From c9c56448e83c65014a1f6efbefdb4e34bcba64e6 Mon Sep 17 00:00:00 2001 From: Cherie Woo Date: Fri, 26 Dec 2025 17:03:15 -0800 Subject: [PATCH 1/6] Added setup section Also added link to Flowise deployment on AWS. --- en/integrations/langchain/llms/aws-bedrock.md | 32 ++++++++++++++++--- 1 file changed, 28 insertions(+), 4 deletions(-) diff --git a/en/integrations/langchain/llms/aws-bedrock.md b/en/integrations/langchain/llms/aws-bedrock.md index 4035d7d8..3b5163de 100644 --- a/en/integrations/langchain/llms/aws-bedrock.md +++ b/en/integrations/langchain/llms/aws-bedrock.md @@ -4,8 +4,32 @@ description: Wrapper around AWS Bedrock large language models. # AWS Bedrock -

AWS Bedrock Node

-{% hint style="info" %} -This section is a work in progress. We appreciate any help you can provide in completing this section. Please check our [Contribution Guide](/broken/pages/G48tdmpQ3z4CTWEspqkA) to get started. -{% endhint %} +AWS Bedrock Large Language Model provides access to Amazon Bedrock's Foundational Models and managed service for generative AI apps. + +To use AWS Bedrock in Flowise, add the **AWS Bedrock LLM** node to your Chatflow. + +# Setup + +1. Configure AWS credentials for Flowise. + +In Amazon Bedrock, ensure that your account has access to the model you want to use with Flowise. + +2. Add the AWS Bedrock node to your Chatflow. + +In the Flowise canvas, drag and drop the AWS Bedrock LLM node into your Chatflow. + +3. Configure the AWS Bedrock inputs: +

AWS Bedrock Node

+ +* AWS Credential: The AWS credential with your AWS access key. Select or create a new AWS credential. Ensure that your AWS credentials or IAM role has access to AWS Bedrock models and other required AWS services in your Chatflow. +* Region: The region where your AWS Bedrock resources are located. Ensure that you select the region where your AWS Bedrock models and resources are deployed. +* Model Name: The AWS Bedrock foundational model for your conversational AI. + +4. Connect the AWS Bedrock node in your Chatflow. + +After you add other Chatflow components (such as input nodes, output nodes, memory nodes), connect the AWS Bedrock LLM node to the appropriate components to create the Chatflow. + +For information about deploying Flowise on AWS, see [AWS](../../../configuration/deployment/aws.md). + + From be076b5f3704fdf3c94e0aa09bf2e7151a2ab6fa Mon Sep 17 00:00:00 2001 From: cheriepwoo <58492801+cheriepwoo@users.noreply.github.com> Date: Tue, 6 Jan 2026 10:07:37 -0800 Subject: [PATCH 2/6] Update en/integrations/langchain/llms/aws-bedrock.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- en/integrations/langchain/llms/aws-bedrock.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/en/integrations/langchain/llms/aws-bedrock.md b/en/integrations/langchain/llms/aws-bedrock.md index 3b5163de..3637afa6 100644 --- a/en/integrations/langchain/llms/aws-bedrock.md +++ b/en/integrations/langchain/llms/aws-bedrock.md @@ -5,7 +5,7 @@ description: Wrapper around AWS Bedrock large language models. # AWS Bedrock -AWS Bedrock Large Language Model provides access to Amazon Bedrock's Foundational Models and managed service for generative AI apps. +The **AWS Bedrock LLM** node integrates with Amazon Bedrock, a managed service that provides access to foundation models for building generative AI applications. To use AWS Bedrock in Flowise, add the **AWS Bedrock LLM** node to your Chatflow. From ab7baa705a7ad12f12bb2890ca6d1b84f230339d Mon Sep 17 00:00:00 2001 From: cheriepwoo <58492801+cheriepwoo@users.noreply.github.com> Date: Tue, 6 Jan 2026 10:07:56 -0800 Subject: [PATCH 3/6] Update en/integrations/langchain/llms/aws-bedrock.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- en/integrations/langchain/llms/aws-bedrock.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/en/integrations/langchain/llms/aws-bedrock.md b/en/integrations/langchain/llms/aws-bedrock.md index 3637afa6..536a8268 100644 --- a/en/integrations/langchain/llms/aws-bedrock.md +++ b/en/integrations/langchain/llms/aws-bedrock.md @@ -20,7 +20,7 @@ In Amazon Bedrock, ensure that your account has access to the model you want to In the Flowise canvas, drag and drop the AWS Bedrock LLM node into your Chatflow. 3. Configure the AWS Bedrock inputs: -

