Create, Get, Update, Delete

Manage the data in your app.

Inputs

The API is built around a simple idea. You send inputs (images) to the service and it returns predictions. In addition to receiving predictions on inputs, you can also index inputs and their predictions to later search against. You can also index inputs with concepts to later train your own model.

When you add an input to your app, the base workflow of your app runs, computing the outputs from all the models in that workflow and indexes those outputs. Those indexed outputs are what incur the indexing fee monthly, and enable search and training on top of the outputs of the base workflow models.

Add Inputs

You can add inputs one by one or in bulk. If you do send bulk, you are limited to sending 128 inputs at a time.

Important: adding inputs is an asynchronous operation. That means it will process indexing of your inputs through your default workflow in the background, which can take some time. In order to check the status of each input you add, see the section on Get Input by ID to look for status 30000 (INPUT_IMAGE_DOWNLOAD_SUCCESS) status code on each input to know when it's successfully been indexed.

Add an input using a publicly accessible URL

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse postInputsResponse = stub.postInputs(
    PostInputsRequest.newBuilder().addInputs(
        Input.newBuilder().setData(
            Data.newBuilder().setImage(
                Image.newBuilder()
                    .setUrl("https://samples.clarifai.com/metro-north.jpg")
                    .setAllowDuplicateUrl(true)
            )
        )
    ).build()
);

if (postInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Post inputs failed, status: " + postInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PostInputs(
    {
        inputs: [{data: {image: {url: "https://samples.clarifai.com/metro-north.jpg", allow_duplicate_url: true}}}]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Post inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

post_inputs_response = stub.PostInputs(
    service_pb2.PostInputsRequest(
        inputs=[
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/metro-north.jpg",
                        allow_duplicate_url=True
                    )
                )
            )
        ]
    ),
    metadata=metadata
)

if post_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

js

app.inputs.create({
  url: "https://samples.clarifai.com/metro-north.jpg"
}).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.inputs.create_image_from_url("https://samples.clarifai.com/metro-north.jpg")

java

client.addInputs()
    .plus(ClarifaiInput.forImage("https://samples.clarifai.com/metro-north.jpg"))
    .executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Inputs;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.AddInputs(
                    new ClarifaiURLImage("https://samples.clarifai.com/metro-north.jpg"))
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiImage *image = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/metro-north.jpg"];
[app addInputs:@[image] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
    NSLog(@"inputs: %@", inputs);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiURLImage;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->addInputs(
        new ClarifaiURLImage('https://samples.clarifai.com/metro-north.jpg'))
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X POST \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/metro-north.jpg",
            "allow_duplicate_url": true
          }
        }
      }
    ]
  }'\
  https://api.clarifai.com/v2/inputs

Add an input using bytes

The data must be base64 encoded. When you add a base64 image to our servers, a copy will be stored and hosted on our servers. If you already have an image hosting service we recommend using it and adding images via the url parameter.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;
import com.google.protobuf.ByteString;
import java.io.File;
import java.nio.file.Files;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse postInputsResponse = stub.postInputs(
    PostInputsRequest.newBuilder().addInputs(
        Input.newBuilder().setData(
            Data.newBuilder().setImage(
                Image.newBuilder()
                    .setBase64(ByteString.copyFrom(Files.readAllBytes(
                        new File("{YOUR_IMAGE_LOCATION}").toPath()
                    )))
            )
        )
    ).build()
);

if (postInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Post inputs failed, status: " + postInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

const fs = require("fs");
const imageBytes = fs.readFileSync("{YOUR_IMAGE_LOCATION}");

stub.PostInputs(
    {
        inputs: [{data: {image: {base64: imageBytes}}}]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Post inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

with open("{YOUR_IMAGE_LOCATION}", "rb") as f:
    file_bytes = f.read()

post_inputs_response = stub.PostInputs(
    service_pb2.PostInputsRequest(
        inputs=[
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        base64=file_bytes
                    )
                )
            )
        ]
    ),
    metadata=metadata
)

if post_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

js

app.inputs.create({
  base64: "Zvfauhti4D..."
}).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

# add from filename
app.inputs.create_image_from_filename(filename)

# add from base64 bytes
app.inputs.create_image_from_base64(base64_bytes)

java

client.addInputs()
    .plus(ClarifaiInput.forImage(new File("image.png")))
    .executeSync();

csharp

using System.IO;
using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Inputs;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.AddInputs(
                    new ClarifaiFileImage(File.ReadAllBytes("image.png")))
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiImage *imageFromImage = [[ClarifaiImage alloc] initWithImage:@"dress.jpg"];
[app addInputs:@[imageFromImage] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
    NSLog(@"inputs: %@", inputs);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiFileImage;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->addInputs(
        new ClarifaiFileImage(file_get_contents('/home/user/image.png')))
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X POST \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "data": {
          "image": {
            "base64": '"`base64 /home/user/image.jpeg`"'"
          }
        }
      }
    ]
  }'\
  https://api.clarifai.com/v2/inputs

