chatbot-ui VS text-generation-webui

One of the first things we did when GPT-4 became available was talk to our Azure rep and get access to the OpenAI models that they'd partnered with Microsoft to host in Azure. Now, we have our own private, not-datamined (so they claim, contractually) API endpoint and we use an OpenAI integration in VS Code[1] to connect to, allowing anyone in the company to use it to help them code.

I also spun up an internal chat UI[2] to replace ChatGPT so people can feel comfortable discussing proprietary data with the LLM endpoint.

The only thing that would make it more secure would be running inference engines internally, but I wouldn't have access to as good of models, and I'd need a _lot_ of hardware to match the speeds.

[1] - https://marketplace.visualstudio.com/items?itemName=AndrewBu...

[2] - https://github.com/mckaywrigley/chatbot-ui (legacy branch)

[3] https://github.com/mckaywrigley/chatbot-ui

Thank you for the work.

Please take this in a nice way: I can't see why I would use this over ChatbotUI+Ollama https://github.com/mckaywrigley/chatbot-ui

Seem the only advantage is having it as MacOS native app and only real distinction is maybe fast import and search - I've yet to try that though.

ChatbotUI (and other similar stuff) are cross-platform, customizable, private, debuggable. I'm easily able to see what it's trying to do.

You can make a privacy request for OpenAI to not train on your data here: https://privacy.openai.com/

Alternatively, you could also use your own UI/API token (API calls aren't trained on). Chatbot UI just got a major update released and has nice things like folders, and chat search: https://github.com/mckaywrigley/chatbot-ui

Also chatbotUI is great https://github.com/mckaywrigley/chatbot-ui it has a ui similar to chatgpt

> The comment I screenshotted is passive-aggressive at best, and there's no really good way to ask "is this repo dead" without being passive-aggressive. My day-to-day job that actually pays me a salary wouldn't ever provide a bulleted list of the reasons I suck, let alone a project I develop in my spare time.

There is nothing passive-aggressive about that comment. There is nothing problematic about it at all. Nobody's calling you slurs or making demands. I see one guy who might as well be a Mormon Boy Scout from Canada. "Is this repo dead" is not passive-aggressive, just ineloquent. Fuck my eyes until the jelly leaks out my ears if a courteous and professionally-written question constitutes "applying pressure and being rude" these days.

I don't know what a "bulleted list of the reasons [you] suck" has to do with anything (I don't see where anybody sent you one) but you're coming across as someone who invites people to your garage sale and then brandishes a shotgun and starts screaming when they set foot on your property.

> I’ve never seen any discussions or articles about whether it’s appropriate to ask if an open source repository is dead. Is there an implicit contract to actively maintain any open source software you publish? Are you obligated to provide free support if you hit a certain star amount on GitHub or ask for funding through GitHub Sponsorships/Patreon? After all, most permissive open source code licenses like the MIT License contain some variant of “the software is provided ‘as is’, without warranty of any kind.”

Here's an example of why everyone should ask if an open source project is dead:

https://github.com/mckaywrigley/chatbot-ui/issues

A number of issues complain about it leaking OpenAI keys. Nobody's figured out how, but it'd be nice to know if anybody's working on it, if it's worth submitting a PR, if it should be forked, if it's worth bothering with at all. This code is a massive liability in its current state. Its creator is absent. It warrants questions being asked about its future. Yeah, it's as-is software, but it's not an affront to your mother's virtue when someone asks if your shit still works or if you have plans to fix it.

> I’ve had an existential crisis about my work in open source AI on GitHub, particularly as there has been both increasingly toxic backlash against AI and because the AI industry has been evolving so rapidly that I flat-out don’t have enough bandwidth to keep up

Herein lies the problem? You sound overwhelmed. I've been there myself. I don't know what your year's been like but you genuinely might want to get away from the screen and get some fresh air. This is a good time of year to do it, since things generally slow down at work.

