Skip to main content

Algorithm of thoughts - Pytorch

Project description

Multi-Modality

Algorithm-Of-Thoughts

AOT BANNER The open source implementation of "Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models"

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Installation

pip install aot-x

Usage

from aot import AoT

system_prompt = """

Use numbers and basic arithmetic operations (+ - * /) to obtain 24. When
considering the next steps, do not choose operations that will result in a
negative or fractional number. In order to help with the calculations, the
numbers in the parenthesis represent the numbers that are left after the
operations and they are in descending order.
Another thing we do is when there are only two numbers left in the parenthesis, we
check whether we can arrive at 24 only by using basic arithmetic operations
(+ - * /). Some examples regarding this idea:
(21 2) no
since 21 + 2 = 23, 21 - 2 = 19, 21 * 2 = 42, 21 / 2 = 10.5, none of which is equal
to 24.
(30 6) 30 - 6 = 24 yes
(8 3) 8 * 3 = 24 yes
(12 8) no
(48 2) 48 / 2 = 24 yes
Most importantly, do not give up, all the numbers that will be given has indeed a
solution.

14 8 8 2
"""


task = "5 10 5 2 "


aot = AoT(task=task, system_prompt=system_prompt)
aot.run()

Todo

  • All thoughts over 0.5 are added to cache or longterm vectorstore
  • DFS search similiar to tree of thoughts
  • Propose solutions function
  • Backtrack to nearest successful states
  • Implement evaluation strategy similiar to tot with [0.0, 1.0]
  • Working demo: Conducts search then backtracks through states, provide visuals green text
  • Streamlit demo

Citation

@misc{2308.10379,
Author = {Bilgehan Sel and Ahmad Al-Tawaha and Vanshaj Khattar and Lu Wang and Ruoxi Jia and Ming Jin},
Title = {Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models},
Year = {2023},

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aot_x-1.5.3.tar.gz (6.6 kB view details)

Uploaded Source

Built Distribution

aot_x-1.5.3-py3-none-any.whl (6.7 kB view details)

Uploaded Python 3

File details

Details for the file aot_x-1.5.3.tar.gz.

File metadata

  • Download URL: aot_x-1.5.3.tar.gz
  • Upload date:
  • Size: 6.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.11.0 Darwin/22.4.0

File hashes

Hashes for aot_x-1.5.3.tar.gz
Algorithm Hash digest
SHA256 831607d89ce72e8508e0d917e51d637e6328c04d87de91b1c0cfbbd96422800d
MD5 d102cef21dece362491ad2963d5b8682
BLAKE2b-256 d320afa69917c14ef442470def68d47cef7206744b5fb5277ed182ad8df06dbb

See more details on using hashes here.

File details

Details for the file aot_x-1.5.3-py3-none-any.whl.

File metadata

  • Download URL: aot_x-1.5.3-py3-none-any.whl
  • Upload date:
  • Size: 6.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.11.0 Darwin/22.4.0

File hashes

Hashes for aot_x-1.5.3-py3-none-any.whl
Algorithm Hash digest
SHA256 9b91f9ab68ff9381f320af32ed1b73ab912a8e015d2d5b4e63d85d29e3f6b07c
MD5 4882e20c8d2a4585cc894ba30c91af38
BLAKE2b-256 86840d999ef9f086da884ea725a36d2b4d92cec37019fe03bdb4da877776b2d5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page