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Chapter 7 shifts its focus from individual features to the broader perspective of how enterprise AI components—such as retrieval-augmented generation, vector databases, fine-tuning pipelines, agent frameworks, and model registries—collaborate on Red Hat platforms. Rather than advocating a single "correct" approach, it introduces various use case patterns, ranging from using different teacher model models to RAG implementation, and shares best practices, including integrating third-party libraries within virtual environments, pinning OSTree images for reproducibility, configuring OpenAI-compatible APIs, and automating processes via Ansible. The chapter also provides deployment snippets to help practitioners develop portable, auditable, and adaptable solutions.

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Use Cases and Best Practices

  • 章节

  • 发表日期：

    2026年

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  • Luca Berton

摘要

Chapter 7 shifts its focus from individual features to the broader perspective of how enterprise AI components—such as retrieval-augmented generation, vector databases, fine-tuning pipelines, agent frameworks, and model registries—collaborate on Red Hat platforms. Rather than advocating a single "correct" approach, it introduces various use case patterns, ranging from using different teacher model models to RAG implementation, and shares best practices, including integrating third-party libraries within virtual environments, pinning OSTree images for reproducibility, configuring OpenAI-compatible APIs, and automating processes via Ansible. The chapter also provides deployment snippets to help practitioners develop portable, auditable, and adaptable solutions.