Create streamlit_audio.py

streamlit_audio.py

@@ -0,0 +1,1059 @@
+import os
+import pprint
+import requests
+from bs4 import BeautifulSoup
+from gnews import GNews
+from datetime import datetime
+import edge_tts
+import arxiv
+import subprocess
+import base64
+import openai
+import streamlit as st
+from langchain.utilities import GoogleSerperAPIWrapper
+from langchain.utilities import GoogleSerperAPIWrapper
+from langchain.llms.openai import OpenAI
+from youtubesearchpython import *
+from youtube_transcript_api import YouTubeTranscriptApi
+from langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter
+from langchain.docstore.document import Document
+from langchain.llms.openai import OpenAI
+from langchain.chains.summarize import load_summarize_chain
+from langchain.chat_models import ChatOpenAI
+from langchain.agents import initialize_agent, Tool
+from langchain.agents import AgentType
+from langchain.chat_models import ChatOpenAI
+from langchain.document_loaders import WebBaseLoader
+from langchain.chains.summarize import load_summarize_chain
+
+os.environ["SERPER_API_KEY"] = st.secrets["SERPER_API_KEY"]
+os.environ["OPENAI_API_KEY"]= st.secrets["OPENAI_API_KEY"]
+openai.api_key = os.environ["OPENAI_API_KEY"]
+
+system_message = '''
+                You are a very talented editor, skilled at consolidating 
+                fragmented information and introductions into a cohesive script, without missing any details.
+                Compile the news article based on the information in 【】.  
+                '''
+
+system_message_2 = '''
+                You are a linguist, skilled in summarizing textual content and presenting it in 3 bullet points using markdown. 
+                '''
+
+system_message_3 = '''
+                你是个语言学家，擅长把英文翻译成中文。要注意表达的流畅和使用中文的表达习惯。不要返回多余的信息，只把文字翻译成中文。
+                '''
+
+def find_next_link_text(url, target_link, target_text):
+    """
+    Find the first link and text after the given target link and text on the specified URL.
+    
+    Parameters:
+        url (str): The URL of the webpage to scrape.
+        target_link (str): The specific link to be found.
+        target_text (str): The specific link text to be found.
+        
+    Returns:
+        tuple: A tuple containing the next link and its text. Returns (None, None) if not found.
+    """
+    
+    # Send a GET request
+    response = requests.get(url)
+    response.raise_for_status()  # This will raise an exception if there's an error
+    
+    # Parse the content using BeautifulSoup
+    soup = BeautifulSoup(response.content, 'html.parser')
+    
+    # Find all the <ul> elements
+    ul_elems = soup.find_all('ul')
+    
+    # Initialize a list to store all links and their texts
+    all_links = []
+    
+    # Extract links and texts from all <ul> elements
+    for ul_elem in ul_elems:
+        links = [(link.get('href'), link.text) for link in ul_elem.find_all('a')]
+        all_links.extend(links)
+    
+    # Extract the first link and text after the specified link-text pair
+    found = False
+    for link, text in all_links:
+        if found:
+            return link, text
+        if link == target_link and text == target_text:
+            found = True
+            
+    return None, None
+  
+def is_link_accessible(url):
+    """Check if a link is accessible."""
+    try:
+        response = requests.get(url, timeout=10)  # setting a timeout to avoid waiting indefinitely
+        # Check if the status code is 4xx or 5xx
+        if 400 <= response.status_code < 600:
+            return False
+        return True
+    except requests.RequestException:
+        return False
+    
+def get_latest_aws_ml_blog():
+    url = 'https://aws.amazon.com/blogs/machine-learning/'
+    
+    response = requests.get(url)
+    
+    if response.status_code != 200:
+        print(f"Failed to retrieve webpage. Status code: {response.status_code}")
+        return None, None
+    
+    soup = BeautifulSoup(response.text, 'html.parser')
+    
+    articles = soup.find_all('div', class_='lb-col lb-mid-18 lb-tiny-24')
+    
+    if not articles:
+        print("No articles found.")