AWS Bedrock Node

+

AWS Bedrock Node

* AWS Credential: The AWS credential with your AWS access key. Select or create a new AWS credential. Ensure that your AWS credentials or IAM role has access to AWS Bedrock models and other required AWS services in your Chatflow. * Region: The region where your AWS Bedrock resources are located. Ensure that you select the region where your AWS Bedrock models and resources are deployed. From a15a2b63dc87d5c0d7c7d048ae26b16209fe1f32 Mon Sep 17 00:00:00 2001 From: cheriepwoo <58492801+cheriepwoo@users.noreply.github.com> Date: Tue, 6 Jan 2026 10:08:25 -0800 Subject: [PATCH 4/6] Update en/integrations/langchain/llms/aws-bedrock.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- en/integrations/langchain/llms/aws-bedrock.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/en/integrations/langchain/llms/aws-bedrock.md b/en/integrations/langchain/llms/aws-bedrock.md index 536a8268..6a0e242e 100644 --- a/en/integrations/langchain/llms/aws-bedrock.md +++ b/en/integrations/langchain/llms/aws-bedrock.md @@ -22,7 +22,7 @@ In the Flowise canvas, drag and drop the AWS Bedrock LLM node into your Chatflow 3. Configure the AWS Bedrock inputs:

AWS Bedrock Node

-* AWS Credential: The AWS credential with your AWS access key. Select or create a new AWS credential. Ensure that your AWS credentials or IAM role has access to AWS Bedrock models and other required AWS services in your Chatflow. +* AWS Credential: Select an existing AWS credential or create a new one. The associated IAM user or role must have permissions for `bedrock:InvokeModel` and any other required AWS services in your Chatflow. * Region: The region where your AWS Bedrock resources are located. Ensure that you select the region where your AWS Bedrock models and resources are deployed. * Model Name: The AWS Bedrock foundational model for your conversational AI. From bf3a92c7b4a2457f9bbcc44c1ff5ac9c7f3185d2 Mon Sep 17 00:00:00 2001 From: cheriepwoo <58492801+cheriepwoo@users.noreply.github.com> Date: Tue, 6 Jan 2026 10:09:49 -0800 Subject: [PATCH 5/6] Update en/integrations/langchain/llms/aws-bedrock.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- en/integrations/langchain/llms/aws-bedrock.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/en/integrations/langchain/llms/aws-bedrock.md b/en/integrations/langchain/llms/aws-bedrock.md index 6a0e242e..8ab4c91c 100644 --- a/en/integrations/langchain/llms/aws-bedrock.md +++ b/en/integrations/langchain/llms/aws-bedrock.md @@ -23,7 +23,7 @@ In the Flowise canvas, drag and drop the AWS Bedrock LLM node into your Chatflow

AWS Bedrock Node

* AWS Credential: Select an existing AWS credential or create a new one. The associated IAM user or role must have permissions for `bedrock:InvokeModel` and any other required AWS services in your Chatflow. -* Region: The region where your AWS Bedrock resources are located. Ensure that you select the region where your AWS Bedrock models and resources are deployed. +* Region: The AWS region where your Bedrock models are available. * Model Name: The AWS Bedrock foundational model for your conversational AI. 4. Connect the AWS Bedrock node in your Chatflow. From 8183079ede2e97a37e207a8126ade71c7005f53e Mon Sep 17 00:00:00 2001 From: cheriepwoo <58492801+cheriepwoo@users.noreply.github.com> Date: Tue, 6 Jan 2026 10:10:06 -0800 Subject: [PATCH 6/6] Update en/integrations/langchain/llms/aws-bedrock.md Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- en/integrations/langchain/llms/aws-bedrock.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/en/integrations/langchain/llms/aws-bedrock.md b/en/integrations/langchain/llms/aws-bedrock.md index 8ab4c91c..37ee1c49 100644 --- a/en/integrations/langchain/llms/aws-bedrock.md +++ b/en/integrations/langchain/llms/aws-bedrock.md @@ -30,6 +30,6 @@ In the Flowise canvas, drag and drop the AWS Bedrock LLM node into your Chatflow After you add other Chatflow components (such as input nodes, output nodes, memory nodes), connect the AWS Bedrock LLM node to the appropriate components to create the Chatflow. -For information about deploying Flowise on AWS, see [AWS](../../../configuration/deployment/aws.md). +For information about deploying Flowise on AWS, see [AWS](../../../configuration/deployment/aws.md).