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# -*- coding: utf-8 -*-
"""
Created on Wed Oct 30 09:14:55 2024
@author: BM109X32G-10GPU-02
"""
import numpy as np
from rdkit.Chem import AllChem
from sklearn.datasets import make_blobs
import json
import numpy as np
import math
from scipy import sparse
from sklearn.metrics import median_absolute_error,r2_score, mean_absolute_error,mean_squared_error
from langchain.tools import BaseTool
import pandas as pd
from rdkit import Chem
import pickle
from sklearn.ensemble import RandomForestRegressor
def split_string(string):
result = []
for char in string:
result.append(char)
return result
def main(sm):
inchis = list([sm])
rts = list([0])
smiles, targets,features = [], [],[]
for i, inc in enumerate(inchis):
mol = Chem.MolFromSmiles(inc)
if mol is None:
continue
else:
smi =AllChem. GetMorganFingerprintAsBitVect(mol,1024)
smi = smi.ToBitString()
a = split_string(smi)
a = np.array(a)
#smi = Chem.MolToSmiles(mol)
features.append(a)
targets.append(rts[i])
features = np.asarray(features)
targets = np.asarray(targets)
X_test=features
Y_test=targets
n_features=10
model = RandomForestRegressor(n_estimators=100)
load_homo = pickle.load(open(r"tool/orbital/homo.dat", 'rb'))
load_lumo = pickle.load(open(r"tool/orbital/lumo.dat", 'rb'))
Y_homo= load_homo.predict(X_test)
Y_lumo = load_lumo.predict(X_test)
homo = float(Y_homo)
lumo = float(Y_lumo)
return homo, lumo
class homolumo_predictor(BaseTool):
name: str = "homolumo_predictor"
description: str = (
"Input SMILES , returns the HOMO/LUMO (Highest Occupied Molecular Orbital (HOMO) \
and Lowest Unoccupied Molecular Orbital)."
)
def __init__(self):
super().__init__()
def _run(self, smiles: str) -> str:
mol = Chem.MolFromSmiles(smiles)
if mol is None:
return "Invalid SMILES string"
Y_homo, Y_lumo = main( str(smiles) )
return f"The HOMO is predicted to be {'{:.2f}'.format(Y_homo)} eV , the LUMO is predicted to be {'{:.2f}'.format(Y_lumo)} eV"
async def _arun(self, smiles: str) -> str:
"""Use the tool asynchronously."""
raise NotImplementedError()
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