+        return None, None
+    
+    title = articles[0].find('h2').text
+    link = articles[0].find('a')['href']
+    
+    return title, link
+
+def fetch_videos_from_channel(channel_id):
+    playlist = Playlist(playlist_from_channel_id(channel_id))
+    while playlist.hasMoreVideos:
+        playlist.getNextVideos()
+    return playlist.videos
+
+def get_h1_text(url):
+    """Fetches the text content of the first h1 element from the given URL."""
+    
+    # Get the HTML content of the URL
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+
+    # Find the first h1 element and get its text
+    h1_element = soup.find('h1', class_='entry-title')
+    if h1_element:
+        return h1_element.text.strip()  # Remove any extra whitespaces
+    else:
+        return None
+    
+def get_transcript(video_id):
+    raw_data = YouTubeTranscriptApi.get_transcript(video_id)
+    texts = [item['text'] for item in raw_data]
+    return ' '.join(texts)
+
+def extract_data_from_url(url, class_name):
+    """
+    从指定的URL中提取特定类名的<a>标签的href属性和文本内容。
+
+    参数:
+    - url (str): 要提取数据的网页URL。
+    - class_name (str): 要查找的<a>标签的类名。
+
+    """
+
+    response = requests.get(url)
+
+    if response.status_code == 200:
+        soup = BeautifulSoup(response.content, 'html.parser')
+        target_a = soup.find('a', class_=class_name)
+
+        if target_a:
+            data_mrf_link = target_a.get('href')
+            text = target_a.get_text().strip()
+            return (data_mrf_link, text)
+        else:
+            raise ValueError("找不到目标元素。")
+    else:
+        raise ConnectionError("请求失败。")
+    
+def split_text_into_documents(long_string, max_docs=20):
+    text_splitter = RecursiveCharacterTextSplitter(
+        chunk_size=500,
+        chunk_overlap=20,
+        length_function=len,
+    )
+    texts = text_splitter.split_text(long_string)
+    docs = [Document(page_content=t) for t in texts[:max_docs]]
+
+    text_splitter = CharacterTextSplitter.from_tiktoken_encoder(
+        chunk_size=500, chunk_overlap=0
+    )
+    split_docs = text_splitter.split_documents(docs)
+    return split_docs
+
+
+def autoplay_audio(file_path: str):
+    with open(file_path, "rb") as f:
+        data = f.read()
+        b64 = base64.b64encode(data).decode()
+        md = f"""
+            <audio controls autoplay style="width: 100%;">
+            <source src="data:audio/mp3;base64,{b64}" type="audio/mp3">
+            </audio>
+            """
+        st.markdown(
+            md,
+            unsafe_allow_html=True,
+        )
+
+def get_h1_from_url(url):
+    response = requests.get(url)
+
+    if response.status_code == 200:
+        soup = BeautifulSoup(response.content, 'html.parser')
+        
+        # 根据class查找<h1>标签
+        h1_tag = soup.find("h1", class_="f-display-2")
+        if h1_tag:
+            return h1_tag.text
+        else:
+            print("Couldn't find the <h1> tag with the specified class on the page.")
+            return None
+    else:
+        print(f"Failed to fetch the webpage. Status code: {response.status_code}")
+        return None
+    
+
+def summarize_documents(split_docs):
+    llm = ChatOpenAI(temperature=1, model_name="gpt-3.5-turbo-16k")
+    chain = load_summarize_chain(llm, chain_type="map_reduce")
+    summary = chain.run(split_docs)
+    return summary
+
+
+def get_completion_from_messages(messages,
+                                 model="gpt-3.5-turbo-16k",
+                                 temperature=1.5, max_tokens=7000):
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=messages,
+        temperature=temperature,
+        max_tokens=max_tokens,
+    )
+    return response.choices[0].message["content"]
+
+def fetch_gnews_links(query, language='en', country='US', period='1d', start_date=None, end_date=None, max_results=5, exclude_websites=None):
+    """
+    Fetch news links from Google News based on the provided query.
+
+    Parameters:
+    - query (str): The search query for fetching news.
+    - ... (other params): Additional parameters for customizing the news fetch.
+
+    Returns:
+    - List[str]: List of URLs based on the search query.