Add multiple inputs with ids

In cases where you have your own id and you only have one item per image, you are encouraged to send inputs with your own id. This will help you later match the input to your own database. If you do not send an id, one will be created for you. If you have more than one item per image, it is recommended that you put the product id in metadata.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse postInputsResponse = stub.postInputs(
    PostInputsRequest.newBuilder()
        .addInputs(
            Input.newBuilder()
                .setId("train1")
                .setData(
                    Data.newBuilder().setImage(
                        Image.newBuilder()
                            .setUrl("https://samples.clarifai.com/metro-north.jpg")
                            .setAllowDuplicateUrl(true)
                    )
                )
        )
        .addInputs(
            Input.newBuilder()
                .setId("puppy1")
                .setData(
                    Data.newBuilder().setImage(
                        Image.newBuilder()
                            .setUrl("https://samples.clarifai.com/puppy.jpeg")
                            .setAllowDuplicateUrl(true)
                    )
                )
        )
        .build()
);

if (postInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    for (Input input : postInputsResponse.getInputsList()) {
        System.out.println("Input " + input.getId() + " status: ");
        System.out.println(input.getStatus() + "\n");
    }

    throw new RuntimeException("Post inputs failed, status: " + postInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PostInputs(
    {
        inputs: [
            {
                id: "train1",
                data: {image: {url: "https://samples.clarifai.com/metro-north.jpg", allow_duplicate_url: true}}
            },
            {
                id: "puppy1",
                data: {image: {url: "https://samples.clarifai.com/puppy.jpeg", allow_duplicate_url: true}}
            },
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            for (const input of response.inputs) {
                console.log("Input " + input.id + " status: ");
                console.log(JSON.stringify(input.status, null, 2) + "\n");
            }

            throw new Error("Post inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

post_inputs_response = stub.PostInputs(
    service_pb2.PostInputsRequest(
        inputs=[
            resources_pb2.Input(
                id="train1",
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/metro-north.jpg",
                        allow_duplicate_url=True
                    )
                )
            ),
            resources_pb2.Input(
                id="puppy1",
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/puppy.jpeg",
                        allow_duplicate_url=True
                    )
                )
            ),
        ]
    ),
    metadata=metadata
)

if post_inputs_response.status.code != status_code_pb2.SUCCESS:
    for input_object in post_inputs_response.inputs:
        print("Input " + input_object.id + " status:")
        print(input_object.status)

    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

% tab title="js" %}

app.inputs.create([
  {
    url: "https://samples.clarifai.com/metro-north.jpg",
    id: 'train1'
  },
  {
    url: "https://samples.clarifai.com/puppy.jpeg",
    id: 'puppy1'
  }
]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
from clarifai.rest import Image as ClImage

app = ClarifaiApp(api_key='YOUR_API_KEY')

img1 = ClImage(url="https://samples.clarifai.com/metro-north.jpg", image_id="train1")
img2 = ClImage(url="https://samples.clarifai.com/puppy.jpeg", image_id="puppy1")

app.inputs.bulk_create_images([img1, img2])

java

client.addInputs()
    .plus(
        ClarifaiInput.forImage("https://samples.clarifai.com/metro-north.jpg")
            .withConcepts(Concept.forID("id1")),
        ClarifaiInput.forImage("https://samples.clarifai.com/wedding.jpg")
            .withConcepts(Concept.forID("id2"))
    )
    .executeSync();

csharp

using System.Collections.Generic;
using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Inputs;
using Clarifai.DTOs.Predictions;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.AddInputs(
                    new ClarifaiURLImage(
                        "https://samples.clarifai.com/metro-north.jpg",
                        positiveConcepts: new List<Concept> {new Concept("id1")}),
                    new ClarifaiURLImage(
                        "https://samples.clarifai.com/wedding.jpg",
                        positiveConcepts: new List<Concept> {new Concept("id2")}))
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiImage *train = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/metro-north.jpg"];
train.inputID = @"train";

ClarifaiImage *puppy = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/puppy.jpeg"];
puppy.inputID = @"puppy";

[app addInputs:@[train, puppy] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
    NSLog(@"inputs: %@", inputs);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiURLImage;
use Clarifai\DTOs\Predictions\Concept;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->addInputs([
        (new ClarifaiURLImage('https://samples.clarifai.com/metro-north.jpg'))
            ->withPositiveConcepts([new Concept('id1')]),
        (new ClarifaiURLImage('https://samples.clarifai.com/wedding.jpg'))
            ->withPositiveConcepts([new Concept('id2')]),
    ])
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X POST \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/metro-north.jpg",
            "allow_duplicate_url": true
          }
        },
        "id": "train1"
      },
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/puppy.jpeg",
            "allow_duplicate_url": true
          }
        },
        "id": "puppy1"
      }
    ]
  }'\
  https://api.clarifai.com/v2/inputs

Add inputs with concepts

If you would like to add an input with concepts, you can do so like this. Concepts play an important role in creating your own models using your own concepts. You can learn more about creating your own models above. Concepts also help you search for inputs. You can learn more about search here.

When you add a concept to an input, you need to indicate whether the concept is present in the image or if it is not present.

You can add inputs with concepts as either a URL or bytes.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse postInputsResponse = stub.postInputs(
    PostInputsRequest.newBuilder().addInputs(
        Input.newBuilder().setData(
            Data.newBuilder()
                .setImage(
                    Image.newBuilder()
                        .setUrl("https://samples.clarifai.com/puppy.jpeg")
                        .setAllowDuplicateUrl(true)
                )
                .addConcepts(
                    Concept.newBuilder()
                        .setId("charlie")
                        .setValue(1f)
                )
        )
    ).build()
);

if (postInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Post inputs failed, status: " + postInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PostInputs(
    {
        inputs: [{data: {
            image: {url: "https://samples.clarifai.com/puppy.jpeg", allow_duplicate_url: true},
            concepts: [{id: "charlie", value: 1.}]
        }}]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Post inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

post_inputs_response = stub.PostInputs(
    service_pb2.PostInputsRequest(
        inputs=[
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/puppy.jpeg",
                        allow_duplicate_url=True
                    ),
                    concepts=[resources_pb2.Concept(id="charlie", value=1.)]
                )
            )
        ]
    ),
    metadata=metadata
)

if post_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

js

app.inputs.create({
  url: "https://samples.clarifai.com/puppy.jpeg",
  concepts: [
    {
      id: "charlie",
      value: true
    }
  ]
}).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
from clarifai.rest import Image as ClImage

app = ClarifaiApp(api_key='YOUR_API_KEY')

