prompt-poet and ppromptor

These are complements: Prompt-Promptor generates prompts programmatically via LLMs while Prompt-Poet provides a framework to refine and optimize those generated prompts for production use.

prompt-poet
72
Verified
ppromptor
48
Emerging
Maintenance 10/25
Adoption 19/25
Maturity 25/25
Community 18/25
Maintenance 0/25
Adoption 9/25
Maturity 25/25
Community 14/25
Stars: 1,139
Forks: 94
Downloads: 11,757
Commits (30d): 0
Language: Python
License: MIT
Stars: 77
Forks: 11
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
No risk flags
Stale 6m

About prompt-poet

character-ai/prompt-poet

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

Combines YAML-based prompt structure with Jinja2 templating to support conditional logic, dynamic message lists, and LangChain integration—enabling features like context-aware few-shot examples and automatic message truncation by priority. Built-in tokenization provides granular token accounting across nested prompt sections, helping optimize context length constraints. Handles complex, compositional prompts through template includes and variable interpolation while maintaining clean separation between prompt logic and data.

About ppromptor

pikho/ppromptor

Prompt-Promptor is a python library for automatically generating prompts using LLMs

Employs a three-agent architecture (Proposer, Evaluator, Analyzer) that iteratively refines prompts through collaborative feedback loops and human expert input. Supports both proprietary APIs (OpenAI) and open-source models (LLaMA, WizardLM), enabling weaker models to be guided by stronger LLMs. Provides a Streamlit-based web interface with experiment tracking and side-by-side prompt comparison for managing the prompt engineering workflow.

Scores updated daily from GitHub, PyPI, and npm data. How scores work