Promptify
by Community
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
OSS
Promptify
Added 1 June 2026
Overview
Promptify is an open-source Python library for prompt engineering and versioning. It provides tools to generate structured outputs from GPT and other prompt-based models. The project is maintained by a community on Discord focused on prompt engineering and LLM research.
Best for
Best for
Python developers seeking a straightforward way to produce structured outputs from LLM prompts while managing prompt versions.
Use cases
- Generate structured data (JSON, lists, etc.) from LLM prompts
- Version and manage prompts for iterative experimentation
- Build Python scripts that call GPT or similar models with reusable prompt templates
Notes
Promptify is an open-source Python library for prompt engineering and versioning. It provides tools to generate structured outputs from GPT and other prompt-based models. The project is maintained by a community on Discord focused on prompt engineering and LLM research.
4,612 stars on GitHub. Last updated 2026-03-27. Licensed Apache-2.0.
Use cases
- Generate structured data (JSON, lists, etc.) from LLM prompts
- Version and manage prompts for iterative experimentation
- Build Python scripts that call GPT or similar models with reusable prompt templates
Pros
- Lightweight and focused on structured output extraction
- Open source with active community support on Discord
- Simple API for integrating LLM calls into Python projects
Cons
- Relies on external LLM providers, requiring API keys and incurring usage costs
- Limited to Python ecosystem, not a cross-language framework
- Smaller feature set compared to broader orchestration libraries like LangChain
Indexed from awesome-llm and enriched against its public facts.
Pros
- Lightweight and focused on structured output extraction
- Open source with active community support on Discord
- Simple API for integrating LLM calls into Python projects
Cons
- Relies on external LLM providers, requiring API keys and incurring usage costs
- Limited to Python ecosystem, not a cross-language framework
- Smaller feature set compared to broader orchestration libraries like LangChain
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Guidance
Community
A guidance language for controlling large language models.
Outlines
Community
Structured Outputs
promptfoo
Community
Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and more. Simple declarative config
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
LangChain
Community
The agent engineering platform.
OpenAI Cookbook
Various
Examples and guides for using the OpenAI API
Prompt Engineering Guide
Various
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.
