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sargamchicholikar/WealthWise_India

sourceHugging Faceupdated 5mo agoView on Hugging Face
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App README

Personal Finance Advisor

AI/ML-powered personal finance advisor with expense analytics, forecasting, smart alerts, and a free offline chatbot mode.

Features

  • —Personalized financial analysis (salary, expenses, savings insights)
  • —Expense analyzer from CSV bank statement
  • —spending categorization
  • —category pie chart
  • —monthly trend chart
  • —Expense prediction
  • —linear regression baseline
  • —deep-learning-style forecasting (NumPy MLP)
  • —MAE comparison vs baseline
  • —Context-aware chatbot memory
  • —Smart alerts and insights (overspending, low savings, etc.)
  • —Goal-based planning
  • —Rule-based investment suggestions
  • —Gamification dashboard
  • —Multi-provider chatbot support:
  • —Offline (No API Key) - fully free
  • —Gemini API
  • —OpenRouter API

Project Structure

text
personal-finance-advisor/
├─ indian_finance_advisor.py
├─ requirements.txt
├─ data/
│  └─ sample_bank_statement.csv
├─ backend/
│  ├─ smart_finance_engine.py
│  └─ features/
│     ├─ personalized_analysis.py
│     ├─ expense_analyzer.py
│     ├─ expense_prediction.py
│     ├─ deep_learning_forecast.py
│     ├─ smart_alerts.py
│     ├─ goal_planning.py
│     ├─ investment_suggestion.py
│     └─ chat_memory.py
└─ frontend/
   └─ pages/
      ├─ dashboard_page.py
      ├─ ai_chat_page.py
      ├─ smart_features_page.py
      ├─ portfolio_page.py
      ├─ gamification_page.py
      ├─ settings_page.py
      └─ layout.py

Installation (Windows / PowerShell)

powershell
cd "C:\Users\Sargam\Desktop\personal-finance-advisor"
python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip setuptools wheel
python -m pip install -r requirements.txt

Run App

powershell
python -m streamlit run indian_finance_advisor.py

Open: http://localhost:8501

How to Use

  1. 1.Go to Settings and complete profile + portfolio.
  2. 2.In API Configuration, choose one provider:
  3. 3.Offline (No API Key) (recommended free mode)
  4. 4.Gemini
  5. 5.OpenRouter
  6. 6.Upload data/sample_bank_statement.csv in Smart Features -> Expense Analyzer.
  7. 7.Check:
  8. 8.Predictions & Alerts
  9. 9.Deep Learning Forecast
  10. 10.AI Advisor Chat

Dataset

Sample dataset included:

  • —data/sample_bank_statement.csv

Columns:

  • —Date
  • —Description
  • —Amount

Tech Stack

  • —Python
  • —Streamlit
  • —Pandas / NumPy / SciPy
  • —Plotly
  • —yFinance
  • —Google Generative AI SDK
  • —OpenRouter (optional)

Notes

  • —Offline chatbot mode works without any API key.
  • —For Gemini/OpenRouter providers, valid API keys are required.
  • —This project is suitable for AI/ML academic demos with practical fintech use cases.