A robust, feature-rich financial management application built with Django 5.1. Designed to help users track income/expenses, visualize spending trends, set budgets, and receive AI-powered financial insights.
The Personal Finance Tracker is a modern web application that simplifies financial management. It goes beyond simple tracking by integrating DeepSeek AI to provide personalized financial advice and spending anomaly detection. With a responsive dark-themed UI, bank statement parsing, and comprehensive reporting, it serves as a complete solution for personal finance.
The application follows a monolithic architecture with modular Django apps, integrated with external services for AI, Email, and Authentication.
graph TD
User([Clients Web/Mobile]) -->|HTTPS| Nginx[Web Server]
Nginx -->|WSGI| Django[Django App Server]
subgraph "Core Backend (Django)"
Django --> Auth[Authentication Allauth]
Django --> Trans[Transaction Engine]
Django --> Report[Reporting System]
Django --> AI[AI Service Layer]
end
subgraph "Data Layer"
Django -->|SQL| DB[(PostgreSQL Database)]
Django -->|Media| Storage[File Storage Receipts/PDFs]
end
subgraph "External Services"
AI -->|API| DeepSeek[OpenRouter / DeepSeek API]
Auth -->|OAuth| Google[Google Identity Platform]
Django -->|SMTP/API| SendGrid[SendGrid Email Service]
end
The AI Assistant flow demonstrates how user data is securely processed to generate insights.
sequenceDiagram
participant User
participant View as Django View
participant DB as PostgreSQL
participant AI as AI Service
participant LLM as DeepSeek API
User->>View: Request AI Chat / Insights
View->>DB: Fetch Recent Transactions (30 days)
DB-->>View: Transaction Data
View->>View: Aggregate Totals (Income/Expense/Savings)
View->>AI: Prepare Prompt with Context
AI->>LLM: Send Context + User Query
LLM-->>AI: Financial Advice / Answer
AI-->>View: Formatted Markdown Response
View-->>User: Display Chat Response
- Real-time Overview: Instant view of total balance, income, expenses, and savings.
- Visual Analytics: Dynamic charts (Income vs Expense, Category Breakdown) using Chart.js.
- Recent Activity: Quick access to latest transactions with color-coded status.
- Smart Chat Interface: Chat with your financial data using DeepSeek AI (via OpenRouter).
- Context-Aware: The AI automatically knows your monthly spending, income, and savings context.
- Spending Insights: Automated detection of spending anomalies and personalized financial advice.
- Comprehensive Tracking: Log income and expenses with categories, dates, and descriptions.
- Receipt Uploads: Attach images/PDFs to transactions for record-keeping.
- Multi-Currency Support: Track transactions in different currencies with automatic conversion estimates.
- Statement Import: Upload PDF or CSV bank statements.
- Auto-Categorization: Intelligent mapping of bank description patterns to your categories.
- Duplicate Detection: Smart logic prevents double-entry of transactions.
- Monthly Reports: Detailed month-over-month comparison.
- Category Analysis: Deep dive into where your money goes.
- Export Options: Download reports as CSV or PDF for offline analysis.
- Budget Alerts: Email notifications when you exceed category budgets (Integrated with SendGrid).
- Weekly Summaries: Scheduled emails with your financial health summary.
- Google OAuth: Fast and secure login with Google (via Django Allauth).
- Role-Based Access: Secure data isolation ensures users only see their own data.
| Component | Technology | Description |
|---|---|---|
| Backend | Django 5.1 | Python Web Framework |
| Language | Python 3.12 | Core logic and scripting |
| Database | PostgreSQL 17 | Relational Data Storage |
| Frontend | HTML5, CSS3, JS | Custom Dark Theme UI |
| Visualization | Chart.js | Interactive Graphs |
| AI Module | DeepSeek (OpenRouter) | LLM for Insights |
| Authentication | Django Allauth | Google OAuth2 & Local Auth |
| SendGrid | Transactional Emails | |
| PDF Generation | WeasyPrint | Report Exporting |
| Data Analysis | Pandas | Bank Statement Parsing |
finance_tracker/
├── apps/
│ ├── accounts/ # User profile & authentication
│ ├── transactions/ # Core transaction logic
│ ├── budgets/ # Budgeting & alerts
│ ├── reports/ # Analytics & PDF/CSV export
│ ├── ai_features/ # Chatbot & Insights
│ ├── bank_import/ # Statement parsing engine
│ ├── categories/ # Category management
│ └── notifications/ # Email & system notifications
├── templates/ # HTML Templates (Tailwind-style)
├── static/ # CSS, JS, Images
├── media/ # User uploads (Receipts)
└── manage.py # Django CLI- Python 3.10+
- PostgreSQL
- Git
git clone https://github.com/SatyamSingh-Git/FJ-BE-R2-Satyam-Singh-NIT-Delhi.git
cd FJ-BE-R2-Satyam-Singh-NIT-Delhipython -m venv venv
# Windows
.\venv\Scripts\activate
# Linux/Mac
source venv/bin/activatepip install -r requirements.txtCreate a .env file in the root directory with the following variables:
DEBUG=True
SECRET_KEY=your_secret_key
DATABASE_URL=postgresql://postgres:password@localhost:5432/finance_tracker
GOOGLE_CLIENT_ID=your_google_client_id
GOOGLE_CLIENT_SECRET=your_google_client_secret
OPENROUTER_API_KEY=your_deepseek_api_key
SENDGRID_API_KEY=your_sendgrid_key
email_host_user=your_email
email_host_password=your_app_password# Create database
createdb -U postgres finance_tracker
# Run migrations
python manage.py migrate
# Create admin user
python manage.py createsuperuserpython manage.py runserverVisit http://127.0.0.1:8000 to access the application.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.