app.py

import gradio as gr
from transformers import pipeline

# ===============================
# Load only text-generation models (simpler, stable)
# ===============================
models = {
    "DistilGPT-2": pipeline("text-generation", model="distilgpt2"),
    "GPT2 (Small)": pipeline("text-generation", model="gpt2"),
    "DialoGPT-small": pipeline("text-generation", model="microsoft/DialoGPT-small"),
    "OPT-350M": pipeline("text-generation", model="facebook/opt-350m"),
    "Bloom-560M": pipeline("text-generation", model="bigscience/bloom-560m"),
    "GPT-Neo-125M": pipeline("text-generation", model="EleutherAI/gpt-neo-125M"),
    "Falcon-RW-1B": pipeline("text-generation", model="tiiuae/falcon-rw-1b"),
}

def compare_models(user_input, max_new_tokens=100, temperature=0.7, top_p=0.95):
    results = {}
    for name, generator in models.items():
        try:
            output = generator(
                user_input,
                max_new_tokens=max_new_tokens,
                temperature=temperature,
                top_p=top_p,
                do_sample=True
            )[0]["generated_text"]
            results[name] = output
        except Exception as e:
            results[name] = f"⚠️ Error: {str(e)}"
    return [results[m] for m in models.keys()]

# ===============================
# Gradio UI
# ===============================
with gr.Blocks(css="style.css") as demo:
    gr.Markdown("## 🤖 Open-Source Model Comparator\n"
                "Compare outputs from multiple open-source LLMs side by side.\n"
                "These are raw, unfiltered outputs from Hugging Face models.")

    with gr.Row():
        user_input = gr.Textbox(label="Your prompt", placeholder="Ask something like 'Write a short poem about the stars'...", lines=2)
        generate_btn = gr.Button("Generate", variant="primary")

    with gr.Row():
        max_tokens = gr.Slider(20, 200, value=100, step=10, label="Max new tokens")
        temp = gr.Slider(0.1, 1.0, value=0.7, step=0.1, label="Creativity (temperature)")
        topp = gr.Slider(0.5, 1.0, value=0.95, step=0.05, label="Nucleus sampling (top_p)")

    with gr.Row():
        outputs = [gr.Textbox(label=name, elem_classes="output-box", interactive=False) for name in models.keys()]

    examples = [
        ["Explain quantum computing in simple terms."],
        ["Write a haiku about autumn leaves."],
        ["What are the pros and cons of nuclear energy?"],
        ["Describe a futuristic city in the year 2200."],
        ["Write a funny short story about a robot learning to cook."],
    ]
    gr.Examples(examples=examples, inputs=[user_input])

    generate_btn.click(compare_models, inputs=[user_input, max_tokens, temp, topp], outputs=outputs)
    user_input.submit(compare_models, inputs=[user_input, max_tokens, temp, topp], outputs=outputs)

if __name__ == "__main__":
    demo.launch()