Clarifai API

Name: Clarifai API API
Brand: Clarifai API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLVisionapiKey14 EndpointsREST

For Agents

Run AI predictions against Clarifai vision and NLP models, manage inputs and concepts within an app, and execute multi-model workflows. Useful for any agent that needs image tagging, embeddings, or content moderation.

Connect the Clarifai API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Clarifai API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Install Jentic One Beta (Self-Hosted)

Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Clarifai API API.

Run a prediction against a Clarifai model and receive concept tags, regions, or embeddings

Pin a prediction to a specific model version for reproducible outputs

Create, list, get, and delete custom models within a Clarifai app

Add and manage inputs (images, video, text) used for indexing or training

GET STARTED

Start building with Clarifai API API

Explore with Jentic

View OpenAPI Document

Use for: I need to classify a set of images against the general model, Detect objects in this video frame and return bounding boxes, Search our Clarifai app for inputs similar to this sample, Run our custom moderation workflow on a new upload

Not supported: Does not handle pixel-level image editing, video transcoding, or large-scale model training pipelines — use for prediction, input management, semantic search, workflow execution, and concept management against Clarifai-hosted models only.

Jentic publishes the only available OpenAPI document for Clarifai API, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for this Clarifai API variant, keeping it validated and agent-ready. Clarifai is a computer vision and NLP platform offering pre-trained and custom models for image classification, object detection, text analysis, and embedding generation. This spec covers the v2 REST surface with the /v2 prefix on every path and camelCase path parameters (userId, appId, modelId), making it convenient for clients generated from this OpenAPI document. Authentication uses a Personal Access Token or API Key sent as 'Key {value}' in the Authorization header.

Use Cases

Patterns agents use Clarifai API API for, with concrete tasks.

★ Custom model lifecycle for visual quality inspection

A manufacturer trains a custom Clarifai model on examples of acceptable and defective parts, then calls POST /v2/users/{userId}/apps/{appId}/models to register the model and POST /v2/users/{userId}/apps/{appId}/models/{modelId}/outputs to run inference on each part photographed on the line. Versions can be deleted via DELETE on the model id when retired.

Create a custom model with the 'good' and 'defective' concepts, then run prediction on a new line photo and return the top concept

Content tagging and embedding for a media library

A media team uploads assets via POST /v2/users/{userId}/apps/{appId}/inputs and runs the general embedding model to tag each one. The embeddings power downstream semantic search through POST /v2/users/{userId}/apps/{appId}/searches. The team can list inputs and remove ones that should not be indexed via the matching DELETE endpoint.

Add 200 media assets as inputs, run general embeddings, and search for the top 5 nearest neighbours of a sample asset

Concept taxonomy management

Teams maintain a concept taxonomy that drives both labelling and prediction outputs. POST /v2/users/{userId}/apps/{appId}/concepts adds new concepts, GET lists the current taxonomy. Keeping the taxonomy explicit lets the application code rely on a stable label vocabulary rather than free-text tags.

Add three new concepts ('outdoor-furniture', 'indoor-furniture', 'lighting') to the app and verify they appear in GET /v2/users/{userId}/apps/{appId}/concepts

Agent integration via Jentic

Through Jentic, an agent can resolve intents like 'classify this image' or 'find similar inputs' to the right Clarifai endpoint, including the userId, appId, and modelId path parameters. The PAT or API key lives in the Jentic credential vault and is attached to the Authorization header only at execution time.

