app.py

# import spaces
import gradio as gr
import torch
import torch.nn as nn
import random
from rdkit import Chem
from rdkit.Chem import Draw

from graph_decoder.diffusion_model import GraphDiT


ATOM_SYMBOLS = ['C', 'N', 'O', 'H']

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

path = 'model_labeled'
# model = GraphDiT(
#         model_config_path=f"{path}/config.yaml",
#         data_info_path=f"{path}/data.meta.json",
#         model_dtype=torch.float32
#         )
# model.to(device)

def generate_random_smiles(length=10):
    return ''.join(random.choices(ATOM_SYMBOLS, k=length))

# @spaces.GPU
def generate_polymer(CH4, CO2, H2, N2, O2, guidance_scale):
    properties = torch.tensor([CH4, CO2, H2, N2, O2], dtype=torch.float32).unsqueeze(0)
    
    print('in generate_polymer')
    try:
        # Generate a random SMILES string (this is a placeholder)
        generated_molecule = generate_random_smiles()
        # model.generate(properties, device)
        
        mol = Chem.MolFromSmiles(generated_molecule)
        if mol is not None:
            standardized_smiles = Chem.MolToSmiles(mol, isomericSmiles=True)
            img = Draw.MolToImage(mol)
            return standardized_smiles, img
    except Exception as e:
        print(f"Error in generation: {e}")
    
    return "Generation failed", None

# Create the Gradio interface
with gr.Blocks(title="Simplified Polymer Design") as iface:
    gr.Markdown("## Polymer Design with Random Neural Network")
    
    with gr.Row():
        CH4_input = gr.Slider(0, 100, value=2.5, label="CH₄ (Barrier)")
        CO2_input = gr.Slider(0, 100, value=15.4, label="CO₂ (Barrier)")
        H2_input = gr.Slider(0, 100, value=21.0, label="H₂ (Barrier)")
        N2_input = gr.Slider(0, 100, value=1.5, label="N₂ (Barrier)")
        O2_input = gr.Slider(0, 100, value=2.8, label="O₂ (Barrier)")
        guidance_scale = gr.Slider(1, 3, value=2, label="Guidance Scale")

    generate_btn = gr.Button("Generate Polymer")

    with gr.Row():
        result_smiles = gr.Textbox(label="Generated SMILES")
        result_image = gr.Image(label="Molecule Visualization", type="pil")

    generate_btn.click(
        generate_polymer,
        inputs=[CH4_input, CO2_input, H2_input, N2_input, O2_input, guidance_scale],
        outputs=[result_smiles, result_image]
    )

if __name__ == "__main__":
    iface.launch()

# import spaces
# import gradio as gr
# import torch
# from rdkit import Chem
# from rdkit.Chem import Draw
# # from graph_decoder.diffusion_model import GraphDiT

# # Load the model
# def load_graph_decoder(path='model_labeled'):
#     model = GraphDiT(
#         model_config_path=f"{path}/config.yaml",
#         data_info_path=f"{path}/data.meta.json",
#         model_dtype=torch.float32,
#     )
#     model.init_model(path)
#     model.disable_grads()
#     return model

# # model = load_graph_decoder()
# # device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

# @spaces.GPU
# def generate_polymer(CH4, CO2, H2, N2, O2, guidance_scale):
#     properties = [CH4, CO2, H2, N2, O2]
    
#     try:
#         model = load_graph_decoder()
#         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
#         model.to(device)
#         print('enter function')
#         generated_molecule, _ = model.generate(properties, device=device, guide_scale=guidance_scale)
        
#         if generated_molecule is not None:
#             mol = Chem.MolFromSmiles(generated_molecule)
#             if mol is not None:
#                 standardized_smiles = Chem.MolToSmiles(mol, isomericSmiles=True)
#                 img = Draw.MolToImage(mol)
#                 return standardized_smiles, img
#     except Exception as e:
#         print(f"Error in generation: {e}")
    
#     return "Generation failed", None

# # Create the Gradio interface
# with gr.Blocks(title="Simplified Polymer Design") as iface:
#     gr.Markdown("## Polymer Design with GraphDiT")
    
#     with gr.Row():
#         CH4_input = gr.Slider(0, 100, value=2.5, label="CH₄ (Barrier)")
#         CO2_input = gr.Slider(0, 100, value=15.4, label="CO₂ (Barrier)")
#         H2_input = gr.Slider(0, 100, value=21.0, label="H₂ (Barrier)")
#         N2_input = gr.Slider(0, 100, value=1.5, label="N₂ (Barrier)")
#         O2_input = gr.Slider(0, 100, value=2.8, label="O₂ (Barrier)")
#         guidance_scale = gr.Slider(1, 3, value=2, label="Guidance Scale")

#     generate_btn = gr.Button("Generate Polymer")

#     with gr.Row():
#         result_smiles = gr.Textbox(label="Generated SMILES")
#         result_image = gr.Image(label="Molecule Visualization", type="pil")

#     generate_btn.click(
#         generate_polymer,
#         inputs=[CH4_input, CO2_input, H2_input, N2_input, O2_input, guidance_scale],
#         outputs=[result_smiles, result_image]
#     )

# if __name__ == "__main__":
#     iface.launch()