Merge branch 'main' into copilot/add-file-processing-notifications

This commit is contained in:
Christian Krakau-Louis
2026-02-07 15:37:17 +01:00
committed by GitHub
19 changed files with 1606 additions and 113 deletions
+132
View File
@@ -0,0 +1,132 @@
# Copilot Instructions for DocuElevate
## Project Overview
DocuElevate is an intelligent document processing system that automates handling, extraction, and processing of documents. It integrates with multiple cloud storage providers (Dropbox, Google Drive, OneDrive, S3, Nextcloud) and uses AI services (OpenAI, Azure Document Intelligence) for metadata extraction and OCR.
## Tech Stack
- **Backend**: FastAPI, SQLAlchemy, Celery, Redis
- **Frontend**: Jinja2 templates, Tailwind CSS
- **AI/ML**: OpenAI API, Azure Document Intelligence
- **Auth**: Authentik (OAuth2), Basic Auth
- **Infrastructure**: Docker, Docker Compose, Alembic (migrations)
- **Testing**: Pytest, pytest-asyncio, httpx
## Core Principles
### Code Quality
- Always use **Black** for formatting (line length: 120)
- Use **isort** with Black profile for import sorting
- Use **flake8** for linting (ignore E203, W503)
- Use **type hints** for all function parameters and return values
- Write **docstrings** for all public functions, classes, and modules
- Maintain **80% test coverage** for new code
### Python Conventions
- Use descriptive variable names (e.g., `user_document_path`, not `udp`)
- Follow PEP 8 naming: `snake_case` for functions/variables, `PascalCase` for classes
- Use type hints from `typing` module (Dict, List, Optional, etc.)
- Prefer `pathlib.Path` over string paths for file operations
- Use f-strings for string formatting, not `.format()` or `%`
- Handle exceptions explicitly - avoid bare `except:` clauses
### Security Best Practices
- **Never commit secrets or credentials** to the repository
- Use environment variables for sensitive configuration (see `.env.demo`)
- Validate and sanitize all user inputs
- Use parameterized queries with SQLAlchemy (never raw SQL with user input)
- Review [SECURITY_AUDIT.md](../SECURITY_AUDIT.md) before making security-related changes
- Run `bandit` to check for security issues in Python code
### FastAPI Patterns
- Organize endpoints by feature in `app/api/` directory
- Use dependency injection for database sessions and authentication
- Return Pydantic models from endpoints for automatic validation
- Use proper HTTP status codes (200, 201, 400, 401, 403, 404, 500)
- Document endpoints with docstrings for OpenAPI documentation
- Use `async def` for I/O-bound operations
### Database (SQLAlchemy)
- All models are defined in `app/models.py`
- Use Alembic for schema migrations (create migration for any model change)
- Use declarative base for models
- Define relationships with `relationship()` and proper `back_populates`
- Use database sessions from `app.database.get_db()` dependency
- Always close sessions in `finally` blocks or use context managers
### Celery Tasks
- Define tasks in `app/tasks/` directory, organized by feature
- Use descriptive task names: `module.action` (e.g., `document.process_ocr`)
- Set appropriate retry policies and error handling
- Log progress and errors using Python's `logging` module
- Use `bind=True` for tasks that need access to task instance
- Keep tasks idempotent when possible
### Frontend
- Templates are in `frontend/templates/` using Jinja2
- Static files (CSS, JS, images) in `frontend/static/`
- Use Tailwind CSS utility classes (already configured)
- Keep JavaScript minimal - prefer server-side rendering
- Follow existing template structure and patterns
### Testing
- Write tests in `tests/` directory, mirroring `app/` structure
- Use pytest markers: `@pytest.mark.unit`, `@pytest.mark.integration`, etc.
- Mock external services (OpenAI, Azure, cloud storage) in tests
- Use `pytest.fixture` for test setup and teardown
- Run tests with: `pytest -v`
- Check coverage with: `pytest --cov=app --cov-report=term-missing`
### Configuration
- All configuration is in `app/config.py` using Pydantic Settings
- Use environment variables for configuration (12-factor app)
- Provide sensible defaults when possible
- Document all configuration options in `docs/ConfigurationGuide.md`
### Documentation
- Keep documentation in `docs/` directory in Markdown format
- Update relevant docs when adding features or changing behavior
- User-facing documentation should be clear and include examples
- Reference existing docs: `docs/UserGuide.md`, `docs/API.md`, `docs/DeploymentGuide.md`
- See [AGENTIC_CODING.md](../AGENTIC_CODING.md) for detailed development guide
### Error Handling
- Use custom exceptions defined in application (follow existing patterns)
- Log errors with context using Python's `logging` module
- Return user-friendly error messages in API responses
- Include error details in development, sanitize in production
### Dependencies
- Add new dependencies to `requirements.txt` (production) or `requirements-dev.txt` (development)
- Document any new dependencies and their licenses in README.md
- Check for security vulnerabilities with `safety check`
- Pin major versions, allow minor updates (e.g., `fastapi>=0.100.0,<1.0.0`)
### Git Workflow
- Write clear, descriptive commit messages
- Keep commits focused and atomic
- Run tests and linters before committing
- Pre-commit hooks are configured (`.pre-commit-config.yaml`)
- Follow conventional commits format when appropriate
### File Organization
- Place API endpoints in `app/api/` organized by feature
- Background tasks go in `app/tasks/`
- Utility functions in `app/utils/`
- UI routes in `app/views/`
- Database models in `app/models.py`
- Configuration in `app/config.py`
### Common Patterns
- Use `from typing import Optional, Dict, List, Any` for type hints
- Import FastAPI dependencies: `from fastapi import Depends, HTTPException, status`
- Get DB session: `db: Session = Depends(get_db)`
- Current user: `current_user: User = Depends(get_current_user)`
- Logger: `import logging; logger = logging.getLogger(__name__)`
## Resources
- [AGENTIC_CODING.md](../AGENTIC_CODING.md) - Comprehensive development guide
- [CONTRIBUTING.md](../CONTRIBUTING.md) - Contribution guidelines
- [SECURITY_AUDIT.md](../SECURITY_AUDIT.md) - Security considerations
- [README.md](../README.md) - Project overview and quickstart
@@ -0,0 +1,267 @@
---
applyTo: "docs/**/*.md"
---
# Documentation Instructions
These instructions apply to all documentation files in the `docs/` directory.
## Documentation Structure
- User-facing documentation in `docs/` directory
- All documentation in Markdown format
- Follow existing documentation style and structure
## Existing Documentation
- `docs/UserGuide.md` - How to use DocuElevate
- `docs/API.md` - API reference and examples
- `docs/DeploymentGuide.md` - Deployment instructions
- `docs/ConfigurationGuide.md` - Configuration options
- `docs/Troubleshooting.md` - Common issues and solutions
- `AGENTIC_CODING.md` - Development guide for AI agents
- `CONTRIBUTING.md` - Contribution guidelines
- `README.md` - Project overview and quickstart
## Markdown Style
### Headers
```markdown
# H1 - Document Title (only one per file)
## H2 - Major Sections
### H3 - Subsections
#### H4 - Minor subsections (use sparingly)
```
### Code Blocks
Always specify the language for syntax highlighting:
````markdown
```python
def example_function():
"""Example Python code."""
return "Hello, World!"
```
```bash
# Shell commands
docker-compose up -d
```
```json
{
"key": "value"
}
```
````
### Lists
```markdown
- Unordered list item 1
- Unordered list item 2
- Nested item
- Another nested item
1. Ordered list item 1
2. Ordered list item 2
3. Ordered list item 3
```
### Links
```markdown
[Link text](https://example.com)
[Internal link](./UserGuide.md)
[Link to section](#installation)
```
### Images
```markdown
![Alt text](path/to/image.png)
<div align="center">
<img src="path/to/image.png" alt="Descriptive alt text" width="80%" />
<p><em>Image caption</em></p>
</div>
```
### Tables
```markdown
| Column 1 | Column 2 | Column 3 |
|----------|----------|----------|
| Value 1 | Value 2 | Value 3 |
| Value 4 | Value 5 | Value 6 |
```
### Admonitions and Notes
```markdown
> **Note:** This is an important note.
> **Warning:** This is a warning message.
> **Tip:** This is a helpful tip.
```
## Content Guidelines
### Writing Style
- Use clear, concise language
- Write in second person (you/your) for user-facing docs
- Use present tense
- Avoid jargon; explain technical terms when necessary
- Use active voice
- Keep sentences short and focused
### Documentation Types
#### User Documentation
- Focus on **how to use** features, not implementation details
- Include step-by-step instructions
- Provide examples for common use cases
- Add screenshots or diagrams when helpful
- Explain what each feature does and when to use it
Example:
```markdown
## Uploading Documents
To upload a document to DocuElevate:
1. Navigate to the Upload page
2. Click "Choose File" and select your document
3. Select the destination (Dropbox, Google Drive, etc.)
4. Click "Upload"
The document will be automatically processed and stored in your selected destination.
```
#### API Documentation
- Document all endpoints with examples
- Show request and response formats
- Include authentication requirements
- Provide example curl commands
- Document error responses
Example:
```markdown
### POST /api/documents/upload
Upload a new document for processing.
**Authentication:** Required
**Request:**
```bash
curl -X POST "http://localhost:8000/api/documents/upload" \
-H "Authorization: Bearer YOUR_TOKEN" \
-F "file=@document.pdf"
```
**Response (201 Created):**
```json
{
"id": 123,
"filename": "document.pdf",
"status": "processing"
}
```
```
#### Configuration Documentation
- List all configuration options
- Provide default values
- Explain what each option does
- Include example configurations
- Note which options are required vs. optional
Example:
```markdown
### OPENAI_API_KEY
**Type:** String
**Required:** Yes
**Default:** None
Your OpenAI API key for metadata extraction.
```bash
OPENAI_API_KEY=sk-...
```
```
#### Troubleshooting Documentation
- Start with the symptom/error
- Provide clear diagnosis steps
- Offer solutions
- Include common causes
Example:
```markdown
### Error: "Connection refused" when starting services
**Cause:** Docker services are not running or ports are already in use.
**Solution:**
1. Check if Docker is running: `docker ps`
2. Check port availability: `lsof -i :8000`
3. Restart Docker services: `docker-compose restart`
```
## Code Examples
- Always test code examples before including them
- Use realistic examples that users can adapt
- Include comments explaining non-obvious parts
- Show complete examples, not just fragments
## Version Information
- Update documentation when changing features
- Note version numbers when features are added
- Mark deprecated features clearly
## Cross-References
- Link to related documentation
- Reference other sections when appropriate
- Keep the documentation interconnected
Example:
```markdown
For deployment instructions, see the [Deployment Guide](./DeploymentGuide.md).
For API details, refer to the [API Documentation](./API.md).
```
## Updating Documentation
When making code changes:
1. Update relevant documentation in the same PR
2. Check for outdated information
3. Add new sections for new features
4. Update examples if behavior changes
5. Review related documentation for consistency
## Screenshots and Diagrams
- Use clear, high-quality images
- Annotate screenshots when helpful
- Keep diagrams simple and focused
- Update screenshots when UI changes
- Use consistent styling in diagrams
## Accessibility
- Use descriptive alt text for images
- Ensure proper heading hierarchy
- Make links descriptive (avoid "click here")
- Use semantic formatting (bold, italic, code) appropriately
## README.md Specific
- Keep README concise and focused on getting started
- Include badges for build status, version, license
- Show the most important features first
- Link to detailed documentation
- Include quick start instructions
- Add screenshots of the main interface
## Configuration Guide Updates
When adding new configuration options:
- Add to `docs/ConfigurationGuide.md`
- Include type, default value, and description
- Provide example usage
- Note any dependencies on other config options
- Update `.env.demo` with the new option
@@ -0,0 +1,152 @@
---
applyTo: "frontend/**/*"
---
# Frontend Instructions
These instructions apply to all files in the `frontend/` directory (templates, CSS, JavaScript, images).
## Templates (Jinja2)
### Location and Structure
- All templates in `frontend/templates/`
- Use template inheritance with `base.html`
- Keep templates organized by feature
### Template Patterns
```jinja2
{% extends "base.html" %}
{% block title %}Document Upload - DocuElevate{% endblock %}
{% block content %}
<div class="container mx-auto px-4 py-8">
<h1 class="text-2xl font-bold mb-4">{{ page_title }}</h1>
{% if error_message %}
<div class="bg-red-100 border border-red-400 text-red-700 px-4 py-3 rounded mb-4">
{{ error_message }}
</div>
{% endif %}
<form method="post" enctype="multipart/form-data">
<!-- Form content -->
</form>
</div>
{% endblock %}
```
### Tailwind CSS Usage
- Use Tailwind utility classes (already configured)
- Follow responsive design: `md:`, `lg:` breakpoints
- Use existing color scheme from the project
- Common patterns:
- Containers: `container mx-auto px-4`
- Buttons: `bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded`
- Cards: `bg-white shadow-md rounded-lg p-6`
- Forms: `w-full px-3 py-2 border rounded`
### Static Files
- CSS files in `frontend/static/css/`
- JavaScript in `frontend/static/js/`
- Images in `frontend/static/images/`
- Reference with `{{ url_for('static', path='css/style.css') }}`
### JavaScript
- Keep JavaScript minimal - prefer server-side rendering
- Use vanilla JavaScript or minimal dependencies
- Place scripts at the end of the body
- Use `defer` or `async` for external scripts
```html
<script src="{{ url_for('static', path='js/upload.js') }}" defer></script>
```
### Forms
- Use CSRF protection when needed
- Include proper validation
- Show clear error messages
- Use proper `method` (GET/POST) and `enctype` for file uploads
```html
<form method="post" enctype="multipart/form-data">
<div class="mb-4">
<label class="block text-gray-700 text-sm font-bold mb-2" for="file">
Document File
</label>
<input
type="file"
id="file"
name="file"
class="w-full px-3 py-2 border rounded"
required
/>
</div>
<button type="submit" class="bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded">
Upload
</button>
</form>
```
### Accessibility
- Use semantic HTML elements (`nav`, `main`, `article`, `section`)
- Include `alt` text for images
- Use proper heading hierarchy (h1 → h2 → h3)
- Add ARIA labels when needed
- Ensure keyboard navigation works
### Error Handling
- Display user-friendly error messages
- Use flash messages for feedback
- Show loading states for async operations
```jinja2
{% with messages = get_flashed_messages(with_categories=true) %}
{% if messages %}
{% for category, message in messages %}
<div class="bg-{{ category }}-100 border border-{{ category }}-400 text-{{ category }}-700 px-4 py-3 rounded mb-4">
{{ message }}
</div>
{% endfor %}
{% endif %}
{% endwith %}
```
### URL Generation
- Always use `url_for()` for URLs, never hardcode
- Examples:
- Routes: `{{ url_for('upload_document') }}`
- Static: `{{ url_for('static', path='css/style.css') }}`
- API: `{{ url_for('api_document', document_id=doc.id) }}`
### Template Variables
- Check if variables exist before using them
- Use filters for formatting
```jinja2
{% if document %}
<p>Uploaded: {{ document.created_at|datetime }}</p>
<p>Size: {{ document.file_size|filesizeformat }}</p>
{% else %}
<p>No document found</p>
{% endif %}
```
### Common Components
- Follow existing patterns for headers, footers, navigation
- Reuse template blocks and includes
- Keep components modular
```jinja2
{% include 'components/navigation.html' %}
{% include 'components/document_card.html' with document=doc %}
```
## UI/UX Guidelines
- Maintain consistent spacing using Tailwind's scale (4, 8, 16, etc.)
- Use the existing color palette from the design
- Ensure mobile responsiveness
- Show loading indicators for long operations
- Provide feedback for user actions (success/error messages)
- Keep the interface clean and minimal
## Performance
- Optimize images (compress, use appropriate formats)
- Minimize JavaScript bundle size
- Use lazy loading for images when appropriate
- Cache static assets
@@ -0,0 +1,164 @@
---
applyTo: "app/**/*.py"
---
# Python Backend Instructions
These instructions apply to all Python code in the `app/` directory.
## Code Style
- Use **Black** formatter with 120 character line length
- Use **isort** with Black profile for import organization
- Follow **flake8** rules (ignore E203, W503 as per `.pre-commit-config.yaml`)
- All functions must have type hints for parameters and return values
- Use `from typing import Optional, Dict, List, Any, Union` as needed
## Import Order (isort with Black profile)
```python
# Standard library imports
import os
from pathlib import Path
from typing import Optional, Dict, List
# Third-party imports
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.orm import Session
# Local application imports
from app.config import settings
from app.database import get_db
from app.models import Document, User
```
## Function Definitions
```python
def process_document(
file_path: Path,
user_id: int,
metadata: Optional[Dict[str, Any]] = None
) -> DocumentMetadata:
"""
Process a document and extract metadata.
Args:
file_path: Path to the document file
user_id: ID of the user uploading the document
metadata: Optional additional metadata
Returns:
DocumentMetadata object with extracted information
Raises:
FileNotFoundError: If file doesn't exist
ProcessingError: If processing fails
"""
pass
```
## FastAPI Endpoints
- Use dependency injection for DB sessions and auth
- Return Pydantic models for automatic validation
- Use proper status codes from `fastapi.status`
- Add detailed docstrings for OpenAPI docs
```python
from fastapi import APIRouter, Depends, status
from sqlalchemy.orm import Session
router = APIRouter(prefix="/api/documents", tags=["documents"])
@router.post("/", status_code=status.HTTP_201_CREATED)
async def create_document(
file: UploadFile,
db: Session = Depends(get_db),
current_user: User = Depends(get_current_user)
) -> DocumentResponse:
"""Create and process a new document."""
pass
```
## Error Handling
- Use custom exceptions from the application
- Log errors with context using `logging.getLogger(__name__)`
- Return user-friendly error messages
- Never expose internal details in production errors
```python
import logging
logger = logging.getLogger(__name__)
try:
result = process_file(file_path)
except FileNotFoundError:
logger.error(f"File not found: {file_path}")
raise HTTPException(status_code=404, detail="File not found")
except Exception as e:
logger.exception(f"Error processing file: {str(e)}")
raise HTTPException(status_code=500, detail="Processing failed")
```
## Database Operations
- Use SQLAlchemy ORM, never raw SQL with user input
- Use `get_db()` dependency for sessions
- Always commit in try/except blocks
```python
from sqlalchemy.orm import Session
from app.database import get_db
def create_document(db: Session, document_data: dict) -> Document:
"""Create a new document in the database."""
db_document = Document(**document_data)
try:
db.add(db_document)
db.commit()
db.refresh(db_document)
return db_document
except Exception as e:
db.rollback()
raise
```
## Celery Tasks
- Define in `app/tasks/` directory
- Use descriptive names: `module.action`
- Set retry policies
- Log progress and errors
```python
from celery import shared_task
import logging
logger = logging.getLogger(__name__)
@shared_task(bind=True, max_retries=3)
def process_ocr(self, document_id: int) -> Dict[str, Any]:
"""Process OCR for a document."""
try:
# Processing logic
logger.info(f"Processing OCR for document {document_id}")
return {"status": "success"}
except Exception as exc:
logger.exception(f"OCR processing failed for {document_id}")
raise self.retry(exc=exc, countdown=60)
```
## Configuration
- All settings in `app/config.py` using Pydantic Settings
- Use environment variables, never hardcode values
- Provide defaults when sensible
```python
from pydantic_settings import BaseSettings
class Settings(BaseSettings):
openai_api_key: str
max_file_size: int = 10485760 # 10MB default
class Config:
env_file = ".env"
```
## Security
- Never commit secrets
- Validate all user inputs
- Use parameterized queries
- Sanitize file paths
- Check file permissions
- Review SECURITY_AUDIT.md for guidelines
@@ -0,0 +1,245 @@
---
applyTo: "tests/**/*.py"
---
# Testing Instructions
These instructions apply to all test files in the `tests/` directory.