# add by url
app.inputs.create_image_from_url("https://samples.clarifai.com/puppy.jpeg", concepts=['charlie'])

# add by base64 bytes
app.inputs.create_image_from_base64(base64_bytes, concepts=['charlie'])

# add by raw bytes
app.inputs.create_image_from_bytes(raw_bytes, concepts=['charlie'])

# add by local file
app.inputs.create_image_from_filename(local_filename, concepts=['charlie'])

# add multiple with concepts
img1 = ClImage(url="https://samples.clarifai.com/puppy.jpeg", concepts=['charlie'], not_concepts=['our_wedding'])
img2 = ClImage(url="https://samples.clarifai.com/wedding.jpg", concepts=['our_wedding'], not_concepts=['cat','charlie'])

app.inputs.bulk_create_images([img1, img2])

java

client.addInputs()
    .plus(ClarifaiInput.forImage("https://samples.clarifai.com/puppy.jpeg")
        .withConcepts(
            // To mark a concept as being absent, chain `.withValue(false)`
            Concept.forID("charlie")
        )
    )
    .executeSync();

csharp

using System.Collections.Generic;
using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Inputs;
using Clarifai.DTOs.Predictions;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.AddInputs(
                    new ClarifaiURLImage(
                        "https://samples.clarifai.com/puppy.jpeg",
                        // To mark a concept as being absent, use negativeConcepts
                        positiveConcepts: new List<Concept> {new Concept("charlie")}))
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiImage *puppy = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/puppy.jpeg"
                                              andConcepts:@[@"cute puppy"]];

[app addInputs:@[puppy] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
    NSLog(@"inputs: %@", inputs);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiURLImage;
use Clarifai\DTOs\Predictions\Concept;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->addInputs(
        (new ClarifaiURLImage('https://samples.clarifai.com/metro-north.jpg'))
            ->withPositiveConcepts([new Concept('id1')]))
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X POST \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/puppy.jpeg",
            "allow_duplicate_url": true
          },
          "concepts":[
            {
              "id": "charlie",
              "value": 1
            }
          ]
        }
      }
    ]
  }'\
  https://api.clarifai.com/v2/inputs

Add inputs with custom metadata

In addition to adding an input with concepts, you can also add an input with custom metadata. This metadata will then be searchable. Metadata can be any arbitrary JSON.

If you have more than one item per image it is recommended to put the id in metadata like:

{
  "product_id": "xyz"
}

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;
import com.google.protobuf.Struct;
import com.google.protobuf.Value;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse postInputsResponse = stub.postInputs(
    PostInputsRequest.newBuilder().addInputs(
        Input.newBuilder().setData(
            Data.newBuilder()
                .setImage(
                    Image.newBuilder()
                        .setUrl("https://samples.clarifai.com/puppy.jpeg")
                        .setAllowDuplicateUrl(true)
                )
                .setMetadata(
                    Struct.newBuilder()
                        .putFields("id", Value.newBuilder().setStringValue("id001").build())
                        .putFields("type", Value.newBuilder().setStringValue("animal").build())
                        .putFields("size", Value.newBuilder().setNumberValue(100).build())
                )
        )
    ).build()
);

if (postInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Post inputs failed, status: " + postInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PostInputs(
    {
        inputs: [{data: {
            image: {url: "https://samples.clarifai.com/puppy.jpeg", allow_duplicate_url: true},
            metadata: {id: "id001", type: "animal", size: 100}
        }}]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Post inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

from google.protobuf.struct_pb2 import Struct

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

input_metadata = Struct()
input_metadata.update({"id": "id001", "type": "animal", "size": 100})

post_inputs_response = stub.PostInputs(
    service_pb2.PostInputsRequest(
        inputs=[
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/puppy.jpeg",
                        allow_duplicate_url=True
                    ),
                    metadata=input_metadata
                )
            )
        ]
    ),
    metadata=metadata
)

if post_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

js

app.inputs.create({
  url: "https://samples.clarifai.com/puppy.jpeg",
  metadata: {id: 'id001', type: 'plants', size: 100}
}).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
from clarifai.rest import Image as ClImage

app = ClarifaiApp(api_key='YOUR_API_KEY')

# metadata must be defined as JSON object
metadata = {'id':'id001', 'type':'plants', 'size':100}

# adding metadata along with url, filename, etc
app.inputs.create_image_from_url(url="https://samples.clarifai.com/puppy.jpeg", metadata=metadata)
app.inputs.create_image_from_filename(filename="aa.jpg", metadata=metadata)

# define an image with metadata for bulk import
img = Image(url="", metadata=metadata)

app.inputs.bulk_create_images([img])

java

final JsonObject metadata = new JsonObject();
metadata.addProperty("isPuppy", true);
client.addInputs()
    .plus(
        ClarifaiInput.forImage("https://samples.clarifai.com/puppy.jpeg")
            .withMetadata(metadata)
    ).executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Inputs;
using Newtonsoft.Json.Linq;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            var metadata = new JObject(
                new JProperty("key1", "val1"),
                new JProperty("key2", "val2"));
            await client.AddInputs(
                    new ClarifaiURLImage(
                        "https://samples.clarifai.com/puppy.jpeg",
                        metadata: metadata))
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiImage *puppy = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/puppy.jpeg"
                                              andConcepts:@[@"cute puppy"]];
puppy.metadata = @{@"my_key": @[@"my",@"values"], @"cuteness": @"extra-cute"};
[app addInputs:@[puppy] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
  NSLog(@"inputs: %@", inputs);
}];

php

//coming soon

cURL

curl -X POST \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/puppy.jpeg",
            "allow_duplicate_url": true
          },
          "metadata": {"id": "id001", "type": "animal", "size": 100}
        }
      }
    ]
  }'\
  https://api.clarifai.com/v2/inputs

List inputs

You can list all the inputs (images) you have previously added either for search or train.

