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Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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# Load multiple open-source models (lightweight for CPU-basic)
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models = {
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"DistilGPT-2": pipeline("text-generation", model="distilgpt2"),
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"GPT2 (Small)": pipeline("text-generation", model="gpt2"),
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"DialoGPT-small": pipeline("text-generation", model="microsoft/DialoGPT-small"),
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"OPT-350M": pipeline("text-generation", model="facebook/opt-350m"),
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"Bloom-560M": pipeline("text-generation", model="bigscience/bloom-560m"),
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}
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def compare_models(user_input, max_new_tokens=100, temperature=0.7):
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results = {}
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for name, generator in models.items():
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try:
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output = generator(user_input, max_new_tokens=max_new_tokens, temperature=temperature)[0]["generated_text"]
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results[name] = output
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except Exception as e:
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results[name] = f"⚠️ Error: {str(e)}"
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return [results[m] for m in models.keys()]
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with gr.Blocks(css="style.css") as demo:
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gr.Markdown("## 🤖 Open-Source Model Comparator\n"
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"Type a prompt once, see how different open-source LLMs respond side-by-side.")
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with gr.Row():
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user_input = gr.Textbox(label="Your prompt", placeholder="Ask something like 'Write a short poem about the stars'...", lines=2)
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generate_btn = gr.Button("Generate", variant="primary")
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with gr.Row():
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max_tokens = gr.Slider(20, 200, value=100, step=10, label="Max new tokens")
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temp = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Creativity (temperature)")
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with gr.Row():
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outputs = [gr.Textbox(label=name, elem_classes="output-box", interactive=False) for name in models.keys()]
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examples = [
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["Explain quantum computing in simple terms."],
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["Write a haiku about autumn leaves."],
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["What are the pros and cons of nuclear energy?"],
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["Describe a futuristic city in the year 2200."],
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["Write a funny short story about a robot learning to cook."],
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]
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gr.Examples(examples=examples, inputs=[user_input])
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generate_btn.click(compare_models, inputs=[user_input, max_tokens, temp], outputs=outputs)
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user_input.submit(compare_models, inputs=[user_input, max_tokens, temp], outputs=outputs)
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if __name__ == "__main__":
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demo.launch()
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