#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
LinkWarden
Self-hosted, open-source #bookmark + archive manager to collect, and save websites for offline use.
The objective is to have a self-hosted place to keep useful links in one place, and since useful links can go away (see the inevitability of Link Rot), LinkWarden also saves a copy of the link as screenshot and PDF.
https://github.com/Daniel31x13/link-warden
📖 Inside the First Art Gallery for Blind Artists and Audiences #bookmark#raindrop
https://www.thrillist.com/travel/nation/envision-arts-gallery-wichita-kansas