Some of the tools offer a path to doing tool use (fetching URLs and doing things with them) or RAG (searching your documents). I think Oobabooga https://github.com/oobabooga/text-generation-webui offers the latter through plugins.

Our tool, https://github.com/transformerlab/transformerlab-app also supports the latter (document search) using local llms.

You can use webui https://github.com/oobabooga/text-generation-webui

Once you get a version up and running I make a copy before I update it as several times updates have broken my working version and caused headaches.

a decent explanation of parameters outside of reading archive papers: https://github.com/oobabooga/text-generation-webui/wiki/03-%...

a news ai website:

The other answers are recommending paths which give you #1. less control and #2. projects with smaller eco-systems.

If you want a truly general purpose front-end for LLMs, the only good solution right now is oobabooga: https://github.com/oobabooga/text-generation-webui

All other alternatives have only small fractions of the features that oobabooga supports. All other alternatives only support a fraction of the LLM backends that oobabooga supports, etc.

The example waifu in text-generation-webui is good enough for me.

https://github.com/oobabooga/text-generation-webui/blob/main...

> Downloading text-generation-webui takes a minute, let's you use any model and get going.

What you're missing here is you're already in this area deep enough to know what ooogoababagababa text-generation-webui is. Let's back out to the "average Windows desktop user" level. Assuming they even know how to find it:

1) Go to https://github.com/oobabooga/text-generation-webui?tab=readm...

2) See a bunch of instructions opening a terminal window and running random batch/powershell scripts. Powershell, etc will likely prompt you with a scary warning. Then you start wondering who ooobabagagagaba is...

3) Assuming you get this far (many users won't even get to step 1) you're greeted with a web interface[0] FILLED to the brim with technical jargon and extremely overwhelming options just to get a model loaded, which is another mind warp because you get to try to select between a bunch of random models with no clear meaning and non-sensical/joke sounding names from someone called "TheBloke". Ok...

Let's say you somehow braved this gauntlet and get this far now you get to chat with it. Ok, what about my local documents? text-generation-webui itself has nothing for that. Repeat this process over the 10 random open source projects from a bunch of names you've never heard of in an attempt to accomplish that.

This is "I saw this thing from Nvidia explode all over media, twitter, youtube, etc. I downloaded it from Nvidia, double-clicked, pointed it at a folder with documents, and it works".

That's the difference and it's very significant.

[0] - https://raw.githubusercontent.com/oobabooga/screenshots/main...

Maybe a copout answer, but setting up a local LLM on my development machine has been invaluable. I use Deep Seek Coder 6.7 [0] and Oobabooga's UI [1]. It helps me solve simple problems and find bugs, while still leaving the larger architecture decisions to me.

[0] https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instr...

[1] https://github.com/oobabooga/text-generation-webui

You can download it and run it with [this](https://github.com/oobabooga/text-generation-webui). There's an API mode that you could leverage from your VS Code extension.

Same question here. Ollama is fantastic as it makes it very easy to run models locally, But if you already have a lot of code that processes OpenAI API responses (with retry, streaming, async, caching etc), it would be nice to be able to simply switch the API client to Ollama, without having to have a whole other branch of code that handles Alama API responses. One way to do an easy switch is using the litellm library as a go-between but it’s not ideal (and I also recently found issues with their chat formatting for mistral models).

For an OpenAI compatible API my current favorite method is to spin up models using oobabooga TGW. Your OpenAI API code then works seamlessly by simply switching out the api_base to the ooba endpoint. Regarding chat formatting, even ooba’s Mistral formatting has issues[1] so I am doing my own in Langroid using HuggingFace tokenizer.apply_chat_template [2]

[1] https://github.com/oobabooga/text-generation-webui/issues/53...

[2] https://github.com/langroid/langroid/blob/main/langroid/lang...

Related question - I assume ollama auto detects and applies the right chat formatting template for a model?