| import gradio as gr |
| def one(text): |
| return text |
| if __name__ == "__main__": |
| title = """<h1 align="center">🔥AMP Sequence Detector</h1>""" |
| css = ".json {height: 527px; overflow: scroll;} .json-holder {height: 527px; overflow: scroll;}" |
| theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="blue", neutral_hue="green", |
| text_size=gr.themes.sizes.text_lg) |
| with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 520px; overflow: auto;}""", |
| theme=theme) as demo: |
|
|
| gr.Markdown("<h1>Diff-AMP</h1>") |
| gr.HTML(title) |
|
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| gr.Markdown( |
| "<p align='center' style='font-size: 20px;'>🔥Welcome to Antimicrobial Peptide Recognition Model. See our <a href='https://github.com/wrab12/diff-amp'>Project</a></p>") |
| gr.HTML( |
| '''<center><a href="https://huggingface.co/spaces/jackrui/diff-amp-AMP_Sequence_Detector?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a></center>''') |
| gr.HTML( |
| '''<center>🌟Note: This is an antimicrobial peptide recognition model derived from Diff-AMP, which is a branch of a comprehensive system integrating generation, recognition, and optimization. In this recognition model, you can simply input a sequence, and it will predict whether it is an antimicrobial peptide. Due to limited website capacity, we can only perform simple predictions. |
| If you require large-scale computations, please contact my email at wangrui66677@gmail.com. Feel free to reach out if you have any questions or inquiries.</center>''') |
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| examples = [ |
| ["QGLFFLGAKLFYLLTLFL"], |
| ["FLGLLFHGVHHVGKWIHGLIHGHH"], |
| ["GLMSTLKGAATNAAVTLLNKLQCKLTGTC"] |
| ] |
|
|
| |
| iface = gr.Interface( |
| fn=one, |
| inputs="text", |
| outputs="text", |
| |
| examples=examples |
| ) |
| gr.Markdown( |
| "<p align='center'><img src='https://pic4.zhimg.com/v2-eb2a7c0e746e67d1768090eec74f6787_b.jpg'></p>") |
|
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| demo.launch() |
