app.py

import gradio as gr
import pickle
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, ImageFont
from ssretro_template import ssretro, ssretro_custom

def custom_template_file(template: str):
    temp = [x.strip() for x in template.split(',')]
    template_dict = {}
    for i in range(len(temp)):
        template_dict[i] = temp[i]
    with open('saved_dictionary.pkl', 'wb') as f:
        pickle.dump(template_dict, f)
    return template_dict


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, custom_template=False):
    model_fn = list_models()[0]
    retro_clf = load_clf(model_fn)
    predict, txt = [], []

    if custom_template:
        outputs = ssretro_custom(molecule, retro_clf)
    else:
        outputs = ssretro(molecule, retro_clf)

    for pred in outputs:
        txt.append(
            f'predicted top-{pred["template_rank"] - 1}, template index: {pred["template_idx"]}, prob: {pred["prob"]: 2.1f}%;')
        predict.append(get_output(pred["reaction"]))

    return predict, txt


def mhn_react_backend(mol, use_custom: bool):
    output_dir = "outputs"
    formatter = "03d"
    images = []

    predictions, comments = ssretro_prediction(mol, use_custom)

    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()
        font = ImageFont.truetype(r'tools/arial.ttf', 20)
        img = Image.open(output_im)
        right = 10
        left = 10
        top = 50
        bottom = 1

        width, height = img.size

        new_width = width + right + left
        new_height = height + top + bottom

        result = Image.new(img.mode, (new_width, new_height), (255, 255, 255))
        result.paste(img, (left, top))

        I1 = ImageDraw.Draw(result)
        I1.text((20, 20), comments[i], font=font, fill=(0, 0, 0))
        images.append(result)
        result.save(output_im)

    return images


with gr.Blocks() as demo:
    gr.Markdown(
        """
        [![arXiv](https://img.shields.io/badge/acs.jcim-1c01065-yellow.svg)](https://doi.org/10.1021/acs.jcim.1c01065)
        [![arXiv](https://img.shields.io/badge/arXiv-2104.03279-b31b1b.svg)](https://arxiv.org/abs/2104.03279)
        [![Python 3.7](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-370/)
        [![Pytorch](https://img.shields.io/badge/Pytorch-1.6-red.svg)](https://pytorch.org/get-started/previous-versions/)
        [![License](https://img.shields.io/badge/License-BSD%202--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause)
        [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ml-jku/mhn-react/blob/main/notebooks/colab_MHNreact_demo.ipynb)
        ### MHN-react   
        Adapting modern Hopfield networks (Ramsauer et al., 2021) (MHN) to associate different data modalities,
        molecules and reaction templates, to improve predictive performance for rare templates and single-step retrosynthesis.
        """
    )

    with gr.Accordion("Guide"):
        gr.Markdown("Information (add) <br> "
                    "In case the output is empty => No suitable templates?"
                    "use one of example molecules: <br> CC(=O)NCCC1=CNc2c1cc(OC)cc2"
                    )

    with gr.Tab("Generate Templates"):
        with gr.Row():
            with gr.Column(scale = 1):
                inp = gr.Textbox(placeholder="Input molecule in SMILES format", label="input molecule")
                radio = gr.Radio([False, True], label="use custom templates")

                btn = gr.Button(value="Generate")

            with gr.Column(scale=2):
                out = gr.Gallery(label="retro-synthesis")

        btn.click(mhn_react_backend, [inp, radio], out)

    with gr.Tab("Create custom templates"):
        gr.Markdown(
            """
            Input the templates separated by comma. <br> Please do not upload templates one-by-one
            """
        )
        with gr.Column():
            inp_t = gr.Textbox(placeholder="custom template", label="add custom template(s)")
            btn = gr.Button(value="upload")
            out_t = gr.Textbox(label = "added templates")
            btn.click(custom_template_file, inp_t, out_t)

demo.launch()