Files
gh-christianlouis-docuelevate/app/utils/step_manager.py
T
copilot-swe-agent[bot] e6dd39c27d fix(status): prevent false Completed status when mandatory pipeline steps have not run
Add a terminal-step guard (send_to_all_destinations) to all status
calculation paths so that files are only marked Completed once the
entire processing pipeline has been recorded.

- get_file_overall_status: require TERMINAL_STEP to be present
- get_files_processing_status: same guard for bulk status
- get_step_summary: count missing terminal step as queued so
  total_main_steps > main_completed when pipeline is incomplete
- apply_status_filter: SQL sub-query requires terminal step for
  completed filter
- process_document: call initialize_file_steps after creating a new
  file record so all mandatory steps are pre-created as pending

Define TERMINAL_STEP constant in step_manager.py and reference it in
file_status.py and file_queries.py to avoid magic strings.

Tests updated: add send_to_all_destinations to completed-file
fixtures; add test verifying initialize_file_steps is called for
new files.

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>
2026-02-27 00:51:14 +00:00

371 lines
12 KiB
Python

"""
Utility functions for managing file processing step status.
This module provides functions to initialize, update, and query the status
of file processing steps using the FileProcessingStep model.
"""
from datetime import datetime
from typing import Dict, List, Optional
from sqlalchemy.orm import Session
from app.config import settings
from app.models import FileProcessingStep, FileRecord
# Define the expected processing steps for a standard file workflow
# The "check_for_duplicates" step is conditionally included based on enable_deduplication setting
BASE_MAIN_PROCESSING_STEPS = [
"create_file_record",
"check_text",
"extract_text", # Or "process_with_azure_document_intelligence"
"extract_metadata_with_gpt",
"embed_metadata_into_pdf",
"finalize_document_storage",
"send_to_all_destinations",
]
OPTIONAL_PROCESSING_STEPS = {
"check_for_duplicates": settings.enable_deduplication, # Only if deduplication is enabled
}
# The terminal step is the last mandatory step in the processing pipeline.
# A file is only considered "completed" once this step has been recorded.
TERMINAL_STEP = "send_to_all_destinations"
# Combine steps based on configuration
MAIN_PROCESSING_STEPS = []
if settings.enable_deduplication:
MAIN_PROCESSING_STEPS.append("check_for_duplicates")
MAIN_PROCESSING_STEPS.extend(BASE_MAIN_PROCESSING_STEPS)
def initialize_file_steps(db: Session, file_id: int, include_uploads: bool = False) -> None:
"""
Initialize processing steps for a file with 'pending' status.
Args:
db: Database session
file_id: ID of the file
include_uploads: Whether to include upload destination steps (set after destinations are known)
"""
# Initialize main processing steps
for step_name in MAIN_PROCESSING_STEPS:
step = FileProcessingStep(file_id=file_id, step_name=step_name, status="pending")
db.add(step)
db.commit()
def add_upload_steps(db: Session, file_id: int, upload_destinations: List[str]) -> None:
"""
Add upload destination steps for a file.
Args:
db: Database session
file_id: ID of the file
upload_destinations: List of upload destination names (e.g., ["dropbox", "s3", "nextcloud"])
"""
for destination in upload_destinations:
# Add both queue and upload steps for each destination
for prefix in ["queue_", "upload_to_"]:
step_name = f"{prefix}{destination}"
# Check if step already exists
existing = (
db.query(FileProcessingStep)
.filter(FileProcessingStep.file_id == file_id, FileProcessingStep.step_name == step_name)
.first()
)
if not existing:
step = FileProcessingStep(file_id=file_id, step_name=step_name, status="pending")
db.add(step)
db.commit()
def update_step_status(
db: Session,
file_id: int,
step_name: str,
status: str,
error_message: Optional[str] = None,
started_at: Optional[datetime] = None,
completed_at: Optional[datetime] = None,
) -> None:
"""
Update the status of a processing step.
Args:
db: Database session
file_id: ID of the file
step_name: Name of the processing step
status: New status ("pending", "in_progress", "success", "failure", "skipped")
error_message: Error message if status is "failure"
started_at: When the step started (for "in_progress")
completed_at: When the step completed (for "success" or "failure")
"""
step = (
db.query(FileProcessingStep)
.filter(FileProcessingStep.file_id == file_id, FileProcessingStep.step_name == step_name)
.first()
)
if not step:
# Create the step if it doesn't exist
step = FileProcessingStep(
file_id=file_id,
step_name=step_name,
status=status,
started_at=started_at,
completed_at=completed_at,
error_message=error_message,
)
db.add(step)
else:
# Update existing step
step.status = status
if error_message is not None:
step.error_message = error_message
if started_at is not None:
step.started_at = started_at
if completed_at is not None:
step.completed_at = completed_at
db.commit()
def get_file_step_status(db: Session, file_id: int) -> Dict[str, Dict]:
"""
Get the current status of all processing steps for a file.
Args:
db: Database session
file_id: ID of the file
Returns:
Dictionary mapping step_name to status info:
{
"step_name": {
"status": "success",
"started_at": datetime,
"completed_at": datetime,
"error_message": None
},
...
}
"""
steps = db.query(FileProcessingStep).filter(FileProcessingStep.file_id == file_id).all()
