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's pre-trained or custom vision and language models, manage the inputs and concepts in an app, and execute multi-step workflows. Useful for any agent that needs vision tagging, embedding generation, 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, bounding boxes, or embeddings

Pin a prediction to a specific model version for reproducible outputs

Add, list, and remove inputs (images, video, text) within a Clarifai app

Run semantic search over indexed inputs to find visually or conceptually similar items

GET STARTED

Start building with Clarifai API API

Explore with Jentic

View OpenAPI Document

Use for: I need to detect objects in this product photo with a Clarifai model, Classify a batch of moderation candidates against the NSFW model, Search our app's input index for images similar to a sample upload, Run our chained tagging workflow on a new asset

Not supported: Does not handle pixel-level image editing, video transcoding, or model training pipelines — use for prediction, input management, semantic search, and workflow execution 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 that runs pre-trained and custom AI models for image recognition, object detection, face detection, text classification, and embedding generation. This spec covers the v2 prediction surface — model inference, input management, semantic search, workflow execution, and concept management — scoped under a user_id and app_id pair so each request is namespaced to the right application. Authentication uses a Personal Access Token in the Authorization header.

Use Cases

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

★ Image moderation pipeline for user-generated content

A marketplace runs every uploaded photo through a Clarifai moderation model by calling POST /users/{user_id}/apps/{app_id}/models/{model_id}/outputs with the image URL. Predictions returning unsafe concepts are routed to a human review queue, while clean inputs are added to the app's index via POST /users/{user_id}/apps/{app_id}/inputs for later semantic search.

POST a moderation prediction for a new upload, and if any unsafe concept exceeds 0.8, queue the asset for review

Visual search for product catalogues

An ecommerce team indexes the product catalogue as Clarifai inputs, then exposes a 'shop the look' feature backed by POST /users/{user_id}/apps/{app_id}/searches. The search request takes a sample image and returns visually similar items from the indexed corpus. Pinning predictions to a specific model version keeps embeddings consistent across reindexes.

Index 1,000 product images as Clarifai inputs, then search the index with a customer-uploaded photo and return top 10 matches

Custom workflow for multi-step tagging

Teams that need more than a single model output build a Clarifai workflow that chains general tagging, brand detection, and demographic estimation, then run it with POST /users/{user_id}/apps/{app_id}/workflows/{workflow_id}/results. One API call returns the combined output, which simplifies the calling agent's parsing and reduces network round-trips.

Run a workflow that tags an image, detects brand logos, and estimates demographics, then return the merged output

Agent integration via Jentic

Through Jentic, an agent can resolve intents like 'tag this image with general concepts' to the right Clarifai prediction endpoint, including the user_id, app_id, and model_id path parameters that scope the request. The PAT is stored in the Jentic credential vault and only injected at execution time.

Search Jentic for 'predict concepts in an image', load the schema for the prediction endpoint, and execute it with the supplied image URL

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

/users/{user_id}/apps/{app_id}/models/{model_id}/outputs

Run a prediction against a model

POST

/users/{user_id}/apps/{app_id}/inputs

Add inputs to the app

GET

/users/{user_id}/apps/{app_id}/inputs

List inputs

POST

/users/{user_id}/apps/{app_id}/searches

Search inputs

GET

/users/{user_id}/apps/{app_id}/models

List models

POST

/users/{user_id}/apps/{app_id}/workflows/{workflow_id}/results

Run a workflow

GET

/users/{user_id}/apps/{app_id}/concepts

List concepts

POST

/users/{user_id}/apps/{app_id}/concepts

Add concepts

POST

/users/{user_id}/apps/{app_id}/models/{model_id}/outputs

Run a prediction against a model

POST

/users/{user_id}/apps/{app_id}/inputs

Add inputs to the app

GET

/users/{user_id}/apps/{app_id}/inputs

List inputs

POST

/users/{user_id}/apps/{app_id}/searches

Search inputs

GET

/users/{user_id}/apps/{app_id}/models

List models

Why though Jentic?

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

Credential isolation

Clarifai Personal Access Tokens are stored encrypted in the Jentic vault and added to the Authorization header at execution time using the required 'Key {PAT}' format. The agent receives a scoped reference, never the raw PAT.

Intent-based discovery

Agents search Jentic with intents like 'predict objects in an image' or 'search a Clarifai app for similar inputs'. Jentic returns the matching prediction or search endpoint with its input schema, including the user_id and app_id placeholders.

Time to first call

Direct integration: 1-2 days to learn the user_id/app_id/model_id path scoping and the 'Key {PAT}' 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-api variant)

The sibling Clarifai spec covering the same REST surface with a slightly different base URL and parameter naming.

Pick the variant whose path parameter casing matches the codebase already calling Clarifai.

Complementary

Claid.ai Image Editing API

Claid edits and reformats the images that Clarifai then classifies or indexes.

Pair Claid (editing) with Clarifai (recognition) when assets need both pixel-level transformation and content understanding.

Complementary

Civic Auth API

Civic Auth verifies the user identity that owns the assets being submitted to Clarifai.

Use Civic Auth ahead of Clarifai when uploads must be tied to a verified wallet or person.

FAQs

Specific to using Clarifai API API through Jentic.

Why is there no official OpenAPI spec for this Clarifai API variant?

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 sent in the Authorization header with the format 'Key YOUR_PAT_HERE'. PATs are issued from https://clarifai.com/settings/security. Through Jentic, the PAT is stored encrypted in the credential vault and injected at execution time.

Can I run predictions against my own custom Clarifai models?

Yes. The prediction endpoint at /users/{user_id}/apps/{app_id}/models/{model_id}/outputs takes whichever model_id you target, including custom models trained in your app. To pin output stability, point to a specific version with /models/{model_id}/versions/{model_version_id}/outputs.

How do I run a Clarifai prediction through Jentic?

Search Jentic for 'predict concepts in an image'. Jentic returns POST /users/{user_id}/apps/{app_id}/models/{model_id}/outputs with its input schema. Load the schema, supply user_id, app_id, model_id, and the image data, and execute — the SDK handles the PAT header for you.

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

Both specs cover the Clarifai REST surface; this 'clarifai' spec uses a base URL with the /v2 prefix already applied and slightly different path parameter casing (user_id vs userId). Pick whichever matches the codebase you are integrating from — both are kept in the catalogue for compatibility with existing integrations.

Does the search endpoint do semantic similarity?

Yes. POST /users/{user_id}/apps/{app_id}/searches performs semantic search over inputs that have been indexed in the app, returning items ranked by similarity to the query input. It is the standard primitive for visual search, deduplication, and 'similar items' features.