+    """
+
+    # Ensure that the exclude_websites parameter is a list
+    content = {'title':[], 'summary':[], 'url':[]}
+
+    # Initialize GNews
+    google_news = GNews(language=language, country=country, period=period, start_date=start_date, end_date=end_date, max_results=max_results, exclude_websites=exclude_websites)
+    
+    # Fetch news based on the query
+    news_items = google_news.get_news(query)
+    print(news_items)
+    # Extract URLs
+    urls = [item['url'] for item in news_items]
+    content['title'] = [item['title'] for item in news_items]
+
+    for url in urls:
+      content['url'].append(url)
+      content['summary'].append(summarize_website_content(url))
+
+    return content
+
+
+
+def summarize_website_content(url, temperature=1, model_name="gpt-3.5-turbo-16k", chain_type="stuff"):
+    """
+    Summarize the content of a given website URL.
+
+    Parameters:
+    - url (str): The website URL to fetch and summarize.
+    - temperature (float, optional): Temperature parameter for ChatOpenAI model. Default is 0.
+    - model_name (str, optional): The model name for ChatOpenAI. Default is "gpt-3.5-turbo-16k".
+    - chain_type (str, optional): The type of summarization chain to use. Default is "stuff".
+
+    Returns:
+    - The summarized content.
+    """
+    if True:
+        # Load the content from the given URL
+        loader = WebBaseLoader(url)
+        docs = loader.load()
+
+        # Initialize the ChatOpenAI model
+        llm = ChatOpenAI(temperature=temperature, model_name=model_name)
+        
+        # Load the summarization chain
+        chain = load_summarize_chain(llm, chain_type=chain_type)
+
+        # Run the chain on the loaded documents
+        summarized_content = chain.run(docs)
+        
+        return summarized_content
+    
+    else:
+        return 'No result'
+
+
+def get_transcript_link(url):
+    """Fetches the first 'Transcript' link from the given URL."""
+    
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+
+    transcript_link_element = soup.find('a', string="Transcript")
+
+    if transcript_link_element:
+        return transcript_link_element['href']
+    else:
+        return None
+
+def get_youtube_link(url):
+    """Fetches the first 'Transcript' link from the given URL."""
+    
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+
+    transcript_link_element = soup.find('a', string="Video")
+
+    if transcript_link_element:
+        return transcript_link_element['href']
+    else:
+        return None
+
+def get_latest_openai_blog_url():
+    base_url = "https://openai.com"
+    blog_url = f"{base_url}/blog"
+
+    response = requests.get(blog_url)
+
+    if response.status_code == 200:
+        soup = BeautifulSoup(response.content, 'html.parser')
+        
+        # 查找具有特定类名的<a>标签
+        target_link = soup.find("a", class_="ui-link group relative cursor-pointer") 
+        if target_link:
+            # Combining base URL with the relative path
+            post_url = base_url + target_link['href']
+            return post_url
+        else:
+            print("Couldn't find the target post URL.")
+            return None
+    else:
+        print(f"Failed to fetch the webpage. Status code: {response.status_code}")
+        return None
+
+def extract_blog_link_info(url):
+    headers = {
+        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.3'
+    }
+
+    response = requests.get(url, headers=headers)
+
+    if response.status_code != 200:
+        return None, None
+
+    soup = BeautifulSoup(response.content, 'html.parser')
+
+    # 由于网站可能有多个这样的链接，我们只选择第一个匹配的项
+    link_element = soup.find('a', class_='f-post-link')
+
+    if link_element:
+        text_content = link_element.h3.text.strip()
+        href_link = link_element['href']
+        return text_content, href_link
+    else:
+        return None, None
+
+
+def get_all_text_from_url(url):
+    # Fetch the content using requests
+    response = requests.get(url)
+    response.raise_for_status()  # Raise an error if the request failed
+
+    # Parse the HTML using BeautifulSoup
+    soup = BeautifulSoup(response.text, 'html.parser')
+    
+    # Extract all text
+    return ' '.join(soup.stripped_strings)  # `stripped_strings` generates strings by stripping extra whitespaces
+
+def contains_keywords(s):
+    keywords = ["AI", "GPT", "LLM"]
+    return any(keyword in s for keyword in keywords)
+
+
+def input_page(st, **state):
+    # Include Font Awesome CSS
+    st.markdown(
+        """
+        <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.3/css/all.min.css">
+        """,
+        unsafe_allow_html=True,
+    )
+
+    # Style and position the GitHub and Twitter icons at the bottom left corner
+    st.markdown(
+        """
+        <style>
+            .social-icons {
+                gap: 10px;  # Space between icons
+            }
+            .social-icons a i {
