73 lines
2.5 KiB
Python
73 lines
2.5 KiB
Python
import random
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from app.configs.constants import GPTModels, TemperatureSettings, EducationalContent
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from app.services.abc import ILLMService
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class FillBlanks:
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def __init__(self, llm: ILLMService):
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self._llm = llm
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async def gen_fill_blanks(
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self, quantity: int, start_id: int, size: int, topic=None
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):
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if not topic:
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topic = random.choice(EducationalContent.MTI_TOPICS)
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messages = [
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{
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"role": "system",
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"content": f'You are a helpful assistant designed to output JSON on this format: {self._fill_blanks_mc_template()}'
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},
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{
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"role": "user",
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"content": f'Generate a text of at least {size} words about the topic {topic}.'
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},
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{
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"role": "user",
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"content": (
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f'From the generated text choose {quantity} words (cannot be sequential words) to replace '
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'once with {{id}} where id starts on ' + str(start_id) + ' and is incremented for each word. '
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'The ids must be ordered throughout the text and the words must be replaced only once. '
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'For each removed word you will place it in the solutions array and assign a letter from A to D,'
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' then you will place that removed word and the chosen letter on the words array along with '
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' other 3 other words for the remaining letter. This is a fill blanks question for an english '
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'exam, so don\'t choose words completely at random.'
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)
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}
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]
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question = await self._llm.prediction(
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GPTModels.GPT_4_O, messages, ["question"], TemperatureSettings.GEN_QUESTION_TEMPERATURE
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)
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return {
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**question,
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"type": "fillBlanks",
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"variant": "mc",
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"prompt": "Click a blank to select the appropriate word for it.",
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}
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@staticmethod
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def _fill_blanks_mc_template():
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return {
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"text": "",
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"solutions": [
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{
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"id": "",
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"solution": ""
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}
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],
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"words": [
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{
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"id": "",
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"options": {
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"A": "",
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"B": "",
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"C": "",
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"D": ""
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}
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}
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]
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} |