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import gradio as gr |
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import openai |
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import yt_dlp |
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import os |
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import io |
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import tempfile |
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from pydub import AudioSegment |
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def split_audio(file_path, chunk_length_ms): |
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audio = AudioSegment.from_file(file_path) |
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duration = len(audio) |
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chunks = [] |
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start_time = 0 |
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while start_time < duration: |
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end_time = start_time + chunk_length_ms |
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if end_time > duration: |
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end_time = duration |
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chunk = audio[start_time:end_time] |
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chunks.append(chunk) |
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start_time += chunk_length_ms |
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return chunks |
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def split_string_by_tokens(text, max_tokens=500): |
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words = text.split() |
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chunks = [] |
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current_chunk = [] |
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for word in words: |
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current_chunk.append(word) |
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if len(current_chunk) >= max_tokens: |
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chunks.append(' '.join(current_chunk)) |
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current_chunk = [] |
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if current_chunk: |
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chunks.append(' '.join(current_chunk)) |
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return chunks |
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openai.api_key = os.environ['OPENAI_API_KEY'] |
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def asr(url): |
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os.system("rm *audio_download*") |
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ydl_opts = { |
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'format': 'bestaudio/best', |
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'outtmpl': 'audio_downloaded.%(ext)s', |
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'no_continue': True, |
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} |
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ydl = yt_dlp.YoutubeDL(ydl_opts) |
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info_dict = ydl.extract_info(url, download=True) |
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if info_dict is not None: |
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audio_file_name = "audio_downloaded.{}".format(info_dict["ext"]) |
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else: |
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return "下载音频发生错误，请确认链接再试一次。", "Error downloading the audio. Check the URL and try again." |
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yield "下载视频完成. 开始分割视频...", "" |
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chunks = split_audio(audio_file_name, chunk_length_ms=30 * 1000) |
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transcripts = [] |
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for idx, chunk in enumerate(chunks): |
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temp_file_path = None |
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with tempfile.NamedTemporaryFile(mode="wb", suffix=".wav", delete=False) as temp_file: |
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temp_file_path = temp_file.name |
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chunk.export(temp_file.name, format="wav") |
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with open(temp_file_path, "rb") as temp_file: |
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transcript = openai.Audio.transcribe("whisper-1", temp_file) |
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os.remove(temp_file_path) |
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transcripts.append(transcript["text"]) |
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yield "请耐心等待语音识别完成...({}/{})".format(idx + 1, len(chunks)), " ".join(transcripts) |
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os.system("rm {}".format(audio_file_name)) |
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translations = [] |
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full_transcript = " ".join(transcripts) |
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transcript_chunks = split_string_by_tokens(full_transcript, max_tokens=500) |
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yield "语音识别完成, 开始翻译...(0/{})".format(len(transcript_chunks)), full_transcript |
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for idx, transcript in enumerate(transcript_chunks): |
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output = openai.ChatCompletion.create( |
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model="gpt-3.5-turbo", |
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messages=[ |
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{"role": "user", |
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"content": "Transcript: {transcript}. \n Translate the video conversation transcript into fluent Chinese. Chinese: ".format(transcript=transcript)}, |
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], |
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stream=True, |
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) |
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for event in output: |
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translations.append(event["choices"][0].get("delta", "").get("content", "")) |
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yield "请耐心等候翻译：({}/{})...".format(idx+1, len(transcript_chunks)) + "".join(translations), " ".join(transcripts) |
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full_translation = "".join(translations) |
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yield full_translation, full_transcript |
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title = """ |
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轻声细译""" |
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instruction = """ |
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<div style="border: 2px solid #000; padding: 10px; border-radius: 5px;"> |
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视频翻译 (video-translation)：输入视频链接，进行中文翻译 <span style="color: grey;">-- powered by OpenAI Whisper & ChatGPT.</span>.<br> |
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1.将视频链接（支持Twitter、YouTube）复制粘贴至输入框，点击提交（Submit）即可; |
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</div>""" |
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demo = gr.Interface(fn=asr, |
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inputs=gr.inputs.Textbox(label="粘贴视频链接"), |
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outputs=[ |
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gr.outputs.Textbox(label="翻译"), |
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gr.outputs.Textbox(label="音频转录") |
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], |
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title=title, |
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description=instruction, |
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theme="JohnSmith9982/small_and_pretty") |
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demo.queue() |
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demo.launch() |
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