This is a submission for the Twilio Challenge
What I Built
Xpenser is not just a simple expense manager. It is an advanced expense management tool designed to simplify logging and analyzing your spending habits. With robust features, including seamless WhatsApp integration powered by Twilio, Xpenser stands out as a unique solution for personal finance management.
Demo
Checkout the Demo on YouTube at:
Experience Xpenser live https://xpenser.amitwani.dev.
Explore the project on GitHub:
mtwn105
/
xpenser-whatsapp-bot
AI Expense Manger with Twilio & Gemini AI
Xpenser
AI Expense Manager with WhatsApp
Built using Twilio & Gemini AI
🥳 Winner of Twilio x Dev.To Hackathon - https://dev.to/devteam/congrats-to-the-twilio-challenge-winners-2b1n
Demo
You can find Xpenser live here: https://xpenser.amitwani.dev.
Join the Twilio Sandbox WhatsApp Number: +14155238886 by sending join per-mud
Tech Stack
Backend: NodeJS, Express
Frontend: Angular, Typescript
Database: MongoDB
Deployment: Docker, Northflank
AI: Gemini 1.5 Flash
Twilio: Verify, Functions, WhatsApp
Architecture
WhatsApp Integration
Portal
To test the WhatsApp integration, join the Twilio Sandbox WhatsApp Number: +14155238886 by sending join per-mud
Workflow
User Registration
Users register on the web portal, verifying their phone numbers via OTP (Powered by Twilio Verify).
Dashboard
The dashboard offers detailed analytics, including AI-driven insights, category-wise distribution, and average spending.
Expenses
Users can easily add, manage, and delete expenses. The AI automatically categorizes expenses upon saving.
WhatsApp Integration
Join the Twilio Sandbox WhatsApp Number: +14155238886 by sending join per-mud
Log new expenses effortlessly via WhatsApp. The AI interprets user messages to gather details for saving the expense.
Request insights on spending, such as top categories or average spending. The AI provides answers based on the last 100 expenses.
Tech Stack
Backend: NodeJS, Express
Frontend: Angular, Typescript
Database: MongoDB
Deployment: Docker, Northflank
AI: Gemini 1.5 Flash
Twilio: Verify, Functions, WhatsApp
Architecture
WhatsApp Integration
Portal
Twilio and AI
Twilio
Xpenser leverages three Twilio services: Verify, Functions and WhatsApp Messaging
Verify
Twilio's Verify service sends OTPs for user authentication.
Send OTP
const verification = await client.verify.v2.services(otpServiceId)
.verifications
.create({ to: req.body.phonenumber, channel: 'sms' });
Verify OTP
const verification = await client.verify.v2.services(otpServiceId)
.verificationChecks
.create({ to: req.body.phonenumber, code: req.body.code })
Functions
Twilio Functions handles incoming WhatsApp messages, interfacing with the backend and Gemini AI.
Generated functions using
twilio serverless:init twilio --typescript
export const handler: ServerlessFunctionSignature = async function (
context: Context<MyContext>,
event: MyEvent,
callback: ServerlessCallback
) {
// Handle Incoming Message
}
WhatsApp Messaging
Twilio's Programmable WhatsApp Messaging facilitates user interaction through WhatsApp.
Send WhatsApp Message using TwiML
const twiml = new Twilio.twiml.MessagingResponse();
twiml.message("Please ask about spends you have done or spend you want to log.");
callback(null, twiml);
AI
Gemini 1.5 Flash, a Google AI Model, enhances Xpenser with advanced analytics and predictions.
Expense Analytics
Analyzing user expense history to provide insights and respond to user queries.
const analyticsModel = genAI.getGenerativeModel({
model: "gemini-1.5-flash",
systemInstruction: "Based on below expenses done by user give answer to user. Optimize as WhatsApp message reply and add emojis.\n\nExpense History:\n" + expenseCsvText,
});
const generationConfig = {
temperature: 0.6,
topP: 0.95,
topK: 64,
maxOutputTokens: 8192,
responseMimeType: "application/json",
};
const chatSession = model.startChat({
generationConfig
});
const result = await chatSession.sendMessage(event.Body);
const aiResponse = result.response.text()
Expense Categorization
Categorizing expenses based on user-provided descriptions.
const analyticsModel = genAI.getGenerativeModel({
model: "gemini-1.5-flash",
systemInstruction: "detect the category and subcategory from below\n1. Housing - Rent, Taxes, Insurance, Utilities, Repairs, Improvement, Fees\n2. Transportation - Payments, Fuel, Insurance, Repairs, Public, Parking, Tolls, Licensing\n3. Food - Groceries, Dining, Coffee, Delivery, Snacks, etc.",
});
const generationConfig = {
temperature: 0.6,
topP: 0.95,
topK: 64,
maxOutputTokens: 8192,
responseMimeType: "application/json",
};
const chatSession = model.startChat({
generationConfig
});
const result = await chatSession.sendMessage(event.Body);
const aiResponse = result.response.text()
Additional Prize Categories
Xpenser qualifies for the Twilio Times Two prize category by utilizing multiple Twilio features: Verify, Functions, and WhatsApp Messaging.
Future Scope
- Spending Habits: Use AI to identify spending patterns and suggest ways to optimize expenses based on historical data.
- Mobile Applications: Develop native iOS and Android applications for enhanced accessibility and a more seamless user experience.
- Custom Reports: Allow users to generate customizable reports based on various parameters such as date range, categories, or tags.
- Investment Tracking: Add features to track investments and provide insights into portfolio performance.
- Manage Categories: Create and manage custom categories and sub-categories for a more personalized experience.
Conclusion
It was a great experience to work on this project while exploring Twilio services and integrating AI to enhance the user experience. Thanks to Dev.to team for this amazing hackathon.
Top comments (2)
Love what you have built!
Thanks a lot 😁