princeton-nlp/tree-of-thought-llm

Health v2 · maintenance only

Adoption not part of the score

6057 stars · 624 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official implementation of the Tree of Thoughts (ToT) framework for deliberate LLM problem solving, generalizing chain-of-thought prompting with tree search over intermediate reasoning steps. It provides the `tot` Python package with BFS/DFS search methods, thought generation and evaluation strategies, and tasks like Game of 24, Creative Writing, and Mini Crosswords.

Use cases

• improve LLM reasoning on planning-heavy problems with tree search
• run tree-of-thoughts prompting instead of plain chain-of-thought
• solve the Game of 24 puzzle with GPT-4
• compare IO sampling, CoT sampling, and ToT search on benchmark tasks
• implement custom tasks with thought generation, evaluation, and selection
• reproduce NeurIPS 2023 Tree of Thoughts paper experiments

When to choose

• you need deliberate multi-step reasoning with lookahead and backtracking over chain-of-thought
• you want the reference implementation of the ToT paper with prompts and model outputs
• your task benefits from exploring multiple reasoning paths and self-evaluation

When to avoid

• you need cheap, low-latency inference since ToT makes many LLM calls per problem
• your task is simple enough that standard prompting or CoT suffices
• you need a production agent framework with tool use and memory rather than a research codebase

Facets

library · maturity stable

llm-inference prompt-engineering agent-framework search-engine large-language-models artificial-intelligence python cli tree-of-thoughts tree-search chain-of-thought reasoning bfs dfs research-code neurips-2023 natural-language-processing algorithms

Member repositories

For agents

markdown · JSON · MCP: product_card(name="princeton-nlp/tree-of-thought-llm")