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bfa_finance_tracker_with_ai_budget_forecasting

https://github.com/ashishbhardwaj138/bfa_finance_tracker_with_ai_budget_forecasting

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (6.5%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: ashishbhardwaj138
  • License: mpl-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 753 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 3
  • Releases: 0
Created 10 months ago · Last pushed 8 months ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

💸 Smart Personal Finance Tracker

A full-stack, AI-powered open-source application that intelligently extracts financial data from your emails, visualizes it via an intuitive dashboard, and predicts your future expenses — all while running securely on your local system.

🧠 Key Features

  • 🔐 Secure Gmail or IMAP login (OAuth2/token-based)
  • 📥 Auto-fetch and parse transaction-related emails
  • 🏷️ NLP-powered classification of credit/debit, vendor, category, etc.
  • 📊 Interactive dashboard for insights
  • 📈 Budget forecasting using time-series ML (Prophet)
  • 🗃️ Fully self-hosted, no cloud or server dependency
  • 🛠️ Modular Django + React + Celery architecture

🚀 Demo Screenshots

To be added after first implementation phase

🧩 Architecture Overview

  • Frontend: React + Tailwind CSS
  • Backend: Django REST Framework
  • ML Modules: spaCy (NLP), Prophet (Forecasting)
  • Database: PostgreSQL
  • Queue: Celery + Redis
  • Deployment: Docker Compose (runs locally)

🧰 Prerequisites

  • Python 3.10+
  • Node.js 16+
  • Docker + Docker Compose
  • Gmail or IMAP-compatible email account
  • Gmail API credentials (if using Gmail)

📦 Local Installation

1. Clone the Repository

```bash git clone https://github.com/yourusername/finance-tracker-ai.git cd finance-tracker-ai

Owner

  • Name: Ashish Bhardwaj
  • Login: ashishbhardwaj138
  • Kind: user
  • Location: Delhi
  • Company: Open-Inventors

Extremely Passionate about using variety of technologies from Analytics to Reinforcement learning to deliver responsive and informed Insigths or make prediction

Citation (CITATION.cff) 

cff-version: 0.0.1
message: "If you use this software, please cite it as below."
title: "Smart Personal Finance Tracker"
authors:
  - family-names: Ashish Bhardwaj
    given-names: [Ashish]
    affiliation: "Open Source Contributor"
    orcid: "https://orcid.org/0000-0000-0000-0000"  # dummy , will update later on
date-released: 2025-06-15
version: "0.1.0"
license: Apache-2.0
repository-code: https://github.com/ashishbhardwaj138/bfa_finance_tracker_with_ai_budget_forecasting
doi: 10.5281/zenodo.1234567 # dummy , will update later on

GitHub Events

Total
  • Issues event: 1
  • Delete event: 1
  • Issue comment event: 1
  • Push event: 7
  • Gollum event: 7
  • Pull request event: 1
  • Create event: 9
Last Year
  • Issues event: 1
  • Delete event: 1
  • Issue comment event: 1
  • Push event: 7
  • Gollum event: 7
  • Pull request event: 1
  • Create event: 9

Dependencies

.github/workflows/gh-pages.yml actions
  • actions/checkout v4 composite
  • actions/deploy-pages v4 composite
  • actions/setup-python v5 composite
  • actions/upload-pages-artifact v3 composite
.github/workflows/release.yml actions
  • actions/checkout v4 composite
  • actions/download-artifact v4 composite
  • actions/setup-python v5 composite
  • actions/upload-artifact v4 composite
  • pypa/gh-action-pypi-publish release/v1 composite
pyproject.toml pypi
  • bokeh >=3,<4
  • pandas >=2
  • pycountry >=22.3.5
  • requests >=2.28.1