This repository provides a curated set of examples and notebooks for integrating Anthropic's Claude models with AWS services. It targets developers and researchers seeking to leverage advanced LLM capabilities within the AWS ecosystem, offering practical demonstrations and tools for prompt engineering, function calling, and building LLM-powered applications.

How It Works

The project serves as a practical guide, offering code examples and structured notebooks that illustrate common LLM use cases on AWS. It emphasizes hands-on implementation for features like tool use and prompt engineering, simplifying the integration of Anthropic models into cloud-based workflows. The examples cover various applications, from basic prompt engineering to more complex scenarios like PDF knowledge bases.

Quick Start & Requirements

This repository primarily contains example code and notebooks; specific installation instructions, dependencies, or setup requirements are not detailed in the provided README content. Users will likely need access to AWS services and Anthropic API keys.

Highlighted Details

• Includes notebooks, cookbooks, and workshops for guided learning.
• Demonstrates prompt engineering techniques for Claude models.
• Features examples of Tool Use (function calling) with complex tool schemas.
• Offers a Claude Streamlit LLM Playground supporting Claude 3.5.
• Provides a PDF Knowledge Base example with citations.

Maintenance & Community

No information regarding maintainers, community channels (e.g., Discord, Slack), roadmap, or project health signals is available in the provided README content.

Licensing & Compatibility

The license type and any compatibility notes for commercial or closed-source use are not specified in the provided README content.

Limitations & Caveats

The README content does not detail specific limitations, known bugs, alpha status, or unsupported platforms. Users should anticipate needing to configure AWS credentials and potentially Anthropic API access.