chyoso-toolkit/chyoso_toolkit_ui.py

import gradio as gr
import subprocess
import os


def convert_to_wav(audio_file):
    # 使用 ffmpeg 将音频文件转换为 wav 格式
    output_wav_file = "output.wav"
    print(f"开始转换音频文件 {audio_file} 为 WAV 格式...")
    subprocess.run([
        "ffmpeg", "-y", "-i", audio_file,
        "-ac", "1",
        "-ar", "16000",
        output_wav_file
    ])
    print(f"音频文件 {audio_file} 已转换为 WAV 格式，输出文件为 {output_wav_file}")
    return output_wav_file


def transcribe_audio(wav_file, original_filename, offset_time, duration_time):
    # 调用 whisper 命令行程序进行转写
    whisper_cmd = [
        "/home/tmfc/apps/whisper/main",
        "--language", "Chinese",
        "-otxt",
        "-ot", str(offset_time * 1000),
        "-d", str(duration_time * 1000),
        "-of", "/home/tmfc/apps/whisper/" + original_filename,
        "-m", "/home/tmfc/apps/whisper/models/ggml-large-v3-q5_0.bin",
        wav_file
    ]
    print(whisper_cmd)
    print(f"开始转写音频文件 {wav_file}...")
    result = subprocess.run(whisper_cmd, capture_output=True, text=True)
    print(result)
    # 将转写结果保存为 txt 文件
    #    txt_file = "transcription.txt"
    #    with open(txt_file, "w") as f:
    #        f.write(result.stdout)

    txt_file = original_filename + ".txt"
    print(f"音频文件 {wav_file} 转写完成，结果已保存为 {txt_file}")

    return txt_file


def process_audio(audio_file, offset_time, duration_time):
    print("开始处理音频文件...")
    # 获取上传的文件名
    original_filename = os.path.basename(audio_file)

    # 转换音频文件为 wav 格式
    wav_file = convert_to_wav(audio_file)

    # 转写音频文件
    txt_file = transcribe_audio(wav_file, original_filename, offset_time, duration_time)

    print("音频文件处理完成")
    return txt_file


def direct_transcribe(audio_file, offset_time, duration_time):
    print("开始直接转写音频文件...")

    # 转写音频文件
    txt_file = transcribe_audio("output.wav", "output.wav", offset_time, duration_time)

    print("音频文件直接转写完成")
    return txt_file


batch_directory = '/mnt/d/share/audio/'


def list_files():
    # 获取目录下的所有文件
    files = os.listdir(batch_directory)
    # 过滤掉目录，只保留文件
    files = [f for f in files if os.path.isfile(os.path.join(batch_directory, f)) and f.lower().endswith(('.mp3', '.m4a'))]
    return files


log_content = ""


def batch_transcribe():
    global log_content
    files = list_files()
    result_file = []
    for file in files:
        # 转换音频文件为 wav 格式
        log_entry = "转换" + file + "为 wav\n"
        log_content += log_entry
        wav_file = convert_to_wav(batch_directory + file)
        log_entry = "转换wav成功，开始转写\n"
        log_content += log_entry
        # 转写音频文件
        txt_file = transcribe_audio(wav_file, file, 10, 0)
        log_entry = "转写 " + file + "完成\n"
        log_content += log_entry
        result_file.append(txt_file)
    return result_file


def display_files():
    files = list_files()
    return "\n".join(files)


def get_log():
    global log_content
    return log_content


def update_log_output():
    return gr.update(value=get_log())


def convert_to_docx(text):
    if text.strip() == "":
        return "输入框不能为空！"

    # 将输入内容写入 file.md 文件
    with open("file.md", "w") as file:
        file.write(text)

    # 使用 pandoc 将 file.md 转换为 file.docx
    try:
        subprocess.run(["pandoc", "file.md", "-o", "file.docx"], check=True)
    except subprocess.CalledProcessError as e:
        return f"转换失败: {e}"

    # 返回 file.docx 文件供用户下载
    return "file.docx"


with gr.Blocks() as iface:
    gr.Markdown("# 大模型工具集")
    with gr.Tabs():
        with gr.TabItem("音频转写"):
            with gr.Row():
                audio_input = gr.Audio(type="filepath", label="上传音频文件")
                with gr.Column():
                    offset_input = gr.Number(label="偏移时间 (秒)")
                    duration_input = gr.Number(label="转写时长 (秒)")

            with gr.Row():
                process_button = gr.Button("处理并转写")
                direct_transcribe_button = gr.Button("直接转写")

            output_file = gr.File(label="转写结果")

            process_button.click(process_audio, inputs=[audio_input, offset_input, duration_input], outputs=output_file)
            direct_transcribe_button.click(direct_transcribe, inputs=[audio_input, offset_input, duration_input],
                                           outputs=output_file)
        with gr.TabItem("音频批量转写"):
            with gr.Row():
                link_upload = gr.HTML(value='<a href="https://webd.willking.tech" target="_blank">点击上传文件</a>')
            with gr.Row():
                file_list = gr.Textbox(label="文件列表")
                with gr.Column():
                    list_file_button = gr.Button("刷新文件")
                    batch_process_button = gr.Button("批量处理")
                with gr.Column():
                    batch_output_file = gr.File(label="批量转写结果")

            with gr.Row():
                log_output = gr.Textbox(label="日志信息", lines=10)

            list_file_button.click(fn=display_files, outputs=file_list)

            batch_process_button.click(batch_transcribe, outputs=batch_output_file)

        with gr.Tab("Markdown 转 Word"):
            gr.Markdown("## Markdown 转 Word 转换器")
            with gr.Row():
                text_input = gr.Textbox(lines=10, placeholder="请在此输入 Markdown 内容...")
            with gr.Row():
                convert_button = gr.Button("转换")
            with gr.Row():
                output_file = gr.File(label="下载转换后的文件")

            convert_button.click(convert_to_docx, inputs=text_input, outputs=output_file)

    iface.load(fn=update_log_output, outputs=[log_output], every=1)

iface.launch(server_name="0.0.0.0")