graph-of-thoughts
Implementation of Graph of Thoughts for large language models problem-solving
GraphCanon updated 3w · GitHub synced 3w
Decision brief
The Graph of Thoughts tool is designed for leveraging large language models and graph structures to solve elaborate problems.
Good fit when
- Use when you need to solve complex problem scenarios that require the interplay between advanced language understanding and structured problem decomposition capabilities.
- Ideal if your project involves deep reasoning tasks where a hierarchical representation of thought processes can be beneficial.
Avoid when
- Avoid using Graph of Thoughts for simpler, straightforward queries or when real-time performance is critical because it may introduce overhead due to its complex graph processing.
- Do not use this tool where privacy and data security are paramount concerns if the official license does not sufficiently protect your needs.
- Pricing:
- freemium
- Requirements:
- Min 8 GB RAM
Observed Jul 17, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Slowing (125d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install graph-of-thoughtsSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository hosts the official implementation of the 'Graph of Thoughts' research focusing on devising solutions to complex problems utilizing large language models and graph structures.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 28, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 28, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 28, 2026)
```python from examples.sorting.sorting_032 import SortingPrompter, SortingParser, utilsSource link
Tags
README
Quick Start
The following code snippet shows how to use the framework to solve the sorting problem for a list of 32 numbers using a CoT-like approach.
Make sure you have followed the Setup Guide before running the code.
from examples.sorting.sorting_032 import SortingPrompter, SortingParser, utils
from graph_of_thoughts import controller, language_models, operations
For agents
This page has a .md twin and JSON over the API.