API Documentation

Authentication & Base URL

The base URL for all requests is https://api.cheapopenaiapi.com/v1. Pass your API key in the Authorization header as a Bearer token. Generate your key instantly via the Get API key page using Google or email.

Chat Completions Endpoint

Send text to the model via POST /v1/chat/completions. The endpoint accepts standard message arrays and returns generated text. We support function calling, JSON mode, and streaming. Only the uncensored model is available for inference.

This is a drop-in replacement for standard LLM calls. Input and output tokens are billed separately at transparent rates.

Streaming Responses (SSE)

Enable streaming by setting stream: true. The API returns Server-Sent Events (SSE). Token usage details appear in the final chunk of the stream.

Stream responses allow you to display text as it generates, reducing perceived latency for users waiting for long outputs.

Supported Parameters

Use standard parameters like temperature, top_p, stop, seed, presence_penalty, and frequency_penalty. Set response_format to {"type": "json_object"} for structured outputs.

The model has a 100,000-token context window and a max output of 16,000 tokens per request.

Python SDK Integration

Install the official OpenAI library. Configure the client with our base URL and your API key. Make a simple chat request to test connectivity.

The Python SDK handles serialization and retries automatically. This makes integration fast for backend services.

Node.js & Streaming

Use the Node.js SDK for server-side integrations. Set the baseURL property to our endpoint. Handle streaming data using async iterators.

Node.js developers can pipe streaming data directly to their responses. This ensures low-latency delivery for real-time applications.

cURL

Copycurl https://api.cheapopenaiapi.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "fetch user profile for id 9921"}]
  }'

Python

Copyfrom openai import OpenAI

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