This guide offers five essential tips for writing effective GitHub Copilot custom instructions, covering project overview, tech stack, coding guidelines, structure, and resources, to help developers get better code suggestions.
GitHub Models is a suite of developer tools for AI development, offering features like prompt management, model comparison, and quantitative evaluations, integrated directly into GitHub workflows.
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).
