How does the uncensored AI API handle content?

The model does not refuse lawful adult, fictional, or controversial topics. It only blocks sexual content involving minors. Responses are direct without standard corporate filtering. This applies to all requests sent to the endpoint.

What happens if I hit the rate limit?

You receive a 429 Too Many Requests error. You can retry after a short delay. The limit is 300 requests per minute per key. Concurrency is restricted to 8 simultaneous connections. Adjust your client logic to handle these constraints gracefully.

Does the uncensored LLM online service store my prompts?

Prompts are not used for training your data. We store minimal data for billing purposes. Your account requires only an email address. No phone number or personal details are necessary for API access. Privacy is maintained by design.

API 文件 | Set It Uncensored

驗證與金鑰

驗證簡單且即時。透過 Google 或電子郵件註冊後，您將獲得單一 API 金鑰。將此金鑰傳遞到 Authorization header 作為 bearer token。此金鑰識別您的預付餘額並執行您的請求限制。透過在儀表板產生新金鑰來輪替金鑰；舊金鑰會立即停止運作。

聊天完成端點

向 /v1/chat/completions 端點。模型 ID 為 uncensored. 它接受標準 OpenAI 訊息結構並回傳原始文字回應。缺少餘額的錯誤回傳 402，無效金鑰回傳 401。使用此端點進行標準文字生成任務。

curl https://api.setituncensored.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "What is the capital of France."}]
  }'

Python SDK

直接使用官方 OpenAI Python 函式庫。將 base URL 配置為指向我們的伺服器。傳遞您的 API key 與模型 ID。此方法適用於期望 OpenAI 相容性的現有客戶端程式碼。調整參數如 temperature 用於控制隨機性。串流傳輸透過 stream flag。

from openai import OpenAI

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

使用 openai 服務器端集成的 Node.js 包。設置 baseURL 連接到我們的 API 端點。使用您的 API 金鑰初始化客戶端。傳送訊息並處理回應物件。此設定可讓您輕鬆地在 Node 應用程式中嵌入 uncensored 文字生成。以程式化方式管理 token 並處理錯誤。

import OpenAI from "openai";

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

串流回應

在請求主體中將 stream: true 在你的請求中。你收到伺服器發送的事件（SSE）區塊。每個區塊包含部分文字 token。最後一個區塊包含用於計數的使用統計數據。此方法可降低長回應的感知延遲。它非常適合網頁應用程式中的即時 UI 更新。

stream = 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)

限制、錯誤與上下文

上下文視窗支援 100,000 個 token 總量。每次請求的最大輸出為 16,000 個 token。您每分鐘限 300 次請求。每個金鑰的併發請求上限為 8 個同時請求。超過 8 MB 的請求將被拒絕。透過實施指數退避來處理 429 錯誤。餘額僅根據實際 token 用量計費。

API 文件