chempleter 0.1.0b5

A lightweight generative model that extends SMILES fragments into syntactically valid molecules

Chempleter

Molecular autocomplete

Chempleter is lightweight generative model which utlises a simple Gated Recurrent Unit (GRU) to predict syntactically valid extensions of a provided molecular fragment. It accepts SMILES notation as input and enforces chemical syntax validity using SELFIES for the generated molecules.

• What can Chempleter do?

  • Currently, Chempleter accepts an intial molecule/molecular fragment in SMILES format and generates a larger molecule with that intial structure included, while respecting chemical syntax. It also shows some interesting descriptors.

  • It can be used to generate a wide range of structural analogs which the share same core structure (by changing the sampling temperature) or decorate a core scaffold iteratively (by increasing generated token lengths)

  • In the future, it might be adapated to predict structures with a specific chemical property using a regressor to rank predictions and transition towards more "goal-directed" predictions.

Prerequisites

• Python ">=3.12"
• uv (optional but recommended)

Getting started

Visit Chempleter's docs.

Quick start

You can find more information about installing Chempleter (also via pip) in installation instructions.

• Run the GUI directly without installing (via uv):

  • On windows:

    uvx --from chempleter chempleter-gui.exe

  • On linux/MacOS:

    uvx --from chempleter chempleter-gui

• Install using uv

  uv pip install chempleter

• Use the GUI

  • To start the Chempleter GUI after installing, execute in a terminal:

    uv run chempleter-gui

  • Type in the SMILES notation for the starting structure or leave it empty to generate random molecules. Click on GENERATE button to generate a molecule.

  • To know more about using the GUI and various options, see here.

  Or

• Use as a python library

  • To use Chempleter as a python library:

    from chempleter.inference import extend
    generated_mol, generated_smiles, generated_selfies = extend(smiles="c1ccccc1")
    print(generated_smiles)
    >> C1=CC=CC=C1C2=CC=C(CN3C=NC4=CC=CC=C4C3=O)O2
    

    To draw the generated molecule :

    from rdkit import Chem
    Chem.Draw.MolToImage(generated_mol)
    

  • For details on available paramenters and inference functions, see generating molecules.

Project structure

• src/chempleter: Contains python modules relating to different functions.
• src/chempleter/processor.py: Contains fucntions for processing csv files containing SMILES data and generating training-related files.
• src/chempleter/dataset.py: ChempleterDataset class
• src/chempleter/model.py: ChempleterModel class
• src/chempleter/inference.py: Contains functions for inference
• src/chempleter/train.py: Contains functions for training
• src/chempleter/gui.py: Chempleter GUI built using NiceGUI
• src/chempleter/data : Contains trained model, vocabulary files

License

MIT License

Copyright (c) 2025-2026 Davis Thomas Daniel

Contributing

Any contribution, improvements, feature ideas or bug fixes are always welcome.