Clarifai/clarifai-csharp-grpc
C#
Captured source
source ↗Clarifai/clarifai-csharp-grpc
Description: Clarifai gRPC C# client
Language: C#
License: NOASSERTION
Stars: 5
Forks: 0
Open issues: 0
Created: 2019-10-25T14:04:31Z
Pushed: 2026-05-29T16:05:58Z
Default branch: master
Fork: no
Archived: no
README: !image
Clarifai C# gRPC Client
This is the official Clarifai gRPC C# 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
Install it via the NuGet Package Manager by searching for ClarifaiGrpc, or use one of the commands below.
dotnet add package ClarifaiGrpc Install-Package ClarifaiGrpc
Versioning
This library doesn't use semantic versioning. The first two version numbers (X.Y out of X.Y.Z) follow the API (backend) versioning, and whenever the API gets updated, this library follows it.
The third version number (Z out of X.Y.Z) is used by this library for any independent releases of library-specific improvements and bug fixes.
Getting started
Construct the client and setup your API key or Personal Access Token in the metadata variable.
using System;
using System.Collections.Generic;
using Clarifai.Api;
using Clarifai.Channels;
using Grpc.Core;
using StatusCode = Clarifai.Api.Status.StatusCode;
var client = new V2.V2Client(ClarifaiChannel.Grpc());
var metadata = new Metadata
{
{"Authorization", "Key {YOUR_PERSONAL_TOKEN}"}
};Predict concepts in an image:
var response = client.PostModelOutputs(
new PostModelOutputsRequest()
{
UserAppId =
new UserAppIDSet()
{
UserId = "{YOUR_USER_ID}",
AppId = "{YOUR_APP_ID}"
},
ModelId = "aaa03c23b3724a16a56b629203edc62c", // ()
{
new Input()
{
Data = new Data()
{
Image = new Image()
{
Url = "https://samples.clarifai.com/dog2.jpeg"
}
}
}
}
}
},
metadata
);
if (response.Status.Code != StatusCode.Success)
throw new Exception("Request failed, response: " + response);
Console.WriteLine("Predicted concepts:");
foreach (var concept in response.Outputs[0].Data.Concepts)
{
Console.WriteLine($"{concept.Name, 15} {concept.Value:0.00}");
}Excerpt shown — open the source for the full document.