Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.
CohereEmbedmodel
Anda membuat permintaan inferensi ke Embed model dengan InvokeModelAnda memerlukan ID model untuk model yang ingin Anda gunakan. Untuk mendapatkan ID model, lihatID model Amazon Bedrock.
catatan
Amazon Bedrock tidak mendukung respons streaming dari Cohere Embed model.
Permintaan dan Tanggapan
Contoh kode
Contoh ini menunjukkan cara memanggil CohereEmbed Englishmodel.
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 """ Shows how to generate text embeddings using the Cohere Embed English model. """ import json import logging import boto3 from botocore.exceptions import ClientError logger = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) def generate_text_embeddings(model_id, body): """ Generate text embedding by using the Cohere Embed model. Args: model_id (str): The model ID to use. body (str) : The reqest body to use. Returns: dict: The response from the model. """ logger.info( "Generating text emdeddings with the Cohere Embed model %s", model_id) accept = '*/*' content_type = 'application/json' bedrock = boto3.client(service_name='bedrock-runtime') response = bedrock.invoke_model( body=body, modelId=model_id, accept=accept, contentType=content_type ) logger.info("Successfully generated text with Cohere model %s", model_id) return response def main(): """ Entrypoint for Cohere Embed example. """ logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") model_id = 'cohere.embed-english-v3' text1 = "hello world" text2 = "this is a test" input_type = "search_document" try: body = json.dumps({ "texts": [ text1, text2], "input_type": input_type} ) response = generate_text_embeddings(model_id=model_id, body=body) response_body = json.loads(response.get('body').read()) print(f"ID: {response_body.get('id')}") print(f"Response type: {response_body.get('response_type')}") print("Embeddings") for i, embedding in enumerate(response_body.get('embeddings')): print(f"\tEmbedding {i}") print(*embedding) print("Texts") for i, text in enumerate(response_body.get('texts')): print(f"\tText {i}: {text}") except ClientError as err: message = err.response["Error"]["Message"] logger.error("A client error occurred: %s", message) print("A client error occured: " + format(message)) else: print( f"Finished generating text embeddings with Cohere model {model_id}.") if __name__ == "__main__": main()