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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() | |