스트림 방식으로 결과 받기

!pip install openai
!pip install gradio

import gradio as gr
from openai import OpenAI

client = OpenAI()

# 응답 생성 함수 (스트림 방식)
def generate_response(prompt_text):

    completion = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "user", "content": prompt_text}
        ],
        temperature=1.0,
        stream=True
    )

    partial_message = ""

    for chunk in completion:
        if chunk.choices[0].delta.content is not None:
              partial_message = partial_message + chunk.choices[0].delta.content
              yield partial_message


with gr.Blocks() as demo:
    gr.Markdown(
    """
    # 홍길동의 AI 화학 전문가
    화학에 대해 궁금한 사항이 있으면 질문해 주세요.
    """)

    with gr.Row():
        with gr.Column():

            input_text = gr.Textbox(label="프롬프트:")
            output_text = gr.Textbox(label="ChatGPT 결과", interactive=False)

            input_text.submit(generate_response, inputs=input_text, outputs=output_text)

demo.launch()

import gradio as gr
from openai import OpenAI

client = OpenAI()

# 응답 생성 함수
def generate_response(prompt_text):

    completion = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "user", "content": prompt_text}
        ],
        temperature=1.0,
        stream=True
    )

    partial_message = ""

    for chunk in completion:
        if chunk.choices[0].delta.content is not None:
              partial_message = partial_message + chunk.choices[0].delta.content
              yield partial_message


with gr.Blocks() as demo:
    gr.Markdown(
    """
    # 홍길동의 AI 화학 전문가
    화학에 대해 궁금한 사항이 있으면 질문해 주세요.
    """)

    with gr.Row():
        with gr.Column():

            input_text = gr.Textbox(label="프롬프트:")
            output_text = gr.Textbox(label="ChatGPT 결과", interactive=False, lines=10)

            input_text.submit(generate_response, inputs=input_text, outputs=output_text)

demo.launch()