Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Create a zero-shot classification pipeline
+classifier = pipeline("zero-shot-classification")
+
+
+def classify_text(text, additional_labels):
+    # Default labels
+    labels = ["Education", "Business", "Sports", "Manufacturing"]
+
+    # Add custom labels if provided
+    if additional_labels:
+        custom_labels = additional_labels.split(',')
+        labels.extend(custom_labels)
+
+    # Perform classification
+    result = classifier(text, candidate_labels=labels)
+
+    # Formatting the output
+    output = []
+    for label, score in zip(result["labels"], result["scores"]):
+        output.append(f"Label: {label}, Score: {round(score, 4)}")
+    return "\n".join(output)
+
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=classify_text,
+    inputs=["text", "text"],
+    outputs="text",
+    title="Text Classification",
+    description="Enter a text to classify into categories: Education, Business, Sports, Manufacturing. Optionally, add more categories separated by commas."
+)
+
+# Launch the interface
+interface.launch()