Speed up AI growth with Amazon Bedrock API keys

As we speak, we’re excited to announce a major enchancment to the developer expertise of Amazon Bedrock: API keys. API keys present fast entry to the Amazon Bedrock APIs, streamlining the authentication course of in order that builders can concentrate on constructing quite than configuration.

CamelAI is an open-source, modular framework for constructing clever multi-agent programs for knowledge era, world simulation, and job automation.

“As a startup with restricted sources, streamlined buyer onboarding is crucial to our success. The Amazon Bedrock API keys allow us to onboard enterprise clients in minutes quite than hours. With Bedrock, our clients can rapidly provision entry to main AI fashions and seamlessly combine them into CamelAI,”

mentioned Miguel Salinas, CTO, CamelAI.

On this publish, discover how API keys work and how one can begin utilizing them at present.

API key authentication

Amazon Bedrock now gives API key entry to streamline integration with instruments and frameworks that count on API key-based authentication. The Amazon Bedrock and Amazon Bedrock runtime SDKs assist API key authentication for strategies together with on-demand inference, provisioned throughput inference, mannequin fine-tuning, distillation, and analysis.

The diagram compares the default authentication course of to Amazon Bedrock (in orange) with the API keys method (in blue). Within the default course of, you have to create an id in AWS IAM Id Heart or IAM, connect IAM insurance policies to supply permissions to carry out API operations, and generate credentials, which you’ll then use to make API calls. The gray containers within the diagram spotlight the steps that Amazon Bedrock now streamlines when producing an API key. Builders can now authenticate and entry Amazon Bedrock APIs with minimal setup overhead.

You’ll be able to generate API keys within the Amazon Bedrock console, selecting between two varieties.

With long-term API keys, you possibly can set expiration instances starting from 1 day to no expiration. These keys are related to an IAM consumer that Amazon Bedrock routinely creates for you. The system attaches the AmazonBedrockLimitedAccess managed coverage to this IAM consumer, and you may then modify permissions as wanted by means of the IAM service. We suggest utilizing long-term keys primarily for exploration of Amazon Bedrock.

Brief-term API keys use the IAM permissions out of your present IAM principal and expire when your account’s session ends or can last as long as 12 hours. Brief-term API keys use AWS Signature Model 4 for authentication. For steady software use, you possibly can implement API key refreshing with a script as proven in this instance. We suggest that you simply use short-term API keys for setups that require the next stage of safety.

Making Your First API Name

When you have entry to basis fashions, getting began with Amazon Bedrock API key’s easy. Right here’s find out how to make your first API name utilizing the AWS SDK for Python (Boto3 SDK) and API keys:

Generate an API key

To generate an API key, observe these steps:

1. Sign up to the AWS Administration Console and open the Amazon Bedrock console
2. Within the left navigation panel, choose API keys
3. Select both Generate short-term API key or Generate long-term API key
4. For long-term keys, set your required expiration time and optionally configure superior permissions
5. Select Generate and replica your API key

Set Your API Key as Atmosphere Variable

You’ll be able to set your API key as an atmosphere variable in order that it’s routinely acknowledged if you make API requests:

# To set the API key as an atmosphere variable, you possibly can open a terminal and run the next command:
export AWS_BEARER_TOKEN_BEDROCK=${api-key}

The Boto3 SDK routinely detects your atmosphere variable if you create an Amazon Bedrock consumer.

Make Your First API Name

Now you can make API calls to Amazon Bedrock in a number of methods:

1. Utilizing curl

   curl -X POST "https://bedrock-runtime.us-east-1.amazonaws.com/mannequin/us.anthropic.claude-3-5-haiku-20241022-v1:0/converse" 
     -H "Content material-Kind: software/json" 
     -H "Authorization: Bearer $AWS_BEARER_TOKEN_BEDROCK" 
     -d '{
       "messages": [
           {
               "role": "user",
               "content": [{"text": "Hello"}]
           }
       ]
     }'

