> ## 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.

# रिस्पॉन्स

> Python SDK से Responses API call करें।

**Method**: `client.generate_response()` (`client.stream_responses()` से parsed chunks stream करें)।

### उदाहरण

```python theme={null}
resp = client.generate_response({
    "model": "openai/gpt-4.1",
    "input": [{"role": "user", "content": [{"type": "input_text", "text": "Summarise this"}]}],
    "temperature": 0.7,
})
```

### स्ट्रीमिंग

```python theme={null}
for chunk in client.stream_responses({
    "model": "openai/gpt-4.1",
    "input": [{"role": "user", "content": [{"type": "input_text", "text": "Stream this"}]}],
    "stream": True,
}):
    if chunk.get("text"):
        print(chunk["text"], end="", flush=True)
```

### मुख्य parameters

* `model` (आवश्यक): लक्ष्य मॉडल ID।
* `input` (आवश्यक): इनपुट आइटम (संदेश, टूल कॉल आदि) की क्रमबद्ध सूची।
* `temperature` (0–2): मान जितना अधिक होगा, आउटपुट उतना ही यादृच्छिक होगा।
* `top_p` (0–1) / `top_k` (>=1): न्यूक्लियस और top-k सैंपलिंग नियंत्रण।
* `max_output_tokens` (integer): हर प्रतिक्रिया में जनरेट होने वाले टोकन की अधिकतम सीमा।
* टूल: `tools` (परिभाषाएँ), `tool_choice` (auto/none/विशिष्ट), `max_tool_calls` (पूर्णांक), `parallel_tool_calls` (बूलियन)।
* लॉग प्रायिकताएँ: `logprobs` (बूलियन), `top_logprobs` (0–20), हर टोकन की लॉग प्रायिकताएँ लौटाने के लिए।
* आउटपुट: `response_format` (json/text), `service_tier`, `store` (बूलियन), `stream` (बूलियन)।
* मेटाडेटा: `metadata` (पास-थ्रू ऑब्जेक्ट), `reasoning` (प्रयास-सूचना वाला ऑब्जेक्ट)।
* Gateway के अतिरिक्त विकल्प: `usage` (उपयोग आँकड़े माँगने के लिए बूलियन), `meta` (मेटा ब्लॉक शामिल करने के लिए बूलियन)।

### रिटर्न मान

`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` होने पर newline-delimited SSE frames:

```
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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