Services or capabilities described in AWS documentation might vary by Region. To see the differences applicable to the AWS European Sovereign Cloud Region, see the AWS European Sovereign Cloud User Guide.Quickstart
In this section, we will show you how to get started with Amazon Bedrock within a few minutes. We will use the OpenAI-compatible APIs: Responses API and Chat Completions API, and the Invoke and Converse API to show you how run an inference request. See Build for list of complete APIs.
Step 1 - AWS Account: If you have an AWS account already, skip this step and go to step 2. If you are new to AWS, sign up for an AWS account and follow instructions.
Step 2 - API key: Once you have an AWS account, you can create a long-term API key to authenticate your requests to Amazon Bedrock. To do that, go to the Amazon Bedrock service in AWS Console and generate a long term key. For more information, see the API keys section in the Build chapter.
Step 3 - Get the SDK: To use this getting started guide, you must have Python already installed. Then install the relevant software depending on the APIs you are using.
- Responses/Chat Completions API
-
pip install boto3 openai
- Invoke/Converse API
-
pip install boto3
Step 4 - Set environment variables: Configure your environment to use the API key for authentication.
- Responses/Chat Completions API
-
OPENAI_API_KEY="<provide your long term key>" OPENAI_BASE_URL="https://bedrock-mantle.<your-region>.api.aws/v1"
- Invoke/Converse API
-
AWS_BEARER_TOKEN_BEDROCK="<provide your long term key>"
Step 5 - Run your first inference request: Amazon Bedrock supports 100+ foundation models. Choose a model, and then use the following Python code to run your first inference request. Save the file as bedrock-first-request.py
- Responses API
-
from openai import OpenAI
client = OpenAI()
response = client.responses.create(
model="openai.gpt-oss-120b",
input="Can you explain the features of Amazon Bedrock?"
)
print(response)
- Chat Completions API
-
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai.gpt-oss-120b",
messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}]
)
print(response)
- Invoke API
-
import json
import boto3
client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.invoke_model(
modelId='anthropic.claude-opus-4-6-v1',
body=json.dumps({
'anthropic_version': 'bedrock-2023-05-31',
'messages': [{ 'role': 'user', 'content': 'Can you explain the features of Amazon Bedrock?'}],
'max_tokens': 1024
})
)
print(json.loads(response['body'].read()))
- Converse API
-
import boto3
client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.converse(
modelId='anthropic.claude-opus-4-6-v1',
messages=[
{
'role': 'user',
'content': [{'text': 'Can you explain the features of Amazon Bedrock?'}]
}
]
)
print(response)
Execute the code with Python by using the command:
python3 bedrock-first-request.py
You should see the output of your inference request.
To learn more about using other APIs and endpoints, please refer to Build.