README.md

metadata

title: Budget Forecasting Gradio App
emoji: 📊
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 6.2.0
app_file: app.py
pinned: false

Budget Forecasting Gradio App

A simple Gradio app that forecasts upcoming monthly budgets for a single family using a trained Linear Regression model.

Files

• app.py: Entry point for Hugging Face Spaces (Gradio app launcher)
• gradio_app.py: App logic; loads data, model bundle, and serves the UI
• budget_forecasting_real_data.py: Preprocessing + forecasting helpers used by the app
• monthly_budget_single_family_24m.csv: 24-month single-family dataset
• output/best_model_linear_regression.joblib: Saved best model bundle
• requirements.txt: Python dependencies for the Space

How It Works

• On start, the app loads monthly_budget_single_family_24m.csv, preprocesses minimal time features, and loads the saved model bundle.
• The UI lets you pick forecast horizon (1–24) and outputs a table of predicted monthly_budget_pkr.

Run Locally

python app.py

Deploy to Hugging Face Spaces

1. Create a new Space (Gradio, Python).
2. Upload these files in the repo root:
   • app.py
   • gradio_app.py
   • budget_forecasting_real_data.py
   • monthly_budget_single_family_24m.csv
   • requirements.txt
   • output/best_model_linear_regression.joblib (create output/ folder in the repo)
3. The Space will install dependencies and launch automatically.

If the model file is large, consider uploading it to a separate Hugging Face Model repo and download it at runtime in gradio_app.py.