app.py

import gradio as gr
import os
import re
import json
import time
from google import genai


# Filter songs based on region and time period
def filter_songs(region, time_period):
    time_map = {
        "过去7天": 7,
        "过去30天": 30
    }
    region_map = {
        "美国": "us",
        "英国": "uk",
        "韩国": "kr",
        "日本": "jp"
    }
    
    file_name = f"trend_data_{region_map[region]}_{time_map[time_period]}.json"
    with open(file_name, "r", encoding="utf-8") as file:
        data = json.load(file)  # 解析 JSON 文件

    return data


# Initial song data
ALL_SONGS = filter_songs("美国", "过去7天")

# Simulate API call for song analysis
def analyze_song(song_name):
    prompt = """
    根据我上传的歌曲音频，站在乐评人的角度进行专业点评，要求包含两方面信息：
    ## 一. 对歌曲的详细解析，必须使用中文描述，需包含以下方面（确保每个部分尽可能详细和具体，以生成精准的音乐评价）：
    1. 流派/风格 (Genre/Style)：{在此处填写一个或多个音乐流派，多个流派可以用逗号或 "和" 连接，例如：classic rock, synthwave 和 nostalgic}
    2. 乐器 (Instrumentation)
        - 主要乐器：{列出主要乐器，并用形容词修饰其音色或演奏方式，例如：distorted electric guitar, soft piano melody}
        - 次要乐器（可选）：{列出次要乐器，同样可以添加修饰，例如：pulsating bass, rhythmic percussion}
    3. 人声 (Vocal Style) (可选)
        - 性别：{male/female/无}
        - 音色/风格：{用形容词描述人声的特点，例如：raspy, warm, soulful, slight reverb}
        - 演唱方式（可选）：{例如：call-and-response vocals, harmonies, spoken word}
    4. 情绪/氛围 (Mood/Atmosphere)：{使用形容词或短语描述音乐的整体感觉，例如：high-energy, smooth, dreamy, uplifting, melancholic}
        - 场景描述（可选）：{用简短的场景描述来进一步强化氛围，例如：late-night lounge setting, driving down a desert highway}
    5. 具体元素/参考 (Specific Elements/References) (可选)：{提供更具体的风格指导、年代参考或特定元素，例如：anthemic chorus, '80s stadium rock, 80s-inspired, reminiscent of Vangelis}
    6. 节奏/动态 (Tempo/Dynamics) (可选)：使用动词或形容词描述节奏的特点, 或乐器动态, 例如: Pulsating, driving, laid-back, syncopated，乐器动态: Crescendo, diminuendo, staccato 等
    
    基于上述详细解析，总结一句用于音乐生成的英文文本提示词，不要超过180个字符，必须使用英文描述，示例如下：An 80s-inspired synthwave track with analog synthesizers, pulsating bass, and dreamy atmospheric pads. Male vocals with slight reverb for a nostalgic, futuristic feel.

    最终使用json返回内容，json格式示例如下，禁止其他多余输出:
    {
        "chinese_description": "..."
        "english_prompt": "..."
    }
    """
    client = genai.Client(api_key=os.getenv("GOOGLE_GEN_KEY"))

    myfile = client.files.upload(file=f'media/{song_name}.mp3')

    response = client.models.generate_content(
        model='gemini-2.0-flash',
        contents=[prompt, myfile]
    )
    text = response.text
    print(text)
    match = re.search(r'```json\n(.*?)\n```', text, re.DOTALL)
    if match:
        json_str = match.group(1)
        try:
            result = json.loads(json_str)
        except json.JSONDecodeError as e:
            print(f"JSON parsing error: {e}")
            
    return {
        "song_description": result["chinese_description"],
        "suno_prompt": result["english_prompt"]
    }

# Simulate Suno API call
def generate_similar_song(suno_prompt):
    # Simulate API call delay
    time.sleep(3)
    
    # Simulated response
    return {
        "audio_url": "https://sf16-ies-music-sg.tiktokcdn.com/obj/tos-alisg-ve-2774/oYYOWM1aKGyB8Eixn0hiAfhWsAjzswMoIItQMI",
        "status": "success"
    }

