Create, Get, Update, Delete

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
gRPC NodeJS
gRPC Python
js
python
java
csharp
objective-c
php
cURL
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
gRPC NodeJS
gRPC Python
js
python
java
csharp
objective-c
php
cURL
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
gRPC NodeJS
gRPC Python
Untitled
Untitled
python
java
csharp
objective-c
php
cURL
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)
Untitled

% tab title="js" %}

Untitled
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
gRPC NodeJS
gRPC Python
js
python
java
csharp
objective-c
php
cURL
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
gRPC NodeJS
gRPC Python
js
python
java
csharp
objective-c
php
cURL
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
gRPC NodeJS
gRPC Python
js
python
java
csharp
objective-c
php
cURL
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
gRPC NodeJS
gRPC Python
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