+                color: #6c6c6c;
+            }
+            </style>
+            """,
+            unsafe_allow_html=True,
+        )
+
+    # Add the GitHub and Twitter icons with hyperlinks
+    github_url = "https://github.com/xl631212/llm_newsletter/tree/main"  # replace with your GitHub repo URL
+    twitter_url = "https://twitter.com/li_xuying"  # replace with your Twitter profile URL
+
+    st.markdown("""
+    <h1 style='text-align: center; color: black;'>
+        Your Personal <span style='color: #FF4B4B; font-size: 1.25em;'>AI News</span> Podcast
+    </h1>
+    <div class="social-icons" style='text-align: center; color: black;'>
+            <a href="https://github.com/xl631212/llm_newsletter/tree/main" target="_blank"><i class="fab fa-github fa-2x"></i></a>
+            <a href="https://twitter.com/li_xuying" target="_blank"><i class="fab fa-twitter fa-2x"></i></a>
+        </div>
+    """, 
+    unsafe_allow_html=True
+    )
+    st.markdown("<h3 style='text-align: center; color: black;'>Empower Your Day with Real-Time Insights: Leveraging AI for Instant News <br> and Podcast Updates.</h3>", unsafe_allow_html=True)
+    st.markdown("""
+        <h4 style='text-align: center; color: #6C6C6C;'>
+            Choose your preferred options🔘 at the bottom, then double-click👆 the button below to initiate. 
+                <br>
+                Sit back and relax while we craft your personalized LLM podcast within <span style='color: #2859C0; font-size: 1.15em;'>3 mins</span>.
+        </h4>
+        <br><br>
+        """, 
+        unsafe_allow_html=True)
+    
+
+    button_placeholder = st.empty()
+    st.markdown("<br>", unsafe_allow_html=True)
+
+    with st.container():
+        col3a, col4a, col5a= st.columns([4,7,4])
+        with col3a:
+            pass
+        with col4a:
+            col1a, col2a, col8a = st.columns([3,1,3])
+            with col1a:
+                st.write("**Options🔘:**")
+        with col5a:
+            pass
+
+    st.markdown("""
+        <style>
+            .stButton > button {
+                font-size: 100px;
+                width: 35%;  /* 设置一个固定的宽度 */
+                height: 50px; /* 设置一个固定的高度 */
+                color: white;
+                background-color: #FF4B4B;
+                border: none;
+                border-radius: 15px;
+                margin: auto;
+                font-weight: bold; 
+                display: flex;
+                justify-content: center;
+                align-items: center;
+            }
+
+            .stButton > button:hover {
+                background-color: #EFEFEF; /* 为按钮添加简单的悬停效果 */
+                color: #9A9A9A;
+            }
+
+            .stButton > button div p {
+                font-size: 24px;  /* 改变按钮文本的字号 */
+                margin: 0;  /* 移除段落的默认边距 */
+            }
+                
+            .stButton > button div p:hover {
+                font-size: 20px;
+            }
+        </style>
+        """, unsafe_allow_html=True)
+    
+
+    with st.container():
+        col3, col4, col5= st.columns([4,7,4])
+        with col3:
+            pass
+        with col4:
+
+            col1, col2, col8 = st.columns([4,2,4])
+            with col1:
+                language = st.selectbox(
+                    "Language",
+                    ("English", "中文"),
+                    key='ahaha'
+                )
+                audio_length_adjust = st.select_slider('Audio length', options=['short', 'medium', 'long'],value=('medium'))
+                if audio_length_adjust == 'short':
+                    audio_length = 200
+                elif audio_length_adjust == 'medium':
+                    audio_length = 350
+                else:
+                    audio_length = 500
+                st.session_state.audio_length = audio_length
+
+            
+            with col8:
+                options_2 = st.selectbox(
+                    'In a tone of',
+                    ['Informal', 'Professional', 'Humorous'],
+                    key='opt3'
+                )
+                day = st.select_slider('Information volume', options=['small', 'medium', 'large'],value=('medium'))
+                if day == 'small':
+                    st.session_state.day = 2
+                    st.session_state.arxiv = 2
+                elif day == 'medium':
+                    st.session_state.day = 4
+                    st.session_state.arxiv = 3
+                else:
+                    st.session_state.day = 6
+                    st.session_state.arxiv = 4
+
+        with col5:
+            pass
+
+
+    with button_placeholder:     
+        # 创建按钮
+        if st.button("👆 Double-Click Generation"):
+            st.session_state.page = "two"
+            st.session_state.language = language
+            if options_2 == 'Informal':
+                st.session_state.tone = """read news and present them in a casual and conversational tone. 
