This tutorial introduces promptrefiner, a tool created by Amirarsalan Rajabi that uses the GPT-4 model to create perfect system prompts for local LLMs.
Tips on improving your GitHub repository organization and structure. Bullet Points:
- Create meaningful branch names - Use descriptive commit messages - Keep a clean project history
- Separate your code into well-organized directories - Follow a consistent naming convention - Make use of pull requests
- Collaborate effectively by writing clear documentation - Maintain good communication within your team Keywords: GitHub, repository best practices, organization, structure, branch names, commit messages, project history, directories, naming conventions, pull requests, collaboration, documentation, effective communication
- Create meaningful branch names - Use descriptive commit messages - Keep a clean project history
- Separate your code into well-organized directories - Follow a consistent naming convention - Make use of pull requests
- Collaborate effectively by writing clear documentation - Maintain good communication within your team Keywords: GitHub, repository best practices, organization, structure, branch names, commit messages, project history, directories, naming conventions, pull requests, collaboration, documentation, effective communication
Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).
