Expanded Self-Query Retriever and Self-Query Retriever with MyScale #2
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chtlp
reviewed
Jun 13, 2023
| "id": "83811610-7df3-4ede-b268-68a6a83ba9e2", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "In this tutorial we follow other example's setting and use `OpenAIEmbeddings`. Remember to get a OpenAI API Key for valid accesss to LLMs." |
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Expanded Self-Query Retriever 👀 and Self-querying with MyScale 🤩
LangChain built with a great interface for self-query retrievers and many super nice contribution has been made during the last few weeks. 🌟 Self-query retrievers are really cool and we believe it will be the future of vector databases! 😎 So we decided to expand self-query retriever with more functions and data types enabled and bring MyScale to the big family of self-query enabled vector databases! 🤗
MyScale can make use of various data types and functions for filters. It will boost up your LLM app no matter if you are scaling up your data or expand your system to broader application. 🚀🚀🚀 And we believe it will be a common feature to every vector database in the future!
In the notebook we'll demo the
SelfQueryRetrieverwrapped around a MyScale vector store with some extra piece we contributed to LangChain. In short, it can be concluded into 4 points:containcomparator 🪣 to match list of any if there is more than one element matchedtimestampdata type 🕰️ for date time match (ISO-format, or YYYY-MM-DD)likecomparator 🔎 for string pattern searchLet's boost LLM apps with vector databases! 🎉🎉🎉
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