Agentic AI Foundations Series · Part 5 of 6
Part 5: Building Agents on OCI – Tools, Knowledge Bases, and Endpoints
OCI gives you a managed agent service: you describe the agent, attach tools and data, and publish it through an endpoint. No servers to patch. (Oracle renames services often, so match the names to what you see in the course videos.)
The help-desk analogy
Picture building an "Ask the DBA team" assistant for your company.
- The agent is the assistant, with instructions like "Answer database questions politely; never share passwords."
- Its tools are what it can do.
- Its knowledge base is the library of runbooks and SOPs it reads from.
- The endpoint is the front door your users' apps knock on.
The tools (know which one fits which question)
| Need | Tool to choose |
|---|---|
| Answer from PDFs, runbooks, SOPs, with citations | RAG tool + knowledge base |
| Answer "How many open SRs this week?" from tables | SQL tool (natural language to SQL; give it a schema description) |
| Create a ticket, call a REST API, run your function | Custom / function-calling tool |
| Use another service or agent | API endpoint / agent tool |
Exam hook: Documents → RAG. Tables → SQL. Actions → custom function.
Knowledge bases: where the agent reads
A knowledge base points to a data store:
- Object Storage – drop files in a bucket; OCI chunks, embeds, and indexes them for you (service-managed).
- OCI Search with OpenSearch – bring an existing search index.
- Oracle AI Database vector store – bring your own vectors, with your own database security.
Files get in through a data source and an ingestion job. If you add new runbooks, rerun ingestion.
The endpoint: front door settings
- Sessions – keep conversation context across turns (with an idle timeout).
- Guardrails – content moderation, prompt-injection protection, PII protection.
- Citations and trace – show sources and the agent's steps.
The OCI pieces around it
- OCI Generative AI – the hosted chat and embedding models the agent uses; dedicated AI clusters for fine-tuning or private hosting.
- IAM policies and compartments – who can create agents and read the data. Same idea as granting privileges.
- Object Storage – usually where source documents live.
Remember for the exam
- RAG tool for documents, SQL tool for tables, custom tool for APIs.
- Knowledge base stores: Object Storage, OpenSearch, Oracle AI Database.
- Turn on sessions to remember context; guardrails live on the endpoint.
Self-check
- Users ask questions about HR policy PDFs. Which tool? (RAG tool with a knowledge base)
- How does the agent keep context between messages? (Sessions on the endpoint)
- Name one guardrail available on the endpoint. (Content moderation, prompt-injection, or PII protection)
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