Grok 채팅 및 추론 가이드

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.apiyi.com/v1"
)

stream = client.chat.completions.create(
    model="grok-4.3",
    messages=[{"role": "user", "content": "Count from 1 to 5, one number per line"}],
    stream=True,
    stream_options={"include_usage": True},
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")
    if chunk.usage:
        print(f"\nUsage: {chunk.usage.total_tokens} tokens")

resp = client.chat.completions.create(
    model="grok-4.20-0309-reasoning",
    messages=[{"role": "user", "content": "Pipe A fills a pool in 8h, pipe B in 12h. How long together?"}]
)
msg = resp.choices[0].message
print("Answer:", msg.content)
print("Chain-of-thought:", msg.reasoning_content)
print("Reasoning tokens:", resp.usage.completion_tokens_details.reasoning_tokens)

resp = client.chat.completions.create(
    model="grok-4.5",
    messages=[{"role": "user", "content": "Zhang San is 25 and lives in Hangzhou. Extract the info."}],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "user_info",
            "strict": True,
            "schema": {
                "type": "object",
                "properties": {
                    "name": {"type": "string"},
                    "age": {"type": "integer"},
                    "city": {"type": "string"}
                },
                "required": ["name", "age", "city"],
                "additionalProperties": False
            }
        }
    }
)
print(resp.choices[0].message.content)   # {"name":"Zhang San","age":25,"city":"Hangzhou"}

tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get current weather for a city",
        "parameters": {
            "type": "object",
            "properties": {"city": {"type": "string", "description": "City name"}},
            "required": ["city"]
        }
    }
}]

messages = [{"role": "user", "content": "What's the weather in Shanghai right now?"}]

# Round 1: the model decides to call the tool
resp = client.chat.completions.create(model="grok-4.5", messages=messages, tools=tools)
msg = resp.choices[0].message
tool_call = msg.tool_calls[0]
print(tool_call.function.name, tool_call.function.arguments)  # get_weather {"city":"Shanghai"}

# Round 2: feed the tool result back
messages += [
    msg,
    {"role": "tool", "tool_call_id": tool_call.id,
     "content": '{"city": "Shanghai", "temp_c": 31, "condition": "sunny"}'}
]
resp2 = client.chat.completions.create(model="grok-4.5", messages=messages, tools=tools)
print(resp2.choices[0].message.content)  # It's sunny in Shanghai, 31°C.

import base64

with open("image.jpg", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()

resp = client.chat.completions.create(
    model="grok-4.5",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What's in this image?"},
            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64}"}}
        ]
    }]
)
print(resp.choices[0].message.content)

resp = client.chat.completions.create(model="grok-4.5", messages=messages)
print("Cache hits:", resp.usage.prompt_tokens_details.cached_tokens)