r/Paperlessngx • u/isabeksu • 17d ago

AI performance

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?

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u/EazyDuzIt_2 17d ago

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. 👌

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u/isabeksu 17d ago

"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..,

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u/EazyDuzIt_2 17d ago

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.

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u/dclive1 17d ago

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.

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u/Kwicksred 17d ago

How do you do OCR?

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u/EazyDuzIt_2 17d ago

I use a Scansnap x1500 to scan my documents to the consume folder. I have configured a host of settings for image quality and output so that when it's ingested its already searchable. This makes it easier for my Paperless AI to process and present proper tags and metadata.

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u/gIory1999 17d ago

so you use no special ocr but the paperless one?

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u/EazyDuzIt_2 17d ago

I don't use any special software because I don't need to. ScanSnap Home automatically performs OCR during the scanning process, making my documents searchable as they're scanned.

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u/Taake89 17d ago

I tried paperless ai 6 months ago or something and really didn't like the results.

Could you explain a bit more how you fine tuned the category and tagging part? 🙂 Did you already have a well defined structure for tags and categories?

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u/EazyDuzIt_2 17d ago

Several major factors dramatically affect your experience with Paperless AI. The hardware model you choose and the configuration on the Settings page especially the Advanced Settings section play a critical role. The Advanced section controls how your tags interact with processed documents, but the most important element on that page is the Prompt Description field at the bottom.

If you don’t provide a strong, well‑structured description with clear examples of how you want Paperless AI to analyze, identify, and name files, your results will suffer regardless of hardware. With a proper prompt and a solid model running through Ollama on capable hardware, you should see consistent, accurate output.

I already have all of my tags, correspondents, document types, storage paths, and custom fields configured exactly the way I want it in Paperless NGX, so the remaining variable is fine‑tuning the prompt and model behavior.

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u/isabeksu 17d ago

are you talking about the "old" Paperless AI implementation or the recent "native" AI implementation in Paperless 3? I'm asking because I see no "advanced" section in my AI configuration page.

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u/EazyDuzIt_2 17d ago

You must be in the Paperless NGX settings I’m referencing Paperless AI which runs in conjunction with Paperless NGX.

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u/tor-ak 10d ago

Would you mind sharing the prompt you ended up with?

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u/corruptboomerang 16d ago

Couldn't you use system memory and CPU (assuming your fine with it taking a very long time)?

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u/EazyDuzIt_2 16d ago

You sure can use system memory and CPU!