feat(tasks): add detailed logging to Azure Document Intelligence task

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>
This commit is contained in:
copilot-swe-agent[bot]
2026-02-11 09:54:53 +00:00
parent 3e78ee4c27
commit acec9954a0
@@ -11,6 +11,7 @@ from app.celery_app import celery
from app.config import settings from app.config import settings
from app.tasks.retry_config import BaseTaskWithRetry from app.tasks.retry_config import BaseTaskWithRetry
from app.tasks.rotate_pdf_pages import rotate_pdf_pages from app.tasks.rotate_pdf_pages import rotate_pdf_pages
from app.utils import log_task_progress
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -56,30 +57,30 @@ def check_page_rotation(result, filename):
Returns: Returns:
dict: Dictionary mapping page indices (integers) to rotation angles dict: Dictionary mapping page indices (integers) to rotation angles
""" """
logger.error(f"Checking rotation for document: {filename}") logger.info(f"Checking rotation for document: {filename}")
rotation_data = {} rotation_data = {}
if not hasattr(result, "pages") or not result.pages: if not hasattr(result, "pages") or not result.pages:
logger.error(f"No page information available for rotation check: {filename}") logger.warning(f"No page information available for rotation check: {filename}")
return rotation_data return rotation_data
for i, page in enumerate(result.pages): for i, page in enumerate(result.pages):
if hasattr(page, "angle"): if hasattr(page, "angle"):
rotation_angle = page.angle rotation_angle = page.angle
if rotation_angle != 0: if rotation_angle != 0:
logger.error(f"Page {i+1} is rotated by {rotation_angle} degrees") logger.info(f"Page {i+1} is rotated by {rotation_angle} degrees")
# Store page index as integer, not string # Store page index as integer, not string
rotation_data[i] = rotation_angle rotation_data[i] = rotation_angle
else: else:
logger.error(f"Page {i+1} has no rotation (0 degrees)") logger.info(f"Page {i+1} has no rotation (0 degrees)")
else: else:
logger.error(f"Page {i+1} rotation information not available") logger.info(f"Page {i+1} rotation information not available")
return rotation_data return rotation_data
@celery.task(base=BaseTaskWithRetry) @celery.task(base=BaseTaskWithRetry, bind=True)
def process_with_azure_document_intelligence(filename: str, file_id: int = None): def process_with_azure_document_intelligence(self, filename: str, file_id: int = None):
""" """
Processes a PDF document using Azure Document Intelligence and overlays OCR text onto Processes a PDF document using Azure Document Intelligence and overlays OCR text onto
the local temporary file (stored under <workdir>/tmp). the local temporary file (stored under <workdir>/tmp).
@@ -96,6 +97,11 @@ def process_with_azure_document_intelligence(filename: str, file_id: int = None)
filename: Name of the file to process filename: Name of the file to process
file_id: Optional file ID to pass through to subsequent tasks file_id: Optional file ID to pass through to subsequent tasks
""" """
task_id = self.request.id
log_task_progress(
task_id, "process_with_azure_document_intelligence", "in_progress",
f"Starting OCR for {filename}", file_id=file_id,
)
try: try:
tmp_file_path = os.path.join(settings.workdir, "tmp", filename) tmp_file_path = os.path.join(settings.workdir, "tmp", filename)
if not os.path.exists(tmp_file_path): if not os.path.exists(tmp_file_path):
@@ -107,7 +113,11 @@ def process_with_azure_document_intelligence(filename: str, file_id: int = None)
error_msg = ( error_msg = (
f"File size ({file_size / (1024 * 1024):.2f} MB) exceeds Azure Document Intelligence limit of 500 MB" f"File size ({file_size / (1024 * 1024):.2f} MB) exceeds Azure Document Intelligence limit of 500 MB"
) )
logger.error(error_msg) logger.error(f"[{task_id}] {error_msg}")
log_task_progress(
task_id, "validate_file", "failure",
f"File too large: {filename}", file_id=file_id, detail=error_msg,
)
return {"error": error_msg, "file": filename, "status": "Failed - Size limit exceeded"} return {"error": error_msg, "file": filename, "status": "Failed - Size limit exceeded"}
