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| title: Quiz Generation | |
| emoji: 📝 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| pinned: false | |
| AI Exam Generator | |
| A FastAPI-based microservice that generates quizzes from uploaded | |
| documents using an AI model. | |
| The API accepts PDF, DOCX, or TXT files, extracts their text, and | |
| generates different types of questions such as: | |
| - Multiple Choice Questions (MCQ) | |
| - Fill in the Blank | |
| - Explanation Questions | |
| The questions are generated using the Groq LLM (Llama 3.3 70B) via | |
| LangChain. | |
| --- | |
| FEATURES | |
| --- | |
| - Upload documents (PDF, DOCX, TXT) | |
| - Automatic text extraction | |
| - AI-generated quizzes | |
| - Multiple question types | |
| - Separate answer key generation | |
| - Optional download as TXT or PDF | |
| - REST API with FastAPI | |
| - Interactive API documentation | |
| --- | |
| INSTALLATION | |
| --- | |
| 1. Clone the repository | |
| 2. Create a virtual environment | |
| `python -m venv .venv` | |
| 3. Activate the environment (Windows PowerShell) | |
| `.\.venv\Scripts\Activate.ps1` | |
| 4. Install dependencies | |
| `pip install -r requirements.txt` | |
| --- | |
| ENVIRONMENT VARIABLES | |
| --- | |
| Create a `.env` file in the project root: | |
| `MY_API_KEY=your_groq_api_key_here` | |
| This key is required to access the Groq LLM. | |
| --- | |
| RUNNING THE API | |
| --- | |
| Start the server: | |
| `uvicorn app.main:app --reload` | |
| The API will run at: | |
| `http://127.0.0.1:8000` | |
| Interactive API documentation: | |
| `http://127.0.0.1:8000/docs` | |
| --- | |
| API ENDPOINTS | |
| --- | |
| - `POST /api/v1/upload` Upload a document (PDF, DOCX, TXT) | |
| - `POST /api/v1/generate` Generate questions from uploaded text | |
| - `GET /api/v1/quiz/{quiz_id}` Returns generated quiz with answer key | |
| - `GET /api/v1/download/{filename}` Download generated quiz file | |
| - `GET /api/v1/uploads` List uploaded documents | |
| - `DELETE /api/v1/upload/{upload_id}` Delete uploaded document | |
| --- | |
| EXAMPLE WORKFLOW | |
| --- | |
| 1. Upload a file | |
| 2. Generate a quiz | |
| 3. Retrieve the quiz results | |
| --- | |
| TECHNOLOGIES USED | |
| --- | |
| FastAPI, LangChain, Groq LLM (Llama 3.3 70B), Python, pdfplumber, | |
| python-docx, FPDF | |
| --- | |
| NOTES | |
| --- | |
| - Uploaded text and quizzes are stored locally in JSON files. | |
| - This implementation uses in-memory storage. | |
| - For production use, a database is recommended. | |