NSFW Video API Documentation

Base URL and Authentication

The NSFW Video API uses standard OpenAI-compatible endpoints. Your base URL is https://api.nsfwvideoapi.com/v1. To authenticate, include your API key in the Authorization header as a Bearer token. You can generate a key on the Get API key page using just an email and password. No phone number or credit card is required to start. The key is shown immediately after signup. If you need a fresh key, you can regenerate it at any time, which instantly revokes the old one. This keeps your integration simple and secure.

First Request

Send a POST request to /v1/chat/completions with the model ID uncensored. This model is tuned for adult content and does not refuse lawful topics. The following example demonstrates a basic text completion using cURL. Replace YOUR_API_KEY with your actual key.

Copycurl https://api.nsfwvideoapi.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Write a blunt product review of a cheap VPN."}]
  }'

The response returns the generated text in choices[0].message.content. You can also check available models using GET /v1/models. This confirms the API is responding correctly before you integrate deeper into your pipeline.

Python SDK Integration

Use the official OpenAI Python SDK to interact with the NSFW Video API. Set the base URL to our endpoint and provide your API key. The following code snippet shows how to initialize the client and send a prompt. This approach works with any standard OpenAI-compatible client library.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.nsfwvideoapi.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)

Ensure you handle the response object to extract the generated content. This method is ideal for backend services where you need structured data processing. The model ID remains uncensored for all requests.

Node.js SDK Usage

For Node.js environments, use the openai npm package. Configure the client with the correct base URL and your API key. The code below demonstrates a simple chat completion request. This is useful for serverless functions or web servers handling NSFW text generation tasks.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.nsfwvideoapi.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);

The response structure matches the OpenAI format. You can parse the content and pass it to your application logic. Remember that the model does not perform image or video generation; it is a pure text API.

Streaming with SSE

Enable streaming by setting stream: true in your request. The API returns Server-Sent Events (SSE) for real-time token delivery. This reduces perceived latency for users. The following example shows how to handle streaming responses in Node.js.

Copystream = 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)

Process each chunk as it arrives. This is critical for chat interfaces where users expect immediate feedback. The streaming works with all OpenAI-compatible SDKs that support SSE. Note that streaming does not affect pricing or token counting.

Rate Limits, Errors, and Context

You are limited to 300 requests per minute per API key. The maximum request body size is 8 MB. Common errors include 401 for invalid keys and 402 if your prepaid credit is exhausted. Upgrade your credit from the dashboard to continue. The context window is 64,000 tokens for prompt and completion combined. If you exceed the limit, the API returns a 429 error. Plan your token usage carefully to avoid interruptions.