app.py

import gradio as gr
import pandas as pd
import joblib
from huggingface_hub import hf_hub_download

# Point to your model repo
REPO_ID = "ClergeF/entrepreneurship-readiness-mini"

# Download model.joblib from the repo
model_path = hf_hub_download(repo_id=REPO_ID, filename="model.joblib")
model = joblib.load(model_path)

# Define input fields
def predict_fn(savings, income, bills, entertainment, sales_skills,
               age, dependents, assets, risk_level, confidence, business_difficulty):
    data = {
        "savings": savings,
        "income": income,
        "bills": bills,
        "entertainment": entertainment,
        "sales_skills": sales_skills,
        "age": age,
        "dependents": dependents,
        "assets": assets,
        "risk_level": risk_level,
        "confidence": confidence,
        "business_difficulty": business_difficulty
    }
    df = pd.DataFrame([data])
    pred = model.predict(df)[0]
    return round(float(pred), 2)

inputs = [
    gr.Number(label="Savings"),
    gr.Number(label="Income"),
    gr.Number(label="Bills"),
    gr.Number(label="Entertainment"),
    gr.Number(label="Sales Skills"),
    gr.Number(label="Age"),
    gr.Number(label="Dependents"),
    gr.Number(label="Assets"),
    gr.Number(label="Risk Level"),
    gr.Number(label="Confidence"),
    gr.Number(label="Business Difficulty"),
]

demo = gr.Interface(
    fn=predict_fn,
    inputs=inputs,
    outputs=gr.Number(label="Predicted Readiness Score"),
    title="Entrepreneurship Readiness Mini Model",
    description="Enter your profile data to estimate your entrepreneurial readiness score."
)

if __name__ == "__main__":
    demo.launch()