API Documentation

Authentication & Base URL

Use your API key with the base URL https://api.bestllmforporn.com/v1. Sign up with Google or email to get your key instantly. Pass it in the Authorization header.

POST /v1/chat/completions

Send your first request to generate text. Set the model to "uncensored". The API accepts standard chat messages.

Copycurl https://api.bestllmforporn.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Set server time to 2024"}]
  }'

Python SDK

Use the official OpenAI Python library. Configure the base URL and API key. This approach works for most Python projects.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.bestllmforporn.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

Install the OpenAI npm package. Initialize the client with the custom base URL. This method is ideal for server-side Node.js applications.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.bestllmforporn.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 & Token Usage

Enable streaming by setting stream: true. The API sends token usage details in the final chunk. This keeps memory usage low for long outputs.

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)

Limits, Errors & Context

Expect a 429 error if you exceed 300 requests per minute. A 402 error means you need more credit. The model supports a 100,000 token context window. Use max_tokens: 16000 for long outputs. Errors are free.