GitHub Uncensored AI API Reference

Authentication & Base URL

The API requires a bearer token for every request. You generate this key instantly via the dashboard using Google or email credentials. Once created, the key authenticates your prepaid account against the hosted model.

Set your base URL to point directly to our API gateway. This ensures all requests route to the correct uncensored model server.

Use the standard Authorization header with the Bearer scheme. Replace the placeholder with your unique key string.

Base Configuration

• Base URL: https://api.githubuncensoredai.com/v1
• Auth Header: Authorization: Bearer YOUR_API_KEY
• Model ID: uncensored

Copycurl https://api.githubuncensoredai.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "Fix the syntax error in this python loop"}]
  }'

Chat Completions Endpoint

Send text data to the chat completions endpoint and receive generated text in response. The system accepts a list of messages with roles like user or assistant. It returns a completion based on the prompt history.

This endpoint handles standard conversation flows. You can send multiple turns, and the model maintains context up to the limit. It does not support images, audio, or video inputs. The response format is standard JSON.

Ensure your payload includes the model identifier. The system ignores unknown fields gracefully. Errors return specific codes if authentication fails or credits run out.

Copyfrom openai import OpenAI

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

Streaming Responses

Enable streaming by setting the stream flag to true. The API returns a series of Server-Sent Events instead of a single JSON object. Each event contains a chunk of the generated text.

This approach reduces perceived latency for long responses. You can start displaying text to users as it is generated. The final chunk includes the token usage statistics for billing.

Handle the stream efficiently in your client code. Close the connection when the stream ends or an error occurs. This method works well for real-time chat interfaces.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.githubuncensoredai.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);

Function Calling & JSON Mode

The model supports structured output via function calling. Define tools in your request with names, descriptions, and parameter schemas. The model selects the appropriate tool and generates arguments.

Use JSON mode for strict schema compliance. Set the response format to json_object to force valid JSON output. This is useful for parsing data or generating code snippets.

Combine function calling with streaming for interactive experiences. The model can invoke multiple tools in sequence. Validate the output schema before executing functions in your application logic.

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)

Parameters & Limits

Control generation behavior with parameters like temperature and top_p. Adjust these values to balance creativity and determinism. The default settings work for most general purposes.

Respect the request limits to avoid errors. You can send up to 300 requests per minute per key. Concurrent requests are capped at eight per key. The maximum request body size is 8 MB.

The context window spans 100,000 tokens. This includes both prompt and completion tokens. Output is limited to 16,000 tokens per request. Exceeding these limits returns an error code.

Token Usage & Billing

Billing is prepaid and based on actual token usage. Input tokens cost $0.15 per million, and output tokens cost $0.50 per million. Errors and refusals do not consume credits.

Credit never expires. Top-ups are processed via crypto only. You receive bonus credit for larger deposits. The system tracks usage accurately for each API key.

Monitor your balance through the dashboard. If credits run low, your requests will fail with a specific error code. Add funds instantly to resume service without waiting for approvals.