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app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load zero-shot classification pipeline
+classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+
+# Labels to classify as AI-written or Human-written
+labels = ["AI-generated text", "Human-written text"]
+
+def detect_ai_content(text):
+    result = classifier(text, labels)
+    scores = dict(zip(result["labels"], result["scores"]))
+    ai_score = scores["AI-generated text"]
+    human_score = scores["Human-written text"]
+    
+    if ai_score > human_score:
+        verdict = "⚠️ This text looks AI-Generated"
+    else:
+        verdict = "✅ This text looks Human-Written"
+
+    return {
+        "AI Probability": f"{ai_score:.2%}",
+        "Human Probability": f"{human_score:.2%}",
+        "Verdict": verdict
+    }
+
+# Gradio Interface
+demo = gr.Interface(
+    fn=detect_ai_content,
+    inputs=gr.Textbox(lines=10, placeholder="Paste text here..."),
+    outputs=[
+        gr.Label(num_top_classes=2, label="Probabilities"),
+        gr.Textbox(label="Verdict")
+    ],
+    title="AI Content Detector",
+    description="Detect whether the given text is AI-generated or Human-written."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+transformers
+torch