style: fix all flake8 linter errors across app/ directory

- Run Black formatter and isort on all app/ files
- Remove unused imports (F401) across multiple files
- Add # noqa: F401 for intentional re-exports in celery_worker.py,
  tasks/__init__.py, utils.py, frontend.py, views/base.py
- Fix f-strings without placeholders (F541) in azure.py, notification.py,
  check_credentials.py, upload_to_onedrive.py, settings.py
- Fix bare except (E722) in upload_to_sftp.py
- Fix block comment format (E265) in models.py
- Move imports to top of file to fix E402 in celery_app.py, celery_worker.py
- Fix line-too-long (E501) by wrapping strings in multiple files
- Remove unused variable (F841) in upload_to_nextcloud.py

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>

app/tasks/refine_text_with_gpt.py

@@ -1,17 +1,15 @@
 #!/usr/bin/env python3
 
-from app.config import settings
 import openai
-from app.tasks.retry_config import BaseTaskWithRetry
 
 # Import the shared Celery instance
 from app.celery_app import celery
+from app.config import settings
+from app.tasks.retry_config import BaseTaskWithRetry
 
 # Initialize OpenAI client dynamically
-client = openai.OpenAI(
-    api_key=settings.openai_api_key,
-    base_url=settings.openai_base_url
-)
+client = openai.OpenAI(api_key=settings.openai_api_key, base_url=settings.openai_base_url)
+
 
 @celery.task(base=BaseTaskWithRetry)
 def refine_text_with_gpt(filename: str, raw_text: str):
@@ -19,16 +17,22 @@ def refine_text_with_gpt(filename: str, raw_text: str):
     response = client.chat.completions.create(
         model=settings.openai_model,
         messages=[
-            {"role": "system", "content": "Clean and format the following text. The idea is that the text you see comes from an OCR system and your task is to eliminate OCR errors. Keep the original language when doing so."},
-            {"role": "user", "content": raw_text}
-        ]
+            {
+                "role": "system",
+                "content": (
+                    "Clean and format the following text. The idea is that the text you see comes from an OCR "
+                    "system and your task is to eliminate OCR errors. Keep the original language when doing so."
+                ),
+            },
+            {"role": "user", "content": raw_text},
+        ],
     )
-    
+
     cleaned_text = response.choices[0].message.content
 
     # Trigger next task (import locally if needed to avoid circular imports)
     from app.tasks.extract_metadata_with_gpt import extract_metadata_with_gpt
+
     extract_metadata_with_gpt.delay(filename, cleaned_text)
 
     return {"filename": filename, "cleaned_text": cleaned_text}
-