Cohere Models on Amazon Bedrock

In this guide, you’ll learn how to use Amazon Bedrock to deploy the Cohere Command, Embed, and Rerank models on the AWS cloud computing platform. The following models are available on Bedrock:

Command R
Command R+
Command Light
Command
Embed - English
Embed - Multilingual
Rerank v3.5

Note that the code snippets below are in Python, but you can find the equivalent code for other languages (if they’re supported) here.

Prerequisites

THese are the steps you’ll need to get set up in advance of running Cohere models on Amazon Bedrock.

Subscribe to Cohere’s models on Amazon Bedrock. For more details, see here.
You’ll also have to configure your authentication credentials for AWS. This document has more information.

Embeddings

You can use this code to invoke Cohere’s Embed English v3 model (cohere.embed-english-v3) or Embed Multilingual v3 model (cohere.embed-multilingual-v3) on Amazon Bedrock:

PYTHON

1 import cohere
2 
3 co = cohere.BedrockClient(
4     aws_region="us-east-1",
5     aws_access_key="...",
6     aws_secret_key="...",
7     aws_session_token="...",
8 )
9 
10 # Input parameters for embed. In this example we are embedding hacker news post titles.
11 texts = [
12     "Interesting (Non software) books?",
13     "Non-tech books that have helped you grow professionally?",
14     "I sold my company last month for $5m. What do I do with the money?",
15     "How are you getting through (and back from) burning out?",
16     "I made $24k over the last month. Now what?",
17     "What kind of personal financial investment do you do?",
18     "Should I quit the field of software development?",
19 ]
20 input_type = "clustering"
21 truncate = "NONE"  # optional
22 model_id = (
23     "cohere.embed-english-v3"  # or "cohere.embed-multilingual-v3"
24 )
25 
26 # Invoke the model and print the response
27 result = co.embed(
28     model=model_id,
29     input_type=input_type,
30     texts=texts,
31     truncate=truncate,
32 )  # aws_client.invoke_model(**params)
33 
34 print(result)

Note that we’ve released multimodal embeddings models that are able to handle images in addition to text. Find more information here.

Text Generation

You can use this code to invoke either Command R (cohere.command-r-v1:0), Command R+ (cohere.command-r-plus-v1:0), Command (cohere.command-text-v14), or Command light (cohere.command-light-text-v14) on Amazon Bedrock:

PYTHON

1 import cohere
2 
3 co = cohere.BedrockClient(
4     aws_region="us-east-1",
5     aws_access_key="...",
6     aws_secret_key="...",
7     aws_session_token="...",
8 )
9 
10 result = co.chat(
11     message="Write a LinkedIn post about starting a career in tech:",
12     model="cohere.command-r-plus-v1:0",  # or 'cohere.command-r-v1:0'
13 )
14 
15 print(result)

Rerank

You can use this code to invoke our latest Rerank models on Bedrock

PYTHON

1 import cohere
2 
3 co = cohere.BedrockClientV2(
4     aws_region="us-west-2",  # pick a region where the model is available
5     aws_access_key="...",
6     aws_secret_key="...",
7     aws_session_token="...",
8 )
9 
10 docs = [
11     "Carson City is the capital city of the American state of Nevada.",
12     "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean. Its capital is Saipan.",
13     "Capitalization or capitalisation in English grammar is the use of a capital letter at the start of a word. English usage varies from capitalization in other languages.",
14     "Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district.",
15     "Capital punishment has existed in the United States since beforethe United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states.",
16 ]
17 
18 response = co.rerank(
19     model="cohere.rerank-v3-5:0",
20     query="What is the capital of the United States?",
21     documents=docs,
22     top_n=3,
23 )
24 
25 print(response)