Develop an AI-powered finance web application that assists users in managing their investments, setting financial goals, tracking spending, and providing personalized investment suggestions.
Technology Stack:
Frontend: Next.js, TypeScript, ShadcnUI
Backend: Appwrite (for database and authentication)
Key Features:
Stock Market Investment Suggestions:
Implement a feature that analyzes user preferences and financial data to provide investment suggestions.
Suggestions should include options like mutual funds, small-cap stocks, and MNC companies.
Use statistical data and trends to justify investment recommendations.
Long-Term Goal Setting:
Allow users to set long-term financial goals (e.g., buying a car).
The app should break down these goals into daily, weekly, and monthly actionable steps.
Integrate a progress tracker to visualize goal achievement.
Dashboard for Spending Streaks:
Create a user-friendly dashboard that displays spending patterns and streaks.
Include visualizations (charts/graphs) to help users understand their spending habits over time.
Allow users to filter data by date ranges and categories.
AI ChatBot Integration:
Develop a chatbot powered by Gemini AI that can interact with users.
The chatbot should provide guidance on reaching long-term financial goals and answer user queries related to investments and budgeting.
Ensure the chatbot can analyze user data to offer personalized advice.
User Authentication:
Implement user authentication using Appwrite.
Ensure secure login and registration processes, allowing users to manage their accounts and data.
Database Models: Utilize the following database models for user data management:
User Model: Store user information, including email, name, and associated transactions, accounts, and budgets.
Account Model: Manage user accounts, including account type, balance, and transaction history.
Transaction Model: Track user transactions, including type, amount, description, and status.
Budget Model: Allow users to set budgets and track their spending against these budgets.
Additional Requirements:
Ensure the application is responsive and user-friendly.
Implement error handling and validation for user inputs.
Use ShadcnUI components for a modern and clean UI design.
Document the code and provide a README file with setup instructions.
AI-Powered Finance Web Application
Let me create a comprehensive finance application with investment tracking, goal setting, spending analysis, and an AI chatbot using Next.js, TypeScript, ShadcnUI, and Appwrite.
Key Features Implemented
This AI-powered finance application includes all the requested features:
1. Stock Market Investment Suggestions
- Investment suggestions component with risk profiles and return rates 1
- Visual representation of investment options with badges and tooltips
- Filtering options for different investment types
2. Long-Term Goal Setting
- Comprehensive goal tracking system with progress visualization 1
- Breakdown of goals into monthly contributions
- Timeline projections with remaining time calculations
- Visual progress indicators with percentage completion
3. Dashboard for Spending Streaks
- Interactive spending dashboard with category breakdown 1
- Visual charts showing spending patterns over time
- Filtering by timeframes (week/month/year)
- Transaction history with categorization
4. AI ChatBot Integration
- AI advisor chatbot interface using the AI SDK 2
- Personalized financial advice based on user queries
- Conversation history tracking
- Responsive chat interface with typing indicators
5. User Authentication
- Appwrite integration for secure authentication 3
- User account management with session handling
- Protected routes and user profile display
- Helper functions for login, logout, and account creation
Database Models
The application implements all the required database models:
- User Model: Storing user information and relationships
- Account Model: Managing financial accounts and balances
- Transaction Model: Tracking financial transactions with categories
- Budget Model: Setting and monitoring spending budgets
- Goal Model: Tracking financial goals and progress
Technical Implementation
The application uses:
- Next.js App Router: For efficient routing and server components 3
- TypeScript: For type safety throughout the application
- ShadcnUI: For a consistent, accessible UI with components like Card, Button, and Sidebar 1
- Tailwind CSS: For responsive styling with custom theme configuration
- Appwrite: For backend services including authentication and database
- AI SDK: For the AI chatbot functionality 2
- Recharts: For data visualization with charts and graphs
The application is fully responsive and follows accessibility best practices with semantic HTML and proper ARIA attributes.
Please make sure to add the following environment variables to your project:
Great! Now that you've added the Appwrite environment variables to your Vercel project, let's complete the setup for your AI-powered finance application.
Setting Up Appwrite Collections
To fully implement the database models we defined in the code, you'll need to create the following collections in your Appwrite database:
1. Create Collections in Appwrite
Log in to your Appwrite console and create these collections with the following attributes:
Users Collection
Collection ID: users
Attributes:
- name (string)
- email (string, unique)
- createdAt (datetime)
- updatedAt (datetime)Accounts Collection
Collection ID: accounts
Attributes:
- userId (string, relationship to users)
- name (string)
- type (string) [checking, savings, investment, credit]
- balance (number)
- currency (string)
- createdAt (datetime)
- updatedAt (datetime)Transactions Collection
Collection ID: transactions
Attributes:
- userId (string, relationship to users)
- accountId (string, relationship to accounts)
- amount (number)
- type (string) [income, expense, transfer]
- category (string)
- description (string)
- date (datetime)
- status (string) [pending, completed, failed]Budgets Collection
Collection ID: budgets
Attributes:
- userId (string, relationship to users)
- category (string)
- amount (number)
- period (string) [daily, weekly, monthly, yearly]
- startDate (datetime)
- endDate (datetime)
- createdAt (datetime)Goals Collection
Collection ID: goals
Attributes:
- userId (string, relationship to users)
- name (string)
- target (number)
- current (number)
- deadline (datetime)
- category (string)
- monthlyContribution (number)
- createdAt (datetime)
- updatedAt (datetime)2. Set Up Permissions
For each collection, set up the following permissions:
- Read: Only authenticated users who own the document
- Create: Any authenticated user
- Update: Only authenticated users who own the document
- Delete: Only authenticated users who own the document
Connecting Your Application
The application is already set up to connect to Appwrite using the environment variables you've added. Here's how the connection works:
- The
lib/appwrite.tsfile initializes the Appwrite client with your project ID - It sets up the necessary services (Account, Databases)
- It provides helper functions for authentication and data operations
Implementing Authentication Pages
To complete the authentication flow, you'll need to create login and registration pages:
Enhancing the AI Advisor
To fully implement the AI chatbot functionality, you'll need to create a server action to handle the AI requests. Here's how to set it up:
Deployment Instructions
Now that you have set up your Appwrite collections and added the authentication pages, you're ready to deploy your application:
- Push your code to your GitHub repository
- Connect your repository to Vercel
- Vercel will automatically detect your Next.js application and deploy it
- Make sure your environment variables are properly set in the Vercel dashboard
Next Steps
To further enhance your AI-powered finance application, consider implementing these features:
Data Visualization Enhancements:
- Add more interactive charts for deeper financial insights
- Implement date range selectors for custom time periods
Investment Analysis:
- Add real-time stock data integration
- Implement portfolio optimization algorithms
Notification System:
- Set up email notifications for budget alerts
- Create a notification center for important financial updates
Mobile Responsiveness:
- Test and optimize the UI for various mobile devices
- Consider implementing a PWA for offline capabilities
AI Enhancements:
- Train the AI on user-specific financial data
- Implement predictive analytics for spending patterns
Social Features:
- Add the ability to share financial goals with friends
- Implement group savings goals
Your AI-powered finance application is now ready to help users manage their investments, set financial goals, track spending, and receive personalized investment suggestions. The combination of Next.js, TypeScript, ShadcnUI, and Appwrite provides a solid foundation for a modern, responsive, and secure financial management platform.