Troubleshooting

No files are added by the consumer

Check for the following issues:

  • Ensure that the directory you’re putting your documents in is the folder paperless is watching. With docker, this setting is performed in the docker-compose.yml file. Without docker, look at the CONSUMPTION_DIR setting. Don’t adjust this setting if you’re using docker.

  • Ensure that redis is up and running. Paperless does its task processing asynchronously, and for documents to arrive at the task processor, it needs redis to run.

  • Ensure that the task processor is running. Docker does this automatically. Manually invoke the task processor by executing

    $ python3 manage.py qcluster
    
  • Look at the output of paperless and inspect it for any errors.

  • Go to the admin interface, and check if there are failed tasks. If so, the tasks will contain an error message.

Consumer fails to pickup any new files

If you notice that the consumer will only pickup files in the consumption directory at startup, but won’t find any other files added later, you will need to enable filesystem polling with the configuration option PAPERLESS_CONSUMER_POLLING, see here.

This will disable listening to filesystem changes with inotify and paperless will manually check the consumption directory for changes instead.

Paperless always redirects to /admin

You probably had the old paperless installed at some point. Paperless installed a permanent redirect to /admin in your browser, and you need to clear your browsing data / cache to fix that.

Operation not permitted

You might see errors such as:

chown: changing ownership of '../export': Operation not permitted

The container tries to set file ownership on the listed directories. This is required so that the user running paperless inside docker has write permissions to these folders. This happens when pointing these directories to NFS shares, for example.

Ensure that chown is possible on these directories.

Classifier error: No training data available

This indicates that the Auto matching algorithm found no documents to learn from. This may have two reasons:

  • You don’t use the Auto matching algorithm: The error can be safely ignored in this case.

  • You are using the Auto matching algorithm: The classifier explicitly excludes documents with Inbox tags. Verify that there are documents in your archive without inbox tags. The algorithm will only learn from documents not in your inbox.

UserWarning in sklearn on every single document

You may encounter warnings like this:

/usr/local/lib/python3.7/site-packages/sklearn/base.py:315:
UserWarning: Trying to unpickle estimator CountVectorizer from version 0.23.2 when using version 0.24.0.
This might lead to breaking code or invalid results. Use at your own risk.

This happens when certain dependencies of paperless that are responsible for the auto matching algorithm are updated. After updating these, your current training data might not be compatible anymore. This can be ignored in most cases. This warning will disappear automatically when paperless updates the training data.

If you want to get rid of the warning or actually experience issues with automatic matching, delete the file classification_model.pickle in the data directory and let paperless recreate it.

504 Server Error: Gateway Timeout when adding Office documents

You may experience these errors when using the optional TIKA integration:

requests.exceptions.HTTPError: 504 Server Error: Gateway Timeout for url: http://gotenberg:3000/convert/office

Gotenberg is a server that converts Office documents into PDF documents and has a default timeout of 10 seconds. When conversion takes longer, Gotenberg raises this error.

You can increase the timeout by configuring an environment variable for gotenberg (see also here). If using docker-compose, this is achieved by the following configuration change in the docker-compose.yml file:

gotenberg:
    image: thecodingmachine/gotenberg
    restart: unless-stopped
    environment:
        DISABLE_GOOGLE_CHROME: 1
        DEFAULT_WAIT_TIMEOUT: 30

Permission denied errors in the consumption directory

You might encounter errors such as:

The following error occured while consuming document.pdf: [Errno 13] Permission denied: '/usr/src/paperless/src/../consume/document.pdf'

This happens when paperless does not have permission to delete files inside the consumption directory. Ensure that USERMAP_UID and USERMAP_GID are set to the user id and group id you use on the host operating system, if these are different from 1000. See Install Paperless from Docker Hub.

Also ensure that you are able to read and write to the consumption directory on the host.

OSError: [Errno 19] No such device when consuming files

If you experience errors such as:

File "/usr/local/lib/python3.7/site-packages/whoosh/codec/base.py", line 570, in open_compound_file
return CompoundStorage(dbfile, use_mmap=storage.supports_mmap)
File "/usr/local/lib/python3.7/site-packages/whoosh/filedb/compound.py", line 75, in __init__
self._source = mmap.mmap(fileno, 0, access=mmap.ACCESS_READ)
OSError: [Errno 19] No such device

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/django_q/cluster.py", line 436, in worker
res = f(*task["args"], **task["kwargs"])
File "/usr/src/paperless/src/documents/tasks.py", line 73, in consume_file
override_tag_ids=override_tag_ids)
File "/usr/src/paperless/src/documents/consumer.py", line 271, in try_consume_file
raise ConsumerError(e)

Paperless uses a search index to provide better and faster full text searching. This search index is stored inside the data folder. The search index uses memory-mapped files (mmap). The above error indicates that paperless was unable to create and open these files.

This happens when you’re trying to store the data directory on certain file systems (mostly network shares) that don’t support memory-mapped files.

Web-UI stuck at “Loading…”

This might have multiple reasons.

  1. If you built the docker image yourself or deployed using the bare metal route, make sure that there are files in <paperless-root>/static/frontend/<lang-code>/. If there are no files, make sure that you executed collectstatic successfully, either manually or as part of the docker image build.

    If the front end is still missing, make sure that the front end is compiled (files present in src/documents/static/frontend). If it is not, you need to compile the front end yourself or download the release archive instead of cloning the repository.

  2. Check the output of the web server. You might see errors like this:

    [2021-01-25 10:08:04 +0000] [40] [ERROR] Socket error processing request.
    Traceback (most recent call last):
    File "/usr/local/lib/python3.7/site-packages/gunicorn/workers/sync.py", line 134, in handle
        self.handle_request(listener, req, client, addr)
    File "/usr/local/lib/python3.7/site-packages/gunicorn/workers/sync.py", line 190, in handle_request
        util.reraise(*sys.exc_info())
    File "/usr/local/lib/python3.7/site-packages/gunicorn/util.py", line 625, in reraise
        raise value
    File "/usr/local/lib/python3.7/site-packages/gunicorn/workers/sync.py", line 178, in handle_request
        resp.write_file(respiter)
    File "/usr/local/lib/python3.7/site-packages/gunicorn/http/wsgi.py", line 396, in write_file
        if not self.sendfile(respiter):
    File "/usr/local/lib/python3.7/site-packages/gunicorn/http/wsgi.py", line 386, in sendfile
        sent += os.sendfile(sockno, fileno, offset + sent, count)
    OSError: [Errno 22] Invalid argument
    

    To fix this issue, add

    SENDFILE=0
    

    to your docker-compose.env file.

Error while reading metadata

You might find messages like these in your log files:

[WARNING] [paperless.parsing.tesseract] Error while reading metadata

This indicates that paperless failed to read PDF metadata from one of your documents. This happens when you open the affected documents in paperless for editing. Paperless will continue to work, and will simply not show the invalid metadata.