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

# 响应

> 使用 TypeScript SDK 调用 Responses API。

**方法**: `client.generateResponse()` (使用以下方法流式传输已解析的内容块： `client.streamResponses()`).

### 示例

```typescript theme={null}
const resp = await client.generateResponse({
  model: "openai/gpt-4.1",
  input: [{ role: "user", content: [{ type: "input_text", text: "Summarise this text" }] }],
  temperature: 0.7,
  stream: false,
});
```

### 流式传输

```typescript theme={null}
for await (const chunk of client.streamResponses({
  model: "openai/gpt-4.1",
  input: [{ role: "user", content: [{ type: "input_text", text: "Stream this" }] }],
  stream: true,
})) {
  if (chunk.text) process.stdout.write(chunk.text);
}
```

### 主要参数

* `model` (required): 目标模型 ID。
* `input` (required): 按顺序排列的输入项数组（消息、工具调用等）。
* `temperature` (0-2): 值越高，随机性越强。
* `top_p` (0-1) / `top_k` (>=1): Nucleus / k-best 采样控制。
* `max_output_tokens` (int): 每个响应生成 Token 数的硬上限。
* 工具： `tools` (定义), `tool_choice` (`auto`/`none`/指定的), `max_tool_calls` (int), `parallel_tool_calls` (bool).
* Logprobs： `logprobs` (bool), `top_logprobs` (0-20) 用于返回每个 Token 的 logprob。
* 输出： `response_format` (json/text), `service_tier`, `store` (bool), `stream` (bool).
* 元数据： `metadata` (object) 用于透传, `reasoning` (object) 用于提示推理力度.
* Gateway 附加参数： `usage` (bool 用于请求用量数据), `meta` (bool 用于包含 meta 块).

### 返回值

`ResponsesResponse`

```json theme={null}
{
  "id": "resp_123",
  "object": "response",
  "created_at": 1677652288,
  "status": "completed",
  "model": "gpt-4.1",
  "output": [
    {
      "type": "message",
      "id": "msg_123",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "Hello there, how may I assist you today?"
        }
      ]
    }
  ],
  "usage": {
    "input_tokens": 9,
    "output_tokens": 12,
    "total_tokens": 21
  }
}
```

`stream: true` 时则返回以换行符分隔的 SSE 帧：

```
data: {"id":"resp_123","object":"response","created_at":1677652288,"status":"in_progress","model":"gpt-4.1","output":[{"type":"message","id":"msg_123","status":"in_progress","role":"assistant","content":[]}]}

data: {"id":"resp_123","object":"response","created_at":1677652288,"status":"in_progress","model":"gpt-4.1","output":[{"type":"message","id":"msg_123","status":"in_progress","role":"assistant","content":[{"type":"output_text","text":"Hello"}]}]}

data: {"id":"resp_123","object":"response","created_at":1677652288,"status":"completed","model":"gpt-4.1","output":[{"type":"message","id":"msg_123","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello there, how may I assist you today?"}]}],"usage":{"input_tokens":9,"output_tokens":12,"total_tokens":21}}

data: [DONE]
```


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