fix(ocr): sync workflow steps with process_with_ocr replacing legacy azure step

- Update _compute_processing_flow to recognize process_with_ocr as the OCR
  stage and remap legacy process_with_azure_document_intelligence log entries
  for backward compatibility
- Normalize legacy OCR step name in _compute_step_summary log fallback
- Add process_with_ocr to REAL_MAIN_STEPS/REAL_STEPS in step_manager,
  file_status, and file_queries (keeping legacy name for old DB entries)
- Update retry logic in api/files.py to retry failed OCR via process_with_ocr
  (handles both step names as aliases)
- Fix process_document.py to log process_with_ocr as skipped (not azure step)
  for the local text extraction path

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>
This commit is contained in:
copilot-swe-agent[bot]
2026-02-24 22:22:06 +00:00
parent f937fd4971
commit 37a3f7aae7
6 changed files with 34 additions and 22 deletions
+8 -11
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@@ -520,7 +520,8 @@ def _retry_pipeline_step(file_record: FileRecord, step_name: str, db: Session) -
Supports restarting from intermediate pipeline steps:
- process_document: Full reprocessing (skips duplicate check)
- process_with_azure_document_intelligence: OCR processing
- process_with_ocr: OCR processing (multi-provider)
- process_with_azure_document_intelligence: OCR processing (legacy alias for process_with_ocr)
- extract_metadata_with_gpt: Metadata extraction
- embed_metadata_into_pdf: Metadata embedding
@@ -554,16 +555,11 @@ def _retry_pipeline_step(file_record: FileRecord, step_name: str, db: Session) -
original_filename=file_record.original_filename,
file_id=file_id,
)
elif step_name == "process_with_azure_document_intelligence":
from app.tasks.process_with_azure_document_intelligence import (
process_with_azure_document_intelligence,
)
elif step_name in ("process_with_ocr", "process_with_azure_document_intelligence"):
from app.tasks.process_with_ocr import process_with_ocr
# OCR needs the file in workdir/tmp
logger.info(
f"Retrying process_with_azure_document_intelligence for file {file_id}: "
f"local_filename={file_record.local_filename!r}"
)
logger.info(f"Retrying process_with_ocr for file {file_id}: local_filename={file_record.local_filename!r}")
if not file_record.local_filename:
logger.error(f"OCR retry failed for file {file_id}: local_filename is None")
raise HTTPException(status_code=400, detail="Local file path is None. Cannot retry OCR.")
@@ -577,7 +573,7 @@ def _retry_pipeline_step(file_record: FileRecord, step_name: str, db: Session) -
logger.info(f"Found file for OCR retry at: {file_record.local_filename!r}")
filename = os.path.basename(file_record.local_filename)
task = process_with_azure_document_intelligence.delay(filename, file_id)
task = process_with_ocr.delay(filename, file_id)
elif step_name == "extract_metadata_with_gpt":
from app.tasks.extract_metadata_with_gpt import extract_metadata_with_gpt
@@ -701,7 +697,7 @@ def retry_subtask(
Retry a specific failed subtask for a file.
Supports both upload tasks (e.g., upload_to_dropbox) and pipeline processing
steps (e.g., process_with_azure_document_intelligence, extract_metadata_with_gpt,
steps (e.g., process_with_ocr, extract_metadata_with_gpt,
embed_metadata_into_pdf).
Args:
@@ -721,6 +717,7 @@ def retry_subtask(
# Pipeline processing steps that can be retried from the failed step
pipeline_step_names = {
"process_document",
"process_with_ocr",
"process_with_azure_document_intelligence",
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
+1 -1
View File
@@ -476,7 +476,7 @@ def process_document(
# Mark OCR as skipped since we extracted text locally
log_task_progress(
task_id,
"process_with_azure_document_intelligence",
"process_with_ocr",
"skipped",
"Local text extraction succeeded, OCR not needed",
file_id=file_id,
+4 -3
View File
@@ -21,9 +21,9 @@ def apply_status_filter(query: Query, db: Session, status: Optional[str]) -> Que
processing status by examining associated FileProcessingStep entries.
