Changes to endpoints so they allow to only get context and then the exercises as well as tidying up a bit
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49
app/services/impl/exam/reading/true_false.py
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49
app/services/impl/exam/reading/true_false.py
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import uuid
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from app.configs.constants import GPTModels, TemperatureSettings
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from app.helpers import ExercisesHelper
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from app.services.abc import ILLMService
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class TrueFalse:
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def __init__(self, llm: ILLMService):
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self._llm = llm
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async def gen_true_false_not_given_exercise(self, text: str, quantity: int, start_id: int, difficulty: str):
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messages = [
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{
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"role": "system",
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"content": (
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'You are a helpful assistant designed to output JSON on this format: '
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'{"prompts":[{"prompt": "statement_1", "solution": "true/false/not_given"}, '
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'{"prompt": "statement_2", "solution": "true/false/not_given"}]}')
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},
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{
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"role": "user",
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"content": (
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f'Generate {str(quantity)} {difficulty} difficulty statements based on the provided text. '
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'Ensure that your statements accurately represent information or inferences from the text, and '
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'provide a variety of responses, including, at least one of each True, False, and Not Given, '
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f'as appropriate.\n\nReference text:\n\n {text}'
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)
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}
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]
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response = await self._llm.prediction(
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GPTModels.GPT_4_O, messages, ["prompts"], TemperatureSettings.GEN_QUESTION_TEMPERATURE
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)
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questions = response["prompts"]
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if len(questions) > quantity:
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questions = ExercisesHelper.remove_excess_questions(questions, len(questions) - quantity)
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for i, question in enumerate(questions, start=start_id):
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question["id"] = str(i)
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return {
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"id": str(uuid.uuid4()),
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"prompt": "Do the following statements agree with the information given in the Reading Passage?",
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"questions": questions,
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"type": "trueFalse"
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}
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