함수 호출 작동 방식

함수 호출: 핵심 패턴

다섯 단계 왕복 과정

1단계: 도구 정의하기

tools = [{
    'type': 'function',
    'function': {
        'name': 'get_weather',
        'description': 'Current weather for a city',
        'parameters': {
            'type': 'object',
            'properties': {
                'city': {'type': 'string'}
            },
            'required': ['city']
        }
    }
}]
import json
print(json.dumps(tools, indent=2))

2단계: 첫 번째 모델 호출

response = client.chat.completions.create(
    model='gpt-4o-mini',
    messages=[{'role': 'user', 'content': 'Weather in Paris?'}],
    tools=tools,
)
message = response.choices[0].message
print(message.tool_calls)
# [ToolCall(name='get_weather', arguments='{"city": "Paris"}')]

3단계: 도구 실행하기

import json

def get_weather(city: str) -> dict:
    # ...call your weather API...
    return {'city': city, 'temp_c': 18, 'condition': 'cloudy'}

tool_call = message.tool_calls[0]
args = json.loads(tool_call.function.arguments)
result = get_weather(**args)

4단계: 도구 결과 append하기

messages.append(message)  # the assistant message with tool_calls
messages.append({
    'role': 'tool',
    'tool_call_id': tool_call.id,
    'content': json.dumps(result)
})

5단계: 두 번째 모델 호출

final = client.chat.completions.create(
    model='gpt-4o-mini',
    messages=messages,
    tools=tools,
)
print(final.choices[0].message.content)
# 'It is currently 18 degrees and cloudy in Paris.'

에이전트 루프

while True:
    response = client.chat.completions.create(model=MODEL, messages=messages, tools=tools)
    msg = response.choices[0].message
    messages.append(msg)
    if not msg.tool_calls:
        return msg.content  # final answer
    for tc in msg.tool_calls:
        result = dispatch(tc)
        messages.append({'role': 'tool', 'tool_call_id': tc.id, 'content': json.dumps(result)})

병렬 도구 호출

import asyncio

async def run_tools(tool_calls):
    coros = [dispatch_async(tc) for tc in tool_calls]
    return await asyncio.gather(*coros)

finish_reason: tool_calls

if response.choices[0].finish_reason == 'tool_calls':
    # the model wants to call tools
    ...
elif response.choices[0].finish_reason == 'stop':
    # done
    ...

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