> ## Documentation Index
> Fetch the complete documentation index at: https://docs-vip.apigo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# OpenAI 思考模式示例

> OpenAI 推理模型接入示例。

## 推荐 endpoint

* [OpenAI /v1/responses](/api-reference/endpoints/openai/responses)

## 最小请求

```json theme={null}
{
  "model": "o4-mini",
  "input": "比较三种缓存架构的取舍，并给出推荐。",
  "reasoning": {
    "effort": "medium"
  },
  "max_output_tokens": 1200
}
```

## cURL 示例

```bash theme={null}
curl https://api-vip.apigo.ai/v1/responses \
  -H "Authorization: Bearer $YOUR API KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "o4-mini",
    "input": "比较三种缓存架构的取舍，并给出推荐。",
    "reasoning": {
      "effort": "medium"
    },
    "max_output_tokens": 1200
  }'
```

## Python 示例

```python theme={null}
from openai import OpenAI

client = OpenAI(
    base_url="https://api-vip.apigo.ai/v1",
    api_key="<YOUR API KEY>",
)

response = client.responses.create(
    model="o4-mini",
    input="比较三种缓存架构的取舍，并给出推荐。",
    reasoning={"effort": "medium"},
    max_output_tokens=1200,
)

print(response.output_text)
```

## Node.js 示例

```js theme={null}
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api-vip.apigo.ai/v1",
  apiKey: process.env.YOUR API KEY,
});

const response = await client.responses.create({
  model: "o4-mini",
  input: "比较三种缓存架构的取舍，并给出推荐。",
  reasoning: { effort: "medium" },
  max_output_tokens: 1200,
});

console.log(response.output_text);
```

## 最佳实践

* 推理场景优先显式控制 `reasoning.effort`
* 不要要求模型暴露完整思维链，重点约束最终结论格式
* 单独监控延迟、token 和成功率，别和普通聊天流量混算