Brushed up the backend, added writing task 1 academic prompt gen and grading ENCOA-274

ielts_be/services/impl/exam/shared/__init__.py

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+from .true_false import TrueFalse
+from .multiple_choice import MultipleChoice
+
+__all__ = [
+    "TrueFalse",
+    "MultipleChoice"
+]

ielts_be/services/impl/exam/shared/multiple_choice.py

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+import uuid
+
+from ielts_be.configs.constants import GPTModels, TemperatureSettings
+from ielts_be.helpers import ExercisesHelper
+from ielts_be.services import ILLMService
+
+
+class MultipleChoice:
+
+    def __init__(self, llm: ILLMService):
+        self._llm = llm
+
+    async def gen_multiple_choice(
+            self, text: str, quantity: int, start_id: int, difficulty: str, n_options: int = 4
+    ):
+        messages = [
+            {
+                "role": "system",
+                "content": (
+                    'You are a helpful assistant designed to output JSON on this format: '
+                    '{"questions": [{"id": "9", "options": [{"id": "A", "text": "Economic benefits"}, {"id": "B", "text": '
+                    '"Government regulations"}, {"id": "C", "text": "Concerns about climate change"}, {"id": "D", "text": '
+                    '"Technological advancement"}], "prompt": "What is the main reason for the shift towards renewable '
+                    'energy sources?", "solution": "C", "variant": "text"}]}')
+            },
+            {
+                "role": "user",
+                "content": (
+                        f'Generate {quantity} {difficulty} difficulty multiple choice questions of {n_options} '
+                        f'options for this text:\n"' + text + '"')
+
+            }
+        ]
+
+        questions = await self._llm.prediction(
+            GPTModels.GPT_4_O,
+            messages,
+            ["questions"],
+            TemperatureSettings.GEN_QUESTION_TEMPERATURE
+        )
+        return {
+            "id": str(uuid.uuid4()),
+            "prompt": "Select the appropriate option.",
+            "questions": ExercisesHelper.fix_exercise_ids(questions, start_id)["questions"],
+            "type": "multipleChoice",
+        }

ielts_be/services/impl/exam/shared/true_false.py

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+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"
+        }