NLP Cloud API

Name: NLP Cloud API
Brand: NLP Cloud API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLLanguage Modelsbearer23 EndpointsREST

For Agents

Run NLP and generative AI inference — text generation, classification, summarization, embeddings, ASR, and image generation — through a uniform per-model REST surface.

Install Jentic One Beta

Connect the NLP Cloud API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the NLP Cloud 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.

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 NLP Cloud API.

Generate completions or chat responses from any selected model via /{model}/generation or /{model}/chatbot

Classify text into custom labels and detect intents through /{model}/classification and /{model}/intent-classification

Extract named entities, keywords, and dependencies from a passage in a single call

GET STARTED

Start building with NLP Cloud API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI specification for NLP Cloud API, keeping it validated and agent-ready. NLP Cloud serves pretrained and custom models for text generation, classification, summarization, paraphrasing, named entity recognition, embeddings, semantic search, speech-to-text, and image generation behind a uniform per-model REST surface. Each operation is parameterized by a model slug, so an agent can swap between models like dolphin, fine-tuned LLaMA variants, or custom fine-tunes without changing the call shape. Both general-purpose and language-specific models are exposed, with GDPR-compliant inference hosted in the EU and US.

Use Cases

Patterns agents use NLP Cloud API for, with concrete tasks.

★ Multilingual Content Pipeline

Marketing and support teams need to translate, summarize, and rewrite content across languages without standing up a separate model stack for each task. The NLP Cloud per-model endpoints expose translation, summarization, paraphrasing, and grammar correction as parallel calls so a single workflow can transform an English brief into French ad copy with a localized summary. EU-hosted models keep the data within GDPR boundaries.

Call /{model}/translation with source 'en', target 'fr' and the input text, then pass the result to /{model}/summarization to produce a 2-sentence French summary

Semantic Search over Internal Docs

Building retrieval-augmented agents requires reliable embeddings and a fast classification step to route queries. The /{model}/embeddings endpoint produces vectors for documents and queries, while /{model}/semantic-search returns ranked matches over a passed-in corpus. Combined with /{model}/intent-classification, a customer-support agent can route a question to the right knowledge base before fetching the top passages.

Generate embeddings for a list of FAQ entries via /{model}/embeddings, then call /{model}/semantic-search with the user query and the corpus to return the top 3 matches

Voice-Enabled Assistant

Voice-driven agents need both accurate transcription and natural-sounding playback. NLP Cloud's /{model}/asr endpoint transcribes audio and /{model}/speech-synthesis renders text to speech using selectable voice models. With the same auth and request shape, a single agent can capture user audio, transcribe, reason over the text, and reply in voice without integrating two vendors.

Send an audio URL to /{model}/asr, take the transcript and pass it to /{model}/generation to draft a reply, then call /{model}/speech-synthesis to render the reply

AI Agent NLP Toolbelt

An LLM-powered agent often needs lightweight NLP tasks — entity extraction, language detection, classification — without invoking a full LLM call for each. Through Jentic, the agent searches for 'extract named entities from text', receives the NLP Cloud operation schema, and runs it as a fast, deterministic step in its toolchain. The bearer token stays in the Jentic vault and never enters the agent's context.

Use Jentic to call /{model}/entities with a customer email body and parse the returned entity spans into a structured ticket

Key Endpoints

23 endpoints — jentic publishes the only available openapi specification for nlp cloud api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/{model}/generation

Generate text from a prompt with the selected model

POST

/{model}/chatbot

Run a chat-style turn with conversation history

POST

/{model}/embeddings

Generate vector embeddings for input text

POST

/{model}/semantic-search

Rank a passed-in corpus against a query

POST

/{model}/entities

Extract named entities from text

POST

/{model}/translation

Translate text between supported languages

POST

/{model}/asr

Transcribe audio to text

POST

/{model}/speech-synthesis

Synthesize speech audio from text

POST

/{model}/generation

Generate text from a prompt with the selected model

POST

/{model}/chatbot

Run a chat-style turn with conversation history

POST

/{model}/embeddings

Generate vector embeddings for input text

POST

/{model}/semantic-search

Rank a passed-in corpus against a query

POST

/{model}/entities

Extract named entities from text

Why Jentic?

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

Credential isolation

NLP Cloud bearer tokens are stored encrypted in the Jentic vault. Agents receive scoped access — the raw token never enters the agent context, and rotation is handled by Jentic without code changes.

Intent-based discovery

Agents search by intent (e.g. 'extract entities from text') and Jentic returns the matching NLP Cloud operation with its model parameter and input schema, so the agent picks the right endpoint without reading docs.

Time to first call

Direct integration: 1-3 days to wire bearer auth, model selection, and per-task request shapes across multiple NLP tasks. Through Jentic: under 1 hour — search, load, execute.

FAQs

Specific to using NLP Cloud API through Jentic.

Why is there no official OpenAPI spec for NLP Cloud API?

NLP Cloud does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call NLP Cloud API via 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 NLP Cloud API use?

NLP Cloud uses HTTP bearer authentication. Pass your API token from the NLP Cloud dashboard in the Authorization header as 'Bearer <token>'. Through Jentic the token sits encrypted in the vault and the agent receives only a scoped reference.

Can I run a custom fine-tuned model with the NLP Cloud API?

Yes. Every endpoint is parameterized by a {model} path segment. Pass the slug of your fine-tuned model (for example a custom LLaMA variant) and the request shape stays identical to the pretrained equivalent.

What are the rate limits for the NLP Cloud API?

Limits depend on the subscribed plan and selected model — typically tens to hundreds of requests per minute. The spec does not declare hard limits; check the NLP Cloud pricing page for current per-plan numbers, and Jentic will surface 429 responses with backoff.

How do I generate text with the NLP Cloud API through Jentic?

Run pip install jentic, then search Jentic for 'generate text from a prompt'. Jentic returns the /{model}/generation operation; load the schema, fill in the model slug and prompt, and execute. The bearer token is injected by Jentic at call time.

Does NLP Cloud support image generation?

Yes. The /{model}/image-generation endpoint accepts a prompt and returns generated images using the selected image model. Use it alongside text-to-text endpoints in the same workflow without changing auth or request structure.

NLP Cloud API

Connect the NLP Cloud API to your agent

Capabilities

Start building with NLP Cloud API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs