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Uncensored LLM API, pay per token.

$0.50trial credit

300requests per minute

API Reference & Quickstart

Get started with our uncensored LLM API in minutes. This guide covers authentication, endpoints, and streaming for your first request.

Authentication and Base URL

Authenticate by passing your API key in the Authorization header. Your base URL is https://api.chataisenzacensura.com/v1 for all requests. This setup works with any OpenAI-compatible client.

Important: You get one active key per account. Generating a new key immediately invalidates the previous one. No phone number is required for signup.

  • Use Bearer YOUR_API_KEY for authorization.
  • Keep your key secure; it grants full access to your prepaid credit.

Chat Completions Endpoint

Send text to the model using the standard chat completions endpoint. The model id is uncensored, tuned for raw output without arbitrary refusals. You can send up to 100,000 tokens in a single context window.

Constraint: The maximum output is 16,000 tokens per request. If you do not set max_tokens, the limit defaults to 2,048 tokens.

curl https://api.chataisenzacensura.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Generate a simple REST endpoint for user login"}]
  }'

Python SDK Integration

Use the official OpenAI Python SDK to interact with the API. Change the base_url and api_key to point to our service. This approach keeps your existing code structure intact while gaining access to uncensored responses.

Note: We do not offer embeddings, audio, or image generation. Stick to text-in, text-out workflows.

from openai import OpenAI

client = OpenAI(base_url="https://api.chataisenzacensura.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

Node SDK Integration

Integrate with Node.js by configuring the OpenAI package to use our base URL. This allows you to build chatbots or data pipelines that require unfiltered content generation. The SDK handles tokenization and request formatting automatically.

Tip: Ensure you are using the latest version of the OpenAI npm package for full compatibility with our streaming and tool-calling features.

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.chataisenzacensura.com/v1", apiKey: process.env.API_KEY });

const resp = await client.chat.completions.create({
  model: "uncensored",
  messages: [{ role: "user", content: "Draft a villain monologue for my game." }],
});
console.log(resp.choices[0].message.content);

Streaming and SSE

Enable real-time responses by setting stream: true. The API returns Server-Sent Events (SSE) with incremental chunks. Token usage details are included in the final chunk for accurate billing tracking.

Benefit: Streaming reduces perceived latency for long responses, especially useful for roleplay or extensive data generation tasks.

stream = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Tell the story in second person."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Rate Limits and Errors

You are limited to 300 requests per minute and 8 concurrent requests per key. If you exceed these limits, you receive a 429 error. A 401 error indicates an invalid or expired key, while 402 means your prepaid credit is exhausted.

Privacy: Prompts are not used for training. Errors and refusals are free, so you only pay for successful token usage.

FAQ

How do I debug missing citations in parallel chat API responses?

Ensure you are setting the correct <code>model</code> parameter to <code>uncensored</code>. Check that your concurrent request limit (8) is not causing timeouts, which can drop chunks in streaming mode. Verify that your client library correctly parses SSE events.

What is the context window size for the uncensored model?

The model supports a 100,000 token context window, combining prompt and completion. The maximum output per request is 16,000 tokens unless you specify a lower <code>max_tokens</code> value.

Can I use this API for NSFW content generation?

Yes, the model is tuned to answer without content refusals for lawful adult use. The only hard limit is sexual content involving minors, which is always refused. You can generate raw, unfiltered text for roleplay or creative writing.

Get your API key

Register, grab your key, and update your base URL. That’s it.

Try with trial credit