## Test Organization
- Mirror the structure of `app/` directory in `tests/`
- Name test files with `test_` prefix (e.g., `test_api.py`)
- Group related tests in classes with `Test` prefix
- Use descriptive test function names: `test_<what>_<condition>_<expected>`
## Pytest Configuration
- Configuration in `pytest.ini`
- Run tests: `pytest -v`
- With coverage: `pytest --cov=app --cov-report=term-missing`
- Run specific markers: `pytest -m unit` or `pytest -m integration`
## Test Markers
Use pytest markers to categorize tests:
```python
import pytest
@pytest.mark.unit
def test_document_validation():
"""Test document validation logic."""
pass
@pytest.mark.integration
def test_document_upload_api():
"""Test document upload endpoint."""
pass
@pytest.mark.slow
def test_large_file_processing():
"""Test processing of large files."""
pass
@pytest.mark.requires_external
def test_openai_integration():
"""Test OpenAI API integration."""
pass
```
Available markers:
- `unit` - Unit tests for individual functions/methods
- `integration` - Integration tests for API endpoints and workflows
- `slow` - Tests that take significant time to run
- `security` - Security-related tests
- `requires_external` - Tests requiring external services (OpenAI, Azure, etc.)
- `requires_db` - Tests requiring database
- `requires_redis` - Tests requiring Redis
## Fixtures
Use pytest fixtures for test setup and teardown:
```python
import pytest
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.database import Base
@pytest.fixture
def db_session():
"""Provide a database session for tests."""
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
yield session
session.close()
Base.metadata.drop_all(engine)
@pytest.fixture
def sample_document():
"""Provide a sample document for tests."""
return {
"filename": "test.pdf",
"content_type": "application/pdf",
"size": 1024
}
```
## API Testing with FastAPI
Use `TestClient` from FastAPI:
```python
from fastapi.testclient import TestClient
from app.main import app
client = TestClient(app)
def test_upload_document():
"""Test document upload endpoint."""
with open("tests/fixtures/sample.pdf", "rb") as f:
response = client.post(
"/api/documents/upload",
files={"file": ("test.pdf", f, "application/pdf")}
)
assert response.status_code == 201
assert "id" in response.json()
```
## Async Testing
For async code, use `pytest-asyncio`:
```python
import pytest
import httpx
@pytest.mark.asyncio
async def test_async_document_processing():
"""Test async document processing."""
async with httpx.AsyncClient(app=app, base_url="http://test") as client:
response = await client.get("/api/documents/1")
assert response.status_code == 200
```
## Mocking External Services
Always mock external services in tests:
```python
from unittest.mock import Mock, patch
@pytest.mark.unit
def test_openai_metadata_extraction(mocker):
"""Test metadata extraction with mocked OpenAI."""
mock_response = {
"document_type": "invoice",
"amount": 100.00,
"date": "2024-01-01"
}
mocker.patch(
"app.utils.openai_client.extract_metadata",
return_value=mock_response
)
result = extract_document_metadata("test.pdf")
assert result["document_type"] == "invoice"
@pytest.mark.unit
def test_azure_ocr_processing(mocker):
"""Test OCR with mocked Azure service."""
mock_text = "Sample extracted text"
mocker.patch(
"app.utils.azure_client.extract_text",
return_value=mock_text
)
result = perform_ocr("test.pdf")
assert result == mock_text
```
## Database Testing
```python
@pytest.mark.requires_db
def test_create_document(db_session):
"""Test document creation in database."""
from app.models import Document
doc = Document(
filename="test.pdf",
user_id=1,
file_path="/tmp/test.pdf"
)
db_session.add(doc)
db_session.commit()
assert doc.id is not None
assert doc.filename == "test.pdf"
```
## Test Coverage Goals
- Aim for **80% code coverage** for all new code
- Focus on critical paths and error handling
- Test both success and failure scenarios
- Don't test third-party library code
## Test Structure
Follow the Arrange-Act-Assert pattern:
```python
def test_document_validation():
"""Test that invalid documents are rejected."""
# Arrange
invalid_document = {
"filename": "", # Empty filename
"size": -1 # Invalid size
}
# Act
result = validate_document(invalid_document)
# Assert
assert result.is_valid is False
assert "filename" in result.errors
assert "size" in result.errors
```
## Parameterized Tests
Use `pytest.mark.parametrize` for multiple test cases:
```python
@pytest.mark.parametrize("filename,expected", [
("document.pdf", True),
("image.jpg", True),
("script.exe", False),
("", False),
])
def test_allowed_file_types(filename, expected):
"""Test file type validation."""
result = is_allowed_file(filename)
assert result == expected
```
## Test Data
- Place test fixtures in `tests/fixtures/` directory
- Use small sample files for testing
- Don't commit large test files
- Clean up test files in teardown
## Error Testing
Always test error conditions:
```python
def test_missing_file_raises_error():
"""Test that missing files raise appropriate error."""
with pytest.raises(FileNotFoundError):
process_document("/nonexistent/file.pdf")
def test_invalid_api_request():
"""Test API error handling."""
response = client.post("/api/documents/", json={})
assert response.status_code == 422 # Validation error
```
## Best Practices
- Test one thing per test function
- Use descriptive test names
- Keep tests independent (no dependencies between tests)
- Use fixtures for common setup
- Mock external dependencies
- Test edge cases and error conditions
- Keep tests fast (use mocks for slow operations)
- Clean up resources after tests
+2
View File
@@ -14,6 +14,7 @@ from app.api.dropbox import router as dropbox_router
from app.api.openai import router as openai_router
from app.api.azure import router as azure_router
from app.api.google_drive import router as google_drive_router
from app.api.logs import router as logs_router
# Set up logging
logger = logging.getLogger(__name__)
@@ -31,3 +32,4 @@ router.include_router(dropbox_router)
router.include_router(openai_router)
router.include_router(azure_router)
router.include_router(google_drive_router)
router.include_router(logs_router)
+164
View File
@@ -0,0 +1,164 @@
"""
Processing logs API endpoints
"""
from fastapi import APIRouter, Request, HTTPException, Depends, Query
from sqlalchemy.orm import Session
from sqlalchemy import desc
from typing import Optional
import logging
from app.auth import require_login
from app.models import ProcessingLog, FileRecord
from app.api.common import get_db
# Set up logging
logger = logging.getLogger(__name__)
router = APIRouter()
@router.get("/logs")
@require_login
def list_processing_logs(
request: Request,
db: Session = Depends(get_db),
file_id: Optional[int] = Query(None, description="Filter by file ID"),
task_id: Optional[str] = Query(None, description="Filter by task ID"),
limit: int = Query(100, ge=1, le=1000, description="Number of logs to return")
):
"""
Returns a JSON list of ProcessingLog entries.
Protected by `@require_login`, so only logged-in sessions can access.
Query Parameters:
- file_id: Optional filter by file ID
- task_id: Optional filter by task ID
- limit: Maximum number of logs to return (default 100, max 1000)
Example response:
[
{
"id": 1,
"file_id": 123,
"task_id": "abc-123-def",
"step_name": "process_document",
"status": "success",
"message": "Processing completed",
"timestamp": "2025-05-01T12:34:56.789000"
},
...
]
"""
query = db.query(ProcessingLog)
# Apply filters
if file_id is not None:
query = query.filter(ProcessingLog.file_id == file_id)
if task_id is not None:
query = query.filter(ProcessingLog.task_id == task_id)
# Order by timestamp descending and limit
logs = query.order_by(desc(ProcessingLog.timestamp)).limit(limit).all()
# Return a simple list of dicts
result = []
for log in logs:
result.append({
"id": log.id,
"file_id": log.file_id,
"task_id": log.task_id,
"step_name": log.step_name,
"status": log.status,
"message": log.message,
"timestamp": log.timestamp.isoformat() if log.timestamp else None
})
return result
@router.get("/logs/file/{file_id}")
@require_login
def get_file_processing_logs(
request: Request,
file_id: int,
db: Session = Depends(get_db)
):
"""
Get all processing logs for a specific file.
Returns logs ordered by timestamp (oldest first to show processing flow).
Also includes file metadata if the file exists.
"""
# Check if file exists
file_record = db.query(FileRecord).filter(FileRecord.id == file_id).first()
if not file_record:
raise HTTPException(
status_code=404,
detail=f"File with ID {file_id} not found"
)
# Get all logs for this file
logs = db.query(ProcessingLog).filter(
ProcessingLog.file_id == file_id
).order_by(ProcessingLog.timestamp).all()
# Build response
log_list = []
for log in logs:
log_list.append({
"id": log.id,
"task_id": log.task_id,
"step_name": log.step_name,
"status": log.status,
"message": log.message,
"timestamp": log.timestamp.isoformat() if log.timestamp else None
})
return {
"file": {
"id": file_record.id,
"original_filename": file_record.original_filename,
"file_size": file_record.file_size,
"mime_type": file_record.mime_type,
"created_at": file_record.created_at.isoformat() if file_record.created_at else None
},
"logs": log_list,
"total_logs": len(log_list)
}
@router.get("/logs/task/{task_id}")
@require_login
def get_task_processing_logs(
request: Request,
task_id: str,
db: Session = Depends(get_db)
):
"""
Get all processing logs for a specific task.
Returns logs ordered by timestamp (oldest first to show processing flow).
"""
# Get all logs for this task
logs = db.query(ProcessingLog).filter(
ProcessingLog.task_id == task_id
).order_by(ProcessingLog.timestamp).all()
if not logs:
raise HTTPException(
status_code=404,
detail=f"No logs found for task {task_id}"
)
# Build response
log_list = []
for log in logs:
log_list.append({
"id": log.id,
"file_id": log.file_id,
"step_name": log.step_name,
"status": log.status,
"message": log.message,
"timestamp": log.timestamp.isoformat() if log.timestamp else None
})
return {
"task_id": task_id,
"logs": log_list,
"total_logs": len(log_list)
}
+25 -10
View File
@@ -7,25 +7,32 @@ import json
from celery import shared_task
from app.config import settings
from app.tasks.process_document import process_document
from app.utils import log_task_progress
logger = logging.getLogger(__name__)
@shared_task
def convert_to_pdf(file_path):
@shared_task(bind=True)
def convert_to_pdf(self, file_path):
"""
Converts a file to PDF using Gotenberg's API.
