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adding MR and LogP Prediction tasks
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internbootcamp/bootcamp/ChemStructure2Property/SMILES2MRBootCamp.py
Executable file
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internbootcamp/bootcamp/ChemStructure2Property/SMILES2MRBootCamp.py
Executable file
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from internbootcamp.bootcamp.base import Basebootcamp
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from internbootcamp.libs.chemStructure2Property.ChemStructureGenerator import SMILESGenerator
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from .utils import last_boxed_only_string, remove_boxed
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from rdkit import Chem
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from rdkit.Chem import Crippen
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from .SMILES2logPBootCamp import SMILES2logPBootCamp
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class SMILES2MRBootCamp(SMILES2logPBootCamp):
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def prompt_func(self, SMILES) -> str:
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instruction = f"Given the SMILES, determine the Molar Refractivity (MR) value of the material. The SMILES is: {SMILES}"
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instruction_following = """Let's think step by step and output the final answer within \\boxed{}.The final answer should be one float number. For example "Final Answer: \\boxed{afloat}"."""
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prompt = instruction + '\n' + instruction_following
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return prompt
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@classmethod
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def _verify_correction(cls, solution, SMILES)->bool:
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"""
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Verify the correction of the solution.
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"""
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mol = Chem.MolFromSmiles(SMILES)
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true_MR = Crippen.MolMR(mol)
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print(f"Comparing pred: {solution}, ground_truth: {true_MR}")
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return abs(true_MR - float(solution)) <= 0.01 # maybe mse or mae better?
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