private-gpt VS vault-ai

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!

There's this GitHub repo for Pinecone Vector with custom knowledge base: VaultAI. But I'm sure the costs would be exorbitant at scale. Basically trains it on specific files, but the API is expensive as expected. Edit: I didn't read and thought you were talking about training your own, sorry. But I'll leave the second paragraph up anyways lol. Someone mentioned LLaMA and another Falcon, the latter of which I hadn't heard of but which looks good too.

Check out the instructions readme here! You may need a little bit of command line know-how but chatgpt can help guide you if you provide it the contents of the readme

Yes, this use-case is a perfect fit actually – This deals very well with any type of manual with lots of human readable text (as opposed to charts or code). It is also better at answering more specific questions, so the example you gave regarding diagnosing engine issues is a really good match for what this is capable of. If you want to try it out you can check out the deployed version of the code here: https://vault.pash.city

Have you tried Vault AI? Saw it pop up on a couple of other Reddits!

OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (https://github.com/pashpashpash/vault-ai)