AGiXT
text-generation-webui
AGiXT | text-generation-webui | |
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26 | 876 | |
2,456 | 36,552 | |
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9.9 | 9.9 | |
4 days ago | 5 days ago | |
Python | Python | |
MIT License | GNU Affero General Public License v3.0 |
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AGiXT
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Conversational "memory loss"?
If you are more interested in AI assistants check out AGiXT. It has some really cool features but it is under heavy development. Not everything works jet and updates break sometimes already working functions. But it is still far better than babyAGI and other proof of concepts.
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Microsoft Research proposes new framework, LongMem, allowing for unlimited context length along with reduced GPU memory usage and faster inference speed. Code will be open-sourced
That's exactly my goal right now too! I have been trying to figure out how to use AGiXT agents to read and write to an "Adventurer's Log" text file to try to mimic a long term memory but honestly I'm not good enough with any of this to get it working yet. The idea I've got rn is that there'd be a DM agent which takes your input and then there'd be "memory" agents which would check text files such as "Adventurer's Log" and "Character Interactions/Relationships" to keep a contiguous understanding of what each character has done, who they've met, what they've been told/haven't been told by certain characters about their motivations. I'm sure there's someone *much* more talented than me working on this already, at this point I've sort of given up on the idea and I'm just waiting for someone to come out with a Tavern style interface where I can paste in world details and character details and just get going!
- AGiXT: A local automation platform with memories and SmartGPT-like prompting. Works with Ooba/LCPP/GPT4All, and more
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What are the best AI tools you've ACTUALLY used?
AGiXT: A Python package for AGI research.
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?Best LLM service for a tiny home server
Even if my (for example, privateGPT) LLM is glacially slow I'd still love to be able to say "Mr Holmes, have Mrs Doubtfire verb the data object in order to verb a product for me, please." (eg: analyse the wikipedia article on the peace of westfalia in order to ELI5 a short summary of it). Hopefully she'd crunch away at the data, and at my convenience, I could have her brief me on her conclusions. I'm sure folks here would do something more clever using AGiXT, or having the old girl prepare lesson-plans for Mycroft to deliver (I just think that sort of thing is world-changing-bonkers for anyone wanting to learn anything, perhaps for kids one day), but I'd have to work up to that.
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LlamaCPP and LangChain Agent Quality
Keep an eye on this project as well. https://github.com/Josh-XT/AGiXT
- Using the right prompt format makes responses so much better
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How big of a jump is 13B Vicuna Uncensored vs 30B Vicuna Uncensored?
File upload and automatic agents. It exists it is just buggy. They are working at an insane pace building it. It is practically broke 90% of the time. Maybe it's working better right now. I had success with v1.1.31 as well. https://github.com/Josh-xt/AGiXT
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Langchain, Langchain.js, vs AutoGPT for local agent development
Maybe you want to check out josh-xt/AGiXT it has its roots in langchain so you can see what the prompts look like and the code. They have made a lot of tools as well although you are going to have issues getting it to work. The newest version kinda works and version 1.1.31 I had the fast API backend working. Maybe you can help them out. They need more people to show them bugs. https://github.com/Josh-XT/AGiXT
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Is there an alternative to AgentGPT that I can run on my CPU with 32 GB of RAM?
https://github.com/Josh-XT/AGiXT I have tested this one and it is pretty much the same as AgentGPT, supports many providers + many local models (you can even make it work with oobabooga api which is pretty easy), don’t wait for insane results, the problem right now is context length with the local models, probably going to be an old issue in a few weeks we hope ;)
text-generation-webui
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Ask HN: What is the current (Apr. 2024) gold standard of running an LLM locally?
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.
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Ask HN: How to get started with local language models?
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:
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text-generation-webui VS LibreChat - a user suggested alternative
2 projects | 29 Feb 2024
- Show HN: I made an app to use local AI as daily driver
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Ask HN: People who switched from GPT to their own models. How was it?
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.
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AI Girlfriend Is a Data-Harvesting Horror Show
The example waifu in text-generation-webui is good enough for me.
https://github.com/oobabooga/text-generation-webui/blob/main...
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Nvidia's Chat with RTX is a promising AI chatbot that runs locally on your PC
> 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...
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Ask HN: What are your top 3 coolest software engineering tools?
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
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Meta AI releases Code Llama 70B
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.
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Ollama Python and JavaScript Libraries
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?
What are some alternatives?
AgentOoba - An autonomous AI agent extension for Oobabooga's web ui
KoboldAI - KoboldAI is generative AI software optimized for fictional use, but capable of much more!
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
llama.cpp - LLM inference in C/C++
AgentGPT - 🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
gpt4all - gpt4all: run open-source LLMs anywhere
babyagi
TavernAI - Atmospheric adventure chat for AI language models (KoboldAI, NovelAI, Pygmalion, OpenAI chatgpt, gpt-4)
vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
KoboldAI-Client
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.