Multi-Agent Conversation(MAC) 프레임워크로 의료 진단 능력 강화하기

# OpenAI API를 활용한 간단한 MAC 패턴 예시
import openai

client = openai.OpenAI()

def doctor_agent(case: str, specialty: str) -> str:
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": f"You are an experienced {specialty} physician. Analyze the case and suggest a diagnosis with reasoning."},
            {"role": "user", "content": case}
        ]
    )
    return response.choices[0].message.content

def supervisor_agent(case: str, doctor_opinions: list[str]) -> str:
    opinions_text = "\n\n".join([f"Doctor {i+1}: {op}" for i, op in enumerate(doctor_opinions)])
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": "You are a senior supervising physician. Review all doctor opinions and provide a final integrated diagnosis."},
            {"role": "user", "content": f"Case:\n{case}\n\nDoctor Opinions:\n{opinions_text}\n\nProvide the final diagnosis."},
        ]
    )
    return response.choices[0].message.content

# 사용 예시
case = "28-year-old patient with progressive muscle weakness, fatigue, and elevated CK levels..."
specialties = ["neurologist", "rheumatologist", "internal medicine specialist", "geneticist"]

# 4명의 Doctor 에이전트 실행
opinions = [doctor_agent(case, s) for s in specialties]

# Supervisor가 최종 진단
final_diagnosis = supervisor_agent(case, opinions)
print(final_diagnosis)