Retrieval augmented generation. > Retrieval Augmented Generation (RAG) is a technique where the capabilities of a large language model (LLM) are augmented by retrieving information from other systems and inserting them into the LLM’s context window via a prompt. (stolen from: https://github.com/psychic-api/rag-stack). - Source: Hacker News / 4 months ago

I spent hours trying to make it work on Ubuntu, solving one error message after another. But I can't make it... Anyone managed ? Https://github.com/psychic-api/rag-stack. Source: 8 months ago

- (Optional) Open-source LLM such as Falcon, Llama, or GPT4All to your virtual private cloud (VPC). We used Langchain to interface with open source LLMs and Ragstack to deploy to Google Cloud: https://github.com/psychic-api/rag-stack. - Source: Hacker News / 11 months ago

Aside from the built-in prompts powered by awesome-chatgpt-prompts (Are you an ETH dev, a financial analyst, or a personal trainer today?), you can also create, share and debug your chat tools with prompt templates. - Source: dev.to / 5 months ago

I've found the following resources helpful: - 15 Rules For Crafting Effective GPT Chat Prompts (https://expandi.io/blog/chat-gpt-rules/) - Awesome ChatGPT Prompts (https://github.com/f/awesome-chatgpt-prompts) For more resources of like nature, you can search for "mega prompt". - Source: Hacker News / 7 months ago

Someone assembled an adhoc page in Github that is amassing quite a large library of prompt ideas [Github]. Source: 7 months ago

I like to use PromptLayer for this. But you could easily set up a simple CRUD web app to track prompts/average completion token # length, different variations. There is also awesome-chatgpt-prompts (https://github.com/f/awesome-chatgpt-prompts) which has some interesting ones. What are you looking for? - Source: Hacker News / 10 months ago

* Built-In Prompts: Channel creativity using integrated prompts sourced from github.com/f/awesome-chatgpt-prompts. Source: 11 months ago