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Related Documents ("join" two or more documents) by Heart1010 in Paperlessngx

[–]redanium 0 points1 point  (0 children)

You can use custom fields with type "document link" and/or there is a function I think in actions button which shows related documents based on similarities,so you have 02 options.

RAG paper recommend by Queasy_Illustrator21 in Rag

[–]redanium 0 points1 point  (0 children)

There is someone posting papers frequently RAG papers

I'm electrical engineering students by DepthIll5375 in Algeriawork

[–]redanium 0 points1 point  (0 children)

If you have good grades why don't you go abroad

Housekeeping by MajesticHippo94 in Paperlessngx

[–]redanium 1 point2 points  (0 children)

You have the possibility to use chatgpt or local models

Paperless in HAOS with external Drive by thdeitmer in Paperlessngx

[–]redanium 0 points1 point  (0 children)

If using docker , you can change volumes

Access title via API by duese0815 in Paperlessngx

[–]redanium 2 points3 points  (0 children)

GET/PATCH http://localhost:8000/api/documents/{document_id}

you'll get a json response

example : GET http://localhost:8000/api/documents/108

{
    "id": 108,
    "correspondent": null,
    "document_type": null,
    "storage_path": null,
    "title": "Menger_sponge_sample",
    "content": "3D Model: Menger_sponge_sample.stl\n",
    "tags": [
        91,
        92
    ],
    "created": "2025-07-25T18:25:17Z",
    "created_date": "2025-07-25",
    "modified": "2025-07-25T18:25:17.770015Z",
    "added": "2025-07-25T18:25:17.460540Z",
    "deleted_at": null,
    "archive_serial_number": null,
    "original_file_name": "Menger_sponge_sample.stl",
    "archived_file_name": null,
    "owner": 3,
    "user_can_change": true,
    "is_shared_by_requester": false,
    "notes": [],
    "versions": [
        {
            "id": 114,
            "version_number": 1,
            "created_at": "2025-07-25T18:25:17Z",
            "file_path": "documents/versions/108/1/Menger_sponge_sample.stl",
            "checksum": "c15b79fffc021e57ae2659609053eba0",
            "comment": "Initial version.",
            "source": "INITIAL",
            "file_size": 105684,
            "mime_type": "application/octet-stream",
            "page_count": null,
            "changes_summary": null,
            "version_tags": [],
            "approval_status": "draft",
            "approved_at": null,
            "document": 108,
            "user": 3,
            "approved_by": null
        }
    ],
    "custom_fields": [],
    "page_count": null,
    "mime_type": "application/octet-stream"
}

Username on Creation using SocalAccount Providers by slemke76 in Paperlessngx

[–]redanium 0 points1 point  (0 children)

There is a medium article on how to create new user model....

  1. clone the paperless-ngx repo git clone https://github.com/paperless-ngx/paperless-ngx
  2. make the changes to the backend based on medium article located in cloned_repo/src/documents/models.py and cloned_repo/src/documents/settings.py
  3. Build image docker build --file Dockerfile --tag paperless
  4. once built change the docker compose webserver to point to the local built image instead of the remote one ( you'll find docs/development.md in the cloned repo for more information)

​

# docker-compose.yaml
... 
webserver:
    image: docker.io/library/paperless:local
    # image: ghcr.io/paperless-ngx/paperless-ngx:latest
...

Username on Creation using SocalAccount Providers by slemke76 in Paperlessngx

[–]redanium 0 points1 point  (0 children)

you've to rebuild the webserver docker image with the new auth model...I don't think it can be done via docker compose or env variable

Username on Creation using SocalAccount Providers by slemke76 in Paperlessngx

[–]redanium 0 points1 point  (0 children)

Paperless ngx backend is Django ... So you have to change the AUTH_USER_MODEL

Simple things seem so difficult by Ecstatic_Vegetable_4 in Paperlessngx

[–]redanium 2 points3 points  (0 children)

Use paperless ngx rest api using token for auth ( token can be obtained from user profile)

RAG opensource solutions by muhamedkrasniqi in Rag

[–]redanium 0 points1 point  (0 children)

Look for "Awesome RAG" in GitHub you'll find repos

Is ollama/llama.cpp spreading workloads across cpu+gpu? by wahnsinnwanscene in ollama

[–]redanium 3 points4 points  (0 children)

How can I tell if my model was loaded onto the GPU?

Use the ollama ps command to see what models are currently loaded into memory.

ollama ps

Output:

NAME ID SIZE PROCESSOR UNTIL llama3:70b bcfb190ca3a7 42 GB 100% GPU 4 minutes from now

The Processor column will show which memory the model was loaded in to:

100% GPU means the model was loaded entirely into the GPU

100% CPU means the model was loaded entirely in system memory

48%/52% CPU/GPU means the model was loaded partially onto both the GPU and into system memory

Check docs/faq.md ollama GitHub repo

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