Clarifai Rust gRPC Client

This is the official Clarifai gRPC Rust client for interacting with our powerful recognition API. Clarifai provides a platform for data scientists, developers, researchers and enterprises to master the entire artificial intelligence lifecycle. Gather valuable business insights from images, video and text using computer vision and natural language processing.

• Try the Clarifai demo at: https://clarifai.com/demo
• Sign up for a free account at: https://portal.clarifai.com/signup
• Read the documentation at: https://docs.clarifai.com/

Installation

Add these dependencies to Cargo.toml: clarifai_grpc, protobuf and grpcio.

[dependencies]
clarifai_grpc = "*"
grpcio = "0.6.0"
protobuf = "2.0"

Getting started

Construct the V2Client object using which you'll access all the Clarifai API functionality, and a CallOption object that will be used for authentication.

use grpcio::{CallOption, MetadataBuilder};
use protobuf::{RepeatedField, SingularPtrField};

use clarifai_grpc::clarifai_channel;
use clarifai_grpc::grpc::resources::{Data, Image, Input};
use clarifai_grpc::grpc::service::PostModelOutputsRequest;
use clarifai_grpc::grpc::service_grpc::V2Client;
use clarifai_grpc::grpc::status_code::StatusCode;

let client = V2Client::new(clarifai_channel::grpc());

// Setup authentication.
let auth = "Key YOUR_CLARIFAI_API_KEY_OR_PAT".to_string();

let mut builder = MetadataBuilder::with_capacity(1);
builder.add_str("Authorization", &auth).unwrap();
let metadata = builder.build();
let call_opt = CallOption::default().headers(metadata);

Predict concepts in an image:

// This is a publicly available model.
const GENERAL_MODEL_ID: &str = "aaa03c23b3724a16a56b629203edc62c";

let request = PostModelOutputsRequest {
    model_id: GENERAL_MODEL_ID.to_string(),
    inputs: RepeatedField::from(vec![Input {
        data: SingularPtrField::some(Data {
            image: SingularPtrField::some(Image {
                url: "https://samples.clarifai.com/dog2.jpeg".to_string(),
                ..Default::default()
            }),
            ..Default::default()
        }),
        ..Default::default()
    }]),
    ..Default::default()
};
let response = client
    .post_model_outputs_opt(&request, call_opt)
    .expect("Failure");

let status = response.get_status();
if status.get_code() != StatusCode::SUCCESS {
    println!("Failure response:");
    println!("\t{:?}", status.get_code());
    println!("\t{}", status.get_description());
    println!("\t{}", status.get_details());
    std::process::exit(1);
}

println!("Predicted concepts:");
for concept in response.get_outputs()[0].get_data().get_concepts() {
    println!("\t{}: {}", concept.get_name(), concept.get_value());
}