Determines the appropriate Gotenberg endpoint based on the file's MIME type.
On success, saves the PDF locally and enqueues it for processing.
"""
task_id = self.request.id
logger.info(f"[{task_id}] Starting PDF conversion: {file_path}")
log_task_progress(task_id, "convert_to_pdf", "in_progress", f"Converting file: {os.path.basename(file_path)}")
gotenberg_url = getattr(settings, "gotenberg_url", None)
if not gotenberg_url:
logger.error("Gotenberg URL is not configured in settings.")
logger.error(f"[{task_id}] Gotenberg URL is not configured in settings.")
log_task_progress(task_id, "convert_to_pdf", "failure", "Gotenberg URL not configured")
return
# Try to guess the MIME type based on file content and extension
mime_type, encoding = mimetypes.guess_type(file_path)
file_ext = os.path.splitext(file_path)[1].lower()
logger.info(f"Guessed MIME type for '{file_path}' is: {mime_type}, extension: {file_ext}")
logger.info(f"[{task_id}] Guessed MIME type for '{file_path}' is: {mime_type}, extension: {file_ext}")
log_task_progress(task_id, "detect_file_type", "success", f"File type: {mime_type or file_ext}")
# Determine which Gotenberg endpoint to use
endpoint = None
@@ -146,11 +153,13 @@ def convert_to_pdf(file_path):
logger.warning(f"Using fallback conversion for unknown type: {mime_type} / {file_ext}")
if not endpoint:
logger.error(f"Could not determine Gotenberg endpoint for file type: {mime_type}")
logger.error(f"[{task_id}] Could not determine Gotenberg endpoint for file type: {mime_type}")
log_task_progress(task_id, "convert_to_pdf", "failure", f"Unknown file type: {mime_type}")
return None
try:
logger.info(f"Converting {file_path} using endpoint: {endpoint}")
logger.info(f"[{task_id}] Converting {file_path} using endpoint: {endpoint}")
log_task_progress(task_id, "call_gotenberg", "in_progress", "Calling Gotenberg API")
# Send the conversion request to Gotenberg
response = requests.post(endpoint, files=files, data=form_data)
@@ -161,19 +170,25 @@ def convert_to_pdf(file_path):
with open(converted_file_path, "wb") as out_file:
out_file.write(response.content)
logger.info(f"Converted file saved as PDF: {converted_file_path}")
logger.info(f"[{task_id}] Converted file saved as PDF: {converted_file_path}")
log_task_progress(task_id, "call_gotenberg", "success", "PDF conversion successful")
log_task_progress(task_id, "convert_to_pdf", "success", f"Converted to PDF: {os.path.basename(converted_file_path)}")
# Enqueue the PDF for further processing
process_document.delay(converted_file_path)
return converted_file_path
else:
error_msg = f"Status code: {response.status_code}"
logger.error(
f"Conversion failed for {file_path}. "
f"Status code: {response.status_code}, "
f"[{task_id}] Conversion failed for {file_path}. "
f"{error_msg}, "
f"Response: {response.text[:500]}..."
)
log_task_progress(task_id, "call_gotenberg", "failure", error_msg)
log_task_progress(task_id, "convert_to_pdf", "failure", f"Conversion failed: {error_msg}")
return None
except Exception as e:
logger.exception(f"Error converting {file_path} to PDF: {e}")
logger.exception(f"[{task_id}] Error converting {file_path} to PDF: {e}")
log_task_progress(task_id, "convert_to_pdf", "failure", f"Exception: {str(e)}")
return None
+52 -15
View File
@@ -3,6 +3,7 @@
import os
import shutil
import tempfile
import logging
import PyPDF2 # Replace fitz with PyPDF2
import json
from app.config import settings
@@ -11,6 +12,19 @@ from app.tasks.finalize_document_storage import finalize_document_storage
# Import the shared Celery instance
from app.celery_app import celery
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
logger = logging.getLogger(__name__)
# Directory constants - defined here to avoid hardcoded strings (BAN-B108)
# Note: These are application-specific subdirectories within settings.workdir,
# not system temporary directories. The workdir is a configurable path specific
# to this application. For actual temporary file creation, tempfile module is
# used (see line 70: tempfile.NamedTemporaryFile)
TMP_SUBDIR = "tmp"
PROCESSED_SUBDIR = "processed"
def unique_filepath(directory, base_filename, extension=".pdf"):
"""
@@ -39,8 +53,8 @@ def persist_metadata(metadata, final_pdf_path):
json.dump(metadata, f, ensure_ascii=False, indent=2)
return json_path
@celery.task(base=BaseTaskWithRetry)
def embed_metadata_into_pdf(local_file_path: str, extracted_text: str, metadata: dict):
@celery.task(base=BaseTaskWithRetry, bind=True)
def embed_metadata_into_pdf(self, local_file_path: str, extracted_text: str, metadata: dict, file_id: int = None):
"""
Embeds extracted metadata into the PDF's standard metadata fields.
The mapping is as follows:
@@ -54,13 +68,25 @@ def embed_metadata_into_pdf(local_file_path: str, extracted_text: str, metadata:
where <suggested_filename.pdf> is derived from metadata["filename"].
Additionally, the metadata is persisted to a JSON file with the same base name.
"""
task_id = self.request.id
logger.info(f"[{task_id}] Starting metadata embedding for: {local_file_path}")
log_task_progress(task_id, "embed_metadata_into_pdf", "in_progress", f"Embedding metadata into {os.path.basename(local_file_path)}", file_id=file_id)
# Get file_id from database if not provided (fallback only, prefer passing file_id explicitly)
if file_id is None:
with SessionLocal() as db:
file_record = db.query(FileRecord).filter_by(local_filename=local_file_path).first()
if file_record:
file_id = file_record.id
# Check for file existence; if not found, try the known shared tmp directory.
if not os.path.exists(local_file_path):
alt_path = os.path.join(settings.workdir, "tmp", os.path.basename(local_file_path))
alt_path = os.path.join(settings.workdir, TMP_SUBDIR, os.path.basename(local_file_path))
if os.path.exists(alt_path):
local_file_path = alt_path
else:
print(f"[ERROR] Local file {local_file_path} not found, cannot embed metadata.")
logger.error(f"[{task_id}] Local file {local_file_path} not found, cannot embed metadata.")
log_task_progress(task_id, "embed_metadata_into_pdf", "failure", "File not found", file_id=file_id)
return {"error": "File not found"}
# Work on a safe copy in a secure temporary directory
@@ -75,7 +101,8 @@ def embed_metadata_into_pdf(local_file_path: str, extracted_text: str, metadata:
shutil.copy(original_file, processed_file)
try:
print(f"[DEBUG] Embedding metadata into {processed_file}...")
logger.info(f"[{task_id}] Embedding metadata into {processed_file}...")
log_task_progress(task_id, "modify_pdf", "in_progress", "Modifying PDF metadata", file_id=file_id)
# Open the PDF and modify metadata
with open(processed_file, 'rb') as file:
@@ -98,49 +125,59 @@ def embed_metadata_into_pdf(local_file_path: str, extracted_text: str, metadata:
with open(processed_file, 'wb') as output_file:
pdf_writer.write(output_file)
print(f"[INFO] Metadata embedded successfully in {processed_file}")
logger.info(f"[{task_id}] Metadata embedded successfully in {processed_file}")
log_task_progress(task_id, "modify_pdf", "success", "PDF metadata embedded", file_id=file_id)
# Use the suggested filename from metadata; if not provided, use the original basename.
suggested_filename = metadata.get("filename", os.path.splitext(os.path.basename(local_file_path))[0])
# Remove any extension and then add .pdf
suggested_filename = os.path.splitext(suggested_filename)[0]
# Define the final directory based on settings.workdir and ensure it exists.
final_dir = os.path.join(settings.workdir, "processed")
final_dir = os.path.join(settings.workdir, PROCESSED_SUBDIR)
os.makedirs(final_dir, exist_ok=True)
# Get a unique filepath in case of collisions.
final_file_path = unique_filepath(final_dir, suggested_filename, extension=".pdf")
logger.info(f"[{task_id}] Moving file to: {final_file_path}")
log_task_progress(task_id, "move_to_processed", "in_progress", f"Moving to processed: {suggested_filename}.pdf", file_id=file_id)
# Move the processed file using shutil.move to handle cross-device moves.
shutil.move(processed_file, final_file_path)
# Ensure the temporary file is deleted if it still exists.
if os.path.exists(processed_file):
os.remove(processed_file)
log_task_progress(task_id, "move_to_processed", "success", f"Moved to: {os.path.basename(final_file_path)}", file_id=file_id)
# Persist the metadata into a JSON file with the same base name.
logger.info(f"[{task_id}] Persisting metadata to JSON")
log_task_progress(task_id, "save_metadata_json", "in_progress", "Saving metadata JSON", file_id=file_id)
json_path = persist_metadata(metadata, final_file_path)
print(f"[INFO] Metadata persisted to {json_path}")
logger.info(f"[{task_id}] Metadata persisted to {json_path}")
log_task_progress(task_id, "save_metadata_json", "success", f"Saved: {os.path.basename(json_path)}", file_id=file_id)
# Trigger the next step: final storage.
finalize_document_storage.delay(original_file, final_file_path, metadata)
logger.info(f"[{task_id}] Queueing final storage task")
log_task_progress(task_id, "embed_metadata_into_pdf", "success", "Metadata embedded, queuing finalization", file_id=file_id)
finalize_document_storage.delay(original_file, final_file_path, metadata, file_id)
