Trenton H
2c58d86380
* Fix: Remove all nodes for multi-chunk documents in update_llm_index incremental path The existing_nodes dict comprehension keyed on document_id silently dropped all but the last node per document, so only that one node was deleted when a modified document was re-indexed, leaving all other chunks as ghost vectors in the FAISS index. Switch to a defaultdict(list) that collects every node per document_id, then iterate and delete all of them before inserting fresh nodes. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix: Wire document_updated signal to LLM index update handler Connect document_updated to add_or_update_document_in_llm_index in DocumentsConfig.ready() so REST API edits (PATCH /api/documents/{id}/) enqueue an LLM vector store update, matching the existing document_consumption_finished behavior. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix: Add file lock around FAISS index mutations to prevent concurrent write corruption Two concurrent Celery workers calling llm_index_add_or_update_document or llm_index_remove_document each loaded the same on-disk index independently, made their own change, and the last writer silently overwrote the first's update. Wrap both functions and the rebuild/persist body of update_llm_index in a filelock.FileLock keyed on LLM_INDEX_DIR/index.lock. Add a TOCTOU comment on queue_llm_index_update_if_needed explaining the residual risk (duplicate rebuild tasks are wasteful but not corrupting because the lock serialises the actual write). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix: Apply _normalize() in extract_unmatched_names to prevent duplicate suggestions extract_unmatched_names was using .lower() while _match_names_to_queryset uses _normalize() (which also strips punctuation). A name like "J. Smith" matched to existing correspondent "J Smith" would still appear in the unmatched list, causing duplicate object creation. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix: Skip LLM index update gracefully when document has no indexable content Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix: Persist empty index when all documents are deleted to clear stale FAISS vectors The early-return guard in update_llm_index fired before persist() when no documents existed, leaving a stale on-disk FAISS index that returned phantom hits for deleted document IDs. Now the guard only returns early for the incremental (rebuild=False) path when no index exists on disk; the rebuild path always continues through to persist(), producing an empty clean index. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Chore: Simplify incremental index update — use docs.values() and deduplicate node extend --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Paperless-ngx
Paperless-ngx is a document management system that transforms your physical documents into a searchable online archive so you can keep, well, less paper.
Paperless-ngx is the official successor to the original Paperless & Paperless-ng projects and is designed to distribute the responsibility of advancing and supporting the project among a team of people. Consider joining us!
Thanks to the generous folks at DigitalOcean, a demo is available at demo.paperless-ngx.com using login demo / demo. Note: demo content is reset frequently and confidential information should not be uploaded.
This project is supported by:
Features
A full list of features and screenshots are available in the documentation.
Getting started
The easiest way to deploy paperless is docker compose. The files in the /docker/compose directory are configured to pull the image from the GitHub container registry.
If you'd like to jump right in, you can configure a docker compose environment with our install script:
bash -c "$(curl -L https://raw.githubusercontent.com/paperless-ngx/paperless-ngx/main/install-paperless-ngx.sh)"
More details and step-by-step guides for alternative installation methods can be found in the documentation.
Migrating from Paperless-ng is easy, just drop in the new docker image! See the documentation on migrating for more details.
Documentation
The documentation for Paperless-ngx is available at https://docs.paperless-ngx.com.
Contributing
If you feel like contributing to the project, please do! Bug fixes, enhancements, visual fixes etc. are always welcome. If you want to implement something big: Please start a discussion about that! The documentation has some basic information on how to get started.
Community Support
People interested in continuing the work on paperless-ngx are encouraged to reach out here on github and in the Matrix Room. If you would like to contribute to the project on an ongoing basis there are multiple teams (frontend, ci/cd, etc) that could use your help so please reach out!
Translation
Paperless-ngx is available in many languages that are coordinated on Crowdin. If you want to help out by translating paperless-ngx into your language, please head over to https://crowdin.com/project/paperless-ngx, and thank you! More details can be found in CONTRIBUTING.md.
Feature Requests
Feature requests can be submitted via GitHub Discussions, you can search for existing ideas, add your own and vote for the ones you care about.
Bugs
For bugs please open an issue or start a discussion if you have questions.
Related Projects
Please see the wiki for a user-maintained list of related projects and software that is compatible with Paperless-ngx.
Important Note
Document scanners are typically used to scan sensitive documents like your social insurance number, tax records, invoices, etc. Paperless-ngx should never be run on an untrusted host because information is stored in clear text without encryption. No guarantees are made regarding security (but we do try!) and you use the app at your own risk. The safest way to run Paperless-ngx is on a local server in your own home with backups in place.