End-to-end testing and deployment of a multi-agent AI system with Docker, LangGraph, and CircleCI

1

CircleCI

In this tutorial, you will walk through the process of building, testing, and deploying a multi-agent AI system using LangGraph, Docker, AWS Lambda, and CircleCI. You will develop a research-driven AI workflow where different agents,such as fact-checking, summarization, and search agents, work together seamlessly. You will package this application into a Docker container, deploy it to AWS Lambda, and automate the entire pipeline using CircleCI.

#Continuous Integration #Continuous Deployment #DevOps Tools 78 social mentions

2

AWS Lambda

In this tutorial, you will walk through the process of building, testing, and deploying a multi-agent AI system using LangGraph, Docker, AWS Lambda, and CircleCI. You will develop a research-driven AI workflow where different agents,such as fact-checking, summarization, and search agents, work together seamlessly. You will package this application into a Docker container, deploy it to AWS Lambda, and automate the entire pipeline using CircleCI.

#Cloud Computing #Cloud Hosting #Business & Commerce 277 social mentions

3

AWS Identity and Access Management

Deploy it to AWS Lambda with the required IAM permissions.

#Identity And Access Management #Identity Provider #SSO 60 social mentions

4

Amazon ECR

AWS Account: Sign up for an AWS account if you do not already have one. You will use AWS Lambda and Elastic Container Registry (ECR) for deployment.

#Cloud Computing #Cloud Hosting #Container Registry 44 social mentions

5

Amazon Bedrock

AWS Bedrock: You will be using AWS Bedrock Anthropic models. Therefore, you will need to request access to these models to be able to use them in your application. Specifically you will be using Claude 3 Haiku. Under AWS Bedrock, go to model access and request access to the model. Once you see "Access granted" in green, you can invoke the model.

#Utilities #Communications #Large Language Model Tools 43 social mentions