KoboldAI VS text-generation-webui

It’s not that big a task as all that. There are a lot of unaligned models available, and user interfaces that aren’t that hard to use.

https://github.com/henk717/KoboldAI

https://github.com/henk717/KoboldAI

- Hosts pick a quantized community LLM to run, which is (IMO) the real magic of this system. Cloud services tend to run generic Llama chat/instruct models, OpenAI API models, or maybe a single proprietary finetune, but the Llama/Mistral finetuning community is red hot. New finetines and crazy merges/hybrids that outperform llama-chat in specific tasks (mostly Chat/Story/RP) come out every day, and each one has a different "flavor" and format:

https://huggingface.co/models?sort=modified&search=mistral+g...

Sourceforge is our official version but that one is to old to run newer models like Holomax, the releases for United can be found here : https://github.com/henk717/KoboldAI/releases

Colab Check: False, TPU: False INIT | OK | KAI Horde Models INFO | __main__::648 - We loaded the following model backends: KoboldAI API KoboldAI Old Colab Method Huggingface GooseAI Horde OpenAI Read Only INFO | __main__:general_startup:1363 - Running on Repo: https://github.com/henk717/koboldai Branch: INIT | Starting | Flask INIT | OK | Flask INIT | Starting | Webserver INIT | OK | Webserver MESSAGE | Webserver started! You may now connect with a browser at http://127.0.0.1:8501 INIT | Searching | GPU support INIT | Found | GPU support INIT | Starting | LUA bridge INIT | OK | LUA bridge INIT | Starting | LUA Scripts INIT | OK | LUA Scripts Setting Seed Traceback (most recent call last): File "B:\python\lib\site-packages\eventlet\hubs\selects.py", line 59, in wait listeners.get(fileno, hub.noop).cb(fileno) File "B:\python\lib\site-packages\eventlet\greenthread.py", line 221, in main result = function(*args, **kwargs) File "B:\python\lib\site-packages\eventlet\wsgi.py", line 837, in process_request proto.__init__(conn_state, self) File "B:\python\lib\site-packages\eventlet\wsgi.py", line 352, in __init__ self.finish() File "B:\python\lib\site-packages\eventlet\wsgi.py", line 751, in finish BaseHTTPServer.BaseHTTPRequestHandler.finish(self) File "B:\python\lib\socketserver.py", line 811, in finish self.wfile.close() File "B:\python\lib\socket.py", line 687, in write return self._sock.send(b) File "B:\python\lib\site-packages\eventlet\greenio\base.py", line 401, in send return self._send_loop(self.fd.send, data, flags) File "B:\python\lib\site-packages\eventlet\greenio\base.py", line 388, in _send_loop return send_method(data, *args) ConnectionAbortedError: [WinError 10053] An established connection was aborted by the software in your host machine Removing descriptor: 1488 Connection Attempt: 127.0.0.1 INFO | __main__:do_connect:2574 - Client connected! UI_1 TODO: Allow config INFO | modeling.inference_models.hf:set_input_parameters:189 - {'0_Layers': 18, 'CPU_Layers': 10, 'Disk_Layers': 0, 'class': 'model', 'label': 'PygmalionAI_pygmalion-6b', 'id': 'PygmalionAI_pygmalion-6b', 'name': 'PygmalionAI_pygmalion-6b', 'size': '', 'menu': 'Custom', 'path': 'C:\\KoboldAI\\models\\PygmalionAI_pygmalion-6b', 'ismenu': 'false', 'plugin': 'Huggingface'} INIT | Searching | GPU support INIT | Found | GPU support Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████| 2/2 [00:19<00:00, 9.60s/it] Loading model tensors: 100%|##########| 56/56 [00:05<00:00, 9.52it/s]INIT | Starting | LUA bridge0, 8.93s/it] INIT | OK | LUA bridge INIT | Starting | LUA Scripts INIT | OK | LUA Scripts Setting Seed Connection Attempt: 127.0.0.1 INFO | __main__:do_connect:2574 - Client connected! UI_1

That is our developer version, its selectable in the Colab version dropdown and also available on https://github.com/henk717/koboldai

Download Kobold from THIS LINK:https://github.com/henk717/KoboldAI. I downloaded Kobold from a different Github link and it wouldnt work, you need to get this specific one. Click on "code", then download zip

https://github.com/henk717/KoboldAI https://github.com/LostRuins/koboldcpp/ https://github.com/ggerganov/llama.cpp https://github.com/AUTOMATIC1111/stable-diffusion-webui https://github.com/oobabooga/text-generation-webui

For the third, I don't think Oobabooga supports the horde but KoboldAI does. I won't go into how to install KoboldAI since Oobabooga should give you enough freedom with 7B, 13B and maybe 30B models (depending on available RAM), but KoboldAI lets you download some models directly from the web interface, supports using online service providers to run the models for you, and supports the horde with a list of available models to choose from.

"Your Pytorch installation did not update correctly, you can solve this by running install_requirements.bat in the mode where it deletes the existing runtime. Alternative you can download a fresh copy of the offline installer for KoboldAI United from : https://github.com/henk717/KoboldAI/releases"

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?