app.py

from youtubesearchpython import VideosSearch, Transcript  # Changed import statement
import gradio as gr  
import openai
import os

# openai.api_key = os.getenv('O_API_KEY')

def search_youtube_videos(keyword):
    videos_search = VideosSearch(keyword, limit=5)
    results = videos_search.result()
    video_urls = [video['link'] for video in results['result']]
    return video_urls

def get_transcript(urls):
    contents = ''
    for url in urls:
        data = Transcript.get(url)
        text = ""
        for segment in data['segments']:
            text += segment['text']
        contents += text
    return contents
    
def summarize_text(contents, OPENAI_API_KEY):
    API_URL = "https://api.openai.com/v1/chat/completions"
    payload = {
        "model": "gpt-4-0125-preview",  # 모델 이름 확인 필요
        "messages": [{
            "role": "system",
            "content": "당신은 내용을 요약하는 챗봇입니다."
        }, {
            "role": "user",
            "content": f"유튜브 내용인 '{contents}'에 대해 요약해주세요."
        }],
    }
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {OPENAI_API_KEY}"
    }
    response = requests.post(API_URL, headers=headers, json=payload)
    if response.status_code == 200:
        data = response.json()
        # 대화형 API 응답에서 적절한 메시지 추출 및 유명인 이름 반환
        return data["choices"][0]["message"]["content"], get_famous_people(lunIljin)
    else:
        # 오류 메시지 개선
        return f"오류가 발생했습니다. 상태 코드: {response.status_code}, 메시지: {response.json().get('error', {}).get('message', 'Unknown error')}", ""

    
# def summarize_text(contents, OPENAI_API_KEY):
    
#     response = openai.ChatCompletion.create(
        
#         model="gpt-4-turbo-preview",  
#         messages=[
#             {"role": "system", "content": "You are a helpful assistant."},
#             {"role": "user", "content": f"Summarize this: {contents}"}
#         ],
#         headers={
#             "Content-Type": "application/json",
#             "Authorization": f"Bearer {OPENAI_API_KEY}"
#         }
#     )
#     return response.choices[0].message['content'].strip()    
    
# def summarize_text(contents):
#     response = openai.ChatCompletion.create(
#         engine="gpt-3.5-turbo",
#         prompt=f"요약: {contents}",
#         max_tokens=150
#     )
#     return response.choices[0].text.strip()

# Function to integrate all the functionalities
    
def summarize_youtube_videos(keyword, OPENAI_API_KEY):
    urls = search_youtube_videos(keyword)
    contents = get_transcript(urls)
    summary = summarize_text(contents,OPENAI_API_KEY)
    return summary

def summarize_button_click(keyword, OPENAI_API_KEY):
    summary = summarize_youtube_videos(keyword, OPENAI_API_KEY)
    return summary


with gr.Blocks(css="footer {visibility: hidden;}") as demo:

    with gr.Tab():
        keyword = gr.Textbox(label="keyword", placeholder='키워드를 입력하세요. (예.비트코인)')
        OPENAI_API_KEY = gr.Textbox(label="OpenAI API 키", placeholder="여기에 OpenAI API 키를 입력하세요")
        output = gr.JSON(label="결과")
        analysis_result = gr.HTML()  # 사주 분석 결과를 출력할 HTML 컴포넌트
        analysis_btn = gr.Button("submit")

        analysis_btn.click(
            fn=summarize_youtube_videos,
            inputs=[keyword, OPENAI_API_KEY],
            outputs=[output, analysis_result]
        ) 

demo.launch()