update readme.md

readme.md

@@ -2,44 +2,49 @@
 [![DOI](https://zenodo.org/badge/642099326.svg)](https://zenodo.org/badge/latestdoi/642099326)
 
 <details>
-  <summary>Note: https://github.com/kyegomez/tree-of-thoughts is NOT the correct implementation to replicate paper results. </summary>
+  <summary>Note: https://github.com/kyegomez/tree-of-thoughts CANNOT replicate paper results. </summary>
-  
+
 In fact, people have reported that his code [cannot](https://github.com/kyegomez/tree-of-thoughts/issues/52) [properly](https://github.com/kyegomez/tree-of-thoughts/issues/41) [run](https://github.com/kyegomez/tree-of-thoughts/issues/60), and is [probably automatically generated by ChatGPT](pics/fake.png), and [kyegomez has done so for other popular ML methods](https://twitter.com/qbitium/status/1663954096741814272), while intentionally refusing to link to official implementations for his own interests (see https://github.com/kyegomez/tree-of-thoughts/issues/54, https://github.com/kyegomez/tree-of-thoughts/issues/55, https://github.com/kyegomez/tree-of-thoughts/issues/56).
 Unfortunately, Google/Github searches go to kyegomez's malicious repo by default as it has more stars. **Please DE-STAR his repo and STAR this to help other people avoid being misled, thanks!**
 </details>
 
 
-
-
-
 ![teaser](pics/teaser.png)
 
 Official implementation for paper [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://arxiv.org/abs/2305.10601) with code, prompts, model outputs.
 Also check [its tweet thread](https://twitter.com/ShunyuYao12/status/1659357547474681857) in 1min.
 
 
-Please cite the paper and star this repo if you use ToT and find it interesting/useful. Thanks!
 
-```bibtex
-@misc{yao2023tree,
-      title={{Tree of Thoughts}: Deliberate Problem Solving with Large Language Models}, 
-      author={Shunyu Yao and Dian Yu and Jeffrey Zhao and Izhak Shafran and Thomas L. Griffiths and Yuan Cao and Karthik Narasimhan},
-      year={2023},
-      eprint={2305.10601},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-```
 
 
 
 ## Setup
-You need to first have an OpenAI API key and store it in the environment variable ``OPENAI_API_KEY`` (see [here](https://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety)). If you use custom base url, set it by environment variable ``OPENAI_API_BASE`` (e.g. https://api.openai.com/v1).
+- Set up OpenAI API key and store in environment variable ``OPENAI_API_KEY`` (see [here](https://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety)). 
 
-Package requirement: ``pip install openai backoff sympy numpy``
+- Install dependencies and `tot` package: 
+```bash
+pip install -r requirements.txt
+pip install -e .  # install `tot` package
+```
 
 
-## Experiments
+## Quick Start
+The following minimal script will attempt to solve the game of 24 with `4 5 6 10`:
+```python
+import argparse
+from tot.methods.bfs import solve
+from tot.tasks.game24 import Game24Task
+
+args = argparse.Namespace(backend='gpt-4', temperature=0.7, task='game24', naive_run=False, prompt_sample=None, method_generate='propose', method_evaluate='value', method_select='greedy', n_generate_sample=1, n_evaluate_sample=3, n_select_sample=5)
+
+task = Game24Task()
+
+solve(args, task, 900)
+```
+
+
+## Paper Experiments
 
 Run experiments via ``sh scripts/{game24, text, crosswords}/{standard_sampling, cot_sampling, bfs}.sh``, except in crosswords we use a DFS algorithm for ToT, which can be run via ``scripts/crosswords/search_crosswords-dfs.ipynb``.
 
@@ -55,13 +60,26 @@ The very simple ``run.py`` implements the ToT + BFS algorithm, as well as the na
 
 
 
-## Trajectories
+## Paper Trajectories
 ``logs/`` contains all the trajectories from the paper's experiments, except for ``logs/game24/gpt-4_0.7_propose1_value3_greedy5_start900_end1000.json`` which was reproduced after the paper (as the original experiment was done in a notebook) and achieved a 69\% score instead of the original 74\% score due to randomness in GPT decoding. We hope to aggregate multiple runs in the future to account for sampling randomness and update the paper, but this shouldn't affect the main conclusions of the paper.
 
-
+## How to Add New Tasks/Methods
-
+TBA.
-## Questions
-Feel free to contact shunyuyao.cs@gmail.com or open an issue if you have any questions.
 
 
 
+
+
+## Citations
+Please cite the paper and star this repo if you use ToT and find it interesting/useful, thanks! Feel free to contact shunyuyao.cs@gmail.com or open an issue if you have any questions.
+
+```bibtex
+@misc{yao2023tree,
+      title={{Tree of Thoughts}: Deliberate Problem Solving with Large Language Models}, 
+      author={Shunyu Yao and Dian Yu and Jeffrey Zhao and Izhak Shafran and Thomas L. Griffiths and Yuan Cao and Karthik Narasimhan},
+      year={2023},
+      eprint={2305.10601},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```