ModelPubSub Safe/Unsafe Image Classifier

Name: ModelPubSub Safe/Unsafe Image Classifier API
Brand: ModelPubSub Safe/Unsafe Image Classifier
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLVisionnone1 EndpointsREST

For Agents

Classify whether an uploaded image is safe or unsafe for work and return descriptive content tags via a single inference endpoint.

Install Jentic One Beta

Connect the ModelPubSub Safe/Unsafe Image Classifier to your agent

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

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: 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

Step 2: 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 ModelPubSub Safe/Unsafe Image Classifier API.

Score an uploaded image as safe or unsafe with a numeric confidence value

Return descriptive content tags such as 'nudity', 'violence', or 'neutral' for an image

Run NSFW screening on user-uploaded photos before they appear in a feed

GET STARTED

Start building with ModelPubSub Safe/Unsafe Image Classifier API

Explore with Jentic

View OpenAPI Document

Use Cases

Patterns agents use ModelPubSub Safe/Unsafe Image Classifier API for, with concrete tasks.

★ User Upload NSFW Screening

Screen profile pictures, post attachments, and chat media uploaded by end users to keep a community feed safe-for-work. The /api-v1.0/SafeUnsafeImageWithTags endpoint accepts a single image and returns a safety verdict along with descriptive tags, so moderation pipelines can auto-block, send to human review, or pass the upload through. Integration is typically a single HTTP call wrapped around an upload handler.

Submit a profile picture to /api-v1.0/SafeUnsafeImageWithTags and reject the upload if the response classifies it as unsafe

Chat Attachment Moderation

Run every image attachment in a chat or messaging app through the classifier before it is delivered to other users. The single-endpoint design keeps latency low and the response includes both a safe/unsafe label and tags that can drive richer policy decisions like 'block nudity but allow violence in news contexts'.

For each image sent in a chat thread, call the classifier and replace the image with a placeholder when the verdict is unsafe

Pre-Publication Content Triage with Jentic

Use a Jentic-connected agent to triage every image submitted to a content management system, calling the classifier and routing only borderline cases to human reviewers. The agent searches Jentic for the operation, loads the schema, and submits each image, freeing moderators to focus on edge cases instead of obvious safe content.

Process a folder of 50 incoming images, classify each with the API, and write a CSV with filename, verdict, and tags

Key Endpoints

1 endpoints — modelpubsub hosts the skymel safe/unsafe nsfw image classifier as a single-endpoint inference service that returns a safety score and content tags for a submitted image.

METHOD

PATH

DESCRIPTION

POST

/api-v1.0/SafeUnsafeImageWithTags

Classify an image as safe or unsafe and return tags

POST

/api-v1.0/SafeUnsafeImageWithTags

Classify an image as safe or unsafe and return tags

Why Jentic?

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

Credential isolation

Any deployment-level credentials for the ModelPubSub endpoint are stored encrypted in the Jentic vault (MAXsystem). Agents receive scoped execution access — raw credentials never enter the agent context.

Intent-based discovery

Agents search Jentic by intent (e.g., 'classify an image for NSFW') and Jentic returns the SafeUnsafeImageWithTags operation with its input schema, so the agent calls it without browsing docs.

Time to first call

Direct integration is fast given the single endpoint — typically under a day. Through Jentic: minutes to search, load schema, and execute the first classification.

FAQs

Specific to using ModelPubSub Safe/Unsafe Image Classifier API through Jentic.

What authentication does the ModelPubSub classifier use?

The OpenAPI spec exposes no security schemes — the /api-v1.0/SafeUnsafeImageWithTags endpoint is callable without authentication in the published interface. If access is restricted in practice through deployment-level controls, a client API key would be supplied at request time. Through Jentic, any future credential is stored in the encrypted vault and never enters the agent context.

Can I get content tags as well as a safe/unsafe verdict?

Yes. The single endpoint /api-v1.0/SafeUnsafeImageWithTags returns both a binary safe/unsafe classification and a list of descriptive tags such as 'nudity', 'partial nudity', or 'neutral' so downstream moderation policies can act on richer signals.

What are the rate limits for the ModelPubSub classifier?

The OpenAPI spec does not declare explicit rate limits. Practical throughput depends on the underlying ModelPubSub deployment of the Skymel model — agents should batch carefully and back off on 429 or 503 responses.

How do I classify an image through Jentic?

Run pip install jentic, search for 'classify an image as safe or unsafe', and Jentic returns the POST /api-v1.0/SafeUnsafeImageWithTags operation with its input schema. Load the schema, pass the image payload, and execute. The agent receives the verdict and tags directly.

Is the ModelPubSub classifier suitable for real-time chat moderation?

Yes for low-volume chat. The classifier is a single inference call so latency is bounded by network round-trip plus model inference time. High-throughput chat platforms should benchmark p95 latency under expected load before using it on the hot path.