Using Command R on AWS Bedrock

Quick Start

1. 1
   Create an account at AWS Bedrock and generate an API key.
2. 2
   Use the AWS Bedrock SDK or REST API to call command-r — see the documentation for request format.
3. 3
   You'll be billed $0.50/1M input, $1.50/1M output tokens. See full pricing.

Code Examples

import boto3

# Reads AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION from env
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
    modelId="command-r",
    messages=[{
        "role": "user",
        "content": [{"text": "Hello"}]
    }]
)
print(response["output"]["message"]["content"][0]["text"])

About AWS Bedrock

Amazon Bedrock is a comprehensive, fully managed service for building and scaling generative AI applications. The platform provides access to a diverse array of high-performing foundation models (FMs) from leading AI companies through a unified API, enabling users to select the most suitable models for their specific use cases. Key features include model customization using proprietary data through techniques like fine-tuning and Retrieval Augmented Generation (RAG), which significantly enhances the relevance and accuracy of AI outputs. Additionally, the platform supports the automation of complex tasks with agents capable of executing multi-step operations, making it versatile for applications ranging from text generation and image creation to conversational AI. Beyond its robust technical capabilities, Amazon Bedrock offers a serverless experience that streamlines infrastructure management, allowing developers to focus on application development without the burden of managing underlying resources. The platform prioritizes security and compliance, ensuring that data remains within the AWS ecosystem and adheres to industry standards. Bedrock's flexible pricing models, including pay-as-you-go options, enable organizations to effectively manage costs while scaling their AI initiatives. This combination of advanced features, ease of use, and cost-effectiveness positions Amazon Bedrock as a powerful tool for businesses looking to innovate rapidly in the generative AI space, ultimately enhancing productivity and operational efficiency.

AWS Bedrock is Amazon's fully managed foundation-model service, providing unified API access to top models from Anthropic, Meta, Mistral, and other leading AI labs with built-in tools for RAG, fine-tuning, and AI agent development.

Pricing on AWS Bedrock

Capabilities

About Command R

Command R is a 35-billion parameter large language model developed by Cohere, tailored for enterprise-scale AI applications. It is optimized for long-context tasks such as retrieval-augmented generation (RAG) and tool use, emphasizing high performance coupled with strong accuracy. This model excels in reasoning, summarization, and question answering across ten key languages. Its use spans various enterprise applications, automating complex tasks that involve interacting with systems like CRMs, APIs, and databases. The model can process up to 128,000 tokens and integrates seamlessly with Cohere's Embed and Rerank models, enhancing accuracy and efficiency in large-scale tasks. Additionally, a more powerful iteration, Command R+ with 104 billion parameters, offers even greater capabilities.