Uncensored LLM API Documentation

Authentication and Base URL

Your API key authenticates every request. Use it in the Authorization header as a bearer token. The base URL for all endpoints is HTTPS://api.aichatbotunrestricted.com/v1. This URL works with official OpenAI SDKs if you configure the base_url parameter correctly. Generate your key instantly via Google or email on the dashboard. No phone verification is required. Keep your key secure, as it grants access to your prepaid credit. If you lose it, generate a new one which replaces the old active key. The system charges by actual token usage, so errors do not consume your balance.

Chat Completions Endpoint

Send messages to the chat completions endpoint. The model id is always uncensored. This model is tuned to answer without content refusals for lawful adult use. It is not GPT or Claude. You provide a list of message objects containing role and content. The API returns a text response in the choices array. Use the POST method for standard requests. This endpoint supports text-in, text-out interactions. It does not handle images or audio. Configure your client to use the correct base URL. The response includes token usage statistics for billing transparency.

Streaming Responses (SSE)

Enable streaming by setting stream to true in your request. The API returns Server-Sent Events (SSE) instead of a single JSON object. Each chunk contains partial data. The final chunk includes the complete token usage statistics. This approach reduces perceived latency for your users. It allows you to display text as it generates. Handle the stream events in your client code. Close the connection when the stream ends. This method is ideal for real-time chat interfaces. It provides a smoother user experience compared to waiting for the full response.

JSON Mode and Function Calling

Request structured output by setting response_format to {"type": "json_object"}. The model will return valid JSON instead of plain text. This is useful for parsing data or integrating with other systems. You can also use function calling to let the model invoke tools. Define your function schema in the tools parameter. The model decides when to call a function based on the context. Use tool_choice to control this behavior. Both features require careful prompt engineering. Ensure your JSON schema matches your application needs. Test thoroughly before deploying to production.

Parameters: Temperature, Top-p, and Seed

Control the model's creativity with temperature. Higher values produce more diverse outputs. Lower values make responses more deterministic. Use top_p for nucleus sampling. This limits the model to the most likely tokens. Set seed for reproducible results. This is useful for debugging. You can also set stop sequences to halt generation. Adjust presence_penalty and frequency_penalty to influence token repetition. These parameters allow fine-tuning of the output style. Experiment with different combinations to find the best fit for your use case.

Rate Limits and Quotas

Each API key allows 300 requests per minute. You can have 8 concurrent requests at any time. The maximum request body size is 8 MB. If you exceed the rate limit, you receive a 429 error. A 401 error indicates an invalid or missing API key. A 402 error means your prepaid credit is exhausted. Top up your credit via crypto to continue using the service. The context window is 100,000 tokens. This includes both prompt and completion tokens. Manage your token usage carefully to avoid unexpected charges. Errors do not consume credit.

cURL

Copycurl https://api.aichatbotunrestricted.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "list the steps to deploy this docker container"}]
  }'

Python

Copyfrom openai import OpenAI

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