Amazon Nova: AWS's Native Foundation Models on Bedrock

import boto3
import json
import base64

bedrock = boto3.client("bedrock-runtime", region_name="us-east-1")

with open("diagram.png", "rb") as f:
    image_data = base64.b64encode(f.read()).decode()

response = bedrock.invoke_model(
    modelId="amazon.nova-pro-v1:0",
    body=json.dumps({
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "image": {
                            "format": "png",
                            "source": {"bytes": image_data}
                        }
                    },
                    {"text": "Describe the architecture shown in this diagram."}
                ]
            }
        ],
        "inferenceConfig": {"max_new_tokens": 1024}
    })
)

result = json.loads(response["body"].read())
print(result["output"]["message"]["content"][0]["text"])

response = bedrock.converse(
    modelId="amazon.nova-pro-v1:0",
    messages=[
        {"role": "user", "content": [{"text": "Summarize the key risks in this contract."}]}
    ],
    inferenceConfig={"maxTokens": 2048, "temperature": 0.3}
)

print(response["output"]["message"]["content"][0]["text"])

bedrock_agent = boto3.client("bedrock-agent-runtime")

response = bedrock_agent.retrieve_and_generate(
    input={"text": "What are the termination clauses in our supplier agreements?"},
    retrieveAndGenerateConfiguration={
        "type": "KNOWLEDGE_BASE",
        "knowledgeBaseConfiguration": {
            "knowledgeBaseId": "your-kb-id",
            "modelArn": "arn:aws:bedrock:us-east-1::foundation-model/amazon.nova-pro-v1:0"
        }
    }
)
print(response["output"]["text"])