Quizy Plus is an educational web application designed to assist students in preparing for exams through interactive quizzes and a 24/7 chat assistant. Instead of merely studying from notes or PDFs, students can convert their study material into engaging quizzes. The application offers:
- Document-based question and answer generation.
- A chat assistant that serves as a study buddy.
- Detailed analytics and personalized recommendations based on quiz performance.
- Microservices Architecture: The application is divided into several microservices to ensure scalability and maintainability.
- Containerization: All services are containerized using Docker, which simplifies deployment and orchestration.
- Kubernetes: Used for service discovery, registration, and load balancing.
We used Kubernetes for microservices orchestration, ensuring each service is independently scalable and manageable. Kubernetes handles the deployment, scaling, and operation of application containers across clusters of hosts.
Functionality: Allows students to upload PDF documents and interact with the chat assistant to clarify doubts. Endpoints:
| Method | URL | Description | Input Parameters | Input Parameters Formats |
|---|---|---|---|---|
| POST | /chat/upload |
Upload document to chat | file | File |
| POST | /chat/query |
Chat with assistant | message | string |
| DELETE | /chat/clear-chat |
Clear chat history | - | - |
| DELETE | /chat/clear-doc |
Clear uploaded documents | - | - |
Inter-service Interactions: Communicates with the vector storage and GPT-3.5 model for query processing.
Functionality: Generates multiple-choice and true/false questions from uploaded PDFs.
Endpoints:
| Method | URL | Description | Input Parameters | Input Parameters Formats |
|---|---|---|---|---|
| POST | /quiz/gen-qa |
Upload a document to generate Q&A | file | File |
| GET | /quiz/get-qa |
Retrieve the generated Q&A | - | - |
| DELETE | /quiz/delete-quiz |
Delete a specified quiz | quiz_id | string |
| POST | /quiz/store-results |
Store specified quiz results | results | Array of objects with each object containing 'question' and 'score' |
Inter-service Interactions: Interacts with the analytics service to store quiz results.
Functionality: Provides insights into quiz performance and personalized recommendations.
Endpoints:
| Method | URL | Description | Input Parameters | Input Parameters Formats |
|---|---|---|---|---|
| GET | /analytics/analyze |
Get insights from results | - | - |
| POST | /analytics/analyze-by-quiz |
Get insights from a specific quiz | quiz_id | string |
| GET | /analytics/get-score |
Get all results | - | - |
| POST | /analytics/get-score-by-quiz |
Get results for a specific quiz | quiz_id | string |
Inter-service Interactions: Consumes data from the quiz service to generate analytics.
- Handles the registration and monitoring of services using Kubernetes.
- Implemented with Flask, uses Kubernetes ingress support to route requests to the relevant services.
- Uses Firebase authentication for user management and authorization.
- Front-end: Built using React, Vite, and Tailwind CSS for a responsive and dynamic user interface.
- Back-end: Developed using Python and Flask, containerized with Docker, and orchestrated with Kubernetes.
- Postman was used extensively to test all API endpoints and ensure their functionality and reliability.
- Clone the repository.
- Install Docker and Kubernetes on your local machine.
- Use Docker Compose to start all services.
- Access the application via localhost.
- Choose a cloud provider (e.g., AWS, GCP, Azure).
- Set up a Kubernetes cluster.
- Deploy the Docker containers to the cluster.
- Configure the Kubernetes ingress to expose the API gateway.
- Inconsistent answers from open-source models: Ensuring reliable responses required thorough testing and fine-tuning.
- Learning new technologies: Adopting new frameworks and tools such as Kubernetes posed a learning curve.
References
- F. Tapia, M. Á. Mora, W. Fuertes, H. Aules, E. Flores, and T. Toulkeridis, “From Monolithic Systems to Microservices: A Comparative Study of Performance,” Applied Sciences, vol. 10, no. 17, p. 5797, Aug. 2020, doi: https://doi.org/10.3390/app10175797.
- freeCodeCamp.org, “Microservice Architecture and System Design with Python & Kubernetes – Full Course,” YouTube, Nov. 08, 2022. https://www.youtube.com/watch?v=hmkF77F9TLw&t=4980s.
- “Tutorials,” Kubernetes. https://kubernetes.io/docs/tutorials/
- Docker, “Overview of Docker Compose,” Docker Documentation, Feb. 10, 2020. https://docs.docker.com/compose/
- Flask, “Welcome to Flask — Flask Documentation (3.0.x),” flask.palletsprojects.com, 2010. https://flask.palletsprojects.com/en/3.0.x/
- “Installation: Tailwind CLI - Tailwind CSS,” tailwindcss.com. https://tailwindcss.com/docs/installation