+                You should use everyday language, contractions, and slang to engage the audience and make the news more relatable. """
+            elif options_2 == 'Humorous':
+                st.session_state.tone = """read news and present in a comical and amusing tone. 
+                You should be able to recognize and exaggerate humorous elements of each article along with jokes and deliver them in a way 
+                that will make the audience laugh."""
+
+
+    st.markdown("""
+        <style>
+            .footer {
+                position: fixed;
+                bottom: 0;
+                left: 10px;
+                width: auto;
+                background-color: transparent;
+                text-align: right;
+                padding-right: 10px;
+                padding-bottom: 10px;
+            }
+        </style>
+        <div class="footer">Made with ❤️ by Xuying Li</div>
+    """, unsafe_allow_html=True)
+        
+        
+      
+def compute_page(st, **state):
+    # Include Font Awesome CSS
+    st.markdown(
+        """
+        <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.3/css/all.min.css">
+        """,
+        unsafe_allow_html=True,
+    )
+
+    # Style and position the GitHub and Twitter icons at the bottom left corner
+    st.markdown(
+        """
+        <style>
+            .social-icons {
+                gap: 10px;  # Space between icons
+            }
+            .social-icons a i {
+                color: #6c6c6c;
+            }
+            </style>
+            """,
+            unsafe_allow_html=True,
+        )
+
+    # Add the GitHub and Twitter icons with hyperlinks
+    github_url = "https://github.com/xl631212/llm_newsletter/tree/main"  # replace with your GitHub repo URL
+    twitter_url = "https://twitter.com/li_xuying"  # replace with your Twitter profile URL
+
+    st.markdown("""
+    <h1 style='text-align: center; color: black;'>
+        Your Personal <span style='color: #FF4B4B; font-size: 1.25em;'>AI News</span> Podcast
+    </h1>
+    <div class="social-icons" style='text-align: center; color: black;'>
+            <a href="https://github.com/xl631212/llm_newsletter/tree/main" target="_blank"><i class="fab fa-github fa-2x"></i></a>
+            <a href="https://twitter.com/li_xuying" target="_blank"><i class="fab fa-twitter fa-2x"></i></a>
+        </div>
+    """, 
+    unsafe_allow_html=True
+    )
+   
+    st.markdown("""
+    <style>
+        /* This styles the main content excluding h1 and h2 */
+        #root .block-container {
+            width: 75%;
+            margin: auto;
+        }
+    </style>
+    """, unsafe_allow_html=True)
+    radio_placeholder = st.empty()
+    progress_placeholder = st.empty()
+    progress_text = "Searching for Openai Blog..."
+    my_bar = progress_placeholder.progress(0, text=progress_text)
+    openai_blog_url = get_latest_openai_blog_url()
+    if openai_blog_url:
+        openai_title = get_h1_from_url(openai_blog_url)
+        openai_blog = summarize_website_content(openai_blog_url)
+
+    my_bar.progress(10, text="Searching for Microsoft Blog...")
+    url = "https://blogs.microsoft.com/"
+    M_title, Microsoft_link = extract_blog_link_info(url)
+    bair_blog = summarize_website_content(Microsoft_link)
+
+
+    my_bar.progress(20, text="Searching for Amazon Blog...")
+    A_title, A_link = get_latest_aws_ml_blog()
+    mit_blog = summarize_website_content(A_link)
+
+    my_bar.progress(30, text="Searching for Apple Blog...")
+    url = 'https://machinelearning.apple.com/'
+    
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+    
+    # 根据提供的HTML片段，定位到文章的标题和链接
+    article = soup.select_one('h3.post-title a')
+    apple_link = 'https://machinelearning.apple.com'+ article['href']
+    
+    Apple_blog_title = article.text
+    Apple_blog = summarize_website_content(apple_link)
+
+    my_bar.progress(35, text='Searching for machine learning street talk...')
