Prompting Python Packages

swarms

The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework. Website: https://swarms.ai

prompt-poet

Streamlines and simplifies prompt design for both developers and non-technical users with a low code approach.

dotpromptz-handlebars

Executable GenAI prompt templates

dedent

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dotprompt-handlebars

Executable GenAI prompt templates

smashed

SMASHED is a toolkit designed to apply transformations to samples in datasets, such as fields extraction, tokenization, prompting, batching, and more. Supports datasets from Huggingface, torchdata iterables, or simple lists of dictionaries.

agentlab

AgentLab: An open-source framework for developing, testing, and benchmarking web agents on diverse tasks, designed for scalability and reproducibility.

codemapper

Perfect for AI Prompts. CodeMapper is a python script that creates a comprehensive Markdown document representing the structure and contents of any given code base

thumb

A simple prompt testing library for LLMs.

tree-of-thoughts-llm

[NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models

sokrates

A Collection of handy llm interaction scripts including Prompt refinement, idea generation and a command line llm client

easyinstruct

An Easy-to-use Instruction Processing Framework for Large Language Models.

coolprompt

Framework for automative prompting creation and optimization

vibeprompt

🦩VibePrompt. A lightweight Python package for adapting prompts by tone, style, and audience. Built on top of LangChain, VibePrompt supports multiple LLM providers and enables structured, customizable prompt transformations for developers, writers, and researchers.

graph-of-thoughts

Official Implementation of "Graph of Thoughts: Solving Elaborate Problems with Large Language Models"

promptify

Use GPT or other prompt based models to get structured output

genetic-prompt-lab

GeneticPromptLab uses genetic algorithms for automated prompt engineering (for LLMs), enhancing quality and diversity through iterative selection, crossover, and mutation, while efficiently exploring minimal yet diverse samples from the training set.

eaot

The open source implementation of "Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers"

treeprompt

Tree prompting