Dive into this repository and unlock the power of integrating Amazon Bedrock's cutting-edge large language models (LLMs) with the scalable NoSQL capabilities of AWS DynamoDB. These comprehensive examples will guide you through building context-aware chatbots and sophisticated AI applications that can maintain seamless conversations across sessions.
These examples are designed to help developers, data scientists, and AI enthusiasts quickly get started with building sophisticated, cloud-native AI applications. By leveraging the power of Bedrock and DynamoDB, you can create scalable, context-aware solutions that push the boundaries of what's possible.
- 🔗 Bedrock Integration: Seamlessly connect to Amazon Bedrock and harness the latest LLM technologies from industry-leading providers like Anthropic, AI21 Labs and more.
- 💾 DynamoDB for Context Management: Leverage DynamoDB's NoSQL database to store and retrieve chat history, enabling your AI models to maintain context and deliver more coherent, relevant responses over time.
- 🚀 Scalable and Serverless Architecture: Build applications that are both scalable and cost-effective, with DynamoDB handling large-scale data storage and Bedrock providing robust AI capabilities without the need to manage underlying infrastructure.
- 🛠️ Real-world Examples: Explore practical examples that cover setting up the environment, creating DynamoDB tables, integrating with Bedrock, and building a fully functional web-based chatbot using Streamlit.
Ready to dive in? Check out the LangChain integration with Bedrock and DynamoDB message history to kickstart your AI journey on AWS.
Let's build the future together! 🚀