2. Utilizing the Amazon Bedrock SDK:

   import boto3
   
   # Create an Amazon Bedrock consumer
   consumer = boto3.consumer(
       service_name="bedrock-runtime",
       region_name="us-east-1"     # When you've configured a default area, you possibly can omit this line
   ) 
   
   # Outline the mannequin and message
   model_id = "us.anthropic.claude-3-5-haiku-20241022-v1:0"
   messages = [{"role": "user", "content": [{"text": "Hello"}]}]
      
   response = consumer.converse(
       modelId=model_id,
       messages=messages,
   )
   
   # Print the response
   print(response['output']['message']['content'][0]['text'])

3. You can even use native libraries like Python Requests:

   import requests
   import os
   
   url = "https://bedrock-runtime.us-east-1.amazonaws.com/mannequin/us.anthropic.claude-3-5-haiku-20241022-v1:0/converse"
   
   payload = {
       "messages": [
           {
               "role": "user",
               "content": [{"text": "Hello"}]
           }
       ]
   }
   
   headers = {
       "Content material-Kind": "software/json",
       "Authorization": f"Bearer {os.environ['AWS_BEARER_TOKEN_BEDROCK']}"
   }
   
   response = requests.request("POST", url, json=payload, headers=headers)
   
   print(response.textual content)

Bridging developer expertise and enterprise safety necessities

Enterprise directors can now streamline their consumer onboarding to Amazon Bedrock basis fashions. With setups that require the next stage of safety, directors can allow short-term API keys for his or her customers. Brief-term API keys use AWS Signature Model 4 and present IAM principals, sustaining established entry controls carried out by directors.

For audit and compliance functions, all API calls are logged in AWS CloudTrail. API keys are handed as authorization headers to API requests and aren’t logged.

Conclusion

Amazon Bedrock API keys can be found in 20 AWS Areas the place Amazon Bedrock is obtainable: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Hyderabad, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Canada (Central), Europe (Frankfurt, Eire, London, Milan, Paris, Spain, Stockholm, Zurich), and South America (São Paulo). To be taught extra about API keys in Amazon Bedrock, go to the API Keys documentation within the Amazon Bedrock consumer information.

Give API keys a attempt within the Amazon Bedrock console at present and ship suggestions to AWS re:Put up for Amazon Bedrock or by means of your traditional AWS Assist contacts.

In regards to the Authors

Sofian Hamiti is a know-how chief with over 10 years of expertise constructing AI options, and main high-performing groups to maximise buyer outcomes. He’s passionate in empowering numerous expertise to drive world impression and obtain their profession aspirations.

Ajit Mahareddy is an skilled Product and Go-To-Market (GTM) chief with over 20 years of expertise in product administration, engineering, and go-to-market. Previous to his present position, Ajit led product administration constructing AI/ML merchandise at main know-how firms, together with Uber, Turing, and eHealth. He’s keen about advancing generative AI applied sciences and driving real-world impression with generative AI.

Nakul Vankadari Ramesh is a Software program Growth Engineer with over 7 years of expertise constructing large-scale distributed programs. He at the moment works on the Amazon Bedrock group, serving to speed up the event of generative AI capabilities. Beforehand, he contributed to Amazon Managed Blockchain, specializing in scalable and dependable infrastructure.

Huong Nguyen is a Principal Product Supervisor at AWS. She is a product chief at Amazon Bedrock, with 18 years of expertise constructing customer-centric and data-driven merchandise. She is keen about democratizing accountable machine studying and generative AI to allow buyer expertise and enterprise innovation. Exterior of labor, she enjoys spending time with household and associates, listening to audiobooks, touring, and gardening.

Massimiliano Angelino is Lead Architect for the EMEA Prototyping group. Over the past 3 and half years he has been an IoT Specialist Answer Architect with a selected concentrate on edge computing, and he contributed to the launch of AWS IoT Greengrass v2 service and its integration with Amazon SageMaker Edge Supervisor. Primarily based in Stockholm, he enjoys skating on frozen lakes.