+    channel_id = "UCMLtBahI5DMrt0NPvDSoIRQ"
+    playlist = Playlist(playlist_from_channel_id(channel_id))
+
+    while playlist.hasMoreVideos:
+        playlist.getNextVideos()
+
+    machine_title = playlist.videos[0]['title']
+    machine_link = playlist.videos[0]['link']
+    machine_learning_boardcast = summarize_website_content(machine_link)
+
+    my_bar.progress(40, text='Searching for lex friman boardcast...')
+    url = "https://lexfridman.com/podcast/"
+    link = get_transcript_link(url)
+    L_title = get_h1_text(link)
+    youtube_link = get_youtube_link(url)
+    lexi_boardcast = summarize_website_content(youtube_link)
+    
+
+    my_bar.progress(50, text="Searching for arxiv ...")
+    search = arxiv.Search(
+        query = "AI, LLM, machine learning, NLP",
+        max_results = st.session_state.arxiv,
+        sort_by = arxiv.SortCriterion.SubmittedDate
+    )
+    ariv_essay = ''
+    for result in search.results():
+        ariv_essay += result.summary
+    
+    my_bar.progress(60, text="Searching Google News...")
+    google_news = fetch_gnews_links(query='AI, LLM, Machine learning', max_results = st.session_state.day)
+
+    my_bar.progress(70, text="Searching Techcrunch...")
+    url = 'https://techcrunch.com/category/artificial-intelligence/'
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+    articles = soup.select('.post-block__title a')
+
+    data_mrf_link, h_title = articles[0]['href'],articles[0].text
+    h_content = summarize_website_content(data_mrf_link)
+
+    my_bar.progress(75, text="Nvidia Podcast...")
+    url = "https://blogs.nvidia.com/ai-podcast/"
+    target_link = "https://blogs.nvidia.com/ai-podcast/"
+    target_text = "AI Podcast"
+    next_link, Nvidia_title = find_next_link_text(url, target_link, target_text)
+    n_content = summarize_website_content(next_link)
+
+
+    my_bar.progress(80, text="Writing Newsletter...")
+
+    query = n_content + str(google_news['summary'])  + str(mit_blog)  + str(h_content)\
+              + openai_blog + 'new arxiv essay' + ariv_essay
+    
+    query = query.replace('<|endoftext|>', '')
+    messages =  [
+                    {'role':'system',
+                    'content': system_message + "keep it equal to {} words.".format(st.session_state.audio_length) + st.session_state.tone},
+                    {'role':'user',
+                    'content': f"【{query}】"},]
+    response = get_completion_from_messages(messages)
+    
+    my_bar.progress(90, text="Generating Podcast...")
+    if st.session_state.language == 'English':
+        updated = response.replace('-', '').replace('--', '').replace('"', '').replace('“', '')
+        command = f'edge-tts --text "{updated}" --write-media hello.mp3'
+        subprocess.run(command, shell=True)
+        my_bar.progress(90, text="Generating Summary...")
+
+        query = response
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_2},
+                        {'role':'user',
+                        'content': f"【{query}】"},]
+        summary = get_completion_from_messages(messages)
+    
+    else:
+        before = response
+        before = before.replace('<|endoftext|>', '')
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{before}】"},]
+        after = get_completion_from_messages(messages)
+        # 构建 edge-tts 命令
+        command = f'edge-tts --voice zh-CN-XiaoyiNeural --text "{after}" --write-media hello2.mp3'
+        # 使用 subprocess 运行命令
+        subprocess.run(command, shell=True)
+
+
+    my_bar.progress(100, text="Almost there...")
