ENCOA-274 and patch to the Dockerfile, in some merge the firebase tools were left out

Dockerfile

@@ -29,6 +29,11 @@ RUN apt update && apt install -y \
     librsvg2-bin \
     && rm -rf /var/lib/apt/lists/*
 
+RUN curl -sL https://deb.nodesource.com/setup_20.x | bash - \
+    && apt-get install -y nodejs
+
+RUN npm install -g firebase-tools
+
 RUN pip install --no-cache-dir -r /app/requirements.txt
 
 EXPOSE 8000

ielts_be/configs/dependency_injection.py

@@ -94,7 +94,7 @@ class DependencyInjector:
         )
 
         self._container.writing_service = providers.Factory(
-            WritingService, llm=self._container.llm, ai_detector=self._container.ai_detector
+            WritingService, llm=self._container.llm, ai_detector=self._container.ai_detector, file_storage=self._container.firebase_instance
         )
 
         with open('ielts_be/services/impl/exam/level/mc_variants.json', 'r') as file:

ielts_be/controllers/impl/exam/writing.py

@@ -15,5 +15,4 @@ class WritingController(IWritingController):
     async def get_writing_task_academic_question(self, task: int, attachment: UploadFile, difficulty: str):
         if attachment.content_type not in ['image/jpeg', 'image/png']:
             raise HTTPException(status_code=400, detail="Invalid file type. Only JPEG and PNG allowed.")
-
         return await self._service.get_writing_task_academic_question(task, attachment, difficulty)

ielts_be/controllers/impl/user.py

@@ -7,6 +7,7 @@ class UserController(IUserController):
 
     def __init__(self, user_service: IUserService):
         self._service = user_service
+        print(self._service)
 
     async def batch_import(self, batch: BatchUsersDTO):
         return await self._service.batch_users(batch)

ielts_be/dtos/writing.py

@@ -9,5 +9,4 @@ class WritingGradeTaskDTO(BaseModel):
     exerciseId: str
     question: str
     answer: str
-    type: str
     attachment: Optional[str]

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

@@ -55,10 +55,8 @@ class WritingService(IWritingService):
             *(await get_writing_args_academic(task, file))
         ]
 
-        llm_model = GPTModels.GPT_3_5_TURBO if task == 1 else GPTModels.GPT_4_O
-
         response = await self._llm.prediction(
-            llm_model,
+            GPTModels.GPT_4_O,
             messages,
             ["prompt"],
             TemperatureSettings.GEN_QUESTION_TEMPERATURE

ielts_be/services/impl/exam/writing/academic.py

@@ -25,6 +25,9 @@ async def get_writing_args_academic(task: int, attachment: UploadFile) -> List[D
     if task == 2:
         raise NotImplemented("Task 2 academic isn't implemented yet, current implementation still uses General Task 2 prompts.")
 
+    attachment_bytes = await attachment.read()
+
+
     messages = [
         {
             "role": "user",
@@ -32,17 +35,19 @@ async def get_writing_args_academic(task: int, attachment: UploadFile) -> List[D
         },
         {
             "role": "user",
-            "content": writing_args[str(task)]["instructions"]
+            "content": [
+                {
+                    "type": "text",
+                    "text": writing_args[str(task)]["instructions"],
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": f"data:image/{attachment.filename.split('.')[-1]};base64,{b64encode(attachment_bytes).decode('utf-8')}"
+                    }
+                }
+            ]
         }
     ]
 
-    if task == 1:
-        attachment_bytes = await attachment.read()
-        messages.append({
-            "type": "image_url",
-            "image_url": {
-                "url": f"data:image/{attachment.filename.split('.')[-1]};base64,{b64encode(attachment_bytes).decode('utf-8')}"
-            }
-        })
-
     return messages

ielts_be/services/impl/exam/writing/grade.py

@@ -57,14 +57,17 @@ class GradeWriting:
                     name = attachment.split('/')[-1]
                     out_path = f'./tmp/{uuid}/{name}'
                     path = await self._file_storage.download_firebase_file(attachment, out_path)
-                    messages.append({
-                        "type": "image_url",
-                        "image_url": {
-                            "url": f"data:image/{name.split('.')[-1]};base64,{FileHelper.encode_image(path)}"
+                    messages.append(
+                        {
+                            "role": "user",
+                            "content": {
+                                "type": "image_url",
+                                "image_url": {
+                                "url": f"data:image/{name.split('.')[-1]};base64,{FileHelper.encode_image(path)}"
+                            }
                         }
                     })
 
-            llm_model = GPTModels.GPT_3_5_TURBO if task == 1 else GPTModels.GPT_4_O
             temperature = (
                 TemperatureSettings.GRADING_TEMPERATURE
                 if task == 1 else
@@ -72,7 +75,7 @@ class GradeWriting:
             )
 
             evaluation_promise = self._llm.prediction(
-                llm_model,
+                GPTModels.GPT_4_O,
                 messages,
                 ["comment"],
                 temperature

ielts_be/services/impl/third_parties/openai.py

@@ -93,7 +93,10 @@ class OpenAI(ILLMService):
     def _count_total_tokens(messages):
         total_tokens = 0
         for message in messages:
-            total_tokens += count_tokens(message["content"])["n_tokens"]
+            # Skip when content isn't text
+            message_content = message.get("content", None)
+            if message_content is not None and isinstance(message_content, str):
+                total_tokens += count_tokens(message["content"])["n_tokens"]
         return total_tokens
 
     @staticmethod