Delete app.py

app.py

@@ -1,89 +0,0 @@
-# -*- coding: utf-8 -*-
-"""gcom_app_project(1).ipynb
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1B_g2XLYu46kFDIFzNnnJzBQ0GBPssCQw
-"""
-
-import pickle
-import pandas as pd
-import shap
-from shap.plots._force_matplotlib import draw_additive_plot
-import gradio as gr
-import numpy as np
-import matplotlib.pyplot as plt
-
-# Load the model
-loaded_model = pickle.load(open("salar_xgb_team.pkl", 'rb'))
-
-# Setup SHAP (do not change)
-explainer = shap.Explainer(loaded_model)
-
-# Define main prediction function
-def main_func(age, sex, education_num, capital_gain, capital_loss, hours_per_week, salary_class):
-    sex = 1 if sex == "Male" else 0
-    new_row = pd.DataFrame.from_dict({
-        'age': age,
-        'sex': sex,
-        'education-num': education_num,
-        'capital-gain': capital_gain,
-        'capital-loss': capital_loss,
-        'hours-per-week': hours_per_week,
-        'salary-class': salary_class
-    }, orient='index').transpose()
-
-    prob = loaded_model.predict_proba(new_row)
-
-    shap_values = explainer(new_row)
-    plot = shap.plots.bar(shap_values[0], max_display=6, order=shap.Explanation.abs, show_data='auto', show=False)
-
-    plt.tight_layout()
-    local_plot = plt.gcf()
-    plt.close()
-
-    return {"≤ $50K": float(prob[0][0]), "> $50K": float(prob[0][1])}, local_plot
-
-# Gradio UI
-title = "**Household Income Predictor & Interpreter** 💰"
-description1 = """This app takes demographic and economic features to predict whether a household earns ≤ $50K or > $50K annually."""
-description2 = """Adjust the values and click Analyze to get predictions and feature importance."""
-
-with gr.Blocks(title=title) as demo:
-    gr.Markdown(f"## {title}")
-    gr.Markdown(description1)
-    gr.Markdown("""---""")
-    gr.Markdown(description2)
-    gr.Markdown("""---""")
-
-    age = gr.Number(label="Age", value=35)
-    sex = gr.Radio(choices=["Male", "Female"], label="Sex", value="Male")  # ✅ Fixed: checkbox -> radio
-    education_num = gr.Number(label="Education Level (numeric)", value=10)
-    capital_gain = gr.Number(label="Capital Gain", value=0)
-    capital_loss = gr.Number(label="Capital Loss", value=0)
-    hours_per_week = gr.Number(label="Hours per Week", value=40)
-    salary_class = gr.Number(label="(Optional) Salary Class for SHAP Context", value=0)  # Can remove if not needed
-
-    submit_btn = gr.Button("Analyze")
-
-    with gr.Column(visible=True) as output_col:
-        label = gr.Label(label="Predicted Income")
-        local_plot = gr.Plot(label='SHAP Interpretation:')
-
-    submit_btn.click(
-        main_func,
-        [age, sex, education_num, capital_gain, capital_loss, hours_per_week, salary_class],
-        [label, local_plot], api_name="Income_Predictor"
-    )
-
-    gr.Markdown("### Try these examples:")
-    gr.Examples(
-        [[39, "Male", 13, 0, 0, 40, 0], [52, "Female", 9, 0, 1876, 45, 1]],
-        [age, sex, education_num, capital_gain, capital_loss, hours_per_week, salary_class],
-        [label, local_plot],
-        main_func,
-        cache_examples=True
-    )
-
-demo.launch()