Learn to split workplace documents into passages, transform these passages into embeddings in Elasticsearch and integrate Amazon Bedrock LLM.

1. Install packages and import modules

2. Init Amazon Bedrock client

3. Connect to Elasticsearch

Getting Your Cloud ID

Creating an API Key

4. Download the dataset

5. Split documents into passages

6. Index data into elasticsearch

7. Init Amazon Bedrock LLM

8. Asking a question

Example Output

Trying it out

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities you need to build generative AI applications, simplifying development while maintaining privacy and security. Since Amazon Bedrock is serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.

What is Amazon Bedrock?

How to use Amazon Bedrock with Elasticsearch and Langchain

How to Use Amazon Bedrock with Elasticsearch and Langchain

Author

Yan Savitski

Articles

How to Use Amazon Bedrock with Elasticsearch and Langchain