✒️Query Analysis In OpenAI's retrieval talk on DevDay, they mention a bunch of strategies they experimented with 3 of these can be classified as **query analysis** a RAG technique that is becoming popular to do with LLMs 📄We've added a docs deep-dive on this We cover six different techniques for query analysis including HyDE, Step Back Prompting, Structured Queries and more 🧪 We also have six in-depth how-to guides covering adding examples, dealing with multiple retrievers, and constructing filters 🪙 Check the docs out! We'll be pushing hard on this over the next week or so Docs: python.langchain.com/docs/use_cases…
@LangChainAI This git project is RAG based using LangChain, including some query analysis trick:routing, query rewriting (or HyDE?) , attributes extract . github.com/metaswang/bao enjoy!
@LangChainAI @LangChainAI - any link to the code or benchmark dataset on which this analysis (the chart in the image) has been done?
@LangChainAI Try out langchain for free using @huggingface and @HelloPaperspace #GenAI #LLMs bit.ly/4bXmjzE
@LangChainAI Awesome stuff; I know companies are struggling to get RAG right - let's hope this pushes the market at least a bit in the right direction!
@LangChainAI tx this are great always 1 thing most people are not focusing on first is the content 100 techniques to extract it but extract what in what form what should that be data science starts w data