If you added inputs with concepts, they will be returned in the response as well.

This request is paginated.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse listInputsResponse = stub.listInputs(
    ListInputsRequest.newBuilder()
        .setPage(1)
        .setPerPage(10)
        .build()
);

if (listInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("List inputs failed, status: " + listInputsResponse.getStatus());
}

for (Input input : listInputsResponse.getInputsList()) {
    System.out.println(input);
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.ListInputs(
    {page: 1, per_page: 10},
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("List inputs failed, status: " + response.status.description);
        }

        for (const input of response.inputs) {
            console.log(JSON.stringify(input, null, 2));
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

list_inputs_response = stub.ListInputs(
    service_pb2.ListInputsRequest(page=1, per_page=10),
    metadata=metadata
)

if list_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("List inputs failed, status: " + list_inputs_response.status.description)

for input_object in list_inputs_response.inputs:
    print(input_object)

js

app.inputs.list({page: 1, perPage: 20}).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

# this is a generator
app.inputs.get_all()

# get a page of inputs
app.inputs.get_by_page(page=1, per_page=20)

java

client.getInputs() // optionally takes a perPage parameter
    .getPage(1)
    .executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.GetInputs()
                .Page(1)
                .ExecuteAsync();
        }
    }
}

objective-c

[app getInputsOnPage:1 pageSize:20 completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
    NSLog(@"inputs: %@", inputs);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiInput;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->getInputs()->executeSync();

if ($response->isSuccessful()) {
    $inputs = $response->get();
    foreach ($inputs as $input) {
        echo $input->id() . "\n";
    }
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X GET \
  -H "Authorization: Key YOUR_API_KEY" \
  https://api.clarifai.com/v2/inputs?page=1&per_page=10

List inputs (streaming)

Another method for listing inputs which was built to scalably list app's inputs in an iterative / streaming fashion. StreamInputs will return per_page number of inputs from a certain input onward, controlled by the optional last_id parameter (defaults to the first input).

By default, the stream will return inputs from oldest to newest. Set the descending field to true to reverse that order.

gRPC Java

import java.util.List;
import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

// To start from beginning, do not provide the last ID parameter.
MultiInputResponse firstStreamInputsResponse = stub.streamInputs(
    StreamInputsRequest.newBuilder()
        .setPerPage(10)
        .build()
);

if (firstStreamInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Stream inputs failed, status: " + firstStreamInputsResponse.getStatus());
}

System.out.println("First response (starting from the first input):");
List<Input> inputs = firstStreamInputsResponse.getInputsList();
for (Input input : inputs) {
    System.out.println("\t" + input.getId());
}

String lastId = inputs.get(inputs.size() - 1).getId();

// Set last ID to get the next set of inputs. The returned inputs will not include the last ID input.
MultiInputResponse secondStreamInputsResponse = stub.streamInputs(
    StreamInputsRequest.newBuilder()
        .setLastId(lastId)
        .setPerPage(10)
        .build()
);

if (secondStreamInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Stream inputs failed, status: " + secondStreamInputsResponse.getStatus());
}

System.out.println(String.format("Second response (first input is the one following input ID %s)", lastId));
for (Input input : secondStreamInputsResponse.getInputsList()) {
    System.out.println("\t" + input.getId());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.StreamInputs(
    {
        per_page: 10
    },
    metadata,
    (err, firstResponse) => {
        if (err) {
            done(err);
            return;
        }

        if (firstResponse.status.code !== 10000) {
            done(new Error("Received status: " + firstResponse.status.description + "\n" + firstResponse.status.details));
            return;
        }

        console.log("First response (starting from the first input):");
        for (const input of firstResponse.inputs) {
            console.log("\t" + input.id);
        }

        const lastId = firstResponse.inputs[firstResponse.inputs.length - 1].id;
        stub.StreamInputs(
            {
                last_id: lastId,
                per_page: 10
            },
            metadata,
            (err, secondResponse) => {
                if (err) {
                    done(err);
                    return;
                }

                if (secondResponse.status.code !== 10000) {
                    done(new Error("Received status: " + secondResponse.status.description + "\n" + secondResponse.status.details));
                    return;
                }

                console.log("Second response (first input is the one following input ID " + lastId + ")");
                for (const input of secondResponse.inputs) {
                    console.log("\t" + input.id);
                }

                done();
            }
        );
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

# To start from beginning, do not provide the last_id parameter.
stream_inputs_response = stub.StreamInputs(
    service_pb2.StreamInputsRequest(per_page=10),
    metadata=metadata
)

if stream_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Stream inputs failed, status: " + stream_inputs_response.status.description)

print("First response (starting from the first input):")
for input_object in stream_inputs_response.inputs:
    print("\t" + input_object.id)

last_id = stream_inputs_response.inputs[-1].id

# Set last_id to get the next set of inputs. The returned inputs will not include the last_id input.
stream_inputs_response = stub.StreamInputs(
    service_pb2.StreamInputsRequest(per_page=10, last_id=last_id),
    metadata=metadata
)

print(f"Second response (first input is the one following input ID {last_id}):")
for input_object in stream_inputs_response.inputs:
    print("\t" + input_object.id)

Get input by id

If you'd like to get a specific input by id, you can do that as well.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

SingleInputResponse getInputResponse = stub.getInput(
    GetInputRequest.newBuilder()
        .setInputId("{YOUR_INPUT_ID}")
        .build()
);

if (getInputResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Get input failed, status: " + getInputResponse.getStatus());
}

Input input = getInputResponse.getInput();
System.out.println(input);

