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

ielts_be/services/abc/third_parties/llm.py

@@ -0,0 +1,38 @@
+from abc import ABC, abstractmethod
+from typing import List, Optional, TypeVar, Callable
+
+from openai.types.chat import ChatCompletionMessageParam
+from pydantic import BaseModel
+
+T = TypeVar('T', bound=BaseModel)
+
+class ILLMService(ABC):
+
+    @abstractmethod
+    async def prediction(
+            self,
+            model: str,
+            messages: List,
+            fields_to_check: Optional[List[str]],
+            temperature: float,
+            check_blacklisted: bool = True,
+            token_count: int = -1
+    ):
+        pass
+
+    @abstractmethod
+    async def prediction_override(self, **kwargs):
+        pass
+
+    @abstractmethod
+    async def pydantic_prediction(
+            self,
+            messages: List[ChatCompletionMessageParam],
+            map_to_model: Callable,
+            json_scheme: str,
+            *,
+            model: Optional[str] = None,
+            temperature: Optional[float] = None,
+            max_retries: int = 3
+    ) -> List[T] | T | None:
+        pass