> ## Documentation Index
> Fetch the complete documentation index at: https://portkey-docs-add-third-party-integration-issues-fixes.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# AWS SageMaker

> Route to your AWS Sagemaker models through Portkey

Sagemaker allows users to host any ML model on their own AWS infrastructure.

With Portkey you can manage/restrict access, log requests, and more.

## Quick Start

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  # 1. Install: pip install portkey-ai
  # 2. Add @sagemaker provider in Model Catalog
  # 3. Use it:

  portkey = Portkey(
      api_key="PORTKEY_API_KEY",
      provider="@sagemaker"
  )

  response = portkey.post(
      url="endpoints/{endpoint_name}/invocations",
      # You can pass any key value pair required by the model
      # (apart from `url`), they are passed to the Sagemaker endpoint
      inputs="my_custom_value",
      my_custom_key="my_custom_value"
  )

  print(response)
  ```

  ```js Javascript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  // 1. Install: npm install portkey-ai
  // 2. Add @sagemaker provider in Model Catalog
  // 3. Use it:

  const portkey = new Portkey({
      apiKey: "PORTKEY_API_KEY",
      provider: "@sagemaker"
  })

  const response = await portkey.post({
      url: "endpoints/{endpoint_name}/invocations",
      // You can pass any key value pair required by the model
      // (apart from `url`), they are passed to the Sagemaker endpoint
      inputs: "my_custom_value",
      my_custom_key: "my_custom_value"
  })

  console.log(response)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  # 1. Add @sagemaker provider in Model Catalog
  # 2. Use it:

  curl https://api.portkey.ai/v1/endpoints/{endpoint_name}/invocations \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -d '{
      "inputs": "my_custom_value",
      "my_custom_key": "my_custom_value"
    }'
  ```
</CodeGroup>

***

## Add Provider in Model Catalog

<Steps>
  <Step title="Navigate to Model Catalog">
    Go to [**Model Catalog → Add Provider**](https://app.portkey.ai/model-catalog/providers) in your Portkey dashboard.
  </Step>

  <Step title="Select AWS Sagemaker">
    Find and select **AWS Sagemaker** from the provider list.
  </Step>

  <Step title="Configure AWS Credentials">
    There are two authentication methods:

    <Note>
      Here's how to find your AWS credentials:

      <CardGroup cols={2}>
        <Card title="AWS Access Key" href="/integrations/llms/aws-bedrock#how-to-find-your-aws-credentials">
          Use your `AWS Secret Access Key`, `AWS Access Key Id`, and `AWS Region` to create your provider.

          [**Integration Guide**](/integrations/llms/aws-bedrock#how-to-find-your-aws-credentials)
        </Card>

        <Card title="AWS Assumed Role" href="/product/model-catalog/connect-bedrock-with-amazon-assumed-role">
          Take your `AWS Assumed Role ARN` and `AWS Region` to create the provider.

          [**Integration Guide**](/product/model-catalog/connect-bedrock-with-amazon-assumed-role)
        </Card>
      </CardGroup>
    </Note>

    Enter your AWS credentials and deployment details for your Sagemaker endpoint.
  </Step>

  <Step title="Save and Use">
    Save your configuration. Your provider slug will be `@sagemaker` (or a custom name you specify).
  </Step>
</Steps>

***

## Direct Integration Without Model Catalog

If you prefer not to store your AWS credentials in Portkey, you can pass them directly when instantiating the Portkey client.

### Supported Parameters

These parameters are supported for Sagemaker (not required if you're using Model Catalog):

| Node SDK                         | Python SDK                             | REST Headers                                       |
| -------------------------------- | -------------------------------------- | -------------------------------------------------- |
| awsAccessKeyId                   | aws\_access\_key\_id                   | x-portkey-aws-access-key-id                        |
| awsSecretAccessKey               | aws\_secret\_access\_key               | x-portkey-aws-secret-access-key                    |
| awsRegion                        | aws\_region                            | x-portkey-aws-region                               |
| awsSessionToken                  | aws\_session\_token                    | x-portkey-aws-session-token                        |
| sagemakerCustomAttributes        | sagemaker\_custom\_attributes          | x-portkey-amzn-sagemaker-custom-attributes         |
| sagemakerTargetModel             | sagemaker\_target\_model               | x-portkey-amzn-sagemaker-target-model              |
| sagemakerTargetVariant           | sagemaker\_target\_variant             | x-portkey-amzn-sagemaker-target-variant            |
| sagemakerTargetContainerHostname | sagemaker\_target\_container\_hostname | x-portkey-amzn-sagemaker-target-container-hostname |
| sagemakerInferenceId             | sagemaker\_inference\_id               | x-portkey-amzn-sagemaker-inference-id              |
| sagemakerEnableExplanations      | sagemaker\_enable\_explanations        | x-portkey-amzn-sagemaker-enable-explanations       |
| sagemakerInferenceComponent      | sagemaker\_inference\_component        | x-portkey-amzn-sagemaker-inference-component       |
| sagemakerSessionId               | sagemaker\_session\_id                 | x-portkey-amzn-sagemaker-session-id                |
| sagemakerModelName               | sagemaker\_model\_name                 | x-portkey-amzn-sagemaker-model-name                |

### Example

<CodeGroup>
  ```python Python icon="python" theme={null}
  from portkey_ai import Portkey

