Flexible and powerful framework for managing multiple AI agents and handling complex conversations
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Updated
Dec 24, 2024 - TypeScript
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
AWS AI Stack – A ready-to-use, full-stack boilerplate project for building serverless AI applications on AWS
A multimodal chat interface with many tools.
Automatic AI-powered test suite generator
Go module for fetching embeddings from embeddings providers
A demo application that uses Amazon SageMaker manuals and pricing data tables as an example to explore the capabilities of a generative AI chatbot.
Hosting Langfuse v2 on Amazon ECS with Fargate using CDK Python
This Guidance demonstrates how to create an intelligent manufacturing digital thread through a combination of knowledge graph and generative artificial intelligence (AI) technologies. A digital thread offers an integrated approach to combine disparate data sources across enterprise systems, increasing traceability, accessibility, collaboration.
This repository contains Node.js examples to get started with the Amazon Bedrock service.
Employee Productivity GenAI Assistant Example is an innovative code sample and architecture pattern designed to enhance writing tasks efficiency using AWS serverless technologies and Amazon Bedrock's generative AI models.
Automate the creation of soccer match highlights with the power of Generative AI and AWS. This solution leverages AWS Bedrock (Anthropic’s Claude 3 Sonnet model), AWS MediaConvert, Lambda, Step Functions and other AWS services to identify and compile exciting game moments without manual editing.
Conversational AI assistant powered by Amazon Bedrock
Simple chatbot for querying metadata of designs in Autodesk Platform Services using Amazon Bedrock.
Question Answering Generative AI application with Large Language Models (LLMs), Amazon Bedrock, and Amazon DocumentDB (with MongoDB Compatibility)
Question Answering Generative AI application with Large Language Models (LLMs), Amazon Bedrock, and Amazon MemoryDB for Redis
RAG Application with LangChain, Terraform, AWS Opensearch and AWS Bedrock
ARIMA ML Model - Oil and Gas Supply Chain Demand Forecasting with LLM Analysis using AWS Bedrock Foundational Model
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