API Documentation

Authentication

Send your API key in the Authorization header. No complex OAuth flows or subscription locks apply here. You get a key immediately after signing up with Google or an email. Errors like 401 indicate an invalid or missing key, while 402 means your prepaid credit is exhausted.

Chat Completions Endpoint

Send requests to POST /v1/chat/completions. This is the standard endpoint for text generation. Use the model ID uncensored to access our specific open-weight model. It answers without content refusals for lawful adult use, though it still blocks sexual content involving minors. Here is how you send a basic request:

Copycurl https://api.ollamauncensoredmodel.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Run the python script and show output"}]
  }'

Python SDK

Use the official openai Python library. Point it to our base URL and provide your key. This allows you to keep your existing logic intact while swapping in our uncensored backend. You do not need to install extra drivers or manage local GPU memory.

Copyfrom openai import OpenAI

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

Initialize the client with the correct base URL. This works with any OpenAI-compatible SDK. The model ID remains uncensored. You can stream responses or process them synchronously. This approach eliminates the need for proxy routing or complex local setups.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.ollamauncensoredmodel.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 server sends Server-Sent Events (SSE). Token usage details appear in the final chunk of the stream. This lets you track costs in real-time. You can also use temperature, top_p, and stop parameters to control the output.

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 Window

The context window supports 100,000 tokens total. You can output up to 16,000 tokens per request, or 2,048 if max_tokens is unset. Rate limits are 300 requests per minute per key. A 429 error means you hit this limit. Keep requests under 8 MB and limit concurrent connections to 8 per key.