# After triggering final storage, delete the original file if it is in workdir/tmp.
workdir_tmp = os.path.join(settings.workdir, "tmp")
workdir_tmp = os.path.join(settings.workdir, TMP_SUBDIR)
if original_file.startswith(workdir_tmp) and os.path.exists(original_file):
try:
os.remove(original_file)
print(f"[INFO] Deleted original file from {original_file}")
logger.info(f"[{task_id}] Deleted original file from {original_file}")
except Exception as e:
print(f"[ERROR] Could not delete original file {original_file}: {e}")
logger.error(f"[{task_id}] Could not delete original file {original_file}: {e}")
return {"file": final_file_path, "metadata_file": json_path, "status": "Metadata embedded"}
except Exception as e:
print(f"[ERROR] Failed to embed metadata into {processed_file}: {e}")
logger.exception(f"[{task_id}] Failed to embed metadata into {processed_file}: {e}")
log_task_progress(task_id, "embed_metadata_into_pdf", "failure", f"Exception: {str(e)}", file_id=file_id)
# Clean up temporary file in case of error
if os.path.exists(processed_file):
try:
os.remove(processed_file)
print(f"[INFO] Cleaned up temporary file {processed_file}")
logger.info(f"[{task_id}] Cleaned up temporary file {processed_file}")
except Exception as cleanup_error:
print(f"[ERROR] Could not clean up temporary file {processed_file}: {cleanup_error}")
logger.error(f"[{task_id}] Could not clean up temporary file {processed_file}: {cleanup_error}")
return {"error": str(e)}
+33 -8
View File
@@ -2,6 +2,7 @@
import json
import re
import os
from app.config import settings
from app.tasks.retry_config import BaseTaskWithRetry
from app.tasks.embed_metadata_into_pdf import embed_metadata_into_pdf
@@ -10,6 +11,9 @@ from app.tasks.embed_metadata_into_pdf import embed_metadata_into_pdf
from app.celery_app import celery
import openai
import logging
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
logger = logging.getLogger(__name__)
@@ -41,9 +45,23 @@ def extract_json_from_text(text):
return text[start:end+1]
return None
@celery.task(base=BaseTaskWithRetry)
def extract_metadata_with_gpt(filename: str, cleaned_text: str):
@celery.task(base=BaseTaskWithRetry, bind=True)
def extract_metadata_with_gpt(self, filename: str, cleaned_text: str, file_id: int = None):
"""Uses OpenAI to classify document metadata."""
task_id = self.request.id
logger.info(f"[{task_id}] Starting metadata extraction for: {filename}")
log_task_progress(task_id, "extract_metadata_with_gpt", "in_progress", f"Extracting metadata for {filename}", file_id=file_id)
# Get file_id from database if not provided
if file_id is None:
tmp_dir = os.path.join(settings.workdir, "tmp")
file_path = os.path.join(tmp_dir, filename)
if os.path.exists(file_path):
with SessionLocal() as db:
file_record = db.query(FileRecord).filter_by(local_filename=file_path).first()
if file_record:
file_id = file_record.id
prompt = f"""
You are a specialized document analyzer trained to extract structured metadata from documents.
Your task is to analyze the given text and return a well-structured JSON object.
@@ -77,7 +95,8 @@ Return only valid JSON with no additional commentary.
"""
try:
print(f"[DEBUG] Sending classification request for {filename}...")
logger.info(f"[{task_id}] Sending classification request for {filename}...")
log_task_progress(task_id, "call_openai", "in_progress", "Calling OpenAI API", file_id=file_id)
completion = client.chat.completions.create(
model=settings.openai_model,
messages=[
@@ -88,21 +107,27 @@ Return only valid JSON with no additional commentary.
)
content = completion.choices[0].message.content
print(f"[DEBUG] Raw classification response for {filename}: {content}")
logger.info(f"[{task_id}] Raw classification response for {filename}: {content[:200]}...")
log_task_progress(task_id, "call_openai", "success", "Received OpenAI response", file_id=file_id)
json_text = extract_json_from_text(content)
if not json_text:
print(f"[ERROR] Could not find valid JSON in GPT response for {filename}.")
logger.error(f"[{task_id}] Could not find valid JSON in GPT response for {filename}.")
log_task_progress(task_id, "extract_metadata_with_gpt", "failure", "Invalid JSON in response", file_id=file_id)
return {}
metadata = json.loads(json_text)
print(f"[DEBUG] Extracted metadata: {metadata}")
logger.info(f"[{task_id}] Extracted metadata: {metadata}")
log_task_progress(task_id, "parse_metadata", "success", f"Parsed metadata: {list(metadata.keys())}", file_id=file_id)
# Trigger the next step: embedding metadata into the PDF
embed_metadata_into_pdf.delay(filename, cleaned_text, metadata)
logger.info(f"[{task_id}] Queueing metadata embedding task")
log_task_progress(task_id, "extract_metadata_with_gpt", "success", "Metadata extracted, queuing embed task", file_id=file_id)
embed_metadata_into_pdf.delay(filename, cleaned_text, metadata, file_id)
return {"s3_file": filename, "metadata": metadata}
except Exception as e:
print(f"[ERROR] OpenAI classification failed for {filename}: {e}")
logger.exception(f"[{task_id}] OpenAI classification failed for {filename}: {e}")
log_task_progress(task_id, "extract_metadata_with_gpt", "failure", f"Exception: {str(e)}", file_id=file_id)
return {}
+41 -12
View File
@@ -1,28 +1,52 @@
#!/usr/bin/env python3
import logging
import os
from app.config import settings
from app.tasks.retry_config import BaseTaskWithRetry
# Import the shared Celery instance
from app.celery_app import celery
# 1) Import the aggregator task
# Import the aggregator task and validator
from app.tasks.send_to_all import send_to_all_destinations, get_configured_services_from_validator
# Import notification utility
from app.utils.notification import notify_file_processed
# Import database and logging utils from main
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
@celery.task(base=BaseTaskWithRetry)
def finalize_document_storage(original_file: str, processed_file: str, metadata: dict):
logger = logging.getLogger(__name__)
@celery.task(base=BaseTaskWithRetry, bind=True)
def finalize_document_storage(self, original_file: str, processed_file: str, metadata: dict, file_id: int = None):
"""
Final storage step after embedding metadata.
We will now call 'send_to_all_destinations' to push the final PDF to Dropbox/Nextcloud/Paperless.
After uploading, send a notification about the processed file.
"""
print(f"[INFO] Finalizing document storage for {processed_file}")
task_id = self.request.id
logger.info(f"[{task_id}] Finalizing document storage for {processed_file}")
# 1. Update Database Status (From Main)
log_task_progress(task_id, "finalize_document_storage", "in_progress", f"Finalizing: {os.path.basename(processed_file)}", file_id=file_id)
# Get file_id from database if not provided (fallback logic from Main)
if file_id is None:
with SessionLocal() as db:
# Only as a last resort, try to find by exact match on local_filename
tmp_path = os.path.join(settings.workdir, "tmp", os.path.basename(original_file))
file_record = db.query(FileRecord).filter(
FileRecord.local_filename == tmp_path
).first()
if file_record:
file_id = file_record.id
# Determine which destinations are configured
# 2. Determine Configured Destinations (From Copilot)
# This is needed for the notification message later
configured_destinations = []
try:
configured_services = get_configured_services_from_validator()
@@ -33,16 +57,21 @@ def finalize_document_storage(original_file: str, processed_file: str, metadata:
display_name = service_name.replace('_', ' ').title()
configured_destinations.append(display_name)
except Exception as e:
print(f"[WARNING] Could not determine configured destinations: {e}")
logger.warning(f"[WARNING] Could not determine configured destinations: {e}")
configured_destinations = ["configured destinations"]
# 2) Enqueue uploads to all destinations (Dropbox, Nextcloud, Paperless)
# 3. Queue Uploads (Merged)
# Uses Main branch signature to ensure file_id is passed, but keeps logic structure
logger.info(f"[{task_id}] Queueing uploads to all destinations")
log_task_progress(task_id, "finalize_document_storage", "success", "Queuing uploads to destinations", file_id=file_id)
# Note: send_to_all_destinations is asynchronous and queues upload tasks
send_to_all_destinations.delay(processed_file)
# We pass 'True' (delete_after) and 'file_id' as per Main branch requirements
send_to_all_destinations.delay(processed_file, True, file_id)
# 3) Send notification about successful file processing
# 4. Send Notification (From Copilot)
# Note: This notification is sent after processing is complete but while uploads
# are being queued. The message reflects that uploads are being initiated.
# are being queued.
try:
# Get file information
file_size = os.path.getsize(processed_file) if os.path.exists(processed_file) else 0
@@ -55,9 +84,9 @@ def finalize_document_storage(original_file: str, processed_file: str, metadata:
destinations=configured_destinations
)
except Exception as e:
print(f"[WARNING] Failed to send file processed notification: {e}")
logger.warning(f"[WARNING] Failed to send file processed notification: {e}")
return {
"status": "Completed",
"file": processed_file
}
}
+43 -10
View File
@@ -4,6 +4,7 @@ import os
import uuid
import shutil
import mimetypes
import logging
import PyPDF2 # Replace fitz with PyPDF2
from app.config import settings
@@ -13,11 +14,13 @@ from app.tasks.extract_metadata_with_gpt import extract_metadata_with_gpt
from app.celery_app import celery
from app.database import SessionLocal
from app.models import FileRecord
from app.utils import hash_file
from app.utils import hash_file, log_task_progress
logger = logging.getLogger(__name__)
@celery.task(base=BaseTaskWithRetry)
def process_document(original_local_file: str):
@celery.task(base=BaseTaskWithRetry, bind=True)
def process_document(self, original_local_file: str):
"""
Process a document file and trigger appropriate text extraction.
