Semantic search langchain example embeddings import SentenceTransformerEmbeddings LangChain Docs) Semantic search Q&A using LangChain and It is up to each specific implementation as to how those examples are selected. This is generally referred to as "Hybrid" search. # The VectorStore class that is used to store the embeddings and do a similarity search over. LangChain has a few different types of example selectors. When the app is loaded, it performs background checks to determine if the Pinecone vector database needs to be created and populated. Conclusion. In the modern information-centric landscape Jan 14, 2024 · Semantic search is a powerful technique that can enhance the quality and relevance of text search results by understanding the meaning and intent of the queries and the documents. "); The model can rewrite user queries, which may be multifaceted or include irrelevant language, into more effective search queries. MaxMarginalRelevanceExampleSelector Jul 12, 2023 · Articles; Practical Examples; Practical Examples. It performs a similarity search in the vectorStore using the input variables and returns the examples with the highest similarity.
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