API Documentation

Base URL and Authentication

The base URL is https://api.aiwithoutfilters.com/v1. Pass your key in the Authorization header as Bearer YOUR_API_KEY. You get one key per account, created instantly via Google or email. This endpoint returns your available model IDs and confirms your authentication status without consuming credits.

First Request

Send a standard chat completion request to POST /v1/chat/completions. The model ID is uncensored. This endpoint handles text-in, text-out interactions with no extra baggage.

Here is a basic curl example to test your connection and see the model respond to a simple prompt.

Cost: Input tokens are charged at $0.15 per 1M tokens. Output tokens cost $0.50 per 1M tokens.

Copycurl https://api.aiwithoutfilters.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "List all active ports on localhost using curl"}]
  }'

Python SDK Integration

Use the official OpenAI Python SDK to interact with our API. Set the base_url and api_key before making calls. This allows you to keep your existing code structure while switching the backend model.

The following snippet demonstrates how to configure the client and send a message to the uncensored model.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.aiwithoutfilters.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.js

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.aiwithoutfilters.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

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)