* Add sidecar.py module for User Story 0 (Paperless-ngx import)
Implements the sidecar data model, schema validation, atomic writes,
and I/O helpers per PRD section 7.
- Sidecar and SidecarEvent dataclasses with full PRD schema
- SidecarStatus and EventType enums
- build_sidecar(), serialize(), deserialize() functions
- validate_sidecar() with type and required field checking
- get_sidecar_key() for .meta.json suffix generation
- write_atomic() for crash-safe temp-key + copy + delete pattern
- read_sidecar(), sidecar_exists(), matching_sha256() for storage I/O
This is a reusable component for both the import script and main service.
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Add storage/ module with S3 and File backends
Implements the storage layer abstraction for User Story 0.
- StorageBackend ABC: defines interface for all storage implementations
- S3Storage: boto3-based backend for Garage S3 (production)
- FileStorage: filesystem-based backend for testing
- get_storage_backend() factory function
- Atomic operations: put, get, delete, copy, exists, list, head
Both backends implement the same interface, allowing seamless
switching between production S3 and local testing.
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Add period.py, extractor.py, and config.py reusable modules
- period.py: Period parsing from filenames and computation from dates
- parse_period_from_filename(): Extracts month-year, quarter, year, date patterns
- compute_period_from_date(): Computes period per template rules (granularity + offset)
- get_period(): Main entry point with filename fallback to rule-based computation
- validate_period_consistency(): Checks period vs emission_date + rule
- Supports French month names (août, janvier, etc.)
- extractor.py: PDF text extraction using PyMuPDF
- extract_first_page_text(): Extracts text from first PDF page
- extract_and_validate(): Extracts and checks minimum text length
- TextExtractor class for dependency injection and mocking
- config.py: Configuration management
- S3Config, PaperlessConfig, PollerConfig, ClassifierConfig dataclasses
- AppConfig: Main application configuration from env vars
- TemplateRegistry: Loads and manages template YAML configurations
- load_config(), load_templates() helper functions
All modules are reusable by both import script and main service.
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Add import_paperless.py script for User Story 0
Implements the standalone import script that:
- Connects to Paperless-ngx REST API (PAPERLESS_URL + token from env)
- Connects to Garage S3 bucket via boto3 (S3_ENDPOINT_URL, credentials, bucket)
- Lists all documents from Paperless via paginated /api/documents/
- Fetches document metadata and maps to sidecar fields:
- template: first path segment of storage_path
- emission_date: document created field
- emitting_company: correspondent name
- document_type: document type name
- period: parsed from filename tail, fallback to month-year from emission_date
- extracted_text: first page text via PyMuPDF
- optional_fields: from Paperless labels
- Downloads PDF via /api/documents/{id}/download/
- Stores PDF at files/{template}/{original filename}
- Writes sidecar {key}.meta.json with atomic temp-key + copy pattern
- Supports resumability (skip if PDF + sidecar exist with matching SHA256)
- Dry-run flag for testing
- Limit flag for trial runs
- Summary reporting at end
- Exit code: 0 if all succeed, 1 if any failures
Dependencies: requests, boto3, pymupdf, python-dateutil
Usage: python scripts/import_paperless.py [--dry-run] [--limit N] [--verbose]
Environment: PAPERLESS_URL, PAPERLESS_TOKEN, S3_ENDPOINT_URL, S3_ACCESS_KEY_ID, S3_SECRET_ACCESS_KEY, S3_BUCKET_NAME
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Add requirements.txt for import script dependencies
Lists all Python dependencies needed to run scripts/import_paperless.py:
- requests: Paperless-ngx API client
- boto3: Garage S3 client
- pymupdf: PDF text extraction
- python-dateutil: Date parsing
- PyYAML: YAML config parsing (optional)
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Update import script: add storage backend selection (s3/file)
- Added --storage-backend argument (choices: s3, file, default: s3)
- Added --file-base-dir argument for file storage
- Storage backend validation based on selection
- Updated help text and epilog with backend-specific env vars
- Importer class now accepts storage_backend and file_base_dir params
- _init_storage() method handles backend initialization
- Summary now shows which storage backend was used
Usage examples:
# S3 storage (default)
python scripts/import_paperless.py
# File storage for testing
python scripts/import_paperless.py --storage-backend file --file-base-dir ./test_storage
# Explicit S3
python scripts/import_paperless.py --storage-backend s3 --s3-endpoint ... --s3-bucket ...
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Add README.md for scripts directory
Comprehensive documentation for import_paperless.py script:
- Overview and features
- Requirements and installation
- Usage examples (env vars + CLI args)
- Storage backends (S3 vs file)
- Metadata mapping table
- Output structure
- Resumability notes
- Exit codes
- Example output
- Troubleshooting guide
- Development/testing notes
- Architecture overview
Helps users understand how to use the import script for User Story 0.
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Fix Paperless API field mapping
The Paperless-ngx API returns IDs for correspondent, document_type, and tags,
not the actual string values. This commit fixes the import script to:
- Use 'archived_file_name' instead of 'filename' for the actual filename
- Fetch correspondent name from /api/correspondents/{id}/ endpoint
- Fetch document type name from /api/document_types/{id}/ endpoint
- Fetch tag names from /api/tags/{id}/ endpoint
- Add caching for fetched entities to avoid duplicate API requests
This ensures the sidecar metadata contains actual human-readable strings
instead of numeric IDs.
Changes:
- PaperlessClient: Added get_correspondent_name(), get_document_type_name(), get_tag_name()
- PaperlessClient: Added caches for fetched entities
- get_all_documents(): Now resolves IDs to names for all fields
- Updated module docstring to document this behavior
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
* Refactor PaperlessClient: change labels to list, add storage path caching, and improve document fetching logic
---------
Co-authored-by: Vibe Nuage Agent <vibe@mistral.ai>
Co-authored-by: napnap75 <napnap75@users.noreply.github.com>
- Introduced alerters package with base Alerter class and implementations for LogAlerter and GotifyAlerter.
- Created fetchers package with abstract LogFetcher class and implementations for FileLogFetcher, LokiLogFetcher, and ParseableLogFetcher.
- Added filters package with base Filter class and implementations for RegexpFilter and GeolocationFilter.
- Implemented rules package with base AlertRule class and SimpleAlertRule for alerting logic.
- Enhanced configuration handling with utilities for loading and validating JSON configuration.
- Updated logging setup for better logging management.
- Modified main application logic to utilize the new modular structure, improving maintainability and readability.
- Updated config.json and config.schema.json to reflect changes in alerting and fetching configurations.
- Added python-dateutil to requirements for date parsing functionality.
