This repository contains technical resources to help AI Developers build AI applications, agents, and systems using Oracle AI Database and OCI services alongside other key components of the AI/Agent stack.
This repository is organized into several key areas:
Applications and reference implementations demonstrating how to build AI-powered solutions with Oracle technologies. These complete, working examples showcase end-to-end implementations of AI applications, agents, and systems that leverage Oracle AI Database and OCI services. Each application includes source code, deployment configurations, and documentation to help developers understand architectural patterns, integration approaches, and best practices for building production-grade AI solutions.
| Name | Description | Link |
|---|---|---|
| oci-generative-ai-jet-ui | Full-stack AI application with Oracle JET UI, OCI Generative AI integration, Kubernetes deployment, and Terraform infrastructure |  |
Jupyter notebooks and interactive tutorials covering:
- AI/ML model development and experimentation
- Oracle Database AI features and capabilities
- OCI AI services integration patterns
- Data preparation and analysis workflows
- Agent development and orchestration examples
| Name | Description | Stack | Link |
|---|---|---|---|
| memory_context_engineering_agents | Build AI agents with 6 types of persistent memory. Covers memory engineering, context window management, and just-in-time retrieval patterns. | LangChain, Oracle AI Database, OpenAI, Tavily |  |
| oracle_rag_agents_zero_to_hero | Learn to build RAG agents from scratch using Oracle AI Database. | Oracle AI Database, OpenAI, OpenAI Agents SDK | |
| oracle_rag_with_evals | Build RAG systems with comprehensive evaluation metrics | Oracle AI Database, OpenAI, BEIR, Galileo | |
Hands-on workshops and guided learning experiences:
- Step-by-step tutorials for building AI applications
- End-to-end project walkthroughs
- Best practices and architectural patterns
- Integration guides for Oracle AI Database and OCI services
| Name | Description | Link |
|---|---|---|
| Coming soon | Workshops will be added here | - |
Comprehensive documentation and reference materials:
- Architecture patterns and design guides
- API documentation and integration examples
- Deployment and operations guides
- Troubleshooting and optimization tips
- Security and compliance best practices
| Name | Description | Link |
|---|---|---|
| Coming soon | Guides will be added here | - |
Notebooks and apps contributed by partners in the AI ecosystem. AI Developers can use these resources to understand how to use Oracle AI Database and OCI alongside tools such as LangChain, Galileo, LlamaIndex, and other popular AI/ML frameworks and platforms.
| Name | Description | Stack | Link |
|---|---|---|---|
| Coming soon | Partner-contributed resources will be added here | - | - |
- Explore Applications: Start with the applications in
/appsto see complete, working examples - Follow Workshops: Check
/workshopsfor guided learning paths - Experiment with Notebooks: Use
/notebooksfor hands-on experimentation - Reference Guides: Consult
/guidesfor detailed documentation - Check Partner Resources: Explore
/partnersfor integrations with popular AI tools and frameworks
This project is open source. Please submit your contributions by forking this repository and submitting a pull request! Oracle appreciates any contributions that are made by the open-source community.
Before contributing, please set up pre-commit hooks to ensure code is automatically formatted:
-
Install pre-commit:
pip install pre-commit
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Install additional dependencies (optional, includes pre-commit and ruff):
pip install -r requirements-dev.txt
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Install pre-commit hooks:
pre-commit install
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Optional: Format existing code:
pre-commit run --all-files
The pre-commit hooks will automatically format your code using:
- Ruff for Python files (formatting and linting)
- Prettier for JavaScript, TypeScript, JSON, YAML, and Markdown files
For more detailed information, see SETUP_PRE_COMMIT.md.
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Licensed under the Universal Permissive License (UPL), Version 1.0.
See LICENSE for more details.
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Note: This repository is actively maintained and updated with new resources, examples, and best practices for Oracle AI development.