spcl/graph-of-thoughts

Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models"

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This framework helps AI/ML engineers and researchers design more effective large language model (LLM) workflows for complex tasks. It takes a problem definition and an LLM, then orchestrates the LLM's 'thought process' through a series of operations, like generating ideas or scoring options, to arrive at a solution. The output is a structured graph detailing the LLM's problem-solving steps.

2,614 stars. No commits in the last 6 months. Available on PyPI.

Use this if you need to build sophisticated LLM applications that solve elaborate problems requiring multiple steps of reasoning, rather than simple, direct prompts.

Not ideal if you are looking for a pre-built, end-user application or if your LLM tasks are straightforward and can be solved with single prompts.

LLM orchestration AI workflow design complex reasoning prompt engineering AI research
Stale 6m
Maintenance 0 / 25
Adoption 10 / 25
Maturity 25 / 25
Community 19 / 25

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2,614

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195

Language

Python

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Last pushed

Dec 11, 2024

Commits (30d)

0

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