AI 주요 서비스와 도구 (2)#

from openai import OpenAI

client = OpenAI()

response = client.responses.create(
  model="gpt-5-mini",
  instructions="You are a helpful assistant.",
  input=[
    {"role": "user", "content": "Who won the world series in 2020?"},
    {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
    {"role": "user", "content": "Where was it played?"},
  ],
)

print(response.output_text)

from openai import OpenAI

client = OpenAI()

response = client.images.generate(
  model="gpt-image-1.5",
  prompt="a white siamese cat",
  size="1024x1024",
  quality="standard",
  n=1,
)

image_url = response.data[0].url
print(image_url)

[응답 예시]
[
  Image(
    b64_json=None,
    revised_prompt="A Siamese cat with a pr..(생략)",
    url="https://oaidalleapiprodscus.blob.core..(생략)",
  )
]

from openai import OpenAI

client = OpenAI()

img_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"

response = client.responses.create(
  model="gpt-5-mini",
  input=[
    {
      "role": "user",
      "content": [
        {"type": "input_text", "text": "What's in this image?"},
        {"type": "input_image", "image_url": img_url},
      ],
    }
  ],
)
print(response.output_text)

[응답 예시]
This image depicts a picturesque scene of a wooden boardwalk path stretching through a grassy field. The sky is blue with some scattered clouds, and the surrounding vegetation is lush and green, suggesting a summer or late spring setting. Trees and shrubs can be seen in the background, adding to the serene and natural atmosphere of the landscape.

from pathlib import Path
from openai import OpenAI

client = OpenAI()

speech_file_path = Path(__file__).parent / "6_text_to_speech_result.mp3"
with client.audio.speech.with_streaming_response.create(
  model="tts-1",
  voice="alloy",
  input="Today is a wonderful day to build something people love!",
) as response:
  response.stream_to_file(speech_file_path)

from pathlib import Path
from openai import OpenAI

client = OpenAI()

audio_file = Path("6_text_to_speech_result.mp3")
transcription = client.audio.transcriptions.create(
  model="whisper-1",
  file=audio_file,
)

print(transcription.text)

[응답 예시]
Today is a wonderful day to build something people love.

from openai import OpenAI

client = OpenAI()

response = client.moderations.create(
  input="Hello world!!",
)
print(response)

[응답 예시]
ModerationCreateResponse(
  id="modr-...",
  model="...",
  results=[...],
)

from openai import OpenAI
from typing_extensions import override
from openai import AssistantEventHandler

client = OpenAI()

assistant = client.beta.assistants.create(
  name="Math Tutor",
  instructions="You are a personal math tutor. Write and run code to answer math questions.",
  tools=[{"type": "code_interpreter"}],
  model="gpt-5-mini",
)

thread = client.beta.threads.create()

class EventHandler(AssistantEventHandler):
  @override
  def on_text_created(self, text) -> None:
    print("\nassistant > ", end="", flush=True)

  @override
  def on_text_delta(self, delta, snapshot):
    print(delta.value, end="", flush=True)

  def on_tool_call_created(self, tool_call):
    print(f"\nassistant > {tool_call.type}\n", flush=True)

  def on_tool_call_delta(self, delta, snapshot):
    if delta.type == "code_interpreter" and delta.code_interpreter:
      if delta.code_interpreter.input:
        print(delta.code_interpreter.input, end="", flush=True)
      if delta.code_interpreter.outputs:
        print("\n\noutput >", flush=True)
        for output in delta.code_interpreter.outputs:
          if output.type == "logs":
            print(f"\n{output.logs}", flush=True)

while True:
  user_input = input("\n\nuser > ")
  if user_input.lower() in ["exit", "quit"]:
    break

  client.beta.threads.messages.create(
    thread_id=thread.id,
    role="user",
    content=user_input,
  )

  with client.beta.threads.runs.stream(
    thread_id=thread.id,
    assistant_id=assistant.id,
    instructions="Please address the user as Ted Kim. The user has a premium account.",
    event_handler=EventHandler(),
  ) as stream:
    stream.until_done()

[실행 로그 예시]

user > Who are you?

assistant > Hello, Ted Kim! I'm your AI assistant, here to help you with information, tasks, and any questions you might have. How can I assist you today?

user > I need to solve the equation `3x + 11 = 14`. Can you help me?

assistant > Sure, Ted Kim! Let's solve the equation (3x + 11 = 14).

1. **Subtract 11 from both sides:**
   3x + 11 - 11 = 14 - 11
   3x = 3

2. **Divide both sides by 3:**
   x = 3/3
   x = 1

So, the solution to the equation (3x + 11 = 14) is (x = 1).

user > Please run the python code. `for i in range(0,3): print('i * 2 = %d' % (i * 2))`

assistant > code_interpreter

output >
i * 2 = 0
i * 2 = 2
i * 2 = 4

user > exit