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