Reflection-Study

A Python-based study assistant that generates and iteratively improves multiple-choice quizzes from lecture notes using the Groq API and a reflection loop.

Features

• Quiz Generation: Automatically creates concise, high-quality multiple-choice quizzes from your study notes.
• Reflection Loop: Evaluates quizzes for clarity, accuracy, and quality, then regenerates improved versions based on feedback.
• Configurable Model: Uses Groq's LLM (default: openai/gpt-oss-120b).
• Environment Variable Support: API keys and secrets managed via .env file.

Project Structure

Reflection-Study/
│
├── reflection_agent.py      # Main agent code
├── README.md                # Project documentation
├── myreflectionstudy/
│   ├── .env                 # API keys (ignored by git)
│   ├── .gitignore           # Ignore venv and sensitive files
│   ├── pyvenv.cfg           # Virtual environment config
│   ├── Include/             # venv include files
│   ├── Lib/                 # venv libraries
│   └── Scripts/             # venv scripts

Setup

1. Clone the repository:

   git clone <your-repo-url>
   cd Reflection-Study

2. Create a virtual environment (if not already present):

   python -m venv myreflectionstudy

3. Activate the virtual environment:

   • Windows:

     myreflectionstudy\Scripts\activate

   • macOS/Linux:

     source myreflectionstudy/bin/activate

4. Install dependencies:

   pip install -r requirements.txt

   (Create requirements.txt with needed packages: groq, python-dotenv)

5. Set up your .env file:

   GROQ_API_KEY="your_groq_api_key_here"
   

Usage

Edit reflection_agent.py to provide your lecture notes.
Run the script:

python reflection_agent.py

The agent will generate a quiz, reflect on its quality, and iteratively improve it.