Update README.md

README.md

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-title: AIHelpStudent
-emoji: 🏢
-colorFrom: purple
-colorTo: yellow
-sdk: gradio
-sdk_version: 6.5.1
-app_file: app.py
-pinned: false
-license: mit
-short_description: AIHelpStudent
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-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+🤖 MAXA – Max Assistance
+AI Integrated Academic & Mental Health Support System for High School Students
+
+Team: B-max
+Members: Ngô Gia Duy Anh – Nguyễn Đức Lâm – Lê Văn Duy Hiếu
+Competition: AI Young Guru
+
+📌 1. Overview
+
+Maxa (Max Assistance) is an AI-powered web application designed to support high school students (15–17 years old) in managing:
+
+📊 Academic stress
+
+🔎 Misinformation related to exams and university admissions
+
+🎯 Personalized study planning
+
+The system integrates Natural Language Processing (NLP), Machine Learning, Generative AI (GenAI), and Retrieval-Augmented Generation (RAG) into one unified platform.
+
+Unlike traditional single-function tools, Maxa provides a holistic support model that combines psychological analysis, academic personalization, and information verification.
+
+🎯 2. Problem Statement
+
+According to the World Health Organization, adolescent mental health is a growing global concern.
+
+High school students face increasing stress due to:
+
+Academic pressure and university entrance exams
+
+Family and societal expectations
+
+Social media comparison (TikTok, Facebook, Instagram)
+
+Exposure to unverified or misleading educational information
+
+At the same time, the education system often applies standardized methods to students who:
+
+Have different learning capacities
+
+Have diverse career orientations
+
+Have different stress tolerance levels
+
+There is currently no integrated system that simultaneously:
+
+Detects stress early
+
+Verifies educational information
+
+Personalizes learning pathways
+
+Maxa addresses this gap.
+
+🧠 3. Core Features
+1️⃣ Stress Level Prediction
+
+Emotion analysis from student journal input
+
+Sentiment classification
+
+Stress scoring and categorization:
+
+🟢 Low
+
+🟡 Medium
+
+🟠 High
+
+🔴 Critical Risk
+
+The system can provide early warnings when stress reaches high levels.
+
+2️⃣ Fake Information Detection (RAG-based)
+
+Using Retrieval-Augmented Generation (RAG), the system:
+
+Retrieves information from trusted educational sources
+
+Compares user input with verified data
+
+Provides:
+
+Reliability percentage
+
+Reference sources
+
+Warning signals for misinformation
+
+This enhances students’ digital literacy and critical thinking skills.
+
+3️⃣ Personalized Study Plan Generator
+
+Based on:
+
+Current stress level
+
+Academic goals (A, B, C, D subject groups…)
+
+Strengths and weaknesses
+
+GenAI generates:
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+Weekly/monthly study schedules
+
+Time management strategies
+
+Balanced subject planning
+
+Career orientation suggestions
+
+If stress is high → study intensity is adjusted.
+If academic imbalance is detected → corrective scheduling is suggested.
+
+🏗 4. System Architecture
+User Input (Web Interface)
+        ↓
+Data Preprocessing (NLP)
+        ↓
+ ┌───────────────┬───────────────┬────────────────┐
+ │ Stress Model  │ Fake News RAG │ Study Planner  │
+ └───────────────┴───────────────┴────────────────┘
+        ↓
+Personalized AI Response
+⚙️ 5. Technologies Used
+Component	Technology
+Programming Language	Python
+UI Framework	Gradio (Hugging Face Spaces)
+NLP	Transformers
+ML Model	Classification model
+GenAI	Text generation
+RAG	FAISS + Retrieval Pipeline
+Database (future expansion)	Structured data storage
+🚀 6. Deployment
+
+This application is deployed on Hugging Face Spaces using:
+
+Gradio interface
+
+Python backend
+
+Transformer-based NLP pipeline
+
+To run locally:
+
+pip install -r requirements.txt
+python app.py