aws-lambda-web-adapter
langchaingo
aws-lambda-web-adapter | langchaingo | |
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12 | 8 | |
1,257 | 3,055 | |
3.7% | - | |
9.1 | 9.8 | |
7 days ago | 8 days ago | |
Rust | Go | |
Apache License 2.0 | MIT License |
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aws-lambda-web-adapter
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Spring Boot 3 application on AWS Lambda - Part 4 Measuring cold and warm starts with AWS Serverless Java Container
In the next part of the series I'll make the introduction to the AWS Lambda Web Adapter and explain how our Serverless Spring Boot application on AWS can make use of it.
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Adding flexibility to your deployments with Lambda Web Adapter
Lambda Web Adapter (LWA) is an open-source project that enables running Web apps on Lambda functions without the need to change or adapt the code.
- AWS-lambda-web-adapter: Run web applications on AWS Lambda
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Build a Serverless GenAI solution with Lambda, DynamoDB, LangChain and Amazon Bedrock
Thanks to the AWS Lambda Web Adapter, the application built as a (good old) REST/HTTP API using a familiar library (in this case, Gin.
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The case for containers on Lambda (with benchmarks)
Using the excellent Lambda web adapter extension with a container, you can very easily move a function from Lambda to Fargate or Apprunner if cost becomes an issue. This optionality is of high value, and shouldn't be overlooked.
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Serverless Simplicity: Deploy & Run your Node.js Framework App on AWS Lambda
We will use AWS Lambda Web Adapter to run our Node.js Application on AWS Lambda.
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We are AWS Serverless and Event Driven Architecture Experts – Ask Us Anything – June 28th @ 6AM PT / 9AM ET / 1PM GMT
For such frameworks, I would look at Lambda Web Adapter (https://github.com/awslabs/aws-lambda-web-adapter/tree/main/examples). Both frameworks have specific examples for them that allow for the execution of those within a Lambda context with few, if any, code changes. For spring, specifically, using Lambda Snapstart can significantly improve cold-start performance. You can read more about Java and Spring framework in this blog post that contains also a code example https://aws.amazon.com/blogs/compute/reducing-java-cold-starts-on-aws-lambda-functions-with-snapstart/ With regards to Flask, you can also use a project like: https://pypi.org/project/flask-lambda/
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AWS staff spending ‘much of their time ’optimizing customers' clouds'
With the lambda web adapter[1], you shouldn't need to make any code changes for web projects, just some dockerfile changes which are only used if it is running as a lambda, so the same container image should still work on ecs or another cloud. [1]https://github.com/awslabs/aws-lambda-web-adapter
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Why or why not use AWS Lambda instead of a web framework for your REST APIs? (Business projects)
Additionally, there is this tool you can use to use the same image in a lambda and any other container runtime. https://github.com/awslabs/aws-lambda-web-adapter
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How does Cloud development work?
You can point your platform team to this: https://github.com/awslabs/aws-lambda-web-adapter , which they can use to get your service running in Lambda.
langchaingo
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How to use Retrieval Augmented Generation (RAG) for Go applications
Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!
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Build a Serverless GenAI solution with Lambda, DynamoDB, LangChain and Amazon Bedrock
This use-case here is a similar one - a chat application. I will switch back to implementing things in Go using langchaingo (I used Python for the previous one) and continue to use Amazon Bedrock. But there are few unique things you can explore in this blog post:
- LangChain for Go, the easiest way to write LLM-based programs in Go
- Langchaingo – LangChain in Idiomatic Go
- Agency: Pure Go LangChain Alternative
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Building LangChain applications with Amazon Bedrock and Go - An introduction
langchaingo is the LangChain implementation for the Go programming language. This blog post covers how to extend langchaingo to use foundation model from Amazon Bedrock.
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Zep: A long-term memory store for LLM apps, written in Go
Langchain Go is being actively developed https://github.com/tmc/langchaingo
What are some alternatives?
LocalStack - 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
yao - :rocket: A performance app engine to create web services and applications in minutes.Suitable for AI, IoT, Industrial Internet, Connected Vehicles, DevOps, Energy, Finance and many other use-cases.
serverless-graphql - Serverless GraphQL Examples for AWS AppSync and Apollo
langchain - 🦜🔗 Build context-aware reasoning applications
warp_lambda - A super simple adapter crate to let you use warp filters with AWS lambda runtime
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
powertools-lambda-python - A developer toolkit to implement Serverless best practices and increase developer velocity.
zep - Zep: Long-Term Memory for AI Assistants.
serverless-aws-rust-http - ⚡🏗️ template for new aws lambda serverless rust http apps
TaskEaseGPT - (WIP) A user-friendly, AI-powered task manager emphasizing efficient work over planning. Streamlines workflow with intelligent task generation & execution. Boost your productivity today!
aws-cdk - The AWS Cloud Development Kit is a framework for defining cloud infrastructure in code
langchaingo-amazon-bedrock-llm - Amazon Bedrock extension for langchaingo