  portkey = Portkey(
      api_key="PORTKEY_API_KEY",
      provider="@sagemaker",
      aws_region="us-east-1",
      aws_access_key_id="AWS_ACCESS_KEY_ID",
      aws_secret_access_key="AWS_SECRET_ACCESS_KEY",
      sagemaker_inference_component="SAGEMAKER_INFERENCE_COMPONENT"
  )

  response = portkey.post(
      url="endpoints/{endpoint_name}/invocations",
      # You can pass any key value pair required by the model
      # (apart from `url`), they are passed to the Sagemaker endpoint
      inputs="my_custom_value",
      my_custom_key="my_custom_value"
  )

  print(response)
  ```

  ```js Javascript icon="square-js" theme={null}
  import Portkey from 'portkey-ai'

  const portkey = new Portkey({
      apiKey: "PORTKEY_API_KEY",
      provider: "@sagemaker",
      awsAccessKeyId: "AWS_ACCESS_KEY_ID",
      awsSecretAccessKey: "AWS_SECRET_ACCESS_KEY",
      awsRegion: "us-east-1",
      sagemakerInferenceComponent: "SAGEMAKER_INFERENCE_COMPONENT"
  })

  const response = await portkey.post({
      url: "endpoints/{endpoint_name}/invocations",
      // You can pass any key value pair required by the model
      // (apart from `url`), they are passed to the Sagemaker endpoint
      inputs: "my_custom_value",
      my_custom_key: "my_custom_value"
  })

  console.log(response)
  ```

  ```sh cURL icon="square-terminal" theme={null}
  curl https://api.portkey.ai/v1/endpoints/{endpoint_name}/invocations \
    -H "Content-Type: application/json" \
    -H "x-portkey-api-key: $PORTKEY_API_KEY" \
    -H "x-portkey-provider: @sagemaker" \
    -H "x-portkey-aws-access-key-id: $AWS_ACCESS_KEY_ID" \
    -H "x-portkey-aws-secret-access-key: $AWS_SECRET_ACCESS_KEY" \
    -H "x-portkey-aws-region: $AWS_REGION" \
    -H "x-portkey-amzn-sagemaker-inference-component: $SAGEMAKER_INFERENCE_COMPONENT" \
    -d '{
      "inputs": "my_custom_value",
      "my_custom_key": "my_custom_value"
    }'
  ```
</CodeGroup>

***

## Next Steps

<CardGroup cols={2}>
  <Card title="SDK Reference" icon="code" href="/api-reference/sdk/list">
    Complete SDK documentation and API reference
  </Card>

  <Card title="Add Metadata" icon="tag" href="/product/observability/metadata">
    Add metadata to your Sagemaker requests
  </Card>

  <Card title="Gateway Configs" icon="sliders" href="/product/ai-gateway/configs">
    Configure advanced gateway features
  </Card>

  <Card title="Tracing" icon="chart-line" href="/product/observability/traces">
    Trace and monitor your Sagemaker requests
  </Card>
</CardGroup>