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cURL

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The Algorithmia API lets developers manage and call algorithms, work with data in object stores using Algorithmia data sources, and access and manage numerous other features of the Algorithmia platform. You can use cURL, an open source command-line tool, to access all features of our REST interface directly over HTTPS.

This guide will cover calling an algorithm using cURL with direct user input, calling an algorithm that accesses data through Algorithmia’s data API, and using Algorithmia’s hosted data capabilities. For a comprehensive listing of the endpoints available through Algorithmia’s API, please refer to our API Docs.

Calling an algorithm

Regardless of whether they’re invoked directly through the API or through a client library, algorithms take three basic types of input: strings, JSON blobs, and binary data. Within these constraints, individual algorithms may have more specific I/O requirements as well—they may only accepting specific data types for input, or they may accept multiple input types but then use internal logic to handle those different types. Consult the Input and Output sections of an algorithm’s documentation for specifics.

To access the API, you’ll need an API key, which Algorithmia uses for authentication and fine-grained resource access across the platform. Log in to Algorithmia’s browser UI and navigate to HomeAPI Keys to locate your API key. For the examples in this guide, you can use the default-key that’s created along with your account. This is a standard API key with a broad set of permissions.

As shown in the code sample below, you’ll provide your API key via an Authorization header, replacing STD_API_KEY with your key and using the Simple prefix to specify the authentication token type. For more information on how to work with API keys, see the API keys documentation.

The first algorithm you’ll call in this guide is the boilerplate hello world algorithm used in the algorithm development Getting Started guide. This algorithm takes a string as input and returns a string as output. You can use the cURL command below to make the request.

Note that if you’re working with a private Algorithmia Enterprise cluster, you’ll need to replace algorithmia.com with your cluster-specific domain name and the algorithm endopint will need to be changed to /v1/algo/ALGO_OWNER/ALGO_NAME, where ALGO_OWNER is the name of your account) and ALGO_NAME is the name of your algorithm.

$ curl https://api.algorithmia.com/v1/algo/demo/hello \
    -X POST \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '"HAL 9000"'

When executed with a valid API key, this will print the phrase Hello HAL 9000 in your terminal.

Complex JSON inputs

Let’s explore an example using the more complicated JSON input associated with a natural language processing (NLP) algorithm. This algorithm takes a list of documents and returns a number of topics that are relevant to those documents. The documents can be a list of strings, a data URI, or a URL. Suppose you want to call this algorithm using a list of strings; you could achieve this with the cURL command below.

$ curl https://api.CLUSTER_DOMAIN/v1/algo/nlp/LDA/1.0.0 \
    -X POST \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '{
      "docsList": [
        "It is apple picking season",
        "The apples are ready for picking"
      ]
    }'

The output is in the format [{'picking': 2}, {'apple': 1}, {'apples': 1, 'ready': 1}, {'season': 1}], which is the list of relevant words and the number of occurrences of each.

Notice that in the command above, the API endpoint includes a version number ALGO_VERSION. We recommend providing a fully specified semantic version to indicate exactly which version of algorithm you’re requesting. This becomes particularly important in production environments to ensure that the correct version is being executed, as the underlying implementation might change between versions.

Request options

The API exposes options for configuring algorithm requests. This includes support for changing the execution timeout or indicating that the API should include stdout in the response. With cURL, you can provide these options as URL parameters. The example below shows how to set the timeout to 60 seconds and disable stdout in the response for the hello world algorithm from above.

$ curl 'https://api.algorithmia.com/v1/algo/demo/hello?timeout=60&stdout=false' \
    -X POST \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '"HAL 9001"'

You can find more details under API DocsInvoke an Algorithm.

Error handling

To be able to better develop across languages, we’ve created a set of standardized error classes that can be returned by either the platform itself or by the individual algorithm being run. If an error occurs while invoking the API, the HTTP response will include an error field with error information.

$ curl https://api.algorithmia.com/v1/algo/ALGO_OWNER/DOES_NOT_EXIST \
    -X POST \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '"Hello, world"'

When this hypothetical DOES_NOT_EXIST algorithm is called, it returns the response {"error": {"message": "algorithm algo://ALGO_OWNER/DOES_NOT_EXIST not found"}}, indicating that the platform couldn’t locate the algorithm resource.

To learn how to handle errors elagantly and expressively in your own algorithms, see Error Handling.

Limits

By default, one account can make up to 80 concurrent algorithm execution requests (this limit can be increased if needed).

Requests are limited to a payload size of 10 MB for input and 15 MB for output. If you need to work with larger payloads, you can make use of Algorithmia’s data API. See considerations for transferring large data payloads for more details.

