Patched backend eval

app/services/abc/evaluation.py

@@ -10,6 +10,7 @@ class IEvaluationService(ABC):
     @abstractmethod
     async def create_evaluation(
         self,
+        user_id: str,
         session_id: str,
         exercise_id: str,
         eval_type: EvaluationType,
@@ -20,7 +21,7 @@ class IEvaluationService(ABC):
     @abstractmethod
     async def begin_evaluation(
         self,
-        session_id: str, task: int,
+        user_id: str, session_id: str, task: int,
         exercise_id: str, exercise_type: str,
         solution: any,
         background_tasks: BackgroundTasks

app/services/impl/exam/evaluation.py

@@ -20,6 +20,7 @@ class EvaluationService(IEvaluationService):
 
     async def create_evaluation(
             self,
+            user_id: str,
             session_id: str,
             exercise_id: str,
             eval_type: EvaluationType,
@@ -28,6 +29,7 @@ class EvaluationService(IEvaluationService):
         await self._db.save_to_db(
         "evaluation",
         {
+                "user": user_id,
                 "session_id": session_id,
                 "exercise_id": exercise_id,
                 "type": eval_type,
@@ -38,20 +40,20 @@ class EvaluationService(IEvaluationService):
 
     async def begin_evaluation(
             self,
-            session_id: str, task: int,
+            user_id: str, session_id: str, task: int,
             exercise_id: str, exercise_type: str,
             solution: Union[WritingGradeTaskDTO, List[GradeSpeakingItem]],
             background_tasks: BackgroundTasks
     ):
         background_tasks.add_task(
             self._begin_evaluation,
-            session_id, task,
+            user_id, session_id, task,
             exercise_id, exercise_type,
             solution
         )
 
     async def _begin_evaluation(
-        self, session_id: str, task: int,
+        self, user_id: str, session_id: str, task: int,
         exercise_id: str, exercise_type: str,
         solution: Union[WritingGradeTaskDTO, List[GradeSpeakingItem]]
     ):
@@ -71,6 +73,7 @@ class EvaluationService(IEvaluationService):
             await self._db.update(
                 "evaluation",
                 {
+                    "user": user_id,
                     "exercise_id": exercise_id,
                     "session_id": session_id,
                 },
@@ -87,6 +90,7 @@ class EvaluationService(IEvaluationService):
             await self._db.update(
                 "evaluation",
                 {
+                    "user": user_id,
                     "exercise_id": exercise_id,
                     "session_id": session_id
                 },

app/services/impl/exam/speaking.py

@@ -1,6 +1,8 @@
 import asyncio
 import logging
 import os
+from uuid import uuid4
+
 import aiofiles
 import re
 import uuid
@@ -249,7 +251,17 @@ class SpeakingService(ISpeakingService):
 
                 response['perfect_answer'] = perfect_answers[0]["answer"]
 
+            solutions = []
+            for file_name in temp_files:
+                solutions.append(await self._file_storage.upload_file_firebase_get_url(f'{FilePaths.FIREBASE_SPEAKING_VIDEO_FILES_PATH}{uuid4()}.wav', file_name))
+
             response["overall"] = self._fix_speaking_overall(response["overall"], response["task_response"])
+            response["solutions"] = solutions
+            if task in {1,3}:
+                response["answer"] = solutions
+            else:
+                response["fullPath"] = solutions[0]
+
             self._log(task, request_id, f'Final response: {response}')
             return response
 
@@ -266,7 +278,7 @@ class SpeakingService(ISpeakingService):
 
     @staticmethod
     async def save_file(item: GradeSpeakingItem) -> str:
-        sound_file_name = FilePaths.AUDIO_FILES_PATH + str(uuid.uuid4())
+        sound_file_name = "tmp/" + str(uuid.uuid4())
         content = await item.answer.read()
         async with aiofiles.open(sound_file_name, 'wb') as f:
             await f.write(content)

app/services/impl/third_parties/whisper.py

@@ -26,7 +26,7 @@ class OpenAIWhisper(ISpeechToTextService):
         self._is_closed = False
 
         for i in range(num_models):
-            self._models[i] = whisper.load_model(self._model_name)
+            self._models[i] = whisper.load_model(self._model_name, in_memory=True)
 
         self._executor = ThreadPoolExecutor(
             max_workers=num_models,