Search Jentic for 'run a Clarifai prediction', load the schema for POST /v2/users/{userId}/apps/{appId}/models/{modelId}/outputs, and execute it with the supplied image

Key Endpoints

14 endpoints — jentic publishes the only available openapi specification for this clarifai api variant, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/v2/users/{userId}/apps/{appId}/models/{modelId}/outputs

Run a prediction

POST

/v2/users/{userId}/apps/{appId}/models

Create a model

GET

/v2/users/{userId}/apps/{appId}/models

List models

POST

/v2/users/{userId}/apps/{appId}/inputs

Add inputs

GET

/v2/users/{userId}/apps/{appId}/inputs

List inputs

POST

/v2/users/{userId}/apps/{appId}/searches

Search inputs

POST

/v2/users/{userId}/apps/{appId}/workflows/{workflowId}/results

Run a workflow

POST

/v2/users/{userId}/apps/{appId}/concepts

Create concepts

POST

/v2/users/{userId}/apps/{appId}/models/{modelId}/outputs

Run a prediction

POST

/v2/users/{userId}/apps/{appId}/models

Create a model

GET

/v2/users/{userId}/apps/{appId}/models

List models

POST

/v2/users/{userId}/apps/{appId}/inputs

Add inputs

GET

/v2/users/{userId}/apps/{appId}/inputs

List inputs

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Clarifai PATs and API keys are stored encrypted in the Jentic vault and added to the Authorization header at execution time using the required 'Key {value}' format. The raw credential never enters the agent's prompt or logs.

Intent-based discovery

Agents search Jentic with intents like 'classify an image with Clarifai' or 'add inputs to a Clarifai app'. Jentic returns the matching v2 endpoint with its input schema, including the userId and appId placeholders.

Time to first call

Direct integration: 1-2 days to learn the userId/appId/modelId path scoping and the 'Key {value}' header format. Through Jentic: under 1 hour — search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Clarifai API (clarifai variant)

The sibling Clarifai spec covering the same REST surface with a different base URL and snake_case parameters.

Pick whichever spec variant matches the path casing the calling codebase already uses.

Complementary

Claid.ai Image Editing API

Claid handles pixel-level image edits that Clarifai then tags or indexes.

Use Claid to prepare assets and Clarifai to classify them when both transformation and recognition are needed.

Complementary

Civic Auth API

Civic Auth verifies the identity behind a content upload pipeline.

Use Civic Auth to gate uploads before Clarifai indexes them when verified-user provenance matters.

FAQs

Specific to using Clarifai API API through Jentic.

Why is there no official OpenAPI spec for the Clarifai API?

Clarifai publishes a gRPC-first reference and language SDKs rather than a maintained OpenAPI specification for the REST surface. Jentic generates and maintains this spec from the public REST documentation so AI agents and developers can call Clarifai through structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Clarifai API use?

Clarifai uses a Personal Access Token or API Key sent in the Authorization header in the format 'Key {your_pat_or_api_key}'. Through Jentic, the credential is stored encrypted in the credential vault and attached to outgoing requests only at execution time.

Can I create custom models with this API?

Yes. POST /v2/users/{userId}/apps/{appId}/models registers a new model, and predictions against it are issued at /v2/users/{userId}/apps/{appId}/models/{modelId}/outputs. Versions of the model are addressable via the /versions/{versionId}/outputs sub-path for reproducibility.

How do I run a workflow through Jentic?

Search Jentic for 'run a Clarifai workflow'. Jentic returns POST /v2/users/{userId}/apps/{appId}/workflows/{workflowId}/results with its input schema. Load the schema, supply userId, appId, workflowId, and the input data, and execute — the SDK handles the 'Key {pat}' Authorization header for you.

What is the difference between this spec and the 'clarifai' spec under the same vendor?

Both specs cover the Clarifai REST surface. This 'clarifai-api' variant uses a root base URL and includes /v2 in every path, with camelCase path parameters (userId, appId). The sibling 'clarifai' spec bakes /v2 into the base URL and uses snake_case parameters. Pick whichever matches the casing your codebase already uses.

Does this API support semantic search across my own inputs?

Yes. POST /v2/users/{userId}/apps/{appId}/searches accepts a query input and returns indexed inputs ranked by similarity. This is the standard primitive for visual search, near-duplicate detection, and 'find more like this' features once your inputs are indexed.