GitHub - explodinggradients/ragas: Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines
Retrieval Augmented Generation (RAG) is one of the most popular techniques to leverage large language models for almost any type of use case.
In a RAG workflow, the user asks a question, like “What is Weaviate?”, and that query is sent into a vector database to search for related documents or chunks to the sentence. The... See more
Victoria Slocumx.com- Query the RAG anyway and let the LLM itself chose whether to use the the RAG context or its built in knowledge
- Query the RAG but only provide the result to the LLM if it meets some level of relevancy (ie embedding distance) to the question
- Run the LLM both on it's own and with the RAG response, use a heuristic (or another LLM) to pick the best answer
r/LocalLLaMA - Reddit
GitHub - infiniflow/ragflow: RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
infiniflowgithub.com