GPT

from openai import OpenAI

client = OpenAI(api_key="your-api-key")

# 기본 Chat Completion
response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Python에서 리스트 컴프리헨션을 설명해주세요."}
    ],
    temperature=0.7,
    max_tokens=500
)
print(response.choices[0].message.content)

# 스트리밍 응답
stream = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": "AI의 미래에 대해 설명해주세요."}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

# Function Calling (도구 사용)
tools = [{
    "type": "function",
    "function": {
        "name": "get_weather",
        "description": "Get current weather for a location",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {"type": "string", "description": "City name"},
                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
            },
            "required": ["location"]
        }
    }
}]

response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[{"role": "user", "content": "서울 날씨 알려줘"}],
    tools=tools,
    tool_choice="auto"
)

# JSON 모드
response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "system", "content": "You output JSON only."},
        {"role": "user", "content": "List 3 programming languages with their use cases."}
    ],
    response_format={"type": "json_object"}
)

# 토큰 수 확인
import tiktoken
encoding = tiktoken.encoding_for_model("gpt-4")
text = "Hello, how are you?"
tokens = encoding.encode(text)
print(f"Token count: {len(tokens)}")  # 5 tokens