An interactive, AI-powered recall trainer built for learners of the Bayyinah Institute Dream curriculum. Type what you remember, let the app retrieve the relevant material, and get instant formative feedback.
Brilliant Muslim’s Arabic Lesson Evaluator helps students shift from passive review to active recall. It embeds the Dream textbook as searchable vectors, evaluates free-text answers with large language models, and delivers color-coded feedback so you know exactly what to fix next.
Layer | Tech & Services |
---|---|
LLM / Eval | OpenAI GPT-4o · Gemini 2.5 Pro |
Retrieval | FAISS vector store + LangChain RAG |
Frontend | Streamlit |
Hosting | Streamlit Community Cloud (demo) |
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Lesson Browser – Flip through textbook units inside the app.
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Active Recall Input – Type everything you remember; no multiple-choice crutches.
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RAG Retrieval – Relevant textbook passages surface automatically.
-
AI Scoring – Your answer is graded on accuracy and completeness.
-
Granular Feedback
- ✅ Correct points
- ❌ Misunderstandings
⚠️ Missed concepts- 💡 Actionable advice
Try it now → https://brilliant-muslim-ai-recall.streamlit.app/
git clone https://github.com/aatif-dawawala/arabic-lesson-eval.git
cd arabic-lesson-eval
pip install -r requirements.txt
Create a .env
or .streamlit/secrets.toml
file:
OPENAI_API_KEY = "your-openai-key"
GEMINI_API_KEY = "your-gemini-key"
streamlit run streamlit_app.py
The app will open at http://localhost:8501.
pytest
┌──────────────┐
│ Streamlit │ ←– UI
└──────┬───────┘
│ user prompt
┌──────▼─────────┐
│ LangChain RAG │ ←– chunking & similarity search
└──────┬─────────┘
│ relevant docs
┌──────▼─────────┐
│ LLM Scorer │ ←– model
└──────┬─────────┘
│ feedback JSON
┌──────▼─────────┐
│ Streamlit UI │ ←– highlights & scores
└────────────────┘
Pull requests are welcome—help us empower Arabic learners worldwide! Please follow the conventional commit style and open an issue first if you plan a large change.
This project is released under the MIT License – see LICENSE
for details.
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