- Overview
- AWS and AI
- Development Timeline
- StorySwap MVP Features
- StorySwap AI-Enhanced Features
- Beyond MVP: Final Version Features
- Integrating AWS Services with Fly.io for Remix App
- Bugs
- Notes
- Todo list
Swap your read books for new adventures, connect with fellow book lovers, and get personalized book recommendations—all in one app! Discover the joy of sharing stories today.
StorySwap aims to revolutionize the way we read, share, and experience books. Forget the days of dusty bookshelves and forgotten novels. StorySwap is a platform designed for avid readers and casual bibliophiles alike to swap books with others in their community.
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Discover Hidden Gems: Browse through an extensive list of books from other readers in your area. You might find your next favorite read just a block away!
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Sustainability: Swap, don't shop! Reduce environmental impact by extending the life cycle of books.
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Community Building: Join book clubs and discussion groups to connect with like-minded individuals.
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Personalized Recommendations: Get recommendations based on your preferences and reading history.
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Safety: Safety guidelines and verified profiles ensure secure transactions.
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Location-based Matching: Find books and book lovers close to you, making swaps convenient and community-centric.
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Wishlist Feature: Can't find the book you're looking for? Add it to your wishlist and get notified when it becomes available.
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Environmental Impact Tracker: See how your swapping activities are contributing to a greener planet.
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Integrated Messaging: Negotiate swaps and make plans without leaving the app.
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Events Calendar: Stay updated on local book-related events, from author visits to book club meetings.
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Scalability: Leveraging AWS services ensures that StorySwap can easily scale as the user base grows.
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Security: AWS's robust security protocols help safeguard user data and transactions.
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Data Analytics: Utilize AWS's powerful analytics tools to gain insights into user behavior, aiding in data-driven decision-making.
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Unified Management: Centralize application services, from database to notifications, streamlining administration and reducing operational complexity.
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Cost Efficiency: Take advantage of bundled AWS services and potential discounts to minimize operating costs.
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Personalized Recommendations: AI algorithms analyze reading habits and preferences to provide custom book recommendations.
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Chat Support: AI-powered chatbots can offer immediate customer service, answering queries and troubleshooting issues.
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Advanced Search: Machine learning enhances search algorithms, making them more precise and context-aware.
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Resource Allocation: AI helps optimize server usage and other resources, further cutting down operational costs.
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Real-Time Analytics: Use AWS and AI for real-time user analytics, enhancing UX by understanding behavior patterns.
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Automated Moderation: AI can automatically screen book listings and user interactions for any inappropriate content.
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AI-Powered Community Building: AI can identify common interests among users, suggesting book clubs or reading circles they might be interested in.
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Cost Predictions: AI can forecast server load and other costs, helping in budget planning.
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Secure Transactions: AWS's proven security services combined with AI-driven fraud detection make for exceptionally secure swaps and transactions.
- Amazon Personalize: Provides real-time and batch recommendations. You can train the recommendation engine based on your users' behavior.
- Amazon Comprehend: Natural Language Processing (NLP) service that could be adapted for text summarization. While not a direct summarization service, its key phrase extraction could be a starting point.
- Amazon Lex: Provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU).
- Amazon Comprehend: Offers sentiment analysis as one of its capabilities. You can directly plug it into your review system.
- Amazon Translate: Real-time and batch language translation service that could help in translating content dynamically.
- Amazon Rekognition: Ideal for image analysis and can be trained to recognize conditions of books based on images.
- AWS Lambda + API Gateway: While AWS doesn't offer a direct service for predictive text, you can build a microservice using Lambda functions triggered by API Gateway to handle this.
- Amazon Transcribe: Can convert voice to text and can be used in conjunction with search functionalities.
- AWS SageMaker: For custom machine learning models that can estimate environmental impacts.
- Amazon Textract: Can extract text and data from scanned documents.
- Ease of Integration: All these services are designed to be plug-and-play to some extent, reducing the need for extensive machine learning expertise.
- Scalability: AWS services are built to scale, fitting both small and large applications.
- Comprehensive SDKs: AWS SDKs often have good support for popular languages, including JavaScript/TypeScript.
- AWS & Fly.io Integration
- Get the app deployed on Fly.io and establish connections to AWS services, as needed.
- User Profiles (MVP & Planned)
- Implement sign-up and login, create data schema in Prisma.
- Safety Guidelines (MVP)
- Draft and display safety guidelines, essential for early adopters.
- Book Listings (MVP & Planned)
- Develop CRUD operations for book listings and API endpoints.
- Wishlist Feature (MVP)
- Implement a basic wishlist feature for user profiles.
- Search & Filter Options (MVP & Planned)
- Implement basic search algorithm and API endpoints.
- Swap Requests & Messaging (MVP & Planned)
- Develop API for swap requests and a simple real-time messaging system.
- Location-based Matching (MVP & Planned)
- Investigate geolocation services and implement them.
- Reviews & Ratings (MVP & Planned)
- Implement the API for ratings and create the frontend UI.
