Integrate the Uncensored Mistral-Compatible API

Prerequisites: Install the Official SDK

Install the official SDK for your language to handle authentication and JSON parsing automatically.

Most developers prefer the standard library because it abstracts HTTP details. You will need Python 3.8+ or Node.js 18+ for best compatibility.

Set Your Base URL and Key

Configure your client to point at our base URL and inject your API key.

Use https://api.mistralapibaseurl.com/v1 as the base URL. Set the model to uncensored for unrestricted responses.

Retrieve your key from the dashboard after signing up with Google or email.

Basic Chat Completion Request

Send a simple text prompt to receive an immediate text response.

This works for roleplay, coding, or creative writing without content filters.

The response includes token usage for accurate billing.

Streaming Responses with SSE

Enable streaming to receive tokens in real-time as they are generated.

This reduces perceived latency for long outputs.

The last chunk contains the total token usage for billing.

Function Calling and JSON Mode

Use structured output for reliable data extraction or tool integration.

Set response_format to {"type": "json_object"} for strict JSON.

Define tools in the tools array for function calling workflows.

Handling Tokens and Limits

Monitor your usage to avoid service interruption.

The context window supports 100,000 tokens total. Max output is 16,000 tokens per request.

Rate limits are 300 requests per minute. Errors like 401 or 429 indicate auth or limit issues.

cURL

Copycurl https://api.mistralapibaseurl.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "List the top five rust crates for async web servers"}]
  }'

Python

Copyfrom openai import OpenAI

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