app.py

import gradio as gr
from transformers import pipeline

# Dictionary of available models
MODELS = {
    "ModelScope (Text-to-Video)": "damo-vilab/modelscope-text-to-video-synthesis",
    "Hunyuan (if available)": "TencentARC/HunyuanVideo-I2V",  
    "Mochi (Genmo)": "genmo/Mochi1",
    "Wan1.2": "Wan-AI/Wan2.1-T2V-14B"
}

def generate_video(prompt, model_name):
    try:
        pipe = pipeline("text-to-video", model=MODELS[model_name])
        output = pipe(prompt)
        return output["video"]
    except Exception as e:
        return f"Error: {e}"

demo = gr.Interface(
    fn=generate_video,
    inputs=[
        gr.Textbox(label="Prompt"),
        gr.Dropdown(choices=list(MODELS.keys()), label="Choose Model")
    ],
    outputs="video",
    title="Text-to-Video Benchmarking Suite",
    description="Test prompt alignment, motion quality, and therapeutic video generation across multiple models"
)

demo.launch()