query_gpt.py

import pandas as pd
from openai import OpenAI

client = OpenAI()
df = pd.read_csv('./Merged_LLU.csv', sep=';')

for i in range(df.shape[0]):
    response = client.responses.create(
        model="o1",
        input=[
            {"role": "system",
             "content": "You are an expert in Answer Set Programming (ASP). Do not output comments or anything other "
                        "than facts and rules. In your response, you must use the following atoms: "
                        "'statement(ID, S, P, O)', where 'ID' is the ID of the sentence, 'S' is the main subject, "
                        "'P' is the main predicate, and 'O' is the object of the sentence; "
                        "'weapon(ID, W)', where 'ID' is the ID of the sentence, and 'W' is the weapon involved "
                        "in the predicate P; "
                        "'incompatible_object(P, O)', where 'O' is an object and 'P' is a predicate of the same "
                        "sentence that cannot be done using the object O; "
                        "'incompatible_predicates(P1, P2)', where 'P1' and 'P2' are two different predicates which "
                        "are not synonyms of each other. "
                        "Example of sentences: "
                        "Sentence1: 'Yesterday, Will said that he saw Mary killing Peter.' "
                        "Sentence2: 'But in front of the judge, Will swore that he saw Mary beating Peter. "
                        "Example of output: statement(s1, mary, kill, peter). statement(s2, mary, beat, peter). "
                        "incompatible_predicates(kill, beat)."
            },
            {"role": "user", "content": [
                {"type": "input_text",
                 "text": "Return ASP facts that model the event involved in the following sentences and their possible "
                         "incompatibilities. If necessary, when you find two words that are similar or synonyms, "
                         "keep only one of the two words. "
                         f"Sentence1: '{df['sentence1'].iloc[i]}' "
                         f"Sentence2: '{df['sentence2'].iloc[i]}' "}
            ]}
        ]
    )
    with open(f'./output/output_o1_{i}.asp', 'w', encoding="utf-8") as f:
        f.write(response.output_text)