快速開始
1. 建立金鑰並選擇模型
在控制台建立金鑰。設定下方環境變數,用該金鑰查詢目錄,選擇 supported_endpoints 包含 /v1/chat/completions 的模型,將其 ID 設為 LAZU_MODEL。目錄說明存取範圍與能力,不代表一次真實上游請求一定成功。
export LAZU_API_ORIGIN="https://api.lazu.ai"
export LAZU_API_KEY="YOUR_LAZU_KEY"
curl --fail-with-body "$LAZU_API_ORIGIN/api/models/catalog" \
-H "Authorization: Bearer $LAZU_API_KEY"
export LAZU_MODEL="MODEL_ID_FROM_CATALOG"2. 發起請求
直接發送 HTTP 請求時,LAZU_API_ORIGIN 是不含 /v1 的網域位址;OpenAI SDK 的 base URL 需在其後加 /v1。自架部署請替換為自己的位址。
# Requires jq. Inspect response headers in response.headers.
jq -n --arg model "$LAZU_MODEL" \
'{model: $model, messages: [{role: "user", content: "Hello"}]}' \
| curl --fail-with-body -D response.headers \
"$LAZU_API_ORIGIN/v1/chat/completions" \
-H "Authorization: Bearer $LAZU_API_KEY" \
-H "Content-Type: application/json" --data-binary @-Python
python -m pip install openaiimport os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["LAZU_API_KEY"],
base_url=os.environ["LAZU_API_ORIGIN"].rstrip("/") + "/v1",
)
response = client.chat.completions.create(
model=os.environ["LAZU_MODEL"],
messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)TypeScript
npm install openaiimport OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.LAZU_API_KEY,
baseURL: `${process.env.LAZU_API_ORIGIN}/v1`,
});
const response = await client.chat.completions.create({
model: process.env.LAZU_MODEL!,
messages: [{ role: "user", content: "Hello" }],
});
console.log(response.choices[0].message.content);3. 查看結果與用量
讀取回傳文字並保存回應標頭的 X-Request-Id。在控制台「用量與日誌」找到請求,核對用量與費用;也可用同一金鑰呼叫 GET /api/usage/requests/{request_id}。不要將上游回應本文的 ID 直接當成 Lazu 請求 ID。