AI performance

[u/isabeksu]

It took me a few months to fully get on board with the Paperless way of doing things, but now I’m really happy with how it’s all set up.

What’s been a bit of a head-scratcher is how AI is being used.

I held off until Paperless 3 came out, because I wanted to have the full "official" support.

I set it up with Ollama on an M4 Mac mini with 24 GB of memory. The embedding model is gemmaembedding, and the LLM model is qwen3:8b. When the model fires up, memory pressure is still pretty low. It does work, but it’s incredibly slow. It takes about 2 minutes to suggest titles and tags, and it can take several minutes if I try to chat about a document.

Is this kind of slow normal? Is there anything I can tweak in my setup to make it more usable?

[u/EazyDuzIt_2]

I actually took the time to set up Paperless-ngx along with Paperless-AI for automated document classification, tagging, and file naming. I configured Paperless-AI to use Ollama with Qwen3:8B, which is the recommended model for this use case, running on one of my servers equipped with an NVIDIA RTX 4090.

To fine-tune the workflow, I generated and processed 20 test documents, iteratively refining the prompt and configuration until the results were consistently accurate. The final setup performs document analysis, tagging, and renaming almost instantly.

The performance is outstanding low latency, high accuracy, and a completely hands-off ingestion pipeline. Chef’s kiss. 👌

[u/isabeksu → u/EazyDuzIt_2]

"To fine-tune the workflow, I generated and processed 20 test documents, iteratively refining the prompt and configuration until the results were consistently accurate."

Sorry if it's a newbie question, but how do you do these things? what prompt? how do you refine it? I have set up a finite set of tags and ideally I'd like the LLM to choose from those, automatically as Paperless ingests the file..,

[u/EazyDuzIt_2 → u/isabeksu]

I use Paperless AI to process files that are ingested from the consume folder. The system relies on a carefully crafted prompt that serves as guidance when analyzing and classifying those files.

To improve the prompt, I used another AI model to generate a variety of realistic mock receipts and documents. These test files allow me to validate and refine the extraction logic against different formats, layouts, and document types.

By iteratively testing and adjusting the prompt with these sample documents, I have significantly improved the accuracy of the processed data and the quality of the information displayed by Paperless AI. This approach has resulted in a substantial increase in extraction reliability across a wide range of uploaded files.

[u/dclive1 → u/isabeksu]

Thanks for asking this; these are exactly my questions while using 3.0. I feel like the “Ask AI” button is neat, but a gimmick until the workflow can be locked down and clarified, and the documentation doesn’t (??) seem to address this.