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import gradio as gr | |
from mammal_demo.demo_framework import ( | |
ModelRegistry, | |
TaskRegistry, | |
) | |
from mammal_demo.dti_task import DtiTask | |
from mammal_demo.ppi_task import PpiTask | |
from mammal_demo.ps_task import PsTask | |
from mammal_demo.tcr_task import TcrTask | |
MAIN_MARKDOWN_TEXT = """ | |
The **[ibm/biomed.omics.bl.sm.ma-ted-458m](https://huggingface.co/models?sort=trending&search=ibm%2Fbiomed.omics.bl)** model family is a biomedical foundation model and its finetuned variants trained on over 2 billion biological samples across multiple modalities, including proteins, small molecules, and single-cell gene data. | |
Designed for robust performance, it achieves state-of-the-art results over a variety of tasks across the entire drug discovery pipeline and the diverse biomedical domains. | |
Based on the [**MAMMAL** - **M**olecular **A**ligned **M**ulti-**M**odal **A**rchitecture and **L**anguage](https://arxiv.org/abs/2410.22367v2), a flexible, multi-domain architecture with an adaptable task prompt syntax. | |
The syntax allows for dynamic combinations of tokens and scalars, enabling classification, regression, and generation tasks either within a single domain or with cross-domain entities. | |
This page demonstraits a variety of drug discovery and biomedical tasks for the model family. Select the task to access the specific demos. | |
""" | |
all_tasks = TaskRegistry() | |
all_models = ModelRegistry() | |
# first create the required tasks | |
# Note that the tasks need access to the models, as the model to use depends on the state of the widget | |
# we pass the all_models dict and update it when we actualy have the models. | |
ppi_task = all_tasks.register_task(PpiTask(model_dict=all_models)) | |
tdi_task = all_tasks.register_task(DtiTask(model_dict=all_models)) | |
ps_task = all_tasks.register_task(PsTask(model_dict=all_models)) | |
tcr_task = all_tasks.register_task(TcrTask(model_dict=all_models)) | |
# create the model holders. hold the model and the tokenizer, lazy download | |
# note that the list of relevent tasks needs to be stated. | |
all_models.register_model( | |
model_path="ibm/biomed.omics.bl.sm.ma-ted-458m.dti_bindingdb_pkd", | |
task_list=[tdi_task], | |
) | |
all_models.register_model( | |
model_path="ibm/biomed.omics.bl.sm.ma-ted-458m.tcr_epitope_bind", | |
task_list=[tcr_task], | |
) | |
all_models.register_model( | |
model_path="ibm/biomed.omics.bl.sm.ma-ted-458m.protein_solubility", | |
task_list=[ps_task], | |
) | |
all_models.register_model( | |
model_path="ibm/biomed.omics.bl.sm.ma-ted-458m", | |
task_list=[ppi_task], | |
) | |
all_models.register_model( | |
"ibm/biomed.omics.bl.sm.ma-ted-458m.moleculenet_clintox_tox" | |
) | |
all_models.register_model( | |
"ibm/biomed.omics.bl.sm.ma-ted-458m.moleculenet_clintox_fda" | |
) | |
all_models.register_model( | |
"ibm/biomed.omics.bl.sm.ma-ted-458m.moleculenet_bbbp" | |
) | |
def create_application(): | |
def task_change(value): | |
visibility = [gr.update(visible=(task == value)) for task in all_tasks.keys()] | |
choices = [ | |
model_name | |
for model_name, model in all_models.items() | |
if value in model.tasks | |
] | |
if choices: | |
return ( | |
gr.update(choices=choices, value=choices[0], visible=True), | |
*visibility, | |
) | |
else: | |
return (gr.update(visible=False, value=None), *visibility) | |
def model_change(value): | |
return gr.update( | |
value=f'[<span style="font-size:4em;">🤗</span>to model](https://huggingface.co/{value})', | |
visible=value is not None, | |
) | |
with gr.Blocks(theme="Zarkel/IBM_Carbon_Theme") as application: | |
application_main_markdown=gr.Markdown(MAIN_MARKDOWN_TEXT, visible=True) | |
task_dropdown = gr.Dropdown( | |
choices=["Select task"] + list(all_tasks.keys()), | |
label="Mammal Task", | |
) | |
task_dropdown.interactive = True | |
with gr.Row(): | |
model_name_dropdown = gr.Dropdown( | |
choices=[ | |
model_name | |
for model_name, model in all_models.items() | |
if task_dropdown.value in model.tasks | |
], | |
interactive=True, | |
label="Matching Mammal models", | |
visible=False, | |
scale=10, | |
) | |
goto_card_button = gr.Markdown( | |
"Link to model card", | |
visible=False, | |
) | |
def echo(value): | |
print(value) | |
return value | |
# goto_card_button.click( | |
# fn=None, | |
# inputs=model_name_dropdown, | |
# js=f"(model_name_dropdown) => {{ window.open('https://huggingface.co/{model_name_dropdown}', '_blank') }}", | |
# ) | |
model_name_dropdown.change( | |
model_change, inputs=[model_name_dropdown], outputs=[goto_card_button] | |
) | |
task_dropdown.change( | |
task_change, | |
inputs=[task_dropdown], | |
outputs=[model_name_dropdown] | |
+ [ | |
all_tasks[task].demo(model_name_widgit=model_name_dropdown) | |
for task in all_tasks | |
], | |
) | |
return application | |
full_demo = None | |
def main(): | |
global full_demo | |
full_demo = create_application() | |
full_demo.launch(show_error=True, share=False) | |
# full_demo.launch(show_error=True, share=True) | |
if __name__ == "__main__": | |
main() | |