# Create song list HTML
def create_song_list(songs):
    html = """
    <style>
    .song-container {
        display: flex;
        flex-direction: column;
        gap: 16px;
        padding: 16px;
    }
    .song-item {
        display: flex;
        align-items: center;
        gap: 16px;
        padding: 12px;
        border-radius: 8px;
        background-color: #f9f9f9;
        box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
    }
    .rank {
        font-size: 24px;
        font-weight: bold;
        min-width: 40px;
        text-align: center;
    }
    .cover {
        width: 80px;
        height: 80px;
        border-radius: 4px;
        object-fit: cover;
    }
    .song-info {
        flex: 1;
    }
    .song-name {
        font-size: 18px;
        font-weight: bold;
        margin-bottom: 4px;
    }
    .video-count {
        color: #666;
        font-size: 14px;
    }
    .button-group {
        display: flex;
        gap: 8px;
    }
    .button {
        padding: 8px 12px;
        border-radius: 4px;
        border: none;
        cursor: pointer;
        font-size: 14px;
        font-weight: bold;
    }
    .tiktok-btn {
        color: white;
    }
    .play-btn {
        background-color: #1db954;
        color: white;
    }
    .stats-btn {
        background-color: #0077b5;
        color: white;
    }
    .analyze-btn {
        background-color: #6c5ce7;
        color: white;
    }
    </style>
    <div class="song-container">
    """
    # <div class="video-count">{song['video_count']}</div>
    # <button class="button play-btn" onclick='playSong("{song['title']}")'>播放</button>
    # <button class="button analyze-btn" onclick='analyzeSong("{song['title']}")'>分析歌曲</button>
    for song in songs:
        html += f"""
        <div class="song-item" id="song-{song['rank']}">
            <div class="rank">{song['rank']}</div>
            <img class="cover" src="{song['cover_url']}" alt="{song['title']}">
            <div class="song-info">
                <div class="song-name">{song['title']} - {song['author']}</div>
               
            </div>
            <div class="button-group">
                <a href="{song['link']}" target="_blank" class="button tiktok-btn">TikTok地址</a>
            </div>
        </div>
        """
    
    html += "</div>"
    
    return html

# Main app function
def app():
    # Create the Gradio interface
    with gr.Blocks() as demo:
        # App title
        gr.Markdown("# TikTok Song Trends Analyzer")
        
        # Main tabs
        with gr.Tabs():
            # Song trends tab
            with gr.TabItem("Song Trends"):
                with gr.Row():
                    region_dropdown = gr.Dropdown(
                        choices=["美国", "英国", "韩国", "日本"],
                        #choices=["All Regions", "US", "UK", "JP", "KR", "CN", "IN", "BR", "FR", "DE", "ES"],
                        value="美国",
                        label="Region"
                    )
                    time_period = gr.Dropdown(
                        choices=["过去7天", "过去30天"],
                        value="过去7天",
                        label="Time Period"
                    )
                
                # Song list container
                song_list = gr.HTML(create_song_list(ALL_SONGS))
                
                # Update song list when filters change
                def update_song_list(region, time_period):
                    filtered_songs = filter_songs(region, time_period)
                    return create_song_list(filtered_songs)
                
                region_dropdown.change(
                    fn=update_song_list,
                    inputs=[region_dropdown, time_period],
                    outputs=song_list
                )
                
                time_period.change(
                    fn=update_song_list,
                    inputs=[region_dropdown, time_period],
                    outputs=song_list
                )
            
            # Song analysis tab
            with gr.TabItem("Song Analysis"):
                with gr.Row():
                    with gr.Column(scale=2):
                        song_name = gr.Dropdown(
                            choices=list(map(lambda x: x["title"], ALL_SONGS)),
                            label="Select a Song",
                            interactive=True
                        )
                        analysis_btn = gr.Button("分析歌曲")
                        song_description = gr.Markdown(label="Song Description")
                        suno_prompt = gr.Textbox(label="Suno Prompt", interactive=False, lines=5)
                    # with gr.Column(scale=2):
                    #     suno_prompt = gr.Textbox(label="Suno Prompt", interactive=False, lines=5)
                    #     generate_btn = gr.Button("生成相似歌曲")
                
                # Audio player for generated song
                audio_player = gr.Audio(label="Generated Song", type="filepath", interactive=False)
                
                # Handle song analysis
                def do_song_analysis(song_name):
                    if not song_name:
                        return "", "", "", "Please select a song from the trends list."
                    
                    analysis_result = analyze_song(song_name)
                    
                    return analysis_result["song_description"], analysis_result["suno_prompt"], f'media/{song_name}.mp3'
                
                # Handle similar song generation
                def do_generate_similar(suno_prompt):
                    if not suno_prompt:
                        return None, "Please analyze a song first to get a Suno prompt."
                    
                    result = generate_similar_song(suno_prompt)
                    
                    if result["status"] == "success":
                        return result["audio_url"]
                    else:
                        return None
                
                # generate_btn.click(
                #     fn=do_generate_similar,
                #     inputs=suno_prompt,
                #     outputs=[audio_player]
                # )
                
                analysis_btn.click(
                    fn=do_song_analysis,
                    inputs=song_name,
                    outputs=[song_description, suno_prompt, audio_player]
                )
        
    # Launch the app
    demo.launch()

if __name__ == "__main__":
    app()