@@ -28,24 +31,34 @@ def process_document(original_local_file: str):
- Check for embedded text. If present, run local GPT extraction
- Otherwise, queue Azure Document Intelligence processing
"""
task_id = self.request.id
logger.info(f"[{task_id}] Starting document processing: {original_local_file}")
log_task_progress(task_id, "process_document", "in_progress", f"Processing file: {original_local_file}")
if not os.path.exists(original_local_file):
print(f"[ERROR] File {original_local_file} not found.")
logger.error(f"[{task_id}] File {original_local_file} not found.")
log_task_progress(task_id, "process_document", "failure", "File not found")
return {"error": "File not found"}
# 0. Compute the file hash and check for duplicates
logger.info(f"[{task_id}] Computing file hash...")
log_task_progress(task_id, "hash_file", "in_progress", "Computing file hash")
filehash = hash_file(original_local_file)
original_filename = os.path.basename(original_local_file)
file_size = os.path.getsize(original_local_file)
mime_type, _ = mimetypes.guess_type(original_local_file)
if not mime_type:
mime_type = "application/octet-stream"
logger.info(f"[{task_id}] File hash: {filehash[:10]}..., Size: {file_size} bytes, MIME: {mime_type}")
log_task_progress(task_id, "hash_file", "success", f"Hash: {filehash[:10]}..., Size: {file_size} bytes")
# Acquire DB session in the task
with SessionLocal() as db:
existing = db.query(FileRecord).filter_by(filehash=filehash).one_or_none()
if existing:
print(f"[INFO] Duplicate file detected (hash={filehash[:10]}...) Skipping processing.")
logger.info(f"[{task_id}] Duplicate file detected (hash={filehash[:10]}...) Skipping processing.")
log_task_progress(task_id, "process_document", "success", "Duplicate file detected, skipping", file_id=existing.id)
return {
"status": "duplicate_file",
"file_id": existing.id,
@@ -53,6 +66,8 @@ def process_document(original_local_file: str):
}
# Not a duplicate -> insert a new record
logger.info(f"[{task_id}] Creating new file record in database")
log_task_progress(task_id, "create_file_record", "in_progress", "Creating file record")
new_record = FileRecord(
filehash=filehash,
original_filename=original_filename,
@@ -63,6 +78,8 @@ def process_document(original_local_file: str):
db.add(new_record)
db.commit()
db.refresh(new_record)
logger.info(f"[{task_id}] File record created with ID: {new_record.id}")
log_task_progress(task_id, "create_file_record", "success", f"File record ID: {new_record.id}", file_id=new_record.id)
# 1. Generate a UUID-based filename and place it in /workdir/tmp
file_ext = os.path.splitext(original_local_file)[1]
@@ -73,14 +90,19 @@ def process_document(original_local_file: str):
os.makedirs(tmp_dir, exist_ok=True)
new_local_path = os.path.join(tmp_dir, new_filename)
logger.info(f"[{task_id}] Copying file to: {new_local_path}")
log_task_progress(task_id, "copy_file", "in_progress", f"Copying file to {new_filename}", file_id=new_record.id)
# Copy the file instead of moving it
shutil.copy(original_local_file, new_local_path)
log_task_progress(task_id, "copy_file", "success", f"File copied to {new_filename}", file_id=new_record.id)
# Update the DB with final local filename
new_record.local_filename = new_local_path
db.commit()
# 2. Check for embedded text (outside the DB session to avoid long open transactions)
logger.info(f"[{task_id}] Checking for embedded text in PDF")
log_task_progress(task_id, "check_text", "in_progress", "Checking for embedded text", file_id=new_record.id)
with open(new_local_path, 'rb') as file:
pdf_reader = PyPDF2.PdfReader(file)
has_text = False
@@ -90,19 +112,30 @@ def process_document(original_local_file: str):
break
if has_text:
print(f"[INFO] PDF {original_local_file} contains embedded text. Processing locally.")
logger.info(f"[{task_id}] PDF {original_local_file} contains embedded text. Processing locally.")
log_task_progress(task_id, "check_text", "success", "Embedded text found, extracting locally", file_id=new_record.id)
# Extract text locally
logger.info(f"[{task_id}] Extracting text from PDF")
log_task_progress(task_id, "extract_text", "in_progress", "Extracting text locally", file_id=new_record.id)
extracted_text = ""
with open(new_local_path, 'rb') as file:
pdf_reader = PyPDF2.PdfReader(file)
for page in pdf_reader.pages:
extracted_text += page.extract_text() + "\n"
logger.info(f"[{task_id}] Extracted {len(extracted_text)} characters")
log_task_progress(task_id, "extract_text", "success", f"Extracted {len(extracted_text)} characters", file_id=new_record.id)
# Call metadata extraction directly
extract_metadata_with_gpt.delay(new_filename, extracted_text)
return {"file": new_local_path, "status": "Text extracted locally"}
logger.info(f"[{task_id}] Queueing metadata extraction")
log_task_progress(task_id, "process_document", "success", "Queued for metadata extraction", file_id=new_record.id)
extract_metadata_with_gpt.delay(new_filename, extracted_text, new_record.id)
return {"file": new_local_path, "status": "Text extracted locally", "file_id": new_record.id}
# 3. If no embedded text, queue Azure Document Intelligence processing
process_with_azure_document_intelligence.delay(new_filename)
return {"file": new_local_path, "status": "Queued for OCR"}
logger.info(f"[{task_id}] No embedded text found. Queueing Azure Document Intelligence processing")
log_task_progress(task_id, "check_text", "success", "No embedded text, queuing OCR", file_id=new_record.id)
log_task_progress(task_id, "process_document", "success", "Queued for OCR processing", file_id=new_record.id)
process_with_azure_document_intelligence.delay(new_filename, new_record.id)
return {"file": new_local_path, "status": "Queued for OCR", "file_id": new_record.id}
@@ -76,7 +76,7 @@ def check_page_rotation(result, filename):
return rotation_data
@celery.task(base=BaseTaskWithRetry)
def process_with_azure_document_intelligence(filename: str):
def process_with_azure_document_intelligence(filename: str, file_id: int = None):
"""
Processes a PDF document using Azure Document Intelligence and overlays OCR text onto
the local temporary file (stored under <workdir>/tmp).
@@ -88,6 +88,10 @@ def process_with_azure_document_intelligence(filename: str):
3. Saves the OCR-processed PDF locally in the same location as before.
4. Checks for page rotation and triggers page rotation if needed.
5. Triggers downstream metadata extraction.
Args:
filename: Name of the file to process
file_id: Optional file ID to pass through to subsequent tasks
"""
try:
tmp_file_path = os.path.join(settings.workdir, "tmp", filename)
@@ -139,7 +143,7 @@ def process_with_azure_document_intelligence(filename: str):
logger.info(f"Extracted text for {filename}: {len(extracted_text)} characters")
# Trigger page rotation task if rotation is detected, otherwise proceed to metadata extraction
rotate_pdf_pages.delay(filename, extracted_text, rotation_data)
rotate_pdf_pages.delay(filename, extracted_text, rotation_data, file_id)
return {"file": filename, "searchable_pdf": searchable_pdf_path, "cleaned_text": extracted_text}
except Exception as e:
+6 -5
View File
@@ -47,7 +47,7 @@ def determine_rotation_angle(detected_angle):
return rotation_value
@celery.task(base=BaseTaskWithRetry)
def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None):
def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None, file_id: int = None):
"""
Rotates pages in a PDF document based on detected rotation angles.
@@ -55,6 +55,7 @@ def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None):
filename: The name of the file to rotate
extracted_text: The extracted text from the document
rotation_data: Optional rotation data dictionary {page_index: angle}
file_id: Optional file ID to pass through to subsequent tasks
"""
try:
pdf_path = os.path.join(settings.workdir, "tmp", filename)
@@ -64,7 +65,7 @@ def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None):
# Skip rotation if no rotation data provided
if not rotation_data:
logger.info(f"No rotation data provided for {filename}, proceeding with metadata extraction")
extract_metadata_with_gpt.delay(filename, extracted_text)
extract_metadata_with_gpt.delay(filename, extracted_text, file_id)
return {"file": filename, "status": "no_rotation_needed"}
# Standardize rotation_data keys to integers
@@ -77,7 +78,7 @@ def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None):
if not any(abs(angle) > 0 for angle in normalized_rotation_data.values()):
logger.info(f"No significant rotations detected in {filename}, proceeding with metadata extraction")
extract_metadata_with_gpt.delay(filename, extracted_text)
extract_metadata_with_gpt.delay(filename, extracted_text, file_id)
return {"file": filename, "status": "no_rotation_needed"}
logger.info(f"Rotating {len(normalized_rotation_data)} pages in {filename}")
@@ -117,7 +118,7 @@ def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None):
logger.info(f"Detected rotations in {filename} but no rotations were actually applied (angles too small or not multiples of 90°)")
# Continue with metadata extraction
extract_metadata_with_gpt.delay(filename, extracted_text)
extract_metadata_with_gpt.delay(filename, extracted_text, file_id)
return {
"file": filename,
@@ -129,5 +130,5 @@ def rotate_pdf_pages(filename: str, extracted_text: str, rotation_data=None):
except Exception as e:
logger.error(f"Error rotating PDF {filename}: {e}")
# Continue with metadata extraction despite rotation failure
extract_metadata_with_gpt.delay(filename, extracted_text)
extract_metadata_with_gpt.delay(filename, extracted_text, file_id)
return {"file": filename, "status": "rotation_failed", "error": str(e)}
+40 -11
View File
@@ -16,6 +16,9 @@ from app.tasks.upload_to_onedrive import upload_to_onedrive
from app.tasks.upload_to_s3 import upload_to_s3
from app.utils.config_validator import get_provider_status
from app.celery_app import celery
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
logger = logging.getLogger(__name__)
@@ -104,8 +107,8 @@ def get_configured_services_from_validator():
return result
@celery.task(base=BaseTaskWithRetry)
def send_to_all_destinations(file_path: str, use_validator=True):
@celery.task(base=BaseTaskWithRetry, bind=True)
def send_to_all_destinations(self, file_path: str, use_validator=True, file_id: int = None):
"""
Distribute a file to all configured storage destinations.
