适合什么场景
- 你要透传 Gemini 的
generationConfig、thinkingConfig或响应模态设置 - 统一模型层需要保留 Google 专有能力
最小请求
{
"model": "gemini-2.5-flash",
"messages": [
{ "role": "user", "content": "总结这份报告。" }
],
"model_extra": {
"generationConfig": {
"thinkingConfig": { "thinkingBudget": 512 },
"responseMimeType": "application/json"
}
}
}
cURL 示例
curl https://mass.apigo.ai/v1/chat/completions \
-H "Authorization: Bearer $TIDEMIND_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-2.5-flash",
"messages": [
{ "role": "user", "content": "总结这份报告。" }
],
"model_extra": {
"generationConfig": {
"thinkingConfig": { "thinkingBudget": 512 },
"responseMimeType": "application/json"
}
}
}'
Python 示例
import requests
response = requests.post(
"https://mass.apigo.ai/v1/chat/completions",
headers={
"Authorization": "Bearer <TIDEMIND_API_KEY>",
"Content-Type": "application/json",
},
json={
"model": "gemini-2.5-flash",
"messages": [
{"role": "user", "content": "总结这份报告。"}
],
"model_extra": {
"generationConfig": {
"thinkingConfig": {"thinkingBudget": 512},
"responseMimeType": "application/json",
}
},
},
timeout=60,
)
response.raise_for_status()
print(response.json()["choices"][0]["message"]["content"])
Node.js 示例
const response = await fetch("https://mass.apigo.ai/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.TIDEMIND_API_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
model: "gemini-2.5-flash",
messages: [
{ role: "user", content: "总结这份报告。" }
],
model_extra: {
generationConfig: {
thinkingConfig: { thinkingBudget: 512 },
responseMimeType: "application/json"
}
}
})
});
const data = await response.json();
console.log(data.choices[0].message.content);
最佳实践
generationConfig这类嵌套字段先做 schema 校验再透传- 同时记录模型名和扩展参数,便于回归测试
