This roadmap is designed to guide the development of the summarizer application, an AI-powered text summarizer and analysis tool. Over the course of four weeks, the interns will learn the basics of Next.js, FastAPI, OpenAI API integration, state management, and database handling. They will implement features such as text summarization, categorization, user authentication, and saving summaries. By the end of the project, they will have built a fully functioning tool with AI-powered capabilities.
Day 1: Introduction to Next.js and Project Setup
- Install and set up Next.js project.
- Learn about Next.js structure: pages, components, public folder.
- Create a homepage and basic layout for the summarizer application.
Day 2: Introduction to FastAPI and API Setup
- Install and set up FastAPI for the back-end.
- Create a basic FastAPI application with one simple endpoint (
/). - Set up CORS to allow communication between Next.js and FastAPI.
Day 3: API Integration with OpenAI
- Introduce OpenAI API for text summarization.
- Set up an API route in FastAPI to communicate with OpenAI.
- Integrate a simple endpoint to summarize text using OpenAI.
Day 4: User Interface for Text Input
- Create a simple user interface in Next.js for users to upload or input text.
- Integrate a form that sends the text to the FastAPI endpoint for summarization.
Day 5: Displaying Results on the Front-End
- Display the summarized text on the front-end.
- Handle different text categories (e.g., title, main points).
- Apply basic styling to the results page.
Day 6: Weekly Review and Debugging
- Review the tasks completed during the week.
- Address any issues or bugs.
- Prepare for the next steps involving user interactions and additional API functionality.
Day 7: Implement User Authentication
- Introduce user authentication using JWT or OAuth.
- Create login and registration pages in Next.js.
- Set up authentication routes in FastAPI.
Day 8: Database Setup and Integration
- Set up a database (e.g., PostgreSQL or SQLite) to store user data and summaries.
- Use SQLAlchemy or Tortoise ORM to create database models.
- Integrate database operations to save and fetch summarized texts.
Day 9: Storing User History
- Implement functionality to store and retrieve users’ past summaries from the database.
- Add a page to display saved summaries for logged-in users.
- Ensure only authenticated users can view and manage their history.
Day 10: Enhancing the Front-End
- Improve the front-end to allow users to view and manage their saved summaries.
- Add basic UI components like buttons to save and delete summaries.
- Implement state management using React Context or Zustand.
Day 11: Category-based Summarization
- Implement categorization features to divide summaries into meaningful sections (e.g., main idea, key points).
- Display these categories clearly on the front-end.
Day 12: Weekly Review and Debugging
- Review the tasks completed during the week.
- Address any issues or bugs in the project.
- Prepare for next week’s focus on advanced features like downloading summaries and AI enhancements.
Day 13: AI-Powered Categorization
- Implement AI models to categorize summaries automatically.
- Integrate HuggingFace or other AI models for advanced categorization.
- Train or fine-tune models as needed for better categorization accuracy.
Day 14: Allowing Users to Download Summaries
- Implement functionality to allow users to download their summaries as text or PDF files.
- Add buttons to download summaries from the user history page.
Day 15: Improving Summarization Quality
- Explore advanced OpenAI parameters for better summary quality.
- Implement summarization improvements (e.g., more concise summaries, handling longer texts).
Day 16: Pagination and Search for Saved Summaries
- Implement pagination for the saved summaries list.
- Add a search feature to allow users to quickly find specific summaries.
Day 17: Performance and Optimization
- Optimize API calls to OpenAI to reduce latency.
- Implement caching where necessary to reduce API call frequency and improve performance.
Day 18: Weekly Review and Debugging
- Review the tasks completed during the week.
- Address any performance issues, bugs, or feedback from the team.
Day 19: Preparing for Deployment
- Set up deployment environments for both the front-end and back-end (using platforms like Vercel for Next.js and Heroku for FastAPI).
- Prepare environment variables for secure handling of sensitive information (e.g., OpenAI API keys).
Day 20: Deploying the Front-End (Next.js)
- Deploy the Next.js application to Vercel.
- Ensure proper routing, environment variables, and static file handling.
Day 21: Deploying the Back-End (FastAPI)
- Deploy FastAPI application to a cloud platform (e.g., Heroku, DigitalOcean).
- Ensure the back-end API is properly integrated with the front-end.
Day 22: Final Testing and Bug Fixes
- Test the full application in a production-like environment.
- Address any issues related to performance, user interface, or functionality.
Day 23: Final Presentation and Demonstration
- Prepare a final demo of the application.
- Interns will showcase the summarizer’s features: text summarization, categorization, history, downloading, etc.
Day 24: Project Wrap-Up and Feedback
- Provide feedback on the project, highlighting strengths and areas for improvement.
- Discuss the potential next steps and enhancements for the application.