Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load model
+pipe = pipeline("text-generation", model="gpt2")  # Replace with your Hugging Face model ID
+
+def generate_response(prompt, max_length, temperature):
+    output = pipe(
+        prompt,
+        max_length=max_length,
+        temperature=temperature,
+        do_sample=True,
+        pad_token_id=pipe.tokenizer.eos_token_id
+    )
+    return output[0]["generated_text"]
+
+# Gradio Interface
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 📝 AI Text Generator")
+    gr.Markdown("Enter your prompt and generate creative text using a Hugging Face model.")
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="Type your prompt here...",
+                lines=4
+            )
+            max_length = gr.Slider(20, 500, value=200, step=10, label="Max Length")
+            temperature = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
+            generate_btn = gr.Button("Generate")
+
+        with gr.Column(scale=3):
+            output = gr.Textbox(label="Generated Output", lines=10)
+
+    generate_btn.click(
+        fn=generate_response,
+        inputs=[prompt, max_length, temperature],
+        outputs=[output]
+    )
+
+demo.launch()