open-webui VS private-gpt

Luckily, there are some open-source projects like Open WebUI, which provide a web-based experience similar to ChatGPT, that you can also run locally and point to any model. To start the Open WebUI Docker container locally, run the command below in your Terminal (make sure, that ollama serve is still running).

I like the project.

What does this have that is better than https://github.com/open-webui/open-webui ?

Be careful with unstructured:

https://github.com/Unstructured-IO/unstructured/blob/d11c70c...

from: https://github.com/open-webui/open-webui/issues/687

For anyone else who missed the announcement a few hours ago, open-webui is the rebranding of the project formerly known as ollama-webui [0].

I can vouch for it as a solid frontend for Ollama. It works really well and has had an astounding pace of development. Every few weeks I pull the latest docker images and am always surprised by how much has improved.

[0] https://github.com/open-webui/open-webui/discussions/764

PrivateGPT is a nice tool for this. It's not exactly what you're asking for, but it gets part of the way there.

https://github.com/zylon-ai/private-gpt

Further details available at: https://docs.privategpt.dev/api-reference/api-reference/ingestion

Run https://github.com/imartinez/privateGPT

Then

make ingest /path/to/folder/with/files

Then chat to the LLM.

Done.

Docs: https://docs.privategpt.dev/overview/welcome/quickstart

PrivateGPT repository in case anyone's interested: https://github.com/imartinez/privateGPT . It doesn't seem to be linked from their official website.

I’m preparing a small internal tool for my work to search documents and provide answers (with references), I’m thinking of using GPT4All [0], Danswer [1] and/or privateGPT [2].

The RAG technique is very close to what I have in mind, but I don’t want the LLM to “hallucinate” and generate answers on its own by synthesizing the source documents. As stated by many others, we’re living in interesting times.

[0] https://gpt4all.io/index.html

[1] https://www.danswer.ai/

[2] https://github.com/imartinez/privateGPT

https://www.reddit.com/r/LocalLLaMA/comments/14niv66/using_a...

https://github.com/imartinez/privateGPT

I've been playing around with https://github.com/imartinez/privateGPT and https://github.com/simonw/llm and wanted to create a simple Python package that made it easier to run ChatGPT-like LLMs on your own machine, use them with non-public data, and integrate them into practical applications.

This resulted in Python package I call OnPrem.LLM.

In the documentation, there are examples for how to use it for information extraction, text generation, retrieval-augmented generation (i.e., chatting with documents on your computer), and text-to-code generation: https://amaiya.github.io/onprem/

Enjoy!