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 Database’s most powerful features, like the following:

• Partitioning Support
• Real Application Clusters scalability
• Exadata smart scans
• Shard processing across geographically distributed databases
• Transactions
• Parallel SQL
• Disaster recovery
• Security
• Oracle Machine Learning
• Oracle Graph Database
• Oracle Spatial and Graph
• Oracle Blockchain
• JSON

Document Loaders

Please check the usage example.

from langchain_community.document_loaders.oracleai import OracleDocLoader

API Reference:

• OracleDocLoader

Text Splitter

Please check the usage example.

from langchain_community.document_loaders.oracleai import OracleTextSplitter

API Reference:

• OracleTextSplitter

Embeddings

Please check the usage example.

from langchain_community.embeddings.oracleai import OracleEmbeddings

API Reference:

• OracleEmbeddings

Summary

Please check the usage example.

from langchain_community.utilities.oracleai import OracleSummary

API Reference:

• OracleSummary

Vector Store

Please check the usage example.

from langchain_community.vectorstores.oraclevs import OracleVS

API Reference:

• OracleVS

End to End Demo

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