graph-of-thoughts
graph-of-thoughts | llmtaskgraph | |
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2 | 1 | |
1,925 | 20 | |
4.2% | - | |
6.0 | 7.5 | |
11 days ago | 12 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | - |
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graph-of-thoughts
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Q* Could Be It - Forget AlphaGO - It's Diplomacy - Peg 1 May Have Fallen - Noam Brown May Have Achieved The Improbable - Is this Q* Leak 2.0?
We introduce Graph of Thoughts (GoT): a framework that advances prompting capabilities in large language models (LLMs) beyond those offered by paradigms such as Chain-ofThought or Tree of Thoughts (ToT). The key idea and primary advantage of GoT is the ability to model the information generated by an LLM as an arbitrary graph, where units of information (“LLM thoughts”) are vertices, and edges correspond to dependencies between these vertices. This approach enables combining arbitrary LLM thoughts into synergistic outcomes, distilling the essence of whole networks of thoughts, or enhancing thoughts using feedback loops. We illustrate that GoT offers advantages over state of the art on different tasks, for example increasing the quality of sorting by 62% over ToT, while simultaneously reducing costs by >31%. We ensure that GoT is extensible with new thought transformations and thus can be used to spearhead new prompting schemes. This work brings the LLM reasoning closer to human thinking or brain mechanisms such as recurrence, both of which form complex networks. Website & code: https://github.com/spcl/graph-of-thoughts
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Graph of Thoughts: Solving Elaborate Problems with Large Language Models
https://github.com/spcl/graph-of-thoughts Code for the paper too
llmtaskgraph
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Graph of Thoughts: Solving Elaborate Problems with Large Language Models
This is a really natural extension of CoT. I was experimenting for a month or two with a similar concept in a hobby project this past spring: https://github.com/knexer/llmtaskgraph . I'm really excited to see more people exploring in this direction!
I was focusing more on an engineering perspective; modeling a complex LLM-and-code process as a dependency graph makes it easy to:
What are some alternatives?
trex - Enforce structured output from LLMs 100% of the time
prompttools - Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
llm-guard - The Security Toolkit for LLM Interactions
prompt-lib - A set of utilities for running few-shot prompting experiments on large-language models
ToolEmu - A language model (LM)-based emulation framework for identifying the risks of LM agents with tool use
ChainFury - 🦋 Production grade chaining engine behind TuneChat. Self host today!
promptmap - automatically tests prompt injection attacks on ChatGPT instances