@@ -113,11 +116,29 @@ def send_to_all_destinations(file_path: str, use_validator=True):
file_path: Path to the file to distribute
use_validator: Whether to use the config validator to determine enabled services
(if False, falls back to individual checks)
file_id: Optional file ID to associate with logs
"""
task_id = self.request.id
if not os.path.exists(file_path):
logger.error(f"[{task_id}] File not found: {file_path}")
log_task_progress(task_id, "send_to_all_destinations", "failure", "File not found", file_id=file_id)
raise FileNotFoundError(f"File not found: {file_path}")
logger.info(f"Sending {file_path} to all configured destinations")
logger.info(f"[{task_id}] Sending {file_path} to all configured destinations")
log_task_progress(task_id, "send_to_all_destinations", "in_progress", f"Distributing: {os.path.basename(file_path)}", file_id=file_id)
# Get file_id from database if not provided (fallback only, prefer passing file_id explicitly)
if file_id is None:
with SessionLocal() as db:
# Only as a last resort, try to find by basename match
# This should not be needed if file_id is passed correctly through the chain
file_record = db.query(FileRecord).filter(
FileRecord.local_filename == os.path.join(settings.workdir, "tmp", os.path.basename(file_path))
).first()
if file_record:
file_id = file_record.id
results = {}
# Define service configurations
@@ -179,12 +200,13 @@ def send_to_all_destinations(file_path: str, use_validator=True):
if use_validator:
try:
configured_services = get_configured_services_from_validator()
logger.info(f"Configured services according to validator: {configured_services}")
logger.info(f"[{task_id}] Configured services according to validator: {configured_services}")
except Exception as e:
logger.warning(f"Failed to get configuration from validator: {str(e)}")
logger.warning(f"[{task_id}] Failed to get configuration from validator: {str(e)}")
use_validator = False
# Process each service
queued_count = 0
for service in services:
service_name = service["name"]
@@ -192,24 +214,31 @@ def send_to_all_destinations(file_path: str, use_validator=True):
is_configured = False
if use_validator and service_name in configured_services:
is_configured = configured_services[service_name]
logger.debug(f"{service_name} configuration from validator: {is_configured}")
logger.debug(f"[{task_id}] {service_name} configuration from validator: {is_configured}")
else:
try:
is_configured = service["should_upload"]()
logger.debug(f"{service_name} configuration from function: {is_configured}")
logger.debug(f"[{task_id}] {service_name} configuration from function: {is_configured}")
except Exception as e:
logger.error(f"Error checking configuration for {service_name}: {str(e)}")
logger.error(f"[{task_id}] Error checking configuration for {service_name}: {str(e)}")
is_configured = False
# Queue the upload task if service is configured
if is_configured:
logger.info(f"Queueing {file_path} for {service_name} upload")
logger.info(f"[{task_id}] Queueing {file_path} for {service_name} upload")
log_task_progress(task_id, f"queue_{service_name}", "in_progress", f"Queueing upload to {service_name}", file_id=file_id)
try:
task = service["upload_func"].delay(file_path)
task = service["upload_func"].delay(file_path, file_id)
results[f"{service_name}_task_id"] = task.id
queued_count += 1
log_task_progress(task_id, f"queue_{service_name}", "success", f"Queued for {service_name}", file_id=file_id)
except Exception as e:
logger.error(f"Failed to queue {service_name} task: {str(e)}")
logger.error(f"[{task_id}] Failed to queue {service_name} task: {str(e)}")
results[f"{service_name}_error"] = str(e)
log_task_progress(task_id, f"queue_{service_name}", "failure", f"Failed: {str(e)}", file_id=file_id)
logger.info(f"[{task_id}] Queued {queued_count} upload tasks")
log_task_progress(task_id, "send_to_all_destinations", "success", f"Queued {queued_count} uploads", file_id=file_id)
return {
"status": "Queued",
+30 -12
View File
@@ -9,6 +9,9 @@ from app.config import settings
from app.tasks.retry_config import BaseTaskWithRetry
from app.celery_app import celery
from app.utils.filename_utils import get_unique_filename, sanitize_filename, extract_remote_path
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
logger = logging.getLogger(__name__)
@@ -99,21 +102,31 @@ def get_dropbox_client():
logger.error(f"Error creating Dropbox client: {str(e)}")
raise
@celery.task(base=BaseTaskWithRetry)
def upload_to_dropbox(file_path: str):
@celery.task(base=BaseTaskWithRetry, bind=True)
def upload_to_dropbox(self, file_path: str, file_id: int = None):
"""
Upload a file to Dropbox.
Args:
file_path: Path to the file to upload
file_id: Optional file ID to associate with logs
"""
task_id = self.request.id
logger.info(f"[{task_id}] Starting Dropbox upload: {file_path}")
log_task_progress(task_id, "upload_to_dropbox", "in_progress", f"Uploading to Dropbox: {os.path.basename(file_path)}", file_id=file_id)
if not os.path.exists(file_path):
error_msg = f"File not found: {file_path}"
logger.error(error_msg)
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_dropbox", "failure", error_msg, file_id=file_id)
raise FileNotFoundError(error_msg)
# Check if Dropbox is properly configured
if not (hasattr(settings, 'dropbox_app_key') and settings.dropbox_app_key and
hasattr(settings, 'dropbox_app_secret') and settings.dropbox_app_secret and
hasattr(settings, 'dropbox_refresh_token') and settings.dropbox_refresh_token):
logger.info("Dropbox upload skipped: Missing configuration")
logger.info(f"[{task_id}] Dropbox upload skipped: Missing configuration")
log_task_progress(task_id, "upload_to_dropbox", "success", "Skipped: Not configured", file_id=file_id)
return {"status": "Skipped", "reason": "Dropbox settings not configured"}
filename = os.path.basename(file_path)
@@ -144,7 +157,8 @@ def upload_to_dropbox(file_path: str):
dropbox_path = get_unique_filename(remote_full_path, check_exists_in_dropbox)
# Upload the file
logger.info(f"Uploading {filename} to Dropbox at {dropbox_path}")
logger.info(f"[{task_id}] Uploading {filename} to Dropbox at {dropbox_path}")
log_task_progress(task_id, "upload_file", "in_progress", f"Uploading to {dropbox_path}", file_id=file_id)
with open(file_path, 'rb') as file_data:
# Use files_upload_session for large files to avoid timeouts
file_size = os.path.getsize(file_path)
@@ -179,7 +193,8 @@ def upload_to_dropbox(file_path: str):
mode=dropbox.files.WriteMode.overwrite
)
logger.info(f"Successfully uploaded {filename} to Dropbox at {dropbox_path}")
logger.info(f"[{task_id}] Successfully uploaded {filename} to Dropbox at {dropbox_path}")
log_task_progress(task_id, "upload_to_dropbox", "success", f"Uploaded to Dropbox: {dropbox_path}", file_id=file_id)
return {
"status": "Completed",
"file_path": file_path,
@@ -187,14 +202,17 @@ def upload_to_dropbox(file_path: str):
}
except AuthError:
error_msg = f"[ERROR] Authentication failed while uploading {filename} to Dropbox. Check token."
logger.error(error_msg)
error_msg = f"Authentication failed while uploading {filename} to Dropbox. Check token."
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_dropbox", "failure", error_msg, file_id=file_id)
raise Exception(error_msg)
except ApiError as e:
error_msg = f"[ERROR] Failed to upload {filename} to Dropbox: {e}"
logger.error(error_msg)
error_msg = f"Failed to upload {filename} to Dropbox: {e}"
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_dropbox", "failure", error_msg, file_id=file_id)
raise Exception(error_msg)
except Exception as e:
error_msg = f"[ERROR] Unexpected error uploading {filename} to Dropbox: {e}"
logger.error(error_msg)
error_msg = f"Unexpected error uploading {filename} to Dropbox: {e}"
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_dropbox", "failure", error_msg, file_id=file_id)
raise Exception(error_msg)
+27 -10
View File
@@ -8,17 +8,29 @@ from app.config import settings
from app.celery_app import celery
from app.tasks.retry_config import BaseTaskWithRetry
from app.utils.filename_utils import get_unique_filename, sanitize_filename, extract_remote_path
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
logger = logging.getLogger(__name__)
@celery.task(base=BaseTaskWithRetry)
def upload_to_nextcloud(file_path: str):
@celery.task(base=BaseTaskWithRetry, bind=True)
def upload_to_nextcloud(self, file_path: str, file_id: int = None):
"""
Upload a file to Nextcloud WebDAV.
Args:
file_path: Path to the file to upload
file_id: Optional file ID to associate with logs
"""
task_id = self.request.id
logger.info(f"[{task_id}] Starting Nextcloud upload: {file_path}")
log_task_progress(task_id, "upload_to_nextcloud", "in_progress", f"Uploading to Nextcloud: {os.path.basename(file_path)}", file_id=file_id)
if not os.path.exists(file_path):
error_msg = f"File not found: {file_path}"
logger.error(error_msg)
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_nextcloud", "failure", error_msg, file_id=file_id)
raise FileNotFoundError(error_msg)
# For Nextcloud, we need to check for 'nextcloud_upload_url' instead of 'nextcloud_url'
@@ -26,7 +38,8 @@ def upload_to_nextcloud(file_path: str):
if not (getattr(settings, 'nextcloud_upload_url', None) and
getattr(settings, 'nextcloud_username', None) and
getattr(settings, 'nextcloud_password', None)):
logger.info("Nextcloud upload skipped: Missing configuration")
logger.info(f"[{task_id}] Nextcloud upload skipped: Missing configuration")
log_task_progress(task_id, "upload_to_nextcloud", "success", "Skipped: Not configured", file_id=file_id)
return {"status": "Skipped", "reason": "Nextcloud settings not configured"}
filename = os.path.basename(file_path)
@@ -99,7 +112,8 @@ def upload_to_nextcloud(file_path: str):
)
# Upload the file
logger.info(f"Uploading {filename} to Nextcloud at {full_url}")
logger.info(f"[{task_id}] Uploading {filename} to Nextcloud at {full_url}")
log_task_progress(task_id, "upload_file", "in_progress", f"Uploading to {remote_path}", file_id=file_id)
with open(file_path, 'rb') as file_data:
response = requests.put(
full_url,
@@ -110,7 +124,8 @@ def upload_to_nextcloud(file_path: str):
)
if response.status_code in (201, 204): # Created or No Content
logger.info(f"Successfully uploaded {filename} to Nextcloud at {remote_path}")
logger.info(f"[{task_id}] Successfully uploaded {filename} to Nextcloud at {remote_path}")
log_task_progress(task_id, "upload_to_nextcloud", "success", f"Uploaded to Nextcloud: {remote_path}", file_id=file_id)
return {
"status": "Completed",
"file_path": file_path,
@@ -118,11 +133,13 @@ def upload_to_nextcloud(file_path: str):
"response_code": response.status_code
}
else:
error_msg = f"[ERROR] Failed to upload {filename} to Nextcloud: {response.status_code} - {response.text}"
logger.error(error_msg)
error_msg = f"Failed to upload {filename} to Nextcloud: {response.status_code} - {response.text}"
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_nextcloud", "failure", error_msg, file_id=file_id)
raise Exception(error_msg)
except Exception as e:
error_msg = f"[ERROR] Failed to upload {filename} to Nextcloud: {str(e)}"
logger.error(error_msg)
error_msg = f"Failed to upload {filename} to Nextcloud: {str(e)}"
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_nextcloud", "failure", error_msg, file_id=file_id)
raise Exception(error_msg)
+32 -8
View File
@@ -10,6 +10,9 @@ from typing import Dict, Any
from app.config import settings
from app.tasks.retry_config import BaseTaskWithRetry
from app.celery_app import celery
from app.utils import log_task_progress
from app.database import SessionLocal
from app.models import FileRecord
logger = logging.getLogger(__name__)
@@ -81,12 +84,24 @@ def poll_task_for_document_id(task_id: str) -> int:
f"Task {task_id} didn't reach SUCCESS within {POLL_MAX_ATTEMPTS} attempts."