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.GetInput(
    {input_id: "{YOUR_INPUT_ID}"},
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Get input failed, status: " + response.status.description);
        }

        const input = response.input;
        console.log(JSON.stringify(input, null, 2));
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

get_input_response = stub.GetInput(
    service_pb2.GetInputRequest(input_id="{YOUR_INPUT_ID}"),
    metadata=metadata
)

if get_input_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Get input failed, status: " + get_input_response.status.description)

input_object = get_input_response.input
print(input_object)

js

app.inputs.get({id}).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

image = app.inputs.get(input_id)

java

client.getInputByID("{id}").executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.GetInput("{id}")
                .ExecuteAsync();
        }
    }
}

objective-c

[_app getInput:input_id completion:^(ClarifaiInput *input, NSError *error) {
    NSLog(@"input": %@, input);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiURLImage;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->getInput('{input_id}')->executeSync();

if ($response->isSuccessful()) {
    // Here we "cast" from ClarifaiInput to ClarifaiURLImage.
    $input = $response->get();
    echo $input->url();
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X GET \
  -H "Authorization: Key YOUR_API_KEY" \
  https://api.clarifai.com/v2/inputs/{YOUR_INPUT_ID}

Get inputs status

If you add inputs in bulk, they will process in the background. You can get the status of all your inputs (processed, to_process and errors) like this:

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

SingleInputCountResponse getInputCountResponse = stub.getInputCount(
    GetInputCountRequest.newBuilder().build()
);

if (getInputCountResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Get input count failed, status: " + getInputCountResponse.getStatus());
}

InputCount inputCount = getInputCountResponse.getCounts();
System.out.println(inputCount);

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.GetInputCount(
    {},
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Get input count failed, status: " + response.status.description);
        }

        const counts = response.counts;
        console.log(JSON.stringify(counts, null, 2));
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

get_input_count_response = stub.GetInputCount(
    service_pb2.GetInputCountRequest(),
    metadata=metadata
)

if get_input_count_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Get input count failed, status: " + get_input_count_response.status.description)

counts = get_input_count_response.counts
print(counts)

js

app.inputs.getStatus().then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.inputs.check_status()

java

client.getInputsStatus().executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.GetInputsStatus()
                .ExecuteAsync();
        }
    }
}

objective-c

[app getInputsStatus:^(int numProcessed, int numToProcess, int errors, NSError *error) {
    NSLog(@"number of inputs processed: %d", numProcessed);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiInputsStatus;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->getInputsStatus()->executeSync();

if ($response->isSuccessful()) {
    $inputsStatus = $response->get();
    echo 'Num. processed: ' . $inputsStatus->processed() . "\n";
    echo 'Num. processing: ' . $inputsStatus->processing() . "\n";
    echo 'Num. to process: ' . $inputsStatus->toProcess() . "\n";
    echo 'Num. errors: ' . $inputsStatus->errors() . "\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X GET \
  -H "Authorization: Key YOUR_API_KEY" \
  https://api.clarifai.com/v2/inputs/status

Update inputs

Update input with concepts

To update an input with a new concept, or to change a concept value from true/false, you can do that:

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse patchInputsResponse = stub.patchInputs(
    PatchInputsRequest.newBuilder()
        .setAction("merge")  // Supported actions: overwrite, merge, remove.
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID}")
                .setData(
                    Data.newBuilder()
                        .addConcepts(
                            Concept.newBuilder()
                                .setId("tree")
                                .setValue(1f)  // 1 means true, this concept is present.
                        )
                        .addConcepts(
                            Concept.newBuilder()
                                .setId("water")
                                .setValue(0f)  // 0 means false, this concept is not present.
                        )
                )
                .build()
        )
        .build()
);

if (patchInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Patch inputs failed, status: " + patchInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PatchInputs(
    {
        action: "merge",  // Supported actions: overwrite, merge, remove.
        inputs: [
            {
                id: "{YOUR_INPUT_ID}",
                // 1 means true, this concept is present.
                // 0 means false, this concept is not present.
                data: {concepts: [{id: "tree", value: 1}, {id: "water", value: 0}]}
            }
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Patch inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

patch_inputs_response = stub.PatchInputs(
    service_pb2.PatchInputsRequest(
        action="merge",  # Supported actions: overwrite, merge, remove.
        inputs=[
            resources_pb2.Input(
                id="{YOUR_INPUT_ID}",
                data=resources_pb2.Data(
                    concepts=[
                        resources_pb2.Concept(id="tree", value=1.),  # 1 means true, this concept is present.
                        resources_pb2.Concept(id="water", value=0.)  # 0 means false, this concept is not present.
                    ]
                )
            )
        ]
    ),
    metadata=metadata
)

if patch_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Patch inputs failed, status: " + patch_inputs_response.status.description)

js

app.inputs.mergeConcepts([
  {
    id: "{id}",
    concepts: [
      {
        id: "tree"
      },
      {
        id: "water",
        value: false
      }
    ]
  },
])


// or if you have an input instance
app.inputs.get({id}).then(
  function(input) {
    input.mergeConcepts([
      {
        id: "tree",
        value: true
      },
      {
        id: "water",
        value: false
      }
    ])
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.inputs.merge_concepts('{id}', concepts=['tree'], not_concepts=['water'])

java

client.mergeConceptsForInput("{input_id}")
    .plus(
        Concept.forID("tree"),
        Concept.forID("water").withValue(false)
    )
    .executeSync();

csharp

using System.Collections.Generic;
using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.API.Requests.Models;
using Clarifai.DTOs.Predictions;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.ModifyInput(
                    "{input_id}",
                    ModifyAction.Merge,
                    positiveConcepts: new List<Concept> {new Concept("tree")},
                    negativeConcepts: new List<Concept> {new Concept("water")})
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiConcept *concept = [[ClarifaiConcept alloc] initWithConceptName:@"cute cat"];
[_app addConcepts:@[concept] forInputWithID:@"{id}" completion:^(ClarifaiInput *input, NSError *error) {
    NSLog(@"input: %@", input);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ModifyAction;
use Clarifai\DTOs\Predictions\Concept;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->modifyInput('{input_id}', ModifyAction::merge())
    ->withPositiveConcepts([new Concept('tree')])
    ->withNegativeConcepts([new Concept('water')])
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