Only tracks "real" processing steps that represent user-facing status:
- Main steps: create_file_record, check_text, extract_text, process_with_azure_document_intelligence,
extract_metadata_with_gpt, embed_metadata_into_pdf, finalize_document_storage,
send_to_all_destinations
- Main steps: create_file_record, check_text, extract_text, process_with_ocr,
process_with_azure_document_intelligence (legacy), extract_metadata_with_gpt,
embed_metadata_into_pdf, finalize_document_storage, send_to_all_destinations
- Upload steps: queue_*, upload_to_*
Diagnostic/internal steps (poll_task, upload_file, set_custom_fields, etc.) are ignored
@@ -58,6 +58,7 @@ def apply_status_filter(query: Query, db: Session, status: Optional[str]) -> Que
"create_file_record",
"check_text",
"extract_text",
"process_with_ocr",
"process_with_azure_document_intelligence",
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
+4 -3
View File
@@ -56,9 +56,9 @@ def get_files_processing_status(db: Session, file_ids: List[int]) -> Dict[int, D
Get processing status for multiple files efficiently.
Only counts "real" processing steps that represent user-facing status:
- Main steps: create_file_record, check_text, extract_text, process_with_azure_document_intelligence,
extract_metadata_with_gpt, embed_metadata_into_pdf, finalize_document_storage,
send_to_all_destinations
- Main steps: create_file_record, check_text, extract_text, process_with_ocr,
process_with_azure_document_intelligence (legacy), extract_metadata_with_gpt,
embed_metadata_into_pdf, finalize_document_storage, send_to_all_destinations
- Upload steps: upload_to_*
Diagnostic/internal steps (poll_task, upload_file, set_custom_fields, etc.) are ignored.
@@ -83,6 +83,7 @@ def get_files_processing_status(db: Session, file_ids: List[int]) -> Dict[int, D
"create_file_record",
"check_text",
"extract_text",
"process_with_ocr",
"process_with_azure_document_intelligence",
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
+6
View File
@@ -201,10 +201,13 @@ def get_file_overall_status(db: Session, file_id: int) -> Dict:
# Define which steps are "real" status-determining steps
# Only high-level logical steps, not implementation sub-steps
# Both process_with_ocr (current) and process_with_azure_document_intelligence (legacy)
# are included to correctly count steps for files processed before the OCR abstraction.
REAL_MAIN_STEPS = {
"create_file_record",
"check_text",
"extract_text",
"process_with_ocr",
"process_with_azure_document_intelligence",
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
@@ -286,10 +289,13 @@ def get_step_summary(db: Session, file_id: int) -> Dict:
"""
# Define which steps are "real" status-determining steps
# Only high-level logical steps, not implementation sub-steps
# Both process_with_ocr (current) and process_with_azure_document_intelligence (legacy)
# are included to correctly count steps for files processed before the OCR abstraction.
REAL_MAIN_STEPS = {
"create_file_record",
"check_text",
"extract_text",
"process_with_ocr",
"process_with_azure_document_intelligence",
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
+11 -4
View File
@@ -222,11 +222,11 @@ def _compute_processing_flow(logs):
"create_file_record": {"label": "Create File Record", "next": ["check_text"]},
"check_text": {
"label": "Check Embedded Text",
"next": ["extract_text", "process_with_azure_document_intelligence"],
"next": ["extract_text", "process_with_ocr"],
},
"extract_text": {"label": "Extract Text (Local)", "next": ["extract_metadata_with_gpt"]},
"process_with_azure_document_intelligence": {
"label": "OCR Processing (Azure)",
"process_with_ocr": {
"label": "OCR Processing",
"next": ["extract_metadata_with_gpt"],
},
"extract_metadata_with_gpt": {"label": "Extract Metadata (GPT)", "next": ["embed_metadata_into_pdf"]},
@@ -285,6 +285,9 @@ def _compute_processing_flow(logs):
{"status": log.status, "message": log.message, "timestamp": log.timestamp, "task_id": log.task_id}
)
else:
# Normalize legacy OCR step name for backward compatibility with old log entries
if step_name == "process_with_azure_document_intelligence":
step_name = "process_with_ocr"
# Regular processing step
if step_name not in step_map:
step_map[step_name] = []
@@ -366,7 +369,7 @@ def _compute_step_summary(logs):
"create_file_record",
"check_text",
"extract_text",
"process_with_azure_document_intelligence",
"process_with_ocr",
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
"finalize_document_storage",
@@ -391,6 +394,10 @@ def _compute_step_summary(logs):
if status == "pending":
status = "queued"
# Normalize legacy OCR step name for backward compatibility
if step_name == "process_with_azure_document_intelligence":
step_name = "process_with_ocr"
# Check if it's an upload task
is_upload = any(step_name.startswith(prefix) for prefix in upload_prefixes)