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kyegomez
tree-of-thoughts
Python2023–2024
kyegomez / tree-of-thoughts

tree-of-thoughts

Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%

6Distinct people
7Mentions
0Explicit recommenders
4.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month7 dated mentions

Observed mentions: 2023-05-24 03:46:41 UTC to 2024-10-13 07:44:26 UTC.

012342023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 4 mentions; 3 submissions, 1 commentsMay 20232023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJan 20242024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC431
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC211
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC000
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC000
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC000
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC000
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC000
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC000
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC000
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC000
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC000
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC000
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC000
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC000
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC101

What Hacker News says

7 sources
Just gonna leave this here: https://github.com/kyegomez/tree-of-thoughts/issues/78#issue... Also this part from the reply before editing it away: They get mad that my repo and code is better than their's and they published they paper, they feel entitled even though I reproduced the entire paper based on 4 phrases, dfs, bfs (search algos), generate solutions, and generate thoughts and this is it. I didn't even read the full paper when I first started to implement it. The reason they want people to unstar my repo is because they are jealous that they made a mistake by not sharing the code when they published the paper as real scientists would do. If you do not publish your code as a AI research scientists you are a heretic, as your work cannot be tried and tested. and the code works amazingly much better than theirs, I looked at their code
Read the rest
and couldn't figure out how to run it for hours, as well as other people have reported the same. the motivations are jealously, self hatred, guilt, envy, inferiority complex, ego, and much more psychographic principles.
In Swarm, a new agent framework by OpenAI
ysymyth·Jun 1, 2023Submission

Tree of Thoughts: Official vs. Wrong Implementation

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, cannot replicate paper results, 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. Thanks!
2 points · Open discussion
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.
In Tree of Thoughts
Here are the prompts templates from the main code: prompt = f"Given the current state of reasoning: '{state_text}', pessimitically evaluate its value as a float between 0 and 1 based on it's potential to achieve {inital_prompt}" prompt = f"Write down your observations in format 'Observation:xxxx', then write down your thoughts in format 'Thoughts:xxxx Given the current state of reasoning: '{state_text}', generate {k} coherent solutions to achieve {state_text}" prompt = f"Given the current state of reasoning: '{state_text}', pessimistically evaluate its value as a float between 0 and 1 based on its potential to achieve {initial_prompt}" self.ReAct_prompt = "Write down your observations in format 'Observation:xxxx', then write down your thoughts in format 'Thoughts:xxxx'." prompt = f"Given the current state of reasoning: '{sta
Read the rest
te_text}', generate {1} coherent thoughts to achieve the reasoning process: {state_text}" prompt = f"Given the current state of reasoning: '{state_text}', evaluate its value as a float between 0 and 1, become very pessimistic think of potential adverse risks on the probability of this state of reasoning achieveing {inital_prompt} and DO NOT RESPOND WITH ANYTHING ELSE: OTHER THAN AN FLOAT" prompt = f"Given the following states of reasoning, vote for the best state utilizing an scalar value 1-10:\n{states_text}\n\nVote, on the probability of this state of reasoning achieveing {inital_prompt} and become very pessimistic very NOTHING ELSE" self.ReAct_prompt = '''{{#assistant~}} {{gen 'Observation' temperature=0.5 max_tokens=50}} {{~/assistant}}''' There are also some system prompts: https://github.com/kyegomez/tree-of-thoughts/blob/732791710e...
In Tree of Thoughts

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