56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
import uuid
|
|
|
|
from ielts_be.configs.constants import GPTModels, TemperatureSettings
|
|
from ielts_be.helpers import ExercisesHelper
|
|
from ielts_be.services import ILLMService
|
|
|
|
|
|
class TrueFalse:
|
|
|
|
def __init__(self, llm: ILLMService):
|
|
self._llm = llm
|
|
|
|
async def gen_true_false_not_given_exercise(self, text: str, quantity: int, start_id: int, difficulty: str, module: str):
|
|
messages = [
|
|
{
|
|
"role": "system",
|
|
"content": (
|
|
'You are a helpful assistant designed to output JSON on this format: '
|
|
'{"prompts":[{"prompt": "statement_1", "solution": "true/false/not_given"}, '
|
|
'{"prompt": "statement_2", "solution": "true/false/not_given"}]}')
|
|
},
|
|
{
|
|
"role": "user",
|
|
"content": (
|
|
f'Generate {str(quantity)} {difficulty} difficulty statements based on the provided text. '
|
|
'Ensure that your statements accurately represent information or inferences from the text, and '
|
|
'provide a variety of responses, including, at least one of each True, False, and Not Given, '
|
|
f'as appropriate.\n\nReference text:\n\n {text}'
|
|
)
|
|
}
|
|
]
|
|
|
|
response = await self._llm.prediction(
|
|
GPTModels.GPT_4_O, messages, ["prompts"], TemperatureSettings.GEN_QUESTION_TEMPERATURE
|
|
)
|
|
questions = response["prompts"]
|
|
|
|
if len(questions) > quantity:
|
|
questions = ExercisesHelper.remove_excess_questions(questions, len(questions) - quantity)
|
|
|
|
for i, question in enumerate(questions, start=start_id):
|
|
question["id"] = str(i)
|
|
|
|
tail = (
|
|
"the information given in the Reading Passage"
|
|
if module == "reading" else
|
|
"what you've heard"
|
|
)
|
|
|
|
return {
|
|
"id": str(uuid.uuid4()),
|
|
"prompt": f"Do the following statements agree with {tail}?",
|
|
"questions": questions,
|
|
"type": "trueFalse"
|
|
}
|