Ejemplos de comprensión de imágenes

En el siguiente ejemplo, se muestra cómo enviar una petición de imagen al modelo de Amazon Nova con 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)

Si desea transferir archivos de imagen de gran tamaño o varios archivos de imagen, en los que la carga útil total sea superior a 25 MB, puede utilizar Amazon S3. El siguiente ejemplo muestra cómo utilizar Amazon S3 para cargar imágenes en Amazon Nova:

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"])