Create app.py

app.py

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+import gradio as gr
+import torch
+import shap
+import numpy as np
+import matplotlib.pyplot as plt
+from transformers import pipeline
+
+# Load sentiment model
+classifier = pipeline("sentiment-analysis")
+
+def predict_with_shap(text):
+    if not text.strip():
+        return "Please enter text", None
+
+    # Get prediction
+    result = classifier(text)[0]
+    label = result["label"]
+    score = result["score"]
+
+    # SHAP explainer
+    explainer = shap.Explainer(classifier)
+    shap_values = explainer([text])
+
+    # Plot SHAP values
+    plt.figure()
+    shap.plots.text(shap_values[0], display=False)
+
+    return f"Prediction: {label} (Confidence: {score:.2f})", plt.gcf()
+
+with gr.Blocks(title="Sentiment Analysis with SHAP") as demo:
+    gr.Markdown("# Sentiment Analysis with SHAP Explanation")
+
+    inp = gr.Textbox(lines=4, placeholder="Enter text here...")
+    out_text = gr.Textbox(label="Prediction")
+    out_plot = gr.Plot(label="SHAP Explanation")
+    btn = gr.Button("Analyze")
+
+    btn.click(predict_with_shap, inp, [out_text, out_plot])
+
+demo.launch()