Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import matplotlib.pyplot as plt
+import numpy as np
+import io
+from PIL import Image
+
+# Function to perform classification and create pie and bar charts
+def classify_and_plot(text, labels):
+    # Splitting labels entered by user
+    labels_list = labels.split(',')
+
+    # Load the zero-shot classification pipeline with the specific model
+    classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+
+    # Perform classification
+    result = classifier(text, labels_list)
+
+    # Extract labels and scores
+    labels = result['labels']
+    scores = result['scores']
+
+    # Generate a colour for each label
+    colors = plt.cm.viridis(np.linspace(0, 1, len(labels)))
+
+    # Create a pie chart
+    fig1, ax1 = plt.subplots()
+    wedges, texts = ax1.pie(scores, startangle=140, colors=colors)
+    ax1.axis('equal')  # Equal aspect ratio ensures the pie chart is circular.
+    ax1.set_title('Pie Chart')
+
+    # Prepare labels with percentages for the pie chart legend
+    legend_labels = ['{0} - {1:1.2f} %'.format(i,j*100) for i,j in zip(labels, scores)]
+    ax1.legend(wedges, legend_labels, title="Labels with Scores", loc="center left", bbox_to_anchor=(1, 0.5))
+
+    # Save the pie chart to a buffer
+    buf1 = io.BytesIO()
+    plt.savefig(buf1, format='png', bbox_inches='tight')
+    buf1.seek(0)
+    pie_chart = Image.open(buf1)
+    pie_chart_array = np.array(pie_chart)
+    plt.close()
+
+    # Create a bar chart
+    fig2, ax2 = plt.subplots()
+    y_pos = np.arange(len(labels))
+    ax2.bar(y_pos, scores, align='center', alpha=0.7, color='blue')
+    ax2.set_xticks(y_pos)
+    ax2.set_xticklabels(labels, rotation=45, ha="right")
+    ax2.set_ylabel('Scores')
+    ax2.set_title('Bar Chart')
+
+    # Save the bar chart to a buffer
+    buf2 = io.BytesIO()
+    plt.savefig(buf2, format='png', bbox_inches='tight')
+    buf2.seek(0)
+    bar_chart = Image.open(buf2)
+    bar_chart_array = np.array(bar_chart)
+    plt.close()
+
+    return pie_chart_array, bar_chart_array
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=classify_and_plot,
+    inputs=["text", "text"],
+    outputs=["image", "image"],
+    title="Zero-Shot Classification with Pie and Bar Charts",
+    description="Enter text and comma-separated labels for classification using the facebook/bart-large-mnli model. The outputs will be separate pie and bar charts representing the classification scores."
+)
+
+# Launch the interface with the 'share' argument
+iface.launch(share=True)