# RAG ### What is RAG RAG is a smart way to make LLMs (e.g. ChatGPT) even better by pulling information from outside sources. This means they can give personalised responses based on the latest and most relevant information, from knowledge snippets to user-specific data. ### How RAG adds value to the Co-Creation Platform Users can easily add their own data to enhance the AI models. **Enhances responses - m**ake the AI's answers more relevant and personalised by using specific data sets. **Reward contributions - c**ombine blockchain to securely reward people who provide and check the data. This combination makes the data more trustworthy and promotes a community-led approach. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.flock.io/flock-products/ai-marketplace/deep-dive/rag.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.