oracle-devrel/oracle-ai-developer-hub

Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services

What it solves

This repository provides a comprehensive set of technical resources, reference implementations, and guides to help developers build production-grade AI applications and agents. It specifically addresses the challenge of managing complex AI agent infrastructure—such as memory, vector search, and data integration—by demonstrating how to use Oracle AI Database and OCI services as a unified backend.

How it works

The project is organized into four primary areas:

  • Apps: Complete, working reference implementations (e.g., agentic RAG, financial AI agents, and supply chain assistants) that showcase end-to-end architectural patterns.
  • Notebooks: Interactive tutorials covering model experimentation, data preparation, and the integration of various cognitive architectures (like Chain of Thought and ReAct) with Oracle AI Database.
  • Guides: Technical presentations and documentation on agent reasoning strategies and "memory engineering" for enterprise agents.
  • Agent Memory: Specialized resources for the oracleagentmemory package, which uses Oracle AI Database as a converged engine for conversation history, durable facts, and entity state.

Who it’s for

AI developers and engineers who are building AI agents, RAG systems, and enterprise AI applications, particularly those leveraging Oracle's AI infrastructure and OCI services.

Highlights

  • Unified Memory Core: Demonstrates using a single database for vector, graph, spatial, and relational queries instead of multiple fragmented stores.
  • Agentic RAG: Implementations of intelligent RAG systems with multi-agent Chain of Thought (CoT) and hybrid search.
  • Crossover Integration: Examples of integrating with popular frameworks like LangChain, LangGraph, and the OpenAI Agents SDK.
  • Multicloud Support: Samples for running Oracle AI Database across AWS, Azure, and Google Cloud.

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