AGiXT
guidance
AGiXT | guidance | |
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26 | 89 | |
2,456 | 12,248 | |
- | - | |
9.9 | 9.5 | |
3 days ago | 9 months ago | |
Python | Jupyter Notebook | |
MIT License | MIT License |
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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 ;)
guidance
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Guidance: A guidance language for controlling large language models
This IS Microsoft Guidance, they seem to have spun off a separate GitHub organization for it.
https://github.com/microsoft/guidance redirects to https://github.com/guidance-ai/guidance now.
- LangChain Agent Simulation – Multi-Player Dungeons and Dragons
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Llama: Add Grammar-Based Sampling
... and it sets the value of "armor" to "leather" so that you can use that value later in your code if you wish to. Guidance is pretty powerful, but I find the grammar hard to work with. I think the idea of being able to upload a bit of code or a context-free grammar to guide the model is super smart.
https://github.com/microsoft/guidance/blob/d2c5e3cbb730e337b...
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Introducing TypeChat from Microsoft
Here's one thing I don't get.
Why all the rigamarole of hoping you get a valid response, adding last-mile validators to detect invalid responses, trying to beg the model to pretty please give me the syntax I'm asking for...
...when you can guarantee a valid JSON syntax by only sampling tokens that are valid? Instead of greedily picking the highest-scoring token every time, you select the highest-scoring token that conforms to the requested format.
This is what Guidance does already, also from Microsoft: https://github.com/microsoft/guidance
But OpenAI apparently does not expose the full scores of all tokens, it only exposes the highest-scoring token. Which is so odd, because if you run models locally, using Guidance is trivial, and you can guarantee your json is correct every time. It's faster to generate, too!
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Accessing Llama 2 from the command-line with the LLM-replicate plugin
Perhaps something as simple as stating it was first built around OpenAI models and later expanded to local via plugins?
I've been meaning to ask you, have you seen/used MS Guidance[0] 'language' at all? I don't know if it's the right abstraction to interface as a plugin with what you've got in llm cli but there's a lot about Guidance that seems incredibly useful to local inference [token healing and acceleration especially].
[0]https://github.com/microsoft/guidance
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AutoChain, lightweight and testable alternative to LangChain
LangChain is just too much, personal solutions are great, until you need to compare metrics or methodologies of prompt generation. Then the onus is on these n-parties who are sharing their resources to ensure that all of them used the same templates, they were generated the same way, with the only diff being the models these prompts were run on.
So maybe a simpler library like Microsoft's Guidance (https://github.com/microsoft/guidance)? It does this really well.
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Structured Output from LLMs (Without Reprompting!)
I am unclear on the status of the project but here is the conversation that seem to be tracking it: https://github.com/microsoft/guidance/discussions/201
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/r/guidance is now a subreddit for Guidance, Microsoft's template language for controlling language models!
Let's have a subreddit about Guidance!
- Is there a UI that can limit LLM tokens to a preset list?
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Any suggestions for an open source model for parsing real estate listings?
You should look at guidance for an LLM to fill out a template. Define the output data structure and provide the real estate listing in the context (see the JSON template example here https://github.com/microsoft/guidance)
What are some alternatives?
AgentOoba - An autonomous AI agent extension for Oobabooga's web ui
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
lmql - A language for constraint-guided and efficient LLM programming.
AgentGPT - 🤖 Assemble, configure, and deploy autonomous AI Agents in your browser.
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
babyagi
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
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.
llama-cpp-python - Python bindings for llama.cpp
gpt-llama.cpp - A llama.cpp drop-in replacement for OpenAI's GPT endpoints, allowing GPT-powered apps to run off local llama.cpp models instead of OpenAI.
langchainrb - Build LLM-powered applications in Ruby