AI Financial Coach Agent with Google ADK

🎓 FREE Step-by-Step Tutorial

👉 Click here to follow our complete step-by-step tutorial and learn how to build this from scratch with detailed code walkthroughs, explanations, and best practices.

The AI Financial Coach is a personalized financial advisor powered by Google's ADK (Agent Development Kit) framework. This app provides comprehensive financial analysis and recommendations based on user inputs including income, expenses, debts, and financial goals.

Features

• Multi-Agent Financial Analysis System
• Budget Analysis Agent: Analyzes spending patterns and recommends optimizations
• Savings Strategy Agent: Creates personalized savings plans and emergency fund strategies
• Debt Reduction Agent: Develops optimized debt payoff strategies using avalanche and snowball methods

• Expense Analysis:
• Supports both CSV upload and manual expense entry
• CSV transaction analysis with date, category, and amount tracking
• Visual breakdown of spending by category
• Automated expense categorization and pattern detection

• Savings Recommendations:
• Emergency fund sizing and building strategies
• Custom savings allocations across different goals
• Practical automation techniques for consistent saving
• Progress tracking and milestone recommendations

• Debt Management:
• Multiple debt handling with interest rate optimization
• Comparison between avalanche and snowball methods
• Visual debt payoff timeline and interest savings analysis
• Actionable debt reduction recommendations

• Interactive Visualizations:
• Pie charts for expense breakdown
• Bar charts for income vs. expenses
• Debt comparison graphs
• Progress tracking metrics

How to Run

Follow the steps below to set up and run the application:

1. Get API Key:

• Get a free Gemini API Key from Google AI Studio: https://aistudio.google.com/apikey
• Create a .env file in the project root and add your API key:

```

GOOGLE_API_KEY=your_api_key_here

```

2. Clone the Repository:

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/advanced_ai_agents/multi_agent_apps/ai_financial_coach_agent/

3. Install Dependencies:

pip install -r requirements.txt

4. Run the Streamlit App:

streamlit run ai_financial_coach_agent.py

CSV File Format

The application accepts CSV files with the following required columns:

• Date: Transaction date in YYYY-MM-DD format
• Category: Expense category
• Amount: Transaction amount (supports currency symbols and comma formatting)

Example:

Date,Category,Amount
2024-01-01,Housing,1200.00
2024-01-02,Food,150.50
2024-01-03,Transportation,45.00

A template CSV file can be downloaded directly from the application's sidebar.