tree-of-thoughts
guidance
tree-of-thoughts | guidance | |
---|---|---|
26 | 89 | |
4,042 | 12,248 | |
- | - | |
8.8 | 9.5 | |
2 months ago | 9 months ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tree-of-thoughts
-
[D] Potential scammer on github stealing work of other ML researchers?
I checked the issues and found https://github.com/kyegomez/tree-of-thoughts/issues/78
-
(2/2) May 2023
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70% (https://github.com/kyegomez/tree-of-thoughts)
-
Statement on AI Extinction - Signed by AGI Labs, Top Academics, and Many Other Notable Figures
same deal with amplification research like Tree of Thoughts, AdaPlanner, and Ghost in the Minecraft. same deal with agentized LLMs like Auto-GPT emphasizing testing regimens. they want efficiency and explainability, not this "mine is bigger than yours" nonsense coming out of Microsoft, Google, or Meta (which isn't even the entire picture of the opensource ML research within those firms either). There's this idealized "neurosymbolic AI" where everyone just wants code to do a job, so there should only be so much probabilistic behavior to learn the jobs that aren't learned to begin with, but the fact remains that the actual researchers and engineers want something that is as deterministic as imperative language can be. perhaps we'll achieve functional depth, and instead of some outdated "paperclip maximizer", we summon Maxwell's demon via a "complete" Church-Turing thesis. in other words, while a "vastly superior being in intelligence" is a really bad time for anyone that has an intellect-based superiority complex, the rest of us are humble enough to utilize this information science to further explore the unknown.
- Tree of Thought (ToT) and AutoGPT
-
Tree of Thoughts
This is Shunyu, author of Tree oF Thoughts (arxiv.org/abs/2305.10601).
The official code to replicate paper results is https://github.com/ysymyth/tree-of-thought-llm
Not https://github.com/kyegomez/tree-of-thoughts which according to many who told me, is not right/good implementation of ToT, and damages the reputation of ToT
I explained the situation here: https://twitter.com/ShunyuYao12/status/1663946702754021383
I'd appreciate your help by unstaring his and staring mine, as currently Github and Google searches go to his repo by default, and it has been very misleading for many users.
-
Has anybody tried their models with "Tree of Thoughts"?
I hacked a dirty PR into this derivative repo, to run it with oobabooga API: https://github.com/kyegomez/tree-of-thoughts/pull/8
- Tree of Thoughts: Deliberate Problem Solving with LLMs
guidance
-
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
-
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...
-
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!
-
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
-
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.
-
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
-
/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?
-
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?
Awesome-Prompt-Engineering - This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
tree-of-thought-llm - [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
lmql - A language for constraint-guided and efficient LLM programming.
GirlfriendGPT - Girlfriend GPT is a Python project to build your own AI girlfriend using ChatGPT4.0
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
prompt-engineering - Tips and tricks for working with Large Language Models like OpenAI's GPT-4.
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
Mr.-Ranedeer-AI-Tutor - A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.
llama-cpp-python - Python bindings for llama.cpp
Neurite - Fractal Graph Desktop for Ai-Agents, Web-Browsing, Note-Taking, and Code.
langchainrb - Build LLM-powered applications in Ruby