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Aim of Creating an AI Based Financial Advisor with python Langgraph and LLM

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� AI-Powered Finance Manager

An intelligent financial management application that combines Object-Oriented Programming with AI-powered insights to help users track expenses, analyze spending patterns, and make informed financial decisions.

🎯 Overview

This project demonstrates advanced OOP concepts while solving real-world financial challenges through:

  • Smart Transaction Management with bank statement imports
  • AI Financial Advisory using LangGraph workflows
  • Intelligent Categorization optimized for Indian financial context
  • Professional Reporting with actionable insights

✨ Key Features

💳 Financial Management

  • Add, update, and categorize transactions
  • Import bank statements (PNB supported)
  • Smart duplicate detection and filtering
  • Export/import functionality

🤖 AI Financial Advisor

  • Goal Analysis - Assess financial objectives and feasibility
  • Behavior Analysis - Identify spending patterns and habits
  • Personalized Advice - Tailored recommendations based on user profile
  • Professional Reports - Comprehensive financial planning documents
  • Risk Assessment - Evaluate financial health and suggest improvements

🖥️ User Interface

  • Beautiful CLI with colored output and tables
  • Streamlit web interface for interactive analysis
  • Export reports and data visualization

🛠️ Tech Stack

Core: Python 3.13+, SQLite, Typer, Streamlit
AI: LangGraph, LangChain, Groq, Pydantic
Tools: Colorama, Tabulate, Python-dotenv

📁 Project Structure

Finance-Manager/
├── main.py                    # CLI entry point
├── basic_gui.py              # Streamlit web interface
├── pyproject.toml            # Project configuration
│
├── src/                      # Core application
│   ├── ai.py                # AI workflow coordinator
│   ├── financeManager.py    # Business logic
│   ├── config.py            # Configuration
│   │
│   ├── Ai/                  # AI Agent System
│   │   ├── graph.py         # LangGraph workflow
│   │   ├── nodes/           # AI processing nodes
│   │   ├── schemas/         # Data validation models
│   │   └── prompts/         # AI prompt templates
│   │
│   ├── database/            # Database management
│   ├── Banks/               # Bank statement parsers
│   └── Classifiers/         # Transaction categorization
│
└── data/                    # Database storage
    └── finance.db          # SQLite database

� Quick Start

Prerequisites

  • Python 3.13+
  • Groq API key (for AI features)

Installation

# Clone repository
git clone https://github.com/siddhant385/Finance-Manager-main.git
cd Finance-Manager-main

# Install dependencies
pip install -e .

# Set up environment
cp .env.template .env
# Add your GROQ_API_KEY to .env

Usage

CLI Interface:

# View financial summary
python main.py

# Add transaction
python main.py add "food" 250.50 "2024-01-15" "Lunch"

# Import bank statement
python main.py import-statement "statement.csv" "pnb"

# AI Financial Advisor
python -c "from src.ai import AI; ai = AI(); print(ai.advisor({'goal': 'Buy laptop'}))"

Web Interface:

streamlit run basic_gui.py

📊 Project Status

✅ Completed:

  • Core financial management system
  • AI-powered financial advisory with LangGraph
  • Bank statement import (PNB)
  • CLI and web interfaces
  • Professional report generation

🔄 In Progress:

  • Enhanced Streamlit dashboard
  • Additional bank integrations

🎯 Planned:

  • Memory system for AI conversations
  • Advanced analytics and visualizations
  • Multi-user support

🏗️ Architecture Highlights

This project showcases Object-Oriented Programming principles:

  • Strategy Pattern for bank parsers and classifiers
  • Abstract Factory for component creation
  • Template Method for processing workflows
  • SOLID Principles throughout the codebase

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

📄 License

This project is open source and available under the MIT License.

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Aim of Creating an AI Based Financial Advisor with python Langgraph and LLM

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