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πŸš€ Experimental AI demos showcasing Amazon Bedrock, open-source LLMs & creative possibilities. AI Agents, RAG systems, streaming agents & more!

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aws-samples/sample-ai-possibilities

Welcome to AI Possibilities Samples

A collection of experimental demos, prototypes, and code snippets showcasing the art of the possible with AI using AWS services and open-source tools.

🌐 Visit our website: https://aws-samples.github.io/sample-ai-possibilities/

⚠️ Note: These samples are proof-of-concepts and experiments intended for learning and demonstration purposes. They are not production-ready and should not be deployed as-is in production environments.

🎯 Purpose

This repository serves as a playground for exploring cutting-edge AI capabilities through practical examples. Each sample illustrates different AI possibilities using AWS services (like Amazon Bedrock, SageMaker) and popular open-source frameworks.

πŸ“ Repository Structure

The repository is organized into three main categories:

Demos (/demos)

Full-featured applications demonstrating complete AI solutions. These are comprehensive examples that showcase end-to-end implementations with frontend interfaces, backend services, and AI integrations.

Examples:

  • Voice-enabled health AI agents with real-time streaming
  • Interactive chatbots with knowledge base integration
  • Multi-modal AI applications

Experiments (/experiments)

Smaller proof-of-concepts and experimental features. These focus on testing specific AI capabilities or integrations without full application scaffolding.

Coming soon:

  • Novel AI model combinations
  • Experimental features and APIs
  • Quick prototypes of emerging AI patterns

Snippets (/snippets)

Code fragments and utility functions that can be reused across projects. These are building blocks for AI applications.

Coming soon:

  • Common AI patterns and utilities
  • Integration helpers
  • Prompt engineering templates

πŸš€ Getting Started

Each demo, experiment, and snippet includes its own README with specific setup instructions. Generally, you'll need:

  1. Prerequisites

    • AWS Account with appropriate service access
    • Python 3.9+ or Node.js 16+ (depending on the sample)
    • AWS CLI configured with credentials
  2. Clone the repository

    git clone https://github.com/aws-samples/sample-ai-possibilities.git
    cd sample-ai-possibilities
  3. Navigate to a specific sample

    # For a demo
    cd demos/recipe-genie-chatbot
    
    # Follow the README.md instructions in that directory

πŸ”„ Continuous Updates

This repository is actively maintained and frequently updated with new samples showcasing the latest AI capabilities. Check back regularly or watch the repository for updates on:

  • New AI service integrations
  • Emerging AI patterns and architectures
  • Updated samples using the latest model versions
  • Community-contributed examples

🀝 Contributing

We welcome contributions! Whether it's a new demo, an experimental feature, or a useful code snippet, please see our CONTRIBUTING guide for details on how to submit your AI possibilities samples.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

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πŸš€ Experimental AI demos showcasing Amazon Bedrock, open-source LLMs & creative possibilities. AI Agents, RAG systems, streaming agents & more!

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