El Plan STEM

El Plan STEM is a Django-based web application that combines the excitement of Formula 1 with engaging, AI-powered STEM education. Whether you're a student learning physics through lap times or an F1 enthusiast curious about race analytics, this project delivers a powerful, interactive experience.

---

Features

F1-Themed Educational Chatbot

• Teaches STEM concepts (Science, Technology, Engineering, Mathematics) using real F1 data.
• Auto-generates quiz-style questions based on:
  • Lap times
  • Pit stops
  • Driver statistics
• Evaluates answers with explanations using Formula 1 analogies.
• Maintains conversational history for context-rich feedback.

General F1 Assistant

• Chat with a bot to retrieve real-time facts and data about drivers, races, and circuits.
• Uses semantic vector search with sentence embeddings for intelligent query handling.

Notes System

• Lets users create, save, and manage notes for studying or strategy planning.

Graphing Module

• Visualizes F1 data such as speed trends, pit stop frequencies, or momentum shifts.

---

Tech Stack

• Backend: Django 5.2.1
• Database: MongoDB (via django-mongodb-backend)
• AI Integration: Google Gemini (Gemini 1.5 Flash)
• Machine Learning: scikit-learn, TensorFlow, sentence-transformers
• Frontend: Django templates + static files (CSS/JS)

---

AI and ML Details

• Chatbot uses Google's Gemini model for generating and evaluating questions.
• Semantic search powered by sentence-transformers for intelligent data retrieval.
• ML models include:
  • turn_severity_rf_model.joblib: Turn severity predictions
  • momentum_lstm_model.h5: Momentum analysis
  • f1_momentum_model.h5: Momentum-based forecasting

---

Project Structure

El-Plan-STEM/
│
├── backend/
│ ├── core/ # General site logic
│ ├── chatbot/ # Chatbot and AI logic
│ ├── ml_models/ # Legacy ML code (merged into chatbot)
│ ├── templates/ # HTML templates
│ ├── static/ # CSS, JS, images
│ └── manage.py
├── requirements.txt
└── .env (your environment variables)

---

Setup Instructions

1. Install Python 3.11

2. Create virtual environment

   py -3.11 -m venv venv

3. Activate the environment

   .\venv\Scripts\activate

4. Install dependencies

   pip install -r requirements.txt

5. Run the server

   cd backend
   python manage.py runserver

6. Stop the server

   ctrl + C

7. Deactivate the environment

   deactivate

---

Routes Overview

Route	Description
/chatbot/	Main chatbot interface
/chatbot/chat/	Chat endpoint for educational bot
/chatbot/general/	General F1 assistant UI
/chatbot/general/chat/	General assistant chat endpoint
/	Home page
/about/	About the project

---

Special Thanks

Thanks to the teams behind:

• Google Generative AI
• Ergast's Formula 1 open datasets
• Django & MongoDB communities

---

"Learning STEM at full throttle with the power of Formula 1!"

---