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

ielts_be/services/abc/third_parties/__init__.py

@@ -0,0 +1,13 @@
+from .stt import ISpeechToTextService
+from .tts import ITextToSpeechService
+from .llm import ILLMService
+from .vid_gen import IVideoGeneratorService
+from .ai_detector import IAIDetectorService
+
+__all__ = [
+    "ISpeechToTextService",
+    "ITextToSpeechService",
+    "ILLMService",
+    "IVideoGeneratorService",
+    "IAIDetectorService"
+]

ielts_be/services/abc/third_parties/ai_detector.py

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+from abc import ABC, abstractmethod
+from typing import Dict, Optional
+
+
+class IAIDetectorService(ABC):
+
+    @abstractmethod
+    async def run_detection(self, text: str):
+        pass
+
+    @abstractmethod
+    def _parse_detection(self, response: Dict) -> Optional[Dict]:
+        pass

ielts_be/services/abc/third_parties/llm.py

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+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

ielts_be/services/abc/third_parties/stt.py

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+from abc import ABC, abstractmethod
+
+
+class ISpeechToTextService(ABC):
+
+    @abstractmethod
+    async def speech_to_text(self, file: bytes):
+        pass

ielts_be/services/abc/third_parties/tts.py

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+from abc import ABC, abstractmethod
+from typing import Union
+
+
+class ITextToSpeechService(ABC):
+
+    @abstractmethod
+    async def synthesize_speech(self, text: str, voice: str, engine: str, output_format: str):
+        pass
+
+    @abstractmethod
+    async def text_to_speech(self, dialog) -> bytes:
+        pass
+
+    @abstractmethod
+    async def _conversation_to_speech(self, conversation: list):
+        pass
+
+    @abstractmethod
+    async def _text_to_speech(self, text: str):
+        pass
+

ielts_be/services/abc/third_parties/vid_gen.py

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+from abc import ABC, abstractmethod
+from typing import Dict, List, Optional
+
+
+class IVideoGeneratorService(ABC):
+
+    def __init__(self, avatars: Dict):
+        self._avatars = avatars
+
+    async def get_avatars(self) -> List[Dict]:
+        return [
+            {"name": name, "gender": data["avatar_gender"]}
+            for name, data in self._avatars.items()
+        ]
+
+    @abstractmethod
+    async def create_video(self, text: str, avatar: str):
+        pass
+
+    @abstractmethod
+    async def poll_status(self, video_id: str):
+        pass