OpenAI 相容 API 文件
幾分鐘內即可使用標準 OpenAI 相容客戶端開始使用我們的無審查 LLM API。此快速入門指南將引導您完成身份驗證、首次請求以及串流設定。
驗證與 Base URL
在儀表板生成您的金鑰。使用 HTTPS://api.keyapiseekdeep.com/v1 作為基礎 URL,並在 Authorization 標頭中傳遞您的金鑰。此設定適用於任何標準 SDK。
curl https://api.keyapiseekdeep.com/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "uncensored",
"messages": [{"role": "user", "content": "What is my API key expiration date"}]
}'您的金鑰為帳戶專屬,產生新金鑰後,舊金鑰會立即失效。
首次使用 Python 的請求
使用官方 Python SDK 發送文字完成請求。將您的基礎 URL 設定為我們的端點,並使用模型 ID "uncensored"。
from openai import OpenAI
client = OpenAI(base_url="https://api.keyapiseekdeep.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)此請求發送簡單的提示詞並回傳生成的文字。不需要複雜的設定。
Node.js
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.keyapiseekdeep.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
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)