Working with Algorithmia data sources

For some algorithms, passing input data at request time is sufficient. However, for algorithms with larger data payload requirements, and for those that require preservation of state between calls, it may be convenient or necessary to use Algorithmia’s various data sources to store text, JSON, or binary data and then access it via the Algorithmia’s data API at run time.

The data API defines connectors to a variety of storage providers, including Algorithmia hosted data, Amazon S3, Azure Blob Storage, Google Cloud Storage, and Dropbox. After creating a connection in the browser UI under Data Sources or through the data API, you can use the API to create, update, and delete directories and files and manage permissions across storage providers.

In this example, you’ll upload an image to Algorithmia’s hosted data storage provider and then use a face detection algorithm to detect any faces in the image. According to the algorithm’s documentation, the algorithm creates a new copy of the image with bounding boxes drawn around the detected faces, and then returns a JSON object with a detected_faces property listing the coordinates of the bounding boxes where faces were found, as well as a url field listing a data URI where the resulting image can be downloaded.

Create a data collection

The documentation for the face detection algorithm says that as input it takes a URL or a data URI of the image to be processed, and a data URI where the algorithm can store the result. We’ll first execute a POST request to create a directory to host the input image. Then, we’ll execute a PATCH request with the appropriate ACL to update the directory’s permissions so that it’s publicly accessible.

$ curl 'https://api.algorithmia.com/v1/data/.my' \
    -X POST \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '{"name": "img_directory"}'

The response indicates the URI of the new collection: {"result": "data://.my/img_directory"}

$ curl 'https://api.algorithmia.com/v1/connector/data/.my/img_directory' \
    -X PATCH \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '{"acl": {"read": ["user://*"]} }'

Note that, as demonstrated above, instead of your account name you can also use .my when calling algorithms. For more information about the .my pseudonym, see the hosted data docs.

Upload data to your data collection

Now you’re ready to upload an image file for processing. For this example, you can use this photo of a group of friends. Download the image and save it locally as friends.jpg, and then upload the local file to the data collection using the following PUT command.

$ curl 'https://api.algorithmia.com/v1/connector/data/.my/img_directory/friends.jpg' \
    -X PUT \
    -H 'Authorization: Simple STD_API_KEY' \
    --data-binary @PATH/TO/LOCAL_DIRECTORY/friends.jpg

NOTE: This method call will replace a file if it already exists at the specified location. If you wish to avoid replacing a file, check if the file exists before using this method.

Confirm that the file was created by navigating to Data Sources in the browser UI and finding the data collection and file.

You can also upload your data through the Algorithmia’s browser UI; see the hosted data docs for details.

Call the algorithm

Once the file has been uploaded, you are ready to call the algorithm, providing the inputs as specified in the FaceDetection documentation—an image URI (which is stored in img_file in the code above) and a URI for the image output:

$ curl https://api.algorithmia.com/v1/algo/dlib/FaceDetection/0.2.1 \
    -X POST \
    -H 'Content-Type: application/json' \
    -H 'Authorization: Simple STD_API_KEY' \
    -d '{
      "images": [
        {
            "url": "data://.my/img_directory/friends.jpg",
            "output": "data://.algo/temp/detected_faces.png"
        }
      ]
    }'

Once the algorithm execution completes, the response will contain the dimensions of the bounding boxes for any detected faces and the URI for the resulting file, which you can then download (or provide as input to another algorithm in a pipeline).

Algorithms can create and store data in folders named with the algorithm name in the algorithm data collection. To access files in this location from within an executing algorithm, the .algo shortcut can be used, as in the input example above. When accessing data from a client context, the algorithm owner and name can be used along with the .algo shortcut to download data, in the format data://.algo/ALGO_OWNER/ALGO_NAME/COLLECTION_NAME/FILE_NAME.

Download the resulting file

The URI included in the algorithm output uses the .algo shortcut, so we’ll need to modify it slightly to download the file by adding the algorithm name and author. We can then attempt to download the file and write it to disk:

$ curl https://api.algorithmia.com/v1/connector/data/.algo/dlib/FaceDetection/temp/detected_faces.png \
    -H 'Authorization: Simple STD_API_KEY' \
    -O # save image locally with remote file name

Additional Functionality

In addition to the functionality covered in this guide, the API provides a complete interface to the Algorithmia platform, including managing algorithms, administering organizations, and working with external source code management providers. You can also visit the API Docs to view the complete API specification.

Next Steps

If you’d like to use a particular programming language for accessing the Algorithmia platform, you can refer to the rest of our Client Guides. If you’ll be building and deploying new algorithms on the platform, , you can move on to the Algorithm Development > Getting Started guide.