximum income limit

🖥️ UI Components

• Streamlit Widgets:
• number_input for GPA, income, and extracurriculars.
• button for triggering eligibility check.
• text_input for chatbot queries.
• radio for page navigation.
• expander for sample data and tips.
• download_button for eligibility report.

📦 TF-IDF Chatbot Setup

• Corpus: List of predefined questions.
• Responses: Corresponding answers.
• Vectorizer: TfidfVectorizer() from scikit-learn.
• Similarity: cosine_similarity() to find best match.

📈 Eligibility Logic

For each scholarship:

• Check if:
• GPA >= Min_GPA
• Income <= Max_Family_Income
• Extracurriculars >= Min_Extracurriculars
• If all conditions are met, add scholarship to eligible list.

🧪 Sample Output

If eligible:

🎉 You are eligible for the following scholarships:
- Scholarship ID: SCH001
- Scholarship ID: SCH005

If not eligible:

⚠️ Sorry, you are not eligible for any scholarships.

📥 Download Feature

• Generates a .txt file with eligible scholarship IDs.
• Uses io.StringIO() to buffer content.

🧩 Extensibility Ideas

• Add student login and profile tracking.
• Include scholarship descriptions and benefits.
• Enable document uploads for verification.
• Add multilingual support for broader accessibility.
• Integrate with external APIs for real-time scholarship updates.

🚀 Deployment

• Can be deployed on platforms like:
• Streamlit Cloud
• Heroku
• AWS or Azure (with minor adjustments)

🧑‍🎓 Target Users

• High school and college students seeking financial aid.
• Educational counselors and institutions.
• Parents exploring scholarship options for their children.

🎯 Benefits

• Simplifies scholarship discovery.
• Provides instant eligibility feedback.
• Offers a conversational interface for guidance.
• Reduces manual filtering of scholarship criteria.