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OracleAI Vector Search

Oracle AI Vector Search is designed for Artificial Intelligence (AI) workloads that allows you to query data based on semantics, rather than keywords. One of the biggest benefits of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data in one single system. This is not only powerful but also significantly more effective because you don't need to add a specialized vector database, eliminating the pain of data fragmentation between multiple systems.

In addition, your vectors can benefit from all of Oracle Databaseโ€™s most powerful features, like the following:

Document Loadersโ€‹

Please check the usage example.

from langchain_community.document_loaders.oracleai import OracleDocLoader
API Reference:OracleDocLoader

Text Splitterโ€‹

Please check the usage example.

from langchain_community.document_loaders.oracleai import OracleTextSplitter
API Reference:OracleTextSplitter

Embeddingsโ€‹

Please check the usage example.

from langchain_community.embeddings.oracleai import OracleEmbeddings
API Reference:OracleEmbeddings

Summaryโ€‹

Please check the usage example.

from langchain_community.utilities.oracleai import OracleSummary
API Reference:OracleSummary

Vector Storeโ€‹

Please check the usage example.

from langchain_community.vectorstores.oraclevs import OracleVS
API Reference:OracleVS

End to End Demoโ€‹

Please check the Oracle AI Vector Search End-to-End Demo Guide.


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