result = {}
for step in steps:
result[step.step_name] = {
"status": step.status,
"started_at": step.started_at,
"completed_at": step.completed_at,
"error_message": step.error_message,
}
return result
def get_file_overall_status(db: Session, file_id: int) -> Dict:
"""
Get the overall processing status for a file based on its steps.
Only considers "real" processing steps that represent user-facing status.
Ignores diagnostic/internal steps like poll_task, upload_file, etc.
Args:
db: Database session
file_id: ID of the file
Returns:
Dictionary with overall status info:
{
"status": "completed", # "pending", "processing", "completed", "failed"
"has_errors": False,
"total_steps": 10,
"completed_steps": 8,
"failed_steps": 0,
"in_progress_steps": 2
}
"""
# If file is marked as duplicate, return duplicate status immediately
file_record = db.query(FileRecord).filter(FileRecord.id == file_id).one_or_none()
if file_record and file_record.is_duplicate:
return {
"status": "duplicate",
"has_errors": False,
"total_steps": 0,
"completed_steps": 0,
"failed_steps": 0,
"in_progress_steps": 0,
"skipped_steps": 0,
}
# 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",
"finalize_document_storage",
"send_to_all_destinations",
}
# Add check_for_duplicates if deduplication is enabled
if settings.enable_deduplication:
REAL_MAIN_STEPS.add("check_for_duplicates")
all_steps = db.query(FileProcessingStep).filter(FileProcessingStep.file_id == file_id).all()
# Filter to only real steps
steps = [
s
for s in all_steps
if s.step_name in REAL_MAIN_STEPS or s.step_name.startswith("queue_") or s.step_name.startswith("upload_to_")
]
if not steps:
return {
"status": "pending",
"has_errors": False,
"total_steps": 0,
"completed_steps": 0,
"failed_steps": 0,
"in_progress_steps": 0,
}
total_steps = len(steps)
completed_steps = sum(1 for s in steps if s.status == "success")
failed_steps = sum(1 for s in steps if s.status == "failure")
in_progress_steps = sum(1 for s in steps if s.status == "in_progress")
skipped_steps = sum(1 for s in steps if s.status == "skipped")
has_errors = failed_steps > 0
# Determine overall status
if has_errors:
status = "failed"
elif in_progress_steps > 0:
status = "processing"
elif completed_steps + skipped_steps == total_steps:
# Only mark as completed if the terminal processing step has been recorded.
# Without this guard, files where later pipeline steps have not yet started
# would be falsely marked as "completed" (e.g. only the first 3 steps ran).
existing_step_names = {s.step_name for s in steps}
if TERMINAL_STEP in existing_step_names:
status = "completed"
else:
status = "pending"
else:
status = "pending"
return {
"status": status,
"has_errors": has_errors,
"total_steps": total_steps,
"completed_steps": completed_steps,
"failed_steps": failed_steps,
"in_progress_steps": in_progress_steps,
"skipped_steps": skipped_steps,
}
def get_step_summary(db: Session, file_id: int) -> Dict:
"""
Get a summary of main steps vs upload steps with status counts.
Only counts "real" processing steps that represent user-facing status.
Ignores diagnostic/internal steps like poll_task, upload_file, etc.
Args:
db: Database session
file_id: ID of the file
Returns:
Dictionary with step counts:
{
"main": {"queued": 0, "in_progress": 1, "success": 7, "failure": 0, "skipped": 0},
"uploads": {"queued": 2, "in_progress": 0, "success": 4, "failure": 0, "skipped": 0},
"total_main_steps": 8,
"total_upload_tasks": 6
}
"""
# 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",
"finalize_document_storage",
"send_to_all_destinations",
}
# Add check_for_duplicates if deduplication is enabled
if settings.enable_deduplication:
REAL_MAIN_STEPS.add("check_for_duplicates")
steps = db.query(FileProcessingStep).filter(FileProcessingStep.file_id == file_id).all()
main_counts = {"queued": 0, "in_progress": 0, "success": 0, "failure": 0, "skipped": 0}
upload_counts = {"queued": 0, "in_progress": 0, "success": 0, "failure": 0, "skipped": 0}
main_steps_count = 0
upload_steps_count = 0
for step in steps:
# Normalize status
status = step.status.lower()
if status == "pending":
status = "queued"
# Check if it's an upload task (only count actual upload_to_* steps, not queue_* steps)
is_upload = step.step_name.startswith("upload_to_")
# Only count "real" steps
is_real_step = step.step_name in REAL_MAIN_STEPS or is_upload or step.step_name.startswith("queue_")
if not is_real_step:
# Skip diagnostic/internal steps like poll_task, upload_file, set_custom_fields, etc.
continue
if is_upload:
if status in upload_counts:
upload_counts[status] += 1
upload_steps_count += 1
elif step.step_name in REAL_MAIN_STEPS:
if status in main_counts:
main_counts[status] += 1
main_steps_count += 1
# Ensure the terminal step is always counted in total_main_steps.
# If the terminal step has not been recorded yet, the pipeline is not
# complete; counting it as "queued" prevents the status banner from
# showing "Completed" before the full pipeline has run.
# Note: if TERMINAL_STEP already appears in `steps`, the loop above has
# already incremented `main_steps_count` for it, so we only add here when
# the step is absent from the DB entirely.
if not any(step.step_name == TERMINAL_STEP for step in steps if step.step_name in REAL_MAIN_STEPS):
main_steps_count += 1
main_counts["queued"] += 1
return {
"main": main_counts,
"uploads": upload_counts,
"total_main_steps": main_steps_count,
"total_upload_tasks": upload_steps_count,
}