Merge remote-tracking branch 'origin/feature/knowledge_lxc' into develop
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@@ -60,6 +60,34 @@ class QWenSeq2txt(Base):
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from dashscope import MultiModalConversation
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audio_path = f"file://{audio_path}"
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prompt_ch = """
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你是一名专业的音频转录助手,能够将MP3音频文件的内容转写为文本,并**精确标记每句话或每个段落对应的时间戳**(开始时间-结束时间)。\n
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**任务要求**:
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1.输入是MP3,解析带时间戳的文本。
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2.时间戳格式为 `[HH:MM:SS.mmm]`(毫秒可选),例如 `[00:01:23.456]`。
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3.时间戳需尽可能贴近实际语音的起止时间,误差不超过1秒。
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4.如果无法确定具体时间,请根据上下文合理估算。
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5.最后总结:这段音频在说什么?
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**示例输出**:
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[00:00:00.000] 今天天气真好,
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[00:00:02.500] 我们一起去公园散步吧。
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[00:00:05.800] 公园里的花开得非常漂亮。
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这段音频讲述的是一个关于**“吃水不忘挖井人”**的感人故事,主 ..."""
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prompt_en = """
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You are a professional audio transcription assistant, capable of transcribing the content of MP3 audio files into text and **precisely marking the timestamps (start time - end time) corresponding to each sentence or paragraph**.
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**Task requirements**:
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1. Input is MP3, parse text with timestamps.
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2. The timestamp format is `[HH:MM:SS.mmm]` (milliseconds are optional), for example, `[00:01:23.456]`.
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3. The timestamp should be as close as possible to the actual start and end time of the voice, with an error not exceeding 1 second.
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4. If a specific time cannot be determined, please make a reasonable estimation based on the context.
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5. Final summary: What is this audio talking about?
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**Example Output**:
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[00:00:00.000] The weather is really nice today,
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[00:00:02.500] let's go for a walk in the park together.
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[00:00:05.800] The flowers in the park are blooming beautifully.
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This audio tells a touching story about **"Remembering the one who dug the well when drinking water"** .."""
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messages = [
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{
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"role": "user",
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@@ -68,7 +96,7 @@ class QWenSeq2txt(Base):
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"audio": audio_path
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},
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{
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"text": "这段音频在说什么?" if self.lang.lower() == "chinese" else "What is this audio saying?",
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"text": prompt_ch if self.lang.lower() == "chinese" else prompt_en,
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},
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],
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}
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