Endpoint 涵蓋範圍
開放 2 個公開 endpoint:chat_completion, response。
curl -X POST https://runapi.ai/v1/chat/completions \
-H "Authorization: Bearer $RUNAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4o-mini",
"messages": [
{
"role": "user",
"content": "Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."
}
]
}'
import { GptClient } from "@runapi.ai/gpt";
const client = new GptClient();
const result = await client.chatCompletion.run({
model: "gpt-4o-mini",
messages: [{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}],
});
import os
import requests
response = requests.post(
"https://runapi.ai/v1/chat/completions",
headers={"Authorization": f"Bearer {os.environ['RUNAPI_API_KEY']}"},
json={"model":"gpt-4o-mini","messages":[{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]}
)
response.raise_for_status()
<?php
$client = curl_init("https://runapi.ai/v1/chat/completions");
curl_setopt_array($client, [
CURLOPT_HTTPHEADER => ["Authorization: Bearer " . getenv("RUNAPI_API_KEY"), "Content-Type: application/json"],
CURLOPT_POSTFIELDS => json_encode([
'model' => 'gpt-4o-mini',
'messages' => [['role' => 'user', 'content' => 'Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations.']],
])
]);
$response = curl_exec($client);
RunApi client = new RunApi(System.getenv("RUNAPI_API_KEY"));
Task task = client.chatCompletion().run({"model":"gpt-4o-mini","messages":[{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]});
task.waitForResult();
require "runapi/gpt"
client = RunApi::Gpt::Client.new
result = client.chat_completion.run(
model: "gpt-4o-mini",
messages: [{role: "user", content: "Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]
)
client := runapi.NewClient(os.Getenv("RUNAPI_API_KEY"))
task, err := client.chatCompletion.Run({"model":"gpt-4o-mini","messages":[{"role":"user","content":"Analyze this quarterly revenue data and produce a summary with key trends, anomalies, and three recommendations."}]})
if err != nil { log.Fatal(err) }
task.Wait()
$ runapi generate \
--model gpt-4o-mini \
--endpoint chat_completion \
--wait
17 個版本可用
選擇任意模型,數秒內即可開始生成。
| 提供者 | OpenAI |
| 模型 ID | gpt-4o-mini |
| 模態 | Text |
| 任務類型 | Synchronous |
| API 端點 | /v1/chat/completions |
| /v1/responses |
| /v1/messages | |
| /v1beta/models/gpt-4o-mini:generateContent | |
| /v1beta/models/gpt-4o-mini:streamGenerateContent | |
| 計費單位 | 1K tokens |
| 目錄狀態 | 可正常運作 |
免費註冊後,在控制台建立 gpt-4o-mini 的 API 金鑰。
向 /v1/chat/completions 發送 POST 請求,並傳入 gpt-4o-mini 模型 ID 和參數。
直接從端點讀取已完成的 gpt-4o-mini 回應。
開放 2 個公開 endpoint:chat_completion, response。
按 1K tokens 計量,無需訂閱。
此端點尚未發布請求參數。
從私有知識庫回答客戶問題,減少工單數量。
草擬合約摘要,並標示重點條款供律師審閱。
在 CI 自動生成單元測試、程式碼審查同重構建議。
此模型目前尚無經驗證的客戶評價。
傳入 quickstart 顯示嘅 model ID。
每個 key 的 rate limit 會按使用層級而定。請查看定價頁了解最新限制。
可以——variant 只係一個旗標。只要更改 model 參數就可以切換。
在可用 streaming 的情況下,RunAPI 會端到端串流。
可以在公開 GitHub repo 開 issue,或者電郵支援團隊。