MHN-React / app.py
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import gradio as gr
from mhnreact.inspect import list_models, load_clf
from rdkit.Chem import rdChemReactions as Reaction
from rdkit.Chem.Draw import rdMolDraw2D
from PIL import Image, ImageDraw
from ssretro_template import ssretro
def get_output(p):
rxn = Reaction.ReactionFromSmarts(p, useSmiles=False)
d = rdMolDraw2D.MolDraw2DCairo(800, 200)
d.DrawReaction(rxn, highlightByReactant=False)
d.FinishDrawing()
text = d.GetDrawingText()
return text
def ssretro_prediction(molecule):
model_fn = list_models()[0]
retro_clf = load_clf(model_fn)
outputs = ssretro(molecule, retro_clf)
predict, txt = [], []
for pred in outputs:
txt.append(f'predicted top-{pred["template_rank"]-1}, prob: {pred["prob"]:2.1f}%; {pred["reaction"]}')
predict.append(get_output(pred["reaction"]))
return predict, txt
def mhn_react_backend(mol):
output_dir = "outputs"
formatter = "03d"
images = []
predictions, comments = ssretro_prediction(mol)
for i in range(len(predictions)):
output_im = f"{str(output_dir)}/{format(i, formatter)}.png"
with open(output_im, "wb") as fh:
fh.write(predictions[i])
fh.close()
img = Image.open(output_im)
I1 = ImageDraw.Draw(img)
I1.text((20, 10), comments[i], fill=(30, 0, 44))
images.append(img)
img.save(output_im)
return images
demo = gr.Interface(fn=mhn_react_backend, inputs="text", outputs="gallery")
demo.launch()