⚡ MindSpark AI

MindSpark AI is an intelligent learning assistant that transforms how you study.
It generates AI-powered flashcards and dynamic quizzes on any topic in seconds — helping learners, educators, and professionals retain knowledge smarter and faster.
Built with Streamlit and MindsDB, MindSpark AI merges simplicity with intelligence.

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🎯 Use Case

Traditional studying methods are often time-consuming and static.
MindSpark AI automates the learning lifecycle:

• Learners enter any topic (e.g., "Neural Networks" or "World War II").
• The system instantly generates interactive flashcards and quizzes powered by AI.
• Knowledge is stored, searchable, and reusable for consistent revision.
• Admins (or educators) can manage topics and curate the learning experience.

Result: Personalized learning, better memory retention, and adaptive AI-driven insights.

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✨ Features

🧠 Flashcard Generator

• Instantly create topic-based flashcards with AI.
• Flip animations for a modern, engaging experience.
• Save and manage flashcards in your Knowledge Base.

🧩 Quiz Creator

• Auto-generate multiple-choice questions (MCQs).
• See instant correct answers and explanations.
• Review quizzes for better understanding.

📊 Knowledge Base

• Store and manage all topics in one place.
• Delete, view, or explore previous AI-generated content.
• Organize by subject or difficulty.

🎨 Modern Streamlit UI

• Animated layout with smooth transitions.
• Easy navigation between Home, Flashcards, and Quiz.
• Responsive design for desktop and tablet users.

🤖 AI Engine

MindSpark AI uses MindsDB as its AI intelligence layer to:

• Generate accurate, context-aware flashcards.
• Produce structured quizzes with correct answers.
• Learn from user inputs to refine topic quality over time.

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Technology

• Python (Best Programming Language :P)
• Streamlit (UI Library)
• MindsDB (AI and KB Layer)
• ChromaDB (Vector DB)
• Nebius (For LLM and Embedding model)

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🧠 Architecture

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📚 Knowledge Base Schema

Name: flashcards_kb

content_columns = ["topic", "question", "answer"]
metadata_columns = ["type", "difficulty", "category"]
id_column = "id"

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Knowledge Base Evaluation metrics

avg_relevancy	avg_relevance_score_by_k	avg_first_relevant_position	mean_mrr	hit_at_k	bin_precision_at_k	avg_entropy	avg_ndcg	avg_query_time	id	name	created_at
0.627670248101896	[1,1,0.92,0.92,0.68,0.35,0.36,0.34,0.35,0.35]	0	1	[1,1,1,1,1,1,1,1,1,1]	[1,1,0.97,0.95,0.87,0.76,0.68,0.62,0.57,0.55]	2.1442872927798353	0.9992926259506063	2.928334045410156	1761660056	my_kb3	2025-10-28 14:00:56.438344

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⚙️ Installation

Follow these steps to set up and run MindSpark AI locally:

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🧩 1. Clone the GitHub Repository

git clone https://github.com/yourusername/mindspark-ai.git
cd mindspark-ai

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🧱 2. Create a Virtual Environment

python -m venv .venv

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Activate the environment:

• On Windows:

.venv\Scripts\activate

• On Linux / Mac:

source .venv/bin/activate

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📦 3. Install Dependencies

pip install -r requirements.txt

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4. Setup project, environment variables and run setup script

uv sync

cp .env.example .env # add your nebius api key from nebius ai cloud to NEBIUS_API_KEY var

uv run setup.py

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🚀 5. Run the Streamlit App

streamlit run app.py

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Blog

https://dev.to/debasis_panda_31e768f5e44/building-mindspark-ai-the-future-of-smart-learning-with-flashcards-and-quizzes-4gp1

Linkdin

https://www.linkedin.com/posts/debasis-panda-07b2912a5_github-guddu-debasismindspark-ai-activity-7388965772624277504-8D6N?utm_source=share&utm_medium=member_desktop&rcm=ACoAAEmLyB8B76-Ngv9FF5gbE3jSxNk-L0kQ9Rk

X

https://x.com/DebasisPan54565/status/1983132238007894480

🎬 Demo Video

![Watch on X]

Author

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