# Real-time analysis for custom entity recognition (API)
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You can use the Amazon Comprehend API to run real-time analysis with a custom model. First, you create an endpoint to run the real-time analysis. After you create the endpoint, you run the real-time analysis.

For information about provisioning endpoint throughput, and the associated costs, see [Using Amazon Comprehend endpoints](using-endpoints.md).

**Topics**
+ [Creating an endpoint for custom entity detection](#detecting-cer-real-time-create-endpoint-api)
+ [Running real-time custom entity detection](#detecting-cer-real-time-run)

## Creating an endpoint for custom entity detection
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For information about the costs associated with endpoints, see [Using Amazon Comprehend endpoints](using-endpoints.md).

### Creating an Endpoint with the AWS CLI
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To create an endpoint by using the AWS CLI, use the `create-endpoint` command:

```
$ aws comprehend create-endpoint \
> --desired-inference-units {{number of inference units}} \
> --endpoint-name {{endpoint name}} \
> --model-arn arn:aws:comprehend:{{region}}:{{account-id}}:model/{{example}} \
> --tags Key={{Key}},Value={{Value}}
```

If your command succeeds, Amazon Comprehend responds with the endpoint ARN:

```
{
   "EndpointArn": "{{Arn}}"
}
```

For more information about this command, its parameter arguments, and its output, see [https://docs.aws.amazon.com/cli/latest/reference/comprehend/create-endpoint.html](https://docs.aws.amazon.com/cli/latest/reference/comprehend/create-endpoint.html) in the AWS CLI Command Reference.

## Running real-time custom entity detection
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After you create an endpoint for your custom entity recognizer model, you use the endpoint to run the [DetectEntities](https://docs.aws.amazon.com/comprehend/latest/APIReference/API_DetectEntities.html) API operation. You can provide text input using the `text` or `bytes` parameter. Enter the other input types using the `bytes` parameter.

For image files and PDF files, you can use the `DocumentReaderConfig` parameter to override the default text extraction actions. For details, see [Setting text extraction options](idp-set-textract-options.md).

### Detecting entities in text using the AWS CLI
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To detect custom entities in text, run the `detect-entities` command with the input text in the `text` parameter.

**Example : Use the CLI to detect entities in input text**  

```
$ aws comprehend detect-entities \
> --endpoint-arn {{arn}} \
> --language-code {{en}} \
> --text  "{{Andy Jassy is the CEO of Amazon.}}"
```
If your command succeeds, Amazon Comprehend responds with the analysis. For each entity that Amazon Comprehend detects, it provides the entity type, text, location, and confidence score.

### Detecting entities in semi-structured documents using the AWS CLI
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To detect custom entities in PDF, Word, or image file, run the `detect-entities` command with the input file in the `bytes` parameter.

**Example : Use the CLI to detect entities in an image file**  
This example shows how to pass in the image file using the `fileb` option to base64 encode the image bytes. For more information, see [Binary large objects](https://docs.aws.amazon.com/cli/latest/userguide/cli-usage-parameters-types.html#parameter-type-blob) in the AWS Command Line Interface User Guide.   
This example also passes in a JSON file named `config.json` to set the text extraction options.  

```
$ aws comprehend detect-entities \
> --endpoint-arn {{arn}} \
> --language-code {{en}} \
> --bytes fileb://image1.jpg   \
> --document-reader-config file://config.json
```
The **config.json** file contains the following content.  

```
 {
    "DocumentReadMode": "FORCE_DOCUMENT_READ_ACTION",
    "DocumentReadAction": "TEXTRACT_DETECT_DOCUMENT_TEXT"    
 }
```

For more information about the command syntax, see [DetectEntities](https://docs.aws.amazon.com/comprehend/latest/APIReference/API_DetectEntities.html) in the *Amazon Comprehend API Reference*.