# Value of 1 means true, this concept is present.
# Value of 0 means false, this concept is not present.
# Supported actions: overwrite, merge, remove.
curl -X PATCH \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "id": "{YOUR_INPUT_ID}",
        "data": {
          "concepts": [
            {
              "id": "tree",
              "value": 1
            },
            {
              "id": "water",
              "value": 0
            }
          ]
        }
      }
    ],
    "action":"merge"
}'\
  https://api.clarifai.com/v2/inputs

Bulk update inputs with concepts

You can update an existing input using its Id. This is useful if you'd like to add concepts to an input after its already been added.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse patchInputsResponse = stub.patchInputs(
    PatchInputsRequest.newBuilder()
        .setAction("merge")  // Supported actions: overwrite, merge, remove.
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID_1}")
                .setData(
                    Data.newBuilder()
                        .addConcepts(
                            Concept.newBuilder()
                                .setId("tree")
                                .setValue(1f)  // 1 means true, this concept is present.
                        )
                        .addConcepts(
                            Concept.newBuilder()
                                .setId("water")
                                .setValue(0f)  // 0 means false, this concept is not present.
                        )
                )
                .build()
        )
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID_2}")
                .setData(
                    Data.newBuilder()
                        .addConcepts(
                            Concept.newBuilder()
                                .setId("animal")
                                .setValue(1f)
                        )
                        .addConcepts(
                            Concept.newBuilder()
                                .setId("fruit")
                                .setValue(0f)
                        )
                )
                .build()
        )
        .build()
);

if (patchInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Patch inputs failed, status: " + patchInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PatchInputs(
    {
        action: "merge",  // Supported actions: overwrite, merge, remove.
        inputs: [
            {
                id: "{YOUR_INPUT_ID_1}",
                data: {concepts: [{id: "tree", value: 1}, {id: "water", value: 0}]}
            },
            {
                id: "{YOUR_INPUT_ID_2}",
                data: {concepts: [{id: "animal", value: 1}, {id: "fruit", value: 0}]}
            }
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Patch inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

patch_inputs_response = stub.PatchInputs(
    service_pb2.PatchInputsRequest(
        action="merge",  # Supported actions: overwrite, merge, remove.
        inputs=[
            resources_pb2.Input(
                id="{YOUR_INPUT_ID_1}",
                data=resources_pb2.Data(
                    concepts=[
                        resources_pb2.Concept(id="tree", value=1.),  # 1 means true, this concept is present.
                        resources_pb2.Concept(id="water", value=0.)  # 0 means false, this concept is not present.
                    ]
                )
            ),
            resources_pb2.Input(
                id="{YOUR_INPUT_ID_2}",
                data=resources_pb2.Data(
                    concepts=[
                        resources_pb2.Concept(id="animal", value=1.),
                        resources_pb2.Concept(id="fruit", value=0.)
                    ]
                )
            ),
        ]
    ),
    metadata=metadata
)

if patch_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Patch inputs failed, status: " + patch_inputs_response.status.description)

js

app.inputs.mergeConcepts([
  {
    id: "{id1}",
    concepts: [
      {
        id: "tree",
        value: true
      },
      {
        id: "water",
        value: false
      }
    ]
  },
  {
    id: "{id2}",
    concepts: [
      {
        id: "animal",
        value: true
      },
      {
        id: "fruit",
        value: false
      }
    ]
  }
]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

input_ids = ["{id1}", "{id2}"]
concept_pairs = [
                 [('tree', True), ('water', False)],
                 [('animal', True), ('fruit', False)],
                ]
app.inputs.bulk_merge_concepts(input_ids, concept_pairs)

java

// Coming soon

csharp

// Coming soon

objective-c

ClarifaiConcept *newConcept = [[ClarifaiConcept alloc] initWithConceptID:@"tree"];
[_app getInput:@"{input_id}" completion:^(ClarifaiInput *input, NSError *error) {
  // Add tree concept to each current input's concept list.
  NSMutableArray *newConceptList = [NSMutableArray arrayWithArray:input.concepts];
  [newConceptList addObject:newConcept];
  input.concepts = newConceptList;

  // Merge the new list for one or more inputs.
  [_app mergeConceptsForInputs:@[input] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error)   {
    NSLog(@"updated inputs: %@", inputs);
  }];
}];

php

//coming soon

cURL

# Value of 1 means true, this concept is present.
# Value of 0 means false, this concept is not present.
# Supported actions: overwrite, merge, remove.
curl -X PATCH \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "id": "{YOUR_INPUT_ID_1}",
        "data": {
          "concepts": [
            {
              "id": "tree",
              "value": 1
            },
            {
              "id": "water",
              "value": 0
            }
          ]
        }
      },
      {
        "id": "{YOUR_INPUT_ID_2}",
        "data": {
          "concepts": [
            {
              "id": "animal",
              "value": 1
            },
            {
              "id": "fruit",
              "value": 0
            }
          ]
        }
      }
    ],
    "action":"merge"
}'\
  https://api.clarifai.com/v2/inputs

Delete inputs

Delete concepts from an input

To remove concepts that were already added to an input, you can do this:

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse patchInputsResponse = stub.patchInputs(
    PatchInputsRequest.newBuilder()
        .setAction("remove")  // Supported actions: overwrite, merge, remove.
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID}")
                .setData(
                    Data.newBuilder()
                        .addConcepts(
                            // We're removing the concept, so there's no need to specify
                            // the concept value.
                            Concept.newBuilder().setId("tree")
                        )
                )
                .build()
        )
        .build()
);

if (patchInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Patch inputs failed, status: " + patchInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse patchInputsResponse = stub.patchInputs(
    PatchInputsRequest.newBuilder()
        .setAction("remove")  // Supported actions: overwrite, merge, remove.
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID}")
                .setData(
                    Data.newBuilder()
                        .addConcepts(
                            // We're removing the concept, so there's no need to specify
                            // the concept value.
                            Concept.newBuilder().setId("tree")
                        )
                )
                .build()
        )
        .build()
);

if (patchInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Patch inputs failed, status: " + patchInputsResponse.getStatus());
}

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

patch_inputs_response = stub.PatchInputs(
    service_pb2.PatchInputsRequest(
        action="remove",  # Supported actions: overwrite, merge, remove.
        inputs=[
            resources_pb2.Input(
                id="{YOUR_INPUT_ID}",
                data=resources_pb2.Data(
                    concepts=[
                        # We're removing the concept, so there's no need to specify
                        # the concept value.
                        resources_pb2.Concept(id="water"),
                    ]
                )
            )
        ]
    ),
    metadata=metadata
)

if patch_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Patch inputs failed, status: " + patch_inputs_response.status.description)

js

app.inputs.deleteConcepts([
  {
    id: "{id}",
    concepts: [
      {
        id: "tree"
      },
      {
        id: "water",
        value: false
      }
    ]
  },
])

// or if you have an input instance
app.inputs.get({id}).then(
  function(input) {
    input.deleteConcepts([
      {
        id: "tree",
        value: true
      },
      {
        id: "water",
        value: false
      }
    ])
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.inputs.delete_concepts({id}, concepts=['tree', 'water'])

java

client.removeConceptsForInput("{input_id}")
    .plus(
        Concept.forID("tree"),
        Concept.forID("water")
    )
    .executeSync();

csharp

using System.Collections.Generic;
using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.API.Requests.Models;
using Clarifai.DTOs.Predictions;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.ModifyInput(
                    "INPUT_ID",
                    ModifyAction.Remove,
                    positiveConcepts: new List<Concept> {new Concept("tree")},
                    negativeConcepts: new List<Concept> {new Concept("water")})
                .ExecuteAsync();
        }
    }
}

objective-c

ClarifaiConcept *concept = [[ClarifaiConcept alloc] initWithConceptName:@"cute cat"];
[app deleteConcepts:@[concept] forInputWithID:{id} completion:^(ClarifaiInput *input, NSError *error) {
    NSLog(@"input: %@", input);
}];

php

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ModifyAction;
use Clarifai\DTOs\Predictions\Concept;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->modifyInput('INPUT_ID', ModifyAction::remove())
    ->withPositiveConcepts([new Concept('tree')])
    ->withNegativeConcepts([new Concept('water')])
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

# We're removing the concept, so there's no need to specify
# the concept value.
curl -X PATCH \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "id":"{YOUR_INPUT_ID}",
        "data": {
            "concepts":[
                {"id":"water"}
            ]
        }
      }
    ],
    "action":"remove"
  }'\
  https://api.clarifai.com/v2/inputs/

Bulk delete concepts from a list of inputs

You can bulk delete multiple concepts from a list of inputs:

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse patchInputsResponse = stub.patchInputs(
    PatchInputsRequest.newBuilder()
        .setAction("remove")  // Supported actions: overwrite, merge, remove.
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID_1}")
                .setData(
                    Data.newBuilder()
                        // We're removing the concepts, so there's no need to specify
                        // the concept value.
                        .addConcepts(
                            Concept.newBuilder().setId("tree")
                        )
                        .addConcepts(
                            Concept.newBuilder().setId("water")
                        )
                )
                .build()
        )
        .addInputs(
            Input.newBuilder()
                .setId("{YOUR_INPUT_ID_2}")
                .setData(
                    Data.newBuilder()
                        .addConcepts(
                            Concept.newBuilder().setId("animal")
                        )
                        .addConcepts(
                            Concept.newBuilder().setId("fruit")
                        )
                )
                .build()
        )
        .build()
);

if (patchInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Patch inputs failed, status: " + patchInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.PatchInputs(
    {
        action: "remove",  // Supported actions: overwrite, merge, remove.
        inputs: [
            {
                id: "{YOUR_INPUT_ID_1}",
                // We're removing the concepts, so there's no need to specify
                // the concept value.
                data: {concepts: [{id: "tree"}, {id: "water"}]}
            },
            {
                id: "{YOUR_INPUT_ID_2}",
                data: {concepts: [{id: "animal"}, {id: "fruit"}]}
            },
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Patch inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

patch_inputs_response = stub.PatchInputs(
    service_pb2.PatchInputsRequest(
        action="remove",  # Supported actions: overwrite, merge, remove.
        inputs=[
            resources_pb2.Input(
                id="{YOUR_INPUT_ID_1}",
                data=resources_pb2.Data(
                    concepts=[
                        # We're removing the concepts, so there's no need to specify
                        # the concept value.
                        resources_pb2.Concept(id="tree"),
                        resources_pb2.Concept(id="water"),
                    ]
                )
            ),
            resources_pb2.Input(
                id="{YOUR_INPUT_ID_2}",
                data=resources_pb2.Data(
                    concepts=[
                        resources_pb2.Concept(id="animal"),
                        resources_pb2.Concept(id="fruit"),
                    ]
                )
            ),
        ]
    ),
    metadata=metadata
)

if patch_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Patch inputs failed, status: " + patch_inputs_response.status.description)

