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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in AI. The solution includes integrations with Amazon Bedrock and its included LLMs, such as Amazon Titan, and pre-built connectors for 3rd-party LLMs.
| Date | Stars |
|---|---|
| 2026-07-31 | 348 |
| 2026-08-06 | 348 |
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growth rate 0.00%/day
| **[✨ Generative AI Application Builder on AWS](https://aws.amazon.com/solutions/implementations/generative-ai-application-builder-on-aws/)** | **[🚧 Feature request](https://github.com/aws-solutions/generative-ai-application-builder-on-aws/issues/new?assignees=&labels=enhancement&template=feature_request.md&title=)** | **[🐛 Bug Report](https://github.com/aws-solutions/generative-ai-application-builder-on-aws/issues/new?assignees=&labels=bug&template=bug_report.md&title=)** | **[📖 Implementation Guide](https://docs.aws.amazon.com/solutions/latest/generative-ai-application-builder-on-aws/solution-overview.html)** | > **_NOTE:_** - If you want to use the solution without any custom changes, navigate to [Solution Landing Page](https://aws.amazon.com/solutions/implementations/generative-ai-application-builder-on-aws/) and click the "Launch in the AWS Console" in the Deployment options for a 1-click deployment into your AWS Console. - If you are upgrading from v1.4.x to the current version, please follow the steps in this [section](https://docs.aws.amazon.com/solutions/latest/generative-ai-application-builder-on-aws/update-the-solution.html) of the implementation guide. The [Generative AI Application Builder on AWS](https://aws.amazon.com/solutions/implementations/generative-ai-application-builder-on-aws/) solution (GAAB) provides a web-based management dashboard to deploy customizable Generative AI (Gen AI) use cases. This Deployment dashboard allows customers to deploy, experiment with, and compare different combinations of Large Language Model (LLM) use cases. Once customers have successfully configured and optimized their use case, they can take their deployment into production and integrate it within their applications. The Generative AI Application Builder is published under an Apache 2.0 license and is targeted for novice to experienced users who want to experiment and productionize different Gen AI use cases. The solution uses [LangChain](https://www.langchain.com/) open-source software (OSS) to configure connections to your choice of Large Language Models (LLMs) for different use cases. The first release of GAAB allows users to deploy chat use cases which allow the ability to query over users' enterprise data in a chatbot-style User Interface (UI), along with an API to support custom end-user implementations. Some of the features of GAAB are: - Rapid experimentation with ability to productionize at scale - Extendable and modularized architecture using nested [Amazon CloudFormation](https://aws.amazon.com/cloudformation/) stacks - Enterprise ready for company-specific data to tackle real-world business problems - Integration with [Amazon Bedrock](https://aws.amazon.com/bedrock/) and [Amazon SageMaker AI](https://aws.amazon.com/sagemaker-ai/) as LLM providers - Multi-LLM comparison and experimentation with metric tracking using [Amazon CloudWatch](https://aws.amazon.com/cloudwatch/) dashboards - Growing list of model providers and Gen AI use cases For a detailed solution implementation guide, refer to [The Generative AI Application Builder on AWS](https://docs.aws.amazon.com/solutions/latest/generative-ai-application-builder-on-aws/overview.html) ## On this page - [Architecture Overview](#architecture-overview) - [Deployment](#deployment) - [Source code](#source-code) - [SageMaker Model Input Documentation](#sagemaker-model-input-documentation) - [Creating a custom build](#creating-a-custom-build) ## Architecture Overview There are 3 unique user personas that are referred to in the solution walkthrough below: - The **DevOps user** is responsible for deploying the solution within the AWS account and for managing the infrastructure, updating the solution, monitoring performance, and maintaining the overall health and lifecycle of the solution. - The **admin users** are responsible for managing the content contained within the deployment. These users gets access to the Deployment da
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:cd9e385db85950e6, llm:Repository topics: bedrock, chatbot, generative-ai, llms, retrieval-augmented-generation. Description: 'Generative AI Application Builder on AWS facilitates development, rapid experimentation, and deployment of generative AI applications... integrations with Amazon Bedrock and its included LLMs... pre-built connectors for 3rd-party LLMs.'
matched fp:cd9e385db85950e6, llm:Repository topics: bedrock, chatbot, generative-ai, llms, retrieval-augmented-generation. Description: 'Generative AI Application Builder on AWS facilitates development, rapid experimentation, and deployment of generative AI applications... integrations with Amazon Bedrock and its included LLMs... pre-built connectors for 3rd-party LLMs.'
matched fp:cd9e385db85950e6, llm:Repository topics: bedrock, chatbot, generative-ai, llms, retrieval-augmented-generation. Description: 'Generative AI Application Builder on AWS facilitates development, rapid experimentation, and deployment of generative AI applications... integrations with Amazon Bedrock and its included LLMs... pre-built connectors for 3rd-party LLMs.'
matched fp:cd9e385db85950e6, llm:Repository topics: bedrock, chatbot, generative-ai, llms, retrieval-augmented-generation. Description: 'Generative AI Application Builder on AWS facilitates development, rapid experimentation, and deployment of generative AI applications... integrations with Amazon Bedrock and its included LLMs... pre-built connectors for 3rd-party LLMs.'