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公式動画&関連する動画 [How to Create a Knowledge Base for AI Agents in Oracle AI Data Platform]
Oracle AI Data Platform Knowledge Bases prepare enterprise documents for semantic retrieval so AI agents can access relevant information during conversations. Configure embeddings, document ingestion, and indexing to support retrieval-augmented generation with your organization’s content. Explore additional details at the resources linked below.
In this tutorial, learn how to create and configure a Knowledge Base for AI agents in Oracle AI Data Platform. A Knowledge Base indexes enterprise documents for semantic retrieval, providing the foundation for AI agents to retrieve relevant information from organizational content during conversations.
The tutorial shows how to create a Knowledge Base and configure an embedding model, chunk size, and chunk overlap. It explains how chunk size determines the number of characters grouped for semantic search and how chunk overlap shares characters between consecutive chunks to help preserve context. The tutorial also covers selecting an optional compute cluster for ingestion and connecting a standard or external volume as a document data source.
Next, learn how to configure supported file types and begin document ingestion. During ingestion, Oracle AI Data Platform creates vector embeddings and indexes the content to prepare documents for semantic search. The tutorial demonstrates how to monitor ingestion from the job runs tab and determine when the Knowledge Base is ready for semantic retrieval. Once ingestion is complete, the Knowledge Base can be selected by a retrieval-augmented generation tool, allowing an AI agent to retrieve relevant enterprise information from the indexed documents during conversations.
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