js

app.inputs.deleteConcepts([
  {
    id: "{id1}",
    concepts: [
      { id: "tree" },
      { id: "water" }
    ]
  },
  {
    id: "{id2}",
    concepts: [
      { id: "animal" },
      { id: "fruit" }
    ]
  }
]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

input_ids = ["{id1}", "{id2}"]
concept_pairs = [
                 ['tree', 'water'],
                 ['animal', 'fruit']
                ]
app.inputs.bulk_delete_concepts(input_ids, concept_pairs)

java

// Coming soon

csharp

// Coming soon

objective-c

ClarifaiConcept *concept = [[ClarifaiConcept alloc] initWithConceptName:@"cute cat"];
[app deleteConcepts:@[concept] forInputWithID:input_id completion:^(ClarifaiInput *input, NSError *error) {
    NSLog(@"input: %@", input);
}];

php

// Coming soon

cURL

# We're removing the concept, so there's no need to specify
# the concept value.
curl -X PATCH \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "id": "{YOUR_INPUT_ID_1}",
        "data": {
          "concepts":[
            {
              "id": "tree"
            },
            {
              "id": "water"
            }
          ]
        }
      },
      {
        "id": "{YOUR_INPUT_ID_2}",
        "data": {
          "concepts":[
            {
              "id": "animal"
            },
            {
              "id": "fruit"
            }
          ]
        }
      }
    ],
    "action":"remove"
  }'\
  https://api.clarifai.com/v2/inputs

Delete Input By Id

You can delete a single input by id:

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

BaseResponse deleteInputResponse = stub.deleteInput(
    DeleteInputRequest.newBuilder()
        .setInputId("{YOUR_INPUT_ID}")
        .build()
);

if (deleteInputResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Delete input failed, status: " + deleteInputResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.DeleteInput(
    {
        input_id: "{YOUR_INPUT_ID}"
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Delete input failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

delete_input_response = stub.DeleteInput(
    service_pb2.DeleteInputRequest(input_id="{YOUR_INPUT_ID}"),
    metadata=metadata
)

if delete_input_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Delete input failed, status: " + delete_input_response.status.description)

js

app.inputs.delete(INPUT_ID).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.inputs.delete("INPUT_ID")

java

client.deleteInput("INPUT_ID")
    .executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.DeleteInputs("INPUT_ID")
                .ExecuteAsync();
        }
    }
}

objective-c

[_app deleteInputsByIDList:@[INPUT_ID] completion:^(NSError *error) {
    NSLog(@"input has been deleted");
}];

php

use Clarifai\API\ClarifaiClient;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->deleteInputs('INPUT_ID')
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X DELETE \
  -H "Authorization: Key YOUR_API_KEY" \
  https://api.clarifai.com/v2/inputs/{YOUR_INPUT_ID}

Delete a list of inputs

You can also delete multiple inputs in one API call. This will happen asynchronously.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

BaseResponse listInputsResponse = stub.deleteInputs(
    DeleteInputsRequest.newBuilder()
        .addIds("{YOUR_INPUT_ID_1}")
        .addIds("{YOUR_INPUT_ID_2}")
        .build()
);

if (listInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Delete inputs failed, status: " + listInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.DeleteInputs(
    {
        ids: ["{YOUR_INPUT_ID_1}", "{YOUR_INPUT_ID_2}"]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Delete inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

delete_inputs_response = stub.DeleteInputs(
    service_pb2.DeleteInputsRequest(
        ids=["{YOUR_INPUT_ID_1}", "{YOUR_INPUT_ID_2}"]
    ),
    metadata=metadata
)

if delete_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Delete inputs failed, status: " + delete_inputs_response.status.description)

js

app.inputs.delete([{id1}, {id2}]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.delete(["{id1}", "{id2}"])

java

client.deleteInputsBatch()
    .plus("{id1}", "{id2}");
    .executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.DeleteInputs("{id1}", "{id2}")
                .ExecuteAsync();
        }
    }
}

objective-c

[_app deleteInputsByIDList:@[{id1}, {id2}] completion:^(NSError *error) {
    NSLog(@"inputs have been deleted");
}];

php

use Clarifai\API\ClarifaiClient;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->deleteInputs(['INPUT_ID1', 'INPUT_ID2'])
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X DELETE \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "ids":["{YOUR_INPUT_ID_1}","{YOUR_INPUT_ID_2}"]
  }'\
  https://api.clarifai.com/v2/inputs

Delete all inputs

If you would like to delete all inputs from an application, you can do that as well. This will happen asynchronously.

gRPC Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

BaseResponse listInputsResponse = stub.deleteInputs(
    DeleteInputsRequest.newBuilder()
        .setDeleteAll(true)
        .build()
);

if (listInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    throw new RuntimeException("Delete inputs failed, status: " + listInputsResponse.getStatus());
}

gRPC NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

stub.DeleteInputs(
    {
        delete_all: true
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Delete inputs failed, status: " + response.status.description);
        }
    }
);

gRPC Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

delete_inputs_response = stub.DeleteInputs(
    service_pb2.DeleteInputsRequest(
        delete_all=True
    ),
    metadata=metadata
)

if delete_inputs_response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Delete inputs failed, status: " + delete_inputs_response.status.description)

js

app.inputs.delete().then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

python

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

app.inputs.delete_all()

java

client.deleteAllInputs().executeSync();

csharp

using System.Threading.Tasks;
using Clarifai.API;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.DeleteAllInputs()
                .ExecuteAsync();
        }
    }
}

objective-c

[app deleteAllInputs:^(ClarifaiInput *input, NSError *error) {
  NSLog(@"all inputs have been deleted");
}];

php

use Clarifai\API\ClarifaiClient;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->deleteInputs([], true)
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

cURL

curl -X DELETE \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "delete_all": true
  }'\
  https://api.clarifai.com/v2/inputs