[Add] Test version for gradio app

app.py

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+from datasets import load_dataset
+import numpy as np
+import matplotlib.pyplot as plt
+import gradio as gr
+
+def compute_similarity(dataset_name):
+    # Load dataset
+    dataset = load_dataset(dataset_name)
+    # Dummy similarity computation (replace with your metric)
+    data = np.random.rand(10, 10)
+    # Create heatmap
+    fig, ax = plt.subplots()
+    cax = ax.matshow(data, cmap='viridis')
+    plt.colorbar(cax)
+    return fig
+
+with gr.Blocks() as demo:
+    dataset_name = gr.Textbox(label="Enter Dataset Name (e.g., 'imdb')")
+    heatmap_plot = gr.Plot(label="Similarity Heatmap")
+    compute_button = gr.Button("Compute Similarity")
+
+    compute_button.click(
+        fn=compute_similarity,
+        inputs=dataset_name,
+        outputs=heatmap_plot
+    )
+
+demo.launch()

requirements.txt

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+gradio
+numpy
+datasets
+matplotlib
+seaborn
+plotly
+pandas
+scienceplots