Changes to endpoints so they allow to only get context and then the exercises as well as tidying up a bit
This commit is contained in:
Carlos-Mesquita
@@ -1,5 +1,191 @@
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from .level import LevelService
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from typing import Dict, Optional
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from fastapi import UploadFile
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__all__ = [
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"LevelService"
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]
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from app.dtos.level import LevelExercisesDTO
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from app.repositories.abc import IDocumentStore
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from app.services.abc import (
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ILevelService, ILLMService, IReadingService,
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IWritingService, IListeningService, ISpeakingService
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)
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from .exercises import MultipleChoice, BlankSpace, PassageUtas, FillBlanks
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from .full_exams import CustomLevelModule, LevelUtas
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from .upload import UploadLevelModule
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class LevelService(ILevelService):
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def __init__(
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self,
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llm: ILLMService,
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document_store: IDocumentStore,
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mc_variants: Dict,
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reading_service: IReadingService,
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writing_service: IWritingService,
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speaking_service: ISpeakingService,
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listening_service: IListeningService
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):
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self._llm = llm
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self._document_store = document_store
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self._reading_service = reading_service
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self._upload_module = UploadLevelModule(llm)
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self._mc_variants = mc_variants
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self._mc = MultipleChoice(llm, mc_variants)
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self._blank_space = BlankSpace(llm, mc_variants)
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self._passage_utas = PassageUtas(llm, reading_service, mc_variants)
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self._fill_blanks = FillBlanks(llm)
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self._level_utas = LevelUtas(llm, self, mc_variants)
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self._custom = CustomLevelModule(
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llm, self, reading_service, listening_service, writing_service, speaking_service
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)
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async def upload_level(self, upload: UploadFile) -> Dict:
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return await self._upload_module.generate_level_from_file(upload)
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async def generate_exercises(self, dto: LevelExercisesDTO):
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exercises = []
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start_id = 1
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for req_exercise in dto.exercises:
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if req_exercise.type == "multipleChoice":
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questions = await self._mc.gen_multiple_choice("normal", req_exercise.quantity, start_id)
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exercises.append(questions)
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elif req_exercise.type == "mcBlank":
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questions = await self._mc.gen_multiple_choice("blank_space", req_exercise.quantity, start_id)
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questions["variant"] = "mc"
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exercises.append(questions)
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elif req_exercise.type == "mcUnderline":
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questions = await self._mc.gen_multiple_choice("underline", req_exercise.quantity, start_id)
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exercises.append(questions)
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elif req_exercise.type == "blankSpaceText":
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questions = await self._blank_space.gen_blank_space_text_utas(
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req_exercise.quantity, start_id, req_exercise.text_size, req_exercise.topic
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)
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exercises.append(questions)
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elif req_exercise.type == "passageUtas":
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questions = await self._passage_utas.gen_reading_passage_utas(
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start_id, req_exercise.mc_qty, req_exercise.text_size
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)
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exercises.append(questions)
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elif req_exercise.type == "fillBlanksMC":
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questions = await self._passage_utas.gen_reading_passage_utas(
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start_id, req_exercise.mc_qty, req_exercise.text_size
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)
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exercises.append(questions)
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start_id = start_id + req_exercise.quantity
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return exercises
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# Just here to support other modules that I don't know if they are supposed to still be used
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async def gen_multiple_choice(self, mc_variant: str, quantity: int, start_id: int = 1):
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return await self._mc.gen_multiple_choice(mc_variant, quantity, start_id)
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async def gen_reading_passage_utas(self, start_id, mc_quantity: int, topic=Optional[str]): # sa_quantity: int,
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return await self._passage_utas.gen_reading_passage_utas(start_id, mc_quantity, topic)
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async def gen_blank_space_text_utas(self, quantity: int, start_id: int, size: int, topic: str):
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return await self._blank_space.gen_blank_space_text_utas(quantity, start_id, size, topic)
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async def get_level_exam(
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self, number_of_exercises: int = 25, min_timer: int = 25, diagnostic: bool = False
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) -> Dict:
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pass
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async def get_level_utas(self):
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return await self._level_utas.get_level_utas()
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async def get_custom_level(self, data: Dict):
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return await self._custom.get_custom_level(data)
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"""
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async def _generate_single_multiple_choice(self, mc_variant: str = "normal"):
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mc_template = self._mc_variants[mc_variant]["questions"][0]
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blank_mod = " blank space " if mc_variant == "blank_space" else " "
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messages = [
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{
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"role": "system",
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"content": (
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f'You are a helpful assistant designed to output JSON on this format: {mc_template}'
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)
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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 1 multiple choice {blank_mod} question of 4 options for an english level exam, '
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f'it can be easy, intermediate or advanced.'
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)
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}
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]
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if mc_variant == "underline":
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messages.append({
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"role": "user",
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"content": (
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'The type of multiple choice in the prompt has wrong words or group of words and the options '
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'are to find the wrong word or group of words that are underlined in the prompt. \nExample:\n'
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'Prompt: "I <u>complain</u> about my boss <u>all the time</u>, but my colleagues <u>thinks</u> '
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'the boss <u>is</u> nice."\n'
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'Options:\na: "complain"\nb: "all the time"\nc: "thinks"\nd: "is"'
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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, ["options"], TemperatureSettings.GEN_QUESTION_TEMPERATURE
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)
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return question
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"""
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"""
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async def _replace_exercise_if_exists(
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self, all_exams, current_exercise, current_exam, seen_keys, mc_variant: str, utas: bool = False
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):
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# Extracting relevant fields for comparison
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key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options'])))
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# Check if the key is in the set
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if key in seen_keys:
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return await self._replace_exercise_if_exists(
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all_exams, await self._generate_single_multiple_choice(mc_variant), current_exam, seen_keys,
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mc_variant, utas
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)
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else:
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seen_keys.add(key)
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if not utas:
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for exam in all_exams:
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exam_dict = exam.to_dict()
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if len(exam_dict.get("parts", [])) > 0:
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exercise_dict = exam_dict.get("parts", [])[0]
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if len(exercise_dict.get("exercises", [])) > 0:
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if any(
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exercise["prompt"] == current_exercise["prompt"] and
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any(exercise["options"][0]["text"] == current_option["text"] for current_option in
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current_exercise["options"])
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for exercise in exercise_dict.get("exercises", [])[0]["questions"]
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):
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return await self._replace_exercise_if_exists(
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all_exams, await self._generate_single_multiple_choice(mc_variant), current_exam,
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seen_keys, mc_variant, utas
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)
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else:
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for exam in all_exams:
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if any(
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exercise["prompt"] == current_exercise["prompt"] and
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any(exercise["options"][0]["text"] == current_option["text"] for current_option in
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current_exercise["options"])
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for exercise in exam.get("questions", [])
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):
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return await self._replace_exercise_if_exists(
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all_exams, await self._generate_single_multiple_choice(mc_variant), current_exam,
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seen_keys, mc_variant, utas
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)
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return current_exercise, seen_keys
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"""
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