aws-samples/generative-ai-on-amazon-sagemaker

Amazon SageMaker AI collection of examples, code samples and recipes.

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Established

This project helps machine learning engineers and data scientists build and deploy custom generative AI applications. It provides practical examples for tasks like fine-tuning large language models (LLMs) with your specific data, building systems that retrieve information and generate responses (RAG), and creating AI agents that can perform multi-step tasks. Users get step-by-step guidance, code samples, and best practices for developing sophisticated AI solutions.

Use this if you are an ML engineer or data scientist looking for practical guidance and code examples to develop, customize, and deploy generative AI models and applications using Amazon SageMaker and Bedrock.

Not ideal if you are looking for a pre-built, off-the-shelf generative AI application that requires no coding or machine learning expertise.

generative-ai-development large-language-models rag-system-design ai-agent-building model-customization
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 23 / 25

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88

Forks

82

Language

Jupyter Notebook

License

MIT-0

Last pushed

Mar 10, 2026

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