# For PDF files, check page count against service limits # For PDF files, check page count against service limits
@@ -116,12 +126,27 @@ def process_with_azure_document_intelligence(filename: str, file_id: int = None)
page_count = get_pdf_page_count(tmp_file_path) page_count = get_pdf_page_count(tmp_file_path)
if page_count is not None and page_count > AZURE_DOC_INTELLIGENCE_LIMITS["max_pages"]: if page_count is not None and page_count > AZURE_DOC_INTELLIGENCE_LIMITS["max_pages"]:
error_msg = f"PDF page count ({page_count}) exceeds Azure Document Intelligence limit of 2000 pages" error_msg = f"PDF page count ({page_count}) exceeds Azure Document Intelligence limit of 2000 pages"
logger.error(error_msg) logger.error(f"[{task_id}] {error_msg}")
log_task_progress(
task_id, "validate_file", "failure",
f"Too many pages: {filename}", file_id=file_id, detail=error_msg,
)
return {"error": error_msg, "file": filename, "status": "Failed - Page limit exceeded"} return {"error": error_msg, "file": filename, "status": "Failed - Page limit exceeded"}
if page_count is None: if page_count is None:
logger.warning(f"Could not determine page count for {filename}, proceeding with processing anyway") logger.warning(
f"[{task_id}] Could not determine page count for {filename}, proceeding with processing anyway"
)
logger.info(f"Processing {filename} with Azure Document Intelligence OCR.") log_task_progress(
task_id, "validate_file", "success",
f"File validation passed for {filename}", file_id=file_id,
)
logger.info(f"[{task_id}] Processing {filename} with Azure Document Intelligence OCR.")
log_task_progress(
task_id, "call_azure_ocr", "in_progress",
f"Sending {filename} to Azure Document Intelligence", file_id=file_id,
)
# Open and send the document for processing # Open and send the document for processing
with open(tmp_file_path, "rb") as f: with open(tmp_file_path, "rb") as f:
@@ -139,16 +164,32 @@ def process_with_azure_document_intelligence(filename: str, file_id: int = None)
searchable_pdf_path = tmp_file_path # Overwrite the original PDF location searchable_pdf_path = tmp_file_path # Overwrite the original PDF location
with open(searchable_pdf_path, "wb") as writer: with open(searchable_pdf_path, "wb") as writer:
writer.writelines(response) writer.writelines(response)
logger.info(f"Searchable PDF saved at: {searchable_pdf_path}") logger.info(f"[{task_id}] Searchable PDF saved at: {searchable_pdf_path}")
# Extract raw text content from the result # Extract raw text content from the result
extracted_text = result.content if result.content else "" extracted_text = result.content if result.content else ""
logger.info(f"Extracted text for {filename}: {len(extracted_text)} characters") logger.info(f"[{task_id}] Extracted text for {filename}: {len(extracted_text)} characters")
log_task_progress(
task_id, "call_azure_ocr", "success",
f"Azure OCR completed for {filename}", file_id=file_id,
detail=f"Extracted {len(extracted_text)} characters, {len(rotation_data)} rotated pages detected",
)
# Trigger page rotation task if rotation is detected, otherwise proceed to metadata extraction # Trigger page rotation task if rotation is detected, otherwise proceed to metadata extraction
rotate_pdf_pages.delay(filename, extracted_text, rotation_data, file_id) rotate_pdf_pages.delay(filename, extracted_text, rotation_data, file_id)
log_task_progress(
task_id, "process_with_azure_document_intelligence", "success",
f"OCR processing complete for {filename}", file_id=file_id,
detail=f"Searchable PDF saved, {len(extracted_text)} characters extracted",
)
return {"file": filename, "searchable_pdf": searchable_pdf_path, "cleaned_text": extracted_text} return {"file": filename, "searchable_pdf": searchable_pdf_path, "cleaned_text": extracted_text}
except Exception as e: except Exception as e:
logger.error(f"Error processing {filename} with Azure Document Intelligence: {e}") logger.error(f"[{task_id}] Error processing {filename} with Azure Document Intelligence: {e}")
log_task_progress(
task_id, "process_with_azure_document_intelligence", "failure",
f"OCR failed for {filename}", file_id=file_id, detail=str(e),
)
raise raise