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app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the paraphrase model
+model_name = "AventIQ-AI/t5-paraphrase-generation"
+paraphrase_pipeline = pipeline("text2text-generation", model=model_name)
+
+def generate_paraphrase(text, max_length, temperature):
+    """Generate a paraphrased version of the input text."""
+    if not text.strip():
+        return "⚠️ Please enter some text to paraphrase."
+    
+    result = paraphrase_pipeline(
+        text,
+        max_length=max_length,
+        temperature=temperature,  # Adds randomness to prevent repetition
+        top_k=50,  # Consider top-k tokens for variation
+        do_sample=True  # Enable sampling
+    )
+    return result[0]["generated_text"]
+
+# Define Gradio Interface
+description = """
+## ✨ AI Paraphrasing Tool
+Enter a sentence and let AI generate a paraphrased version!
+- Adjust **max length** for longer outputs.
+- Tune **temperature** for more creative results.
+"""
+
+demo = gr.Interface(
+    fn=generate_paraphrase,
+    inputs=[
+        gr.Textbox(label="Enter text", placeholder="Type a sentence to paraphrase..."),
+        gr.Slider(20, 100, value=50, step=5, label="Max Output Length"),
+        gr.Slider(0.5, 1.5, value=1.0, step=0.1, label="Creativity (Temperature)"),
+    ],
+    outputs=gr.Textbox(label="Paraphrased Text"),
+    title="📝 AI Paraphraser",
+    description=description,
+    theme="huggingface",
+    live=True,
+)
+
+demo.launch()

requirements.txt

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+torch
+transformers
+gradio
+sentencepiece
+torchvision
+huggingface_hub
+pillow
+numpy