From 6ae888dceda5e50d39005a8d77125f016f9b5961 Mon Sep 17 00:00:00 2001 From: Cameron Bates Date: Tue, 9 Apr 2024 13:58:03 -0400 Subject: [PATCH] Amazon bedrock stage 3 changes --- content/integrate/amazon-bedrock/_index.md | 8 ++++---- content/integrate/amazon-bedrock/create-agent.md | 2 +- content/integrate/amazon-bedrock/create-knowledge-base.md | 2 +- content/integrate/amazon-bedrock/set-up-redis.md | 6 +++--- 4 files changed, 9 insertions(+), 9 deletions(-) diff --git a/content/integrate/amazon-bedrock/_index.md b/content/integrate/amazon-bedrock/_index.md index 71bbc013e..bc8141f78 100644 --- a/content/integrate/amazon-bedrock/_index.md +++ b/content/integrate/amazon-bedrock/_index.md @@ -11,19 +11,19 @@ categories: description: Shows how to use your Redis database with Amazon Bedrock to customize foundational models. group: cloud-service +hideListLinks: true summary: With Amazon Bedrock, users can access foundational AI models from a variety of vendors through a single API, streamlining the process of leveraging generative artificial intelligence. type: integration weight: 3 -hideListLinks: true --- -[Amazon Bedrock](https://aws.amazon.com/bedrock/) is a service that allows you to securely customize foundational models (FMs) with your own data, and to use these models without having to build complex infrastructure management. With Amazon Bedrock, users can access FMs from a variety of vendors through a single API, streamlining the process of creating generative artificial intelligence (AI). +[Amazon Bedrock](https://aws.amazon.com/bedrock/) streamlines GenAI deployment by offering foundational models (FMs) as a unified API, eliminating complex infrastructure management. It lets you create AI-powered [Agents](https://aws.amazon.com/bedrock/agents/) that execute complex tasks. Through [Knowledge Bases](https://aws.amazon.com/bedrock/knowledge-bases/) within Amazon Bedrock, you can seamlessly tether FMs to your proprietary data sources using retrieval-augmented generation (RAG). This direct integration amplifies the FM's intelligence based on your organization's resources. -Amazon Bedrock allows you to choose Redis Cloud as the [vector database](https://redis.com/solutions/use-cases/vector-database/) for your knowledge base. After your database is set up and connected to Amazon Bedrock, it will import text data from an Amazon Simple Storage Service (S3) bucket into Redis Cloud and use it to extract relevant information when prompted. +Amazon Bedrock lets you choose Redis Cloud as the [vector database](https://redis.io/solutions/vector-search/) for your agent's Knowledge Base. Once Redis Cloud is integrated with Amazon Bedrock, it automatically reads text documents from your Amazon Simple Storage Service (S3) buckets. This process lets the large language model (LLM) pinpoint and extract pertinent context in response to user queries, ensuring your AI agents are well-informed and grounded in their responses. -For more information about the Redis integration with Amazon Bedrock, see the [Amazon Bedrock integration blog post](https://redis.com/blog/amazon-bedrock-integration-with-redis-enterprise/). +For more information about the Redis integration with Amazon Bedrock, see the [Amazon Bedrock integration blog post](https://redis.io/blog/amazon-bedrock-integration-with-redis-enterprise/). To fully set up Bedrock with Redis Cloud, you will need to do the following: diff --git a/content/integrate/amazon-bedrock/create-agent.md b/content/integrate/amazon-bedrock/create-agent.md index f7bd9297b..dd1b34856 100644 --- a/content/integrate/amazon-bedrock/create-agent.md +++ b/content/integrate/amazon-bedrock/create-agent.md @@ -1,5 +1,5 @@ --- -LinkTitle: Create agent +LinkTitle: Create Bedrock agent Title: Create a Bedrock agent alwaysopen: false categories: diff --git a/content/integrate/amazon-bedrock/create-knowledge-base.md b/content/integrate/amazon-bedrock/create-knowledge-base.md index 5be6f372f..53587531c 100644 --- a/content/integrate/amazon-bedrock/create-knowledge-base.md +++ b/content/integrate/amazon-bedrock/create-knowledge-base.md @@ -1,5 +1,5 @@ --- -LinkTitle: Create knowledge base +LinkTitle: Create Bedrock knowledge base Title: Create a Bedrock knowledge base alwaysopen: false categories: diff --git a/content/integrate/amazon-bedrock/set-up-redis.md b/content/integrate/amazon-bedrock/set-up-redis.md index 0b6277c57..d0d6d0f37 100644 --- a/content/integrate/amazon-bedrock/set-up-redis.md +++ b/content/integrate/amazon-bedrock/set-up-redis.md @@ -99,9 +99,9 @@ To set up a Redis Cloud instance for Bedrock, you need to: {{The New Database dialog with basic settings.}} - We selected **Search and query** and **JSON** for you already. You can remove **JSON** if you want. + We selected **Search and query** and **JSON** for you already. **Search and query** enables vector database features for your database. You can remove **JSON** if you want. -1. Set the Memory limit of your database based on the amount of data that will be pulled from your Simple Storage Service (S3) [bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/creating-buckets-s3.html). See [Find out the size of your S3 buckets](https://aws.amazon.com/blogs/storage/find-out-the-size-of-your-amazon-s3-buckets/) to find out how much training data is stored in your S3 bucket and pick the closest size, rounded up, from the table below. +1. Set the Memory limit of your database based on the amount of data that Bedrock will pull from your Simple Storage Service (S3) [bucket](https://docs.aws.amazon.com/AmazonS3/latest/userguide/creating-buckets-s3.html). See [Find out the size of your S3 buckets](https://aws.amazon.com/blogs/storage/find-out-the-size-of-your-amazon-s3-buckets/) to find out how much knowledge base data is stored in your S3 bucket and pick the closest size, rounded up, from the table below. | Total Size of Documents in S3 | Database size without replication | Database size with replication | |-------------------------------|-----------------------------------|--------------------------------| @@ -192,7 +192,7 @@ After you store this secret, you can view and copy the [Amazon Resource Name (AR ## Create a vector index in your database {#create-vector-index} -After your database is set up, create an index with a vector field using [FT.CREATE]({{< relref "/commands" >}}/ft.create/) as your knowledge base for Amazon Bedrock. You can accomplish this using **RedisInsight** or `redis-cli`. +After your Redis Cloud database is set up, create a search index with a vector field using [FT.CREATE]({{< relref "/commands" >}}/ft.create/) as your knowledge base for Amazon Bedrock. You can accomplish this using **RedisInsight** or `redis-cli`. ### RedisInsight