- Community Features (Planned)
- Implement book clubs and discussion groups.
- Notification System (MVP)
- Implement backend logic for notifications using Fly.io.
- Environmental Impact Tracker (Planned)
- Begin work on environmental impact tracking.
- Recommendation System (Planned)
- Design and implement a recommendation algorithm.
- Integration Tests
- Implement integration tests for all features.
- Performance Optimization
- Optimize for performance, especially if using AWS and Fly.io together.
- Implement sign-up and login functionality using Remix and Prisma.
- Create data schema for storing user profiles in Prisma.
- Develop frontend components for personal bio and genre preferences using Remix and Tailwind.
- Implement API for CRUD operations on user profiles and books list.
- Add a wishlist feature where users can add books they'd like to read.
- Create Prisma schema for book listings.
- Develop API endpoints to add a new book, including uploading photos and metadata.
- Create frontend components for adding and editing book listings.
- Implement a toggle feature to mark a book as 'Available for Swap' or 'Wishlist'.
- Implement a basic search algorithm to find books or users.
- Develop API endpoints for search and filter functionalities.
- Create frontend UI components for search and filtering.
- Create Prisma schema for swap requests and messages.
- Implement API for sending and receiving swap requests.
- Develop a simple real-time messaging or chat system.
- Create frontend components for swap requests and messaging.
- Investigate geolocation services suitable for local matching.
- Develop API endpoints for geolocation-based search.
- Create frontend components to display books available for swap nearby.
- Create a Prisma schema for storing user reviews and ratings.
- Implement API endpoints for posting and retrieving ratings.
- Create frontend UI for users to rate each other after a swap.
- Draft safety guidelines for safe meetups and transactions.
- Create frontend components to display safety guidelines during the swap process.
- Implement backend logic for sending notifications using Fly.io.
- Create frontend notification UI.
- Develop API endpoints for notifications.
- Research and choose an AI-based recommendation engine API that fits the project requirements.
- Implement API integration in the backend using Node.js and Prisma.
- Set up API endpoints to fetch recommendations.
- Develop frontend UI components using React and Tailwind to display
personalized book recommendations.
- Create a 'Recommended Books' section on the user dashboard.
- Evaluate available text summarization APIs.
- Implement the chosen API in the backend.
- Create an endpoint that sends a book's full description and receives the summary in return.
- Update the front-end book listing component to display the summarized
synopsis.
- Add a toggle switch to view full description or summary.
- Identify a chatbot API that can be easily integrated and customized.
- Integrate the chatbot API into the backend.
- Design and implement frontend UI for the chatbot overlay using React and
Tailwind.
- Implement UI logic to open and close the chatbot window.
- Research sentiment analysis APIs that can analyze text reviews.
- Integrate the chosen API in the backend.
- Update review endpoints to also return sentiment scores.
- Modify the frontend review display to include sentiment score, possibly as
a visual indicator.
- Implement this as a separate React component.
- Identify a language translation API.
- Backend implementation to support multiple languages.
- Include language preference in user profile data.
- Implement a language toggle on the frontend.
- Use React's context or another state management solution to switch languages dynamically.
- Research image recognition APIs that can assess book conditions.
- Implement chosen API in the backend.
- Add an endpoint for image analysis results.
- Modify the book listing UI to include a visual indicator of book condition
based on image recognition.
- Update the book listing React component.
- Find a predictive text API suitable for web applications.
- Integrate the API in the backend.
- Update search and messaging endpoints to include predictive text options.
- Implement predictive text in the frontend search and chat components.
- Use async features in React for real-time suggestions.
- Research voice recognition APIs compatible with web applications.
- Implement chosen API in the backend.
- Create an endpoint for voice-to-text results.
- Design and implement a voice search button in the frontend UI.
- Update the search bar component to include a microphone icon for voice search.
- Find or develop a basic machine learning model to estimate environmental impact.
- Integrate this model into the backend.
- Create an endpoint to fetch environmental impact estimates.
- Add an "Environmental Impact Tracker" dashboard in the frontend.
- Create a separate React component for this feature.
- Research available OCR APIs.
- Integrate the chosen OCR API in the backend.
- Create an endpoint to send images and receive text data.
- Implement a camera scan option in the frontend to capture book details.
- Add a 'Scan' button in the book listing form to trigger the camera.
- Automatically populate form fields with scanned data.
- Create the data schema in Prisma for user information
- Implement the API endpoints for CRUD operations on user profiles using Node.js/Remix
- Develop the frontend components in Remix and Tailwind
- Add integration tests for user profile operations
- Create the data schema in Prisma for book listings
- Implement API endpoints for CRUD operations on book listings
- Create frontend components using Remix and Tailwind
- Develop an option for users to report unsatisfactory book conditions
- Add integration tests for book listing features
- Design the search algorithm for genre, author, title, etc.
