Low-Hanging Fruit for RAG Search - jxnl.co

For a collection of advanced Retrieval-Augmented Generation (RAG) techniques this is a very resourceful repo.
Many topics are covered like
- Metadata Filtering: Apply filters based on attributes like date, source, author, or document type.
- Similarity... See more
GitHub - infiniflow/ragflow: RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
infiniflowgithub.comI think the biggest mistake around improving the system is that most people are spending too much time on the actual synthesis without actually understanding whether or not the data is being retrieved correctly. To avoid this:
- Create synthetic questions for each text chunk in your database
- Use these questions to test your retrieval system
- Calculate
Systematically Improving Your RAG - jxnl.co
RAG (Retrieval-Augmented Generation) is the most common pattern for building chatbots that answer questions about specific documents.
The Problem: Models like ChatGPT don't know about your company's internal documents or events that happened after their 2023 training cut-off. Asking them will lead to hallucinations.
The Architecture:
Retrieve: When a