Beispiele für das Verständnis von Bildern

Das folgende Beispiel zeigt, wie Sie mit eine Bildaufforderung an Amazon Nova Model senden InvokeModel.

# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import base64
import boto3
import json
# Create a Bedrock Runtime client in the AWS Region of your choice.
client = boto3.client(
    "bedrock-runtime",
    region_name="us-east-1",
)

MODEL_ID = "us.amazon.nova-lite-v1:0"
# Open the image you'd like to use and encode it as a Base64 string.
with open("media/sunset.png", "rb") as image_file:
    binary_data = image_file.read()
    base_64_encoded_data = base64.b64encode(binary_data)
    base64_string = base_64_encoded_data.decode("utf-8")
# Define your system prompt(s).
system_list = [    {
        "text": "You are an expert artist. When the user provides you with an image, provide 3 potential art titles"
    }
]
# Define a "user" message including both the image and a text prompt.
message_list = [
    {
        "role": "user",
        "content": [
            {
                "image": {
                    "format": "png",
                    "source": {
                        "bytes": image // Binary array (Converse API) or Base64-encoded string (Invoke API)
                    },
                }
            },
            {
                "text": "Provide art titles for this image."
            }
        ],
    }
]
# Configure the inference parameters.
inf_params = {"maxTokens": 300, "topP": 0.1, "topK": 20, "temperature": 0.3}

native_request = {
    "schemaVersion": "messages-v1",
    "messages": message_list,
    "system": system_list,
    "inferenceConfig": inf_params,
}
# Invoke the model and extract the response body.
response = client.invoke_model(modelId=MODEL_ID, body=json.dumps(native_request))
model_response = json.loads(response["body"].read())
# Pretty print the response JSON.
print("[Full Response]")
print(json.dumps(model_response, indent=2))
# Print the text content for easy readability.
content_text = model_response["output"]["message"]["content"][0]["text"]
print("\n[Response Content Text]")
print(content_text)

Für die Weitergabe großer Bilddateien oder mehrerer Bilddateien, bei denen die Gesamtnutzlast mehr als 25 MB beträgt, können Sie Amazon S3 verwenden. Das folgende Beispiel zeigt, wie Sie Amazon S3 verwenden, um Bilder auf Amazon Nova hochzuladen:

import boto3
import json
import base64
# Create a Bedrock Runtime client
client = boto3.client("bedrock-runtime", 
                      region_name="us-east-1", 
                     )
PRO_MODEL_ID = "us.amazon.nova-pro-v1:0"
LITE_MODEL_ID = "us.amazon.nova-lite-v1:0"
MICRO_MODEL_ID = "us.amazon.nova-micro-v1:0"
PREMIER_MODEL_ID = "us.amazon.nova-premier-v1:0"
messages = [
    {
        "role": "user",
        "content": [
            {
                "image": {
                    "format": "png",
                    "source": {
                        "s3Location": {
                            #Replace the s3 bucket URI 
                            "uri": "s3://demo-bucket/cat.png"
                            "bucketOwner" : "123456789012"
                        }
                    },
                }
            },
            {"text": "Describe the following image"},
        ],
    }
]
inf_params = {"maxTokens": 300, "topP": 0.1, "temperature": 0.3}
model_response = client.converse(
    modelId=LITE_MODEL_ID, messages=messages, inferenceConfig=inf_params
)
print("\n[Full Response]")
print(json.dumps(model_response, indent=2))
print("\n[Response Content Text]")
print(model_response["output"]["message"]["content"][0]["text"])