)
@celery.task(base=BaseTaskWithRetry)
def upload_to_paperless(file_path: str):
"""Uploads a file to Paperless-ngx."""
@celery.task(base=BaseTaskWithRetry, bind=True)
def upload_to_paperless(self, file_path: str, file_id: int = None):
"""
Uploads a file to Paperless-ngx.
Args:
file_path: Path to the file to upload
file_id: Optional file ID to associate with logs
"""
task_id = self.request.id
logger.info(f"[{task_id}] Starting Paperless upload: {file_path}")
log_task_progress(task_id, "upload_to_paperless", "in_progress", f"Uploading to Paperless: {os.path.basename(file_path)}", file_id=file_id)
if not os.path.exists(file_path):
raise FileNotFoundError(f"File not found: {file_path}")
error_msg = f"File not found: {file_path}"
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_paperless", "failure", error_msg, file_id=file_id)
raise FileNotFoundError(error_msg)
# Extract filename
filename = os.path.basename(file_path)
@@ -94,10 +109,13 @@ def upload_to_paperless(file_path: str):
# Check if Paperless settings are configured
if not settings.paperless_host or not settings.paperless_ngx_api_token:
error_msg = "Paperless-ngx credentials are not fully configured"
logger.error(error_msg)
logger.error(f"[{task_id}] {error_msg}")
log_task_progress(task_id, "upload_to_paperless", "failure", error_msg, file_id=file_id)
raise ValueError(error_msg)
# Upload the PDF
logger.info(f"[{task_id}] Posting document to Paperless")
log_task_progress(task_id, "post_document", "in_progress", "Posting to Paperless API", file_id=file_id)
post_url = _paperless_api_url("/api/documents/post_document/")
with open(file_path, "rb") as f:
files = {
@@ -110,18 +128,24 @@ def upload_to_paperless(file_path: str):
resp = requests.post(post_url, headers=_get_headers(), files=files, data=data)
resp.raise_for_status()
except requests.exceptions.RequestException as exc:
error_msg = f"Failed to upload to Paperless: {exc}"
logger.error(
"Failed to upload document '%s' to Paperless. Error: %s. Response=%s",
f"[{task_id}] Failed to upload document '%s' to Paperless. Error: %s. Response=%s",
file_path, exc, getattr(exc.response, "text", "<no response>")
)
log_task_progress(task_id, "upload_to_paperless", "failure", error_msg, file_id=file_id)
raise
raw_task_id = resp.text.strip().strip('"').strip("'")
logger.info(f"Received Paperless task ID: {raw_task_id}")
logger.info(f"[{task_id}] Received Paperless task ID: {raw_task_id}")
log_task_progress(task_id, "post_document", "success", f"Task ID: {raw_task_id}", file_id=file_id)
# Poll tasks until success/fail => get doc_id
logger.info(f"[{task_id}] Polling for document ID")
log_task_progress(task_id, "poll_task", "in_progress", "Waiting for Paperless processing", file_id=file_id)
doc_id = poll_task_for_document_id(raw_task_id)
logger.info(f"Document {file_path} successfully ingested => ID={doc_id}")
logger.info(f"[{task_id}] Document {file_path} successfully ingested => ID={doc_id}")
log_task_progress(task_id, "upload_to_paperless", "success", f"Uploaded to Paperless: Doc ID {doc_id}", file_id=file_id)
return {
"status": "Completed",
+145 -10
View File
@@ -43,6 +43,20 @@
.delete-btn:hover {
background-color: #fed7d7;
}
.view-logs-btn {
color: #3182ce;
cursor: pointer;
padding: 0.25rem 0.5rem;
border-radius: 0.25rem;
background: none;
border: none;
display: flex;
align-items: center;
margin-right: 0.5rem;
}
.view-logs-btn:hover {
background-color: #bee3f8;
}
.error-message {
background-color: #FEE2E2;
border: 1px solid #F87171;
@@ -76,8 +90,10 @@
background-color: white;
border-radius: 0.5rem;
padding: 2rem;
max-width: 500px;
max-width: 800px;
width: 90%;
max-height: 80vh;
overflow-y: auto;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
}
.modal-title {
@@ -110,6 +126,48 @@
.modal-btn-delete:hover {
background-color: #c53030;
}
/* Logs styles */
.logs-container {
margin-top: 1rem;
}
.log-entry {
padding: 0.75rem;
border-left: 3px solid #e2e8f0;
margin-bottom: 0.5rem;
background-color: #f7fafc;
border-radius: 0.25rem;
}
.log-entry.success {
border-left-color: #48bb78;
background-color: #f0fff4;
}
.log-entry.failure {
border-left-color: #f56565;
background-color: #fff5f5;
}
.log-entry.in_progress {
border-left-color: #4299e1;
background-color: #ebf8ff;
}
.log-step {
font-weight: 600;
color: #2d3748;
}
.log-message {
color: #4a5568;
margin-top: 0.25rem;
}
.log-timestamp {
font-size: 0.875rem;
color: #718096;
margin-top: 0.25rem;
}
.no-logs {
text-align: center;
padding: 2rem;
color: #718096;
}
</style>
{% endblock %}
@@ -147,9 +205,14 @@
<td>{{ file.mime_type }}</td>
<td>{{ file.created_at }}</td>
<td>
<button onclick="showDeleteModal('{{ file.id }}')" class="delete-btn">
<i class="fas fa-trash"></i>
</button>
<div style="display: flex; align-items: center;">
<button onclick="showLogs('{{ file.id }}')" class="view-logs-btn" title="View processing logs">
<i class="fas fa-list"></i>
</button>
<button onclick="showDeleteModal('{{ file.id }}')" class="delete-btn" title="Delete file">
<i class="fas fa-trash"></i>
</button>
</div>
</td>
</tr>
{% else %}
@@ -173,32 +236,104 @@
</div>
</div>
<!-- Processing logs modal -->
<div id="logsModal" class="modal">
<div class="modal-content">
<div class="modal-title">Processing Logs</div>
<div id="logsContent">
<p>Loading logs...</p>
</div>
<div class="modal-buttons">
<button id="closeLogsModal" class="modal-btn modal-btn-cancel">Close</button>
</div>
</div>
</div>
<!-- Add JavaScript for handling DELETE requests -->
<script>
// Modal functionality
const modal = document.getElementById('deleteModal');
const deleteModal = document.getElementById('deleteModal');
const logsModal = document.getElementById('logsModal');
const cancelDelete = document.getElementById('cancelDelete');
const confirmDelete = document.getElementById('confirmDelete');
const closeLogsModal = document.getElementById('closeLogsModal');
let currentFileId = null;
function showDeleteModal(fileId) {
currentFileId = fileId;
modal.style.display = 'flex';
deleteModal.style.display = 'flex';
}
function showLogs(fileId) {
logsModal.style.display = 'flex';
document.getElementById('logsContent').innerHTML = '<p>Loading logs...</p>';
// Fetch logs from API
fetch(`/api/logs/file/${fileId}`)
.then(response => {
if (!response.ok) {
throw new Error('Failed to fetch logs');
}
return response.json();
})
.then(data => {
displayLogs(data);
})
.catch(error => {
console.error('Error:', error);
document.getElementById('logsContent').innerHTML =
`<div class="error-message">Error loading logs: ${error.message}</div>`;
});
}
function displayLogs(data) {
const logsContent = document.getElementById('logsContent');
if (!data.logs || data.logs.length === 0) {
logsContent.innerHTML = '<div class="no-logs">No processing logs found for this file.</div>';
return;
}
let html = '<div class="logs-container">';
html += `<h3 style="margin-bottom: 1rem;">File: ${data.file.original_filename}</h3>`;
data.logs.forEach(log => {
const statusClass = log.status.toLowerCase().replace(' ', '_');
const timestamp = new Date(log.timestamp).toLocaleString();
html += `
<div class="log-entry ${statusClass}">
<div class="log-step">${log.step_name} - ${log.status}</div>
${log.message ? `<div class="log-message">${log.message}</div>` : ''}
<div class="log-timestamp">${timestamp}</div>
</div>
`;
});
html += '</div>';
logsContent.innerHTML = html;
}
cancelDelete.addEventListener('click', () => {
modal.style.display = 'none';
deleteModal.style.display = 'none';
});
confirmDelete.addEventListener('click', () => {
deleteFile(currentFileId);
modal.style.display = 'none';
deleteModal.style.display = 'none';
});
closeLogsModal.addEventListener('click', () => {
logsModal.style.display = 'none';
});
// Close modal if clicking outside of it
window.addEventListener('click', (event) => {
if (event.target === modal) {
modal.style.display = 'none';
if (event.target === deleteModal) {
deleteModal.style.display = 'none';
}
if (event.target === logsModal) {
logsModal.style.display = 'none';
}
});