文件 AWS 開發套件範例 GitHub 儲存庫中有更多可用的 [AWS SDK 範例](https://github.com/awsdocs/aws-doc-sdk-examples)。

本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

# DeepSeek for Amazon Bedrock 執行時期
<a name="bedrock-runtime_code_examples_deepseek"></a>

下列程式碼範例示範如何使用 Amazon Bedrock Runtime AWS SDKs。

**Topics**
+ [理解文件](bedrock-runtime_example_bedrock-runtime_DocumentUnderstanding_DeepSeek_section.md)

# 在 Amazon Bedrock 上使用 DeepSeek 傳送和處理文件
<a name="bedrock-runtime_example_bedrock-runtime_DocumentUnderstanding_DeepSeek_section"></a>

下列程式碼範例示範如何在 Amazon Bedrock 上使用 DeepSeek 傳送和處理文件。

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#### [ Python ]

**適用於 Python 的 SDK (Boto3)**  
 GitHub 上提供更多範例。尋找完整範例，並了解如何在 [AWS 程式碼範例儲存庫](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/bedrock-runtime#code-examples)中設定和執行。
在 Amazon Bedrock 上使用 DeepSeek 傳送和處理文件。  

```
# Send and process a document with DeepSeek on Amazon Bedrock.

import boto3
from botocore.exceptions import ClientError

# Create a Bedrock Runtime client in the AWS Region you want to use.
client = boto3.client("bedrock-runtime", region_name="us-east-1")

# Set the model ID, e.g. DeepSeek-R1
model_id = "us.deepseek.r1-v1:0"

# Load the document
with open("example-data/amazon-nova-service-cards.pdf", "rb") as file:
    document_bytes = file.read()

# Start a conversation with a user message and the document
conversation = [
    {
        "role": "user",
        "content": [
            {"text": "Briefly compare the models described in this document"},
            {
                "document": {
                    # Available formats: html, md, pdf, doc/docx, xls/xlsx, csv, and txt
                    "format": "pdf",
                    "name": "Amazon Nova Service Cards",
                    "source": {"bytes": document_bytes},
                }
            },
        ],
    }
]

try:
    # Send the message to the model, using a basic inference configuration.
    response = client.converse(
        modelId=model_id,
        messages=conversation,
        inferenceConfig={"maxTokens": 2000, "temperature": 0.3},
    )

    # Extract and print the reasoning and response text.
    reasoning, response_text = "", ""
    for item in response["output"]["message"]["content"]:
        for key, value in item.items():
            if key == "reasoningContent":
                reasoning = value["reasoningText"]["text"]
            elif key == "text":
                response_text = value

    print(f"\nReasoning:\n{reasoning}")
    print(f"\nResponse:\n{response_text}")

except (ClientError, Exception) as e:
    print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}")
    exit(1)
```
+  如需 API 詳細資訊，請參閱《AWS SDK for Python (Boto3) API 參考》**中的 [Converse](https://docs.aws.amazon.com/goto/boto3/bedrock-runtime-2023-09-30/Converse)。

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