trueFalse added to listening

app/services/impl/exam/reading/__init__.py

@@ -10,7 +10,7 @@ from app.services.abc import IReadingService, ILLMService
 from .fill_blanks import FillBlanks
 from .idea_match import IdeaMatch
 from .paragraph_match import ParagraphMatch
-from .true_false import TrueFalse
+from ..shared import TrueFalse
 from .import_reading import ImportReadingModule
 from .write_blanks import WriteBlanks
 
@@ -88,7 +88,7 @@ class ReadingService(IReadingService):
 
         elif req_exercise.type == "trueFalse":
             question = await self._true_false.gen_true_false_not_given_exercise(
-                text, req_exercise.quantity, start_id, difficulty
+                text, req_exercise.quantity, start_id, difficulty, "reading"
             )
             self._logger.info(f"Added trueFalse: {question}")
             return question

app/services/impl/exam/reading/true_false.py

@@ -1,49 +0,0 @@
-import uuid
-
-from app.configs.constants import GPTModels, TemperatureSettings
-from app.helpers import ExercisesHelper
-from app.services.abc 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):
-        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)
-
-        return {
-            "id": str(uuid.uuid4()),
-            "prompt": "Do the following statements agree with the information given in the Reading Passage?",
-            "questions": questions,
-            "type": "trueFalse"
-        }