- Implement the API for search functionality
- Create UI components for search and filters
- Optimize database queries using SQLite indexes for efficient search
- Investigate third-party libraries or APIs for geolocation services
- Implement geolocation-based search in the backend
- Integrate with the frontend, showcasing nearby books
- Optimize for performance and costs on Fly.io
- Create data schema in Prisma for messages and swap requests
- Implement API endpoints for messaging and swap requests
- Develop frontend components for real-time messaging and notifications
- Write tests for messaging and swap requests
- Create the data schema in Prisma for reviews and ratings
- Implement API for posting and retrieving reviews
- Develop frontend UI for submitting and viewing reviews
- Write tests for review features
- Research algorithms for calculating environmental savings
- Implement backend logic for tracking
- Develop frontend UI for displaying impact
- Write tests for impact calculations
- Investigate libraries for barcode scanning
- Implement barcode scanning feature in the frontend
- Integrate with backend to quickly add books
- Write tests for barcode scanning
- Create data schema in Prisma for virtual bookshelf
- Implement API endpoints for managing the virtual bookshelf
- Develop frontend UI components
- Write tests for virtual bookshelf features
- Create data schema in Prisma for book clubs and discussion groups
- Implement API endpoints for community features
- Develop frontend components for book clubs and discussion groups
- Write tests for community features
- Design recommendation algorithm based on user data and activity
- Implement recommendation logic in the backend
- Develop frontend UI for displaying recommendations
- Write tests for recommendation features
- Research payment gateway APIs
- Implement donation functionality in backend
- Develop frontend UI for donations
- Write tests for donation features
- Research and write safety guidelines
- Develop frontend UI for displaying safety guidelines
- Implement verified user badges in Prisma schema and frontend UI
- Write tests for safety features
- Design onboarding experience
- Develop frontend UI for tutorials
- Implement onboarding logic in the backend
- Write tests for onboarding and tutorials
- Create data schema in Prisma for events
- Implement API endpoints for events
- Develop frontend components for the events calendar
- Write tests for event features
- Research APIs for platforms like Goodreads
- Implement data import/export feature in the backend
- Develop frontend UI for external integration
- Write tests for external integration features
- Investigate best practices for accessibility
- Implement voice-over, high contrast theme, adjustable font size
- Develop frontend UI components for accessibility
- Write tests for accessibility features
- Design data schema for updates and notifications
- Implement API endpoints for sending and receiving updates
- Develop frontend UI for displaying updates
- Write tests for update features
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SDKs and APIs
- Utilize AWS SDKs or APIs within your app, deployed on Fly.io, to interact with AWS services.
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Security
- Securely store AWS credentials as environment variables or use services like AWS Secrets Manager.
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Networking
- Ensure network permissions and firewall settings on both sides (AWS and Fly.io) allow for necessary interactions.
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Data Transfer Costs
- Be aware that using AWS services while hosting elsewhere can incur additional data transfer costs.
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Monitoring
- AWS provides CloudWatch for detailed monitoring, but you may need multiple monitoring solutions for full observability.
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Unified Management
- Simplifies administration, scaling, and monitoring.
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Cost Optimization
- Lower internal data transfer costs and potential bundled service pricing.
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Integrated Services
- AWS services are tightly integrated with each other for seamless data and service flow.
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Vendor Lock-in
- AWS services often work best with each other, leading to potential vendor lock-in.
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Best of Both Worlds
- Use Fly.io for edge deployments and AWS for its rich ecosystem of services.
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Complexity
- May result in more complex system architecture and data flow.
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Cost Analysis
- Balancing resources across two platforms may require more stringent cost monitoring.
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If you’re happy with Fly.io, you can easily integrate AWS services into your Fly.io-deployed application.
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If you foresee the need for multiple, tightly-integrated AWS services, consider migrating to AWS.
- Status: Open
- Priority: Low
- Description: Its possible for a user to have multiple active sessions
- Consider implementing CI/CD for automated tests and deployments.
- Ask @larister to review some of the code so far
- [] develop CRUD API for all data models
- [] squash dev commits to eliminate deploy testing litter
- [] configure eslint to order imports akin to CI
- [] navbar dropdown icons
- [] find out SQL join for user -> roles
- [] add user nav config to conditionally render nav items
- [] split root layout into separate components
- [] use open library for book cover images; create a service that fetches them on upload
- [] use goodreads api to add descriptions to added books; create a service that fetches them on upload
- [] build out concept of a "suggest me a book" based on reading/swap history. Is there an api for this?
- [] research: can the app be integrated with goodreads accounts?
- [] BUG: books index calls loader many times, repeating the same if logging out from that page. Why?
- [] book list can have author/genre/condition link to a search page revealing more of the same
- [] list pages need filters
- [] research: can we integrate with a courier service, printing delivery labels, organising book pick ups etc
- [] why do the constants not hot reload on change?
- [] add meta functions to all routes
- [] community/history models/api
- [] about page model/api
- [] welcome index model/api
- deleting book search string creates an infinite loop of requests that I think remix eventually halts; how can I circumvent this? On every change in search term, the loader should only run once. Required revalidation prevention!
- [] passport.js for SSOs
- [] convert prisma to SQL statements
- [] use Wes Bos CSS hack
