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import logging
import pathlib
import gradio as gr
import pandas as pd
from gt4sd.algorithms.conditional_generation.reinvent import Reinvent, ReinventGenerator
from gt4sd.algorithms.registry import ApplicationsRegistry
from utils import draw_grid_generate
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
def run_inference(
algorithm_version: str,
smiles: str,
length: float,
sample_uniquely: bool,
number_of_samples: int,
):
config = ReinventGenerator(
algorithm_version=algorithm_version,
max_sequence_length=length,
randomize=True,
sample_uniquely=sample_uniquely,
)
model = Reinvent(config, target=smiles)
samples = list(model.sample(number_of_samples))
return draw_grid_generate(samples=samples, n_cols=5, seeds=[smiles])
if __name__ == "__main__":
# Preparation (retrieve all available algorithms)
all_algos = ApplicationsRegistry.list_available()
algos = [
x["algorithm_version"]
for x in list(filter(lambda x: "Reinvent" in x["algorithm_name"], all_algos))
]
# Load metadata
metadata_root = pathlib.Path(__file__).parent.joinpath("model_cards")
examples = pd.read_csv(metadata_root.joinpath("examples.csv"), header=None).fillna(
""
)
with open(metadata_root.joinpath("article.md"), "r") as f:
article = f.read()
with open(metadata_root.joinpath("description.md"), "r") as f:
description = f.read()
demo = gr.Interface(
fn=run_inference,
title="REINVENT",
inputs=[
gr.Dropdown(
algos,
label="Algorithm version",
value="v0",
),
gr.Textbox(
label="Primer SMILES",
placeholder="FP(F)F.CP(C)c1ccccc1.[Au]",
lines=1,
),
gr.Slider(
minimum=5,
maximum=400,
value=100,
label="Maximal sequence length",
step=1,
),
gr.Radio(choices=[True, False], label="Sampling uniquely", value=True),
gr.Slider(
minimum=1, maximum=50, value=10, label="Number of samples", step=1
),
],
outputs=gr.HTML(label="Output"),
article=article,
description=description,
examples=examples.values.tolist(),
)
demo.launch(debug=True, show_error=True)
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