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.
