LangGPT and DecryptPrompt

One project provides a framework and methodology for structured prompt engineering, while the other compiles and summarizes research papers, open-source data, and models related to prompts and LLMs, making them **complements** where one offers a practical approach and the other provides foundational knowledge and resources.

LangGPT
55
Established
DecryptPrompt
51
Established
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 19/25
Maintenance 13/25
Adoption 10/25
Maturity 8/25
Community 20/25
Stars: 11,744
Forks: 913
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 3,366
Forks: 319
Downloads:
Commits (30d): 4
Language:
License:
No Package No Dependents
No License No Package No Dependents

About LangGPT

langgptai/LangGPT

LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词(Structured Prompt)提出者 📌 元提示词(Meta-Prompt)发起者 📌 最流行的提示词落地范式 | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树

LangGPT helps you create powerful instructions for AI chatbots (like ChatGPT) by providing a structured, template-based approach. You start with an idea for how the AI should behave or what it should produce, and LangGPT helps you define its role, goals, skills, and rules, resulting in a consistent and high-quality AI interaction. This is for anyone who uses large language models and wants to get better, more predictable results from them, such as content creators, researchers, or business users.

AI interaction prompt engineering content creation AI workflow optimization digital assistant

About DecryptPrompt

DSXiangLi/DecryptPrompt

总结Prompt&LLM论文,开源数据&模型,AIGC应用

This project offers a comprehensive guide and curated resources for understanding and implementing advanced techniques in large language models (LLMs). It provides deep dives into prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and agent design through a series of detailed articles. Practitioners in AI/ML, researchers, and engineers who are building or optimizing LLM-powered applications will find this resource invaluable for keeping up with the latest advancements.

Large Language Models Prompt Engineering AI Agents Retrieval-Augmented Generation Machine Learning Research

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