+
+    with radio_placeholder:
+        #audio_file = open('hello.mp3', 'rb')
+        #audio_bytes = audio_file.read()
+        #st.audio(audio_bytes, format='wav')
+        if st.session_state.language == 'English':
+          autoplay_audio("hello.mp3")
+        else:
+          autoplay_audio("hello2.mp3")
+        
+
+    my_bar.empty()
+    if st.session_state.language == 'English':
+        st.subheader('Summary and Commentary', divider='rainbow')
+        st.markdown(summary)
+
+        st.subheader('Technology News', divider='red')
+        for i in range(len(google_news['title'])):
+            if len(google_news['summary'][i]) > 100:
+                st.markdown(f'<a href="{google_news["url"][i]}" style="color: #2859C0; text-decoration: none; \
+                font-size: 20px;font-weight: bold;"> {google_news["title"][i]} </a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Google News</span>', unsafe_allow_html=True)
+                st.markdown(google_news['summary'][i])
+        
+        st.markdown(f'<a href="{data_mrf_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{h_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Techcrunch</span>', unsafe_allow_html=True)
+        st.markdown(h_content)
+
+        st.subheader('Podcast and Speeches', divider='orange')
+
+        st.markdown(f'<a href="{youtube_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{L_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Lex Fridman</span>', unsafe_allow_html=True)
+        st.markdown(lexi_boardcast)
+
+        st.markdown(f'<a href="{next_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{Nvidia_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Nvidia</span>', unsafe_allow_html=True)
+        st.markdown(n_content)
+
+        st.markdown(f'<a href="{machine_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{machine_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Machine Learning Street Talk</span>', unsafe_allow_html=True)
+        st.markdown(machine_learning_boardcast)
+      
+        st.subheader('Technology Blogs', divider='green')
+        st.markdown(f'<a href= {openai_blog_url} style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {openai_title}</a>\
+                <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Openai</span>', unsafe_allow_html=True)
+        st.markdown(openai_blog)  
+
+        st.markdown(f'<a href={Microsoft_link} style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {M_title}</a>\
+                <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Microsoft</span>', unsafe_allow_html=True)
+        st.markdown(bair_blog)
+        
+        st.markdown(f'<a href="https://aws.amazon.com/blogs/machine-learning/" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {A_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Amazon</span>', unsafe_allow_html=True)
+        st.markdown(mit_blog)
+
+        st.markdown(
+            f'<a href={apple_link} style="color:  #2859C0; text-decoration: none; font-size: 20px; font-weight: bold;">{Apple_blog_title}</a>\
+            <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Apple</span>', 
+            unsafe_allow_html=True
+        )
+        st.markdown(Apple_blog)
+
+
+        st.subheader('Cutting-edge Papers', divider='green')
+        for result in search.results():
+            st.markdown(f'<a href="{result.entry_id}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {result.title} </a>\
+             <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">{result.primary_category}</span>\
+                ', unsafe_allow_html=True)
+            st.markdown(result.summary)
+            
+
+    elif st.session_state.language == '中文':
+        st.subheader('摘要与评论', divider='rainbow')
+        summary = after.replace('<|endoftext|>', '')
+        st.markdown(summary)
+        st.subheader('科技新闻', divider='rainbow')
+        for i in range(len(google_news['title'])):
+            title = google_news['title'][i]
+            messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{title}】"},]
+            
+            title = get_completion_from_messages(messages)
+            news_summary = google_news['summary'][i]
+            messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+            news_summary = get_completion_from_messages(messages)
+ 
+            st.markdown(f'<a href="{google_news["url"][i]}" style="color: #2859C0; text-decoration: none; \
+                font-size: 20px;font-weight: bold;"> {title} </a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Google News</span>', unsafe_allow_html=True)
+            st.markdown(news_summary)
+        news_summary = h_title
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        h_title = get_completion_from_messages(messages)
+        st.markdown(f'<a href="{data_mrf_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{h_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Techcrunch</span>', unsafe_allow_html=True)
+        news_summary = h_content
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        h_content = get_completion_from_messages(messages)
+        st.markdown(h_content)
+
+        st.subheader('播客与博客', divider='orange')
+        news_summary = L_title
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        L_title = get_completion_from_messages(messages)
+        st.markdown(f'<a href="{youtube_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{L_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Lex Fridman</span>', unsafe_allow_html=True)
+        news_summary = lexi_boardcast
