awslabs/agentcore-samples
Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.
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This is a workshop designed for Amazon Bedrock a foundational model service.
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Latest capture 2026-06-19 22:39
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Scanned 2026-06-19 22:39
pyproject.toml
python ecosystem,
28 dependencies
uv.lock
python ecosystem,
0 dependencies
04_Agents/requirements.txt
python ecosystem,
4 dependencies
tutor/requirements.txt
python ecosystem,
11 dependencies
03_Model_customization/model_distillation/dataset-validation/requirements.txt
python ecosystem,
3 dependencies
03_Model_customization/model_distillation/distillation_recipes/01_citations/Pipfile
python ecosystem,
6 dependencies
03_Model_customization/model_distillation/distillation_recipes/01_citations/Pipfile.lock
python ecosystem,
125 dependencies
03_Model_customization/bedrock-fine-tuning/nova/understanding/nova_tooluse_customization/tooluse_finetuner_main/requirements.txt
python ecosystem,
11 dependencies
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Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.
OpenAI-Compatible RESTful APIs for Amazon Bedrock
A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS
Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry 🚀
Build your own coding agent workshop - Feb 19th 2026
This sample has the full End2End process of creating RAG application with Prompty and Azure AI Foundry. It includes GPT-4 LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.