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        lexi_boardcast = get_completion_from_messages(messages)
+        st.markdown(lexi_boardcast)
+
+        news_summary = Nvidia_title
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        Nvidia_title = get_completion_from_messages(messages)
+        st.markdown(f'<a href="{next_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{Nvidia_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Nvidia</span>', unsafe_allow_html=True)
+        news_summary = n_content
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        n_content = get_completion_from_messages(messages)
+        st.markdown(n_content)
+
+        news_summary = machine_title
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        machine_title = get_completion_from_messages(messages)
+        st.markdown(f'<a href="{machine_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;">{machine_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Machine Learning Street Talk</span>', unsafe_allow_html=True)
+        
+        news_summary = machine_learning_boardcast
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{news_summary}】"},]
+        machine_learning_boardcast = get_completion_from_messages(messages)
+        st.markdown(machine_learning_boardcast)
+
+        st.subheader('科技博客', divider='green')
+        openai_blog = openai_blog.replace('<|endoftext|>', '')
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"{openai_blog}"},]
+        openai_blog = get_completion_from_messages(messages)
+
+
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{openai_title}】"},]
+        openai_title = get_completion_from_messages(messages)
+
+        st.markdown(f'<a href= {openai_blog_url} style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {openai_title}</a>\
+                <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Openai</span>', unsafe_allow_html=True)
+        st.markdown(openai_blog)
+
+        bair_blog = bair_blog.replace('<|endoftext|>', '')
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{bair_blog}】"},]
+        bair_blog = get_completion_from_messages(messages)
+
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"{M_title}"},]
+        M_title = get_completion_from_messages(messages)
+        st.markdown(f'<a href={link} style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {M_title}</a>\
+                <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Microsoft</span>', unsafe_allow_html=True)
+        st.markdown(bair_blog)
+
+        mit_blog = mit_blog.replace('<|endoftext|>', '')
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"【{mit_blog}】"},]
+        mit_blog = get_completion_from_messages(messages)
+
+        messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"{A_title}"},]
+        A_title = get_completion_from_messages(messages)
+        st.markdown(f'<a href="{A_link}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {A_title}</a>\
+                    <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">Amazon</span>', unsafe_allow_html=True)
+        st.markdown(mit_blog)
+        
+
+        st.subheader('尖端论文', divider='green')
+        for result in search.results():
+            title = result.title
+            result_summary = result.summary
+            messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"{title}"},]
+            result_title = get_completion_from_messages(messages)
+
+            messages =  [
+                        {'role':'system',
+                        'content': system_message_3},
+                        {'role':'user',
+                        'content': f"{result_summary}"},]
+            result_summary = get_completion_from_messages(messages)
+
+            st.markdown(f'<a href="{result.entry_id}" style="color:  #2859C0; text-decoration: none; \
+            font-size: 20px;font-weight: bold;"> {result_title} </a>\
+             <span style="margin-left: 10px; background-color: white; padding: 0px 7px; border: 1px solid rgb(251, 88, 88); border-radius: 20px; font-size: 7px; color: rgb(251, 88, 88)">{result.primary_category}</span>\
+                ', unsafe_allow_html=True)
+            st.markdown(result_summary)
+    st.markdown("""
+    <style>
+        .footer {
+            position: fixed;
+            bottom: 0;
+            left: 10px;
+            width: auto;
+            background-color: transparent;
+            text-align: left;
+            padding-left: 10px;
+            padding-top: 10px;
+        }
+    </style>
+    <div class="footer">Made with ❤️ by Xuying Li</div>
+""", unsafe_allow_html=True)
+
+def page_one():
+    input_page(st)
+
+def page_two():
+    compute_page(st)
+
+
+def main():
+    # 初始化session状态
+    if "page" not in st.session_state:
+        st.session_state.page = "one"
+
+    if "choice" not in st.session_state:
+        st.session_state.choice = ""
+    
+    if "language" not in st.session_state:
+        st.session_state.language = "English"
+
+    if "audio_length" not in st.session_state:
+        st.session_state.audio_length = '5'
+
+    if "day" not in st.session_state:
+        st.session_state.day = 0
+        st.session_state.arxiv = 0
+    
+    if "tone" not in st.session_state:
+        st.session_state.tone = ''
+
+
+    # 根据session状态来渲染页面
+    if st.session_state.page == "one":
+        page_one()
+    elif st.session_state.page == "two":
+        page_two()
+
+if __name__ == "__main__":
+    st.set_page_config(layout="wide", initial_sidebar_state="collapsed")
+    main()