DEPRECATION: Loading egg at /usr/local/lib/python3.12/dist-packages/cloud_init-20.3-py3.12.egg is deprecated. pip 24.3 will enforce this behaviour change. A possible replacement is to use pip for package installation.. Discussion can be found at https://github.com/pypa/pip/issues/12330
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv


exec

# 测试 transformers 是否可用
python3 -c "import transformers; print(transformers.__version__)" 2>&1


好！现在重写 `transcribe_local_whisper` 直接用 transformers 的 whisper pipeline，不再依赖 pywhispercpp：


    print("☁  Gemini 转录中（有标点）...", flush=True)
    client = genai.Client(api_key=api_key)
    audio_file = client.files.upload(file=pathlib.Path(audio_path))
    response = client.models.generate_content(
        model="gemini-2.5-flash",
        contents=[
            audio_file,
            "请将这段音频完整逐字转录成文字。如果是中文就输出中文，如果是英文就输出英文。"
            "不要总结，保留原话，包括语气词和口语表达。"
        ]
    )
    return response.text

# ─── 转录引擎：mlx-whisper（本地）────────────────────────

def transcribe_mlx(audio_path):
    """用 mlx-whisper 本地转录，无标点"""
    try:
        import mlx_whisper
    except ImportError:
        raise RuntimeError("mlx-whisper 未安装，请运行：pip3 install mlx-whisper")

    print("🖥  本地 mlx-whisper 转录中（无标点，首次需下载模型）...", flush=True)
    result = mlx_whisper.transcribe(
        audio_path,
        path_or_hf_repo="mlx-community/whisper-turbo",
        language=None,   # 自动检测语言
        verbose=False
    )
    return result["text"]

# ─── 转录引擎：pywhispercpp（本地，所有平台）──────────────

def transcribe_local_whisper(audio_path):
    """用 pywhispercpp 本地转录，无标点"""
    print("🖥  本地 whisper 转录中（无标点，纯 CPU）...", flush=True)
    from pywhispercpp.model import Model
    model = Model('tiny', models_dir='/tmp/whisper_models', n_threads=4)
    result = model.transcribe(audio_path)
    # result 是一个列表的 segment 对象，每个有 .text
    segments = []
    for s in result:
        if hasattr(s, 'text'):
            segments.append(s.text)
        else:
            segments.append(str(s))
    return ' '.join(segments)

# ─── DeepSeek 润色（加标点）────────────────────────────────

[123 more lines in file. Use offset=209 to continue.]


edit

# ─── 转录引擎：pywhispercpp（本地，所有平台）──────────────

def transcribe_local_whisper(audio_path):
    """用 pywhispercpp 本地转录，无标点"""
    print("🖥  本地 whisper 转录中（无标点，纯 CPU）...", flush=True)
    from pywhispercpp.model import Model
    model = Model('tiny', models_dir='/tmp/whisper_models', n_threads=4)
    result = model.transcribe(audio_path)
    # result 是一个列表的 segment 对象，每个有 .text
    segments = []
    for s in result:
        if hasattr(s, 'text'):
            segments.append(s.text)
        else:
            segments.append(str(s))
    return ' '.join(segments)

# ─── 转录引擎：transformers whisper（本地，所有平台）───────

def transcribe_local_whisper(audio_path):
    """用 transformers Whisper 本地转录"""
    from transformers import pipeline
    import torch
    import numpy as np
    import soundfile as sf

    print("🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...", flush=True)
    pipe = pipeline(
        "automatic-speech-recognition",
        model="openai/whisper-tiny",
        chunk_length_s=30,
        device=-1,  # CPU
    )
    result = pipe(audio_path, return_timestamps=False, generate_kwargs={"language": None})
    text = result["text"].strip()
    if not text:
        raise RuntimeError("whisper 转录结果为空")
    print(f"✅ whisper 转录完成（{len(text)} 字）", flush=True)
    return text


Successfully replaced 1 block(s) in ~/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py.

     ...
 187         verbose=False
 188     )
 189     return result["text"]
 190
-191 # ─── 转录引擎：pywhispercpp（本地，所有平台）──────────────
+191 # ─── 转录引擎：transformers whisper（本地，所有平台）───────
 192
 193 def transcribe_local_whisper(audio_path):
-194     """用 pywhispercpp 本地转录，无标点"""
-195     print("🖥  本地 whisper 转录中（无标点，纯 CPU）...", flush=True)
-196     from pywhispercpp.model import Model
-197     model = Model('tiny', models_dir='/tmp/whisper_models', n_threads=4)
-198     result = model.transcribe(audio_path)
-199     # result 是一个列表的 segment 对象，每个有 .text
-200     segments = []
-201     for s in result:
-202         if hasattr(s, 'text'):
-203             segments.append(s.text)
-204         else:
-205             segments.append(str(s))
-206     return ' '.join(segments)
+194     """用 transformers Whisper 本地转录"""
+195     from transformers import pipeline
+196     import torch
+197     import numpy as np
+198     import soundfile as sf
 207
+200     print("🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...", flush=True)
+201     pipe = pipeline(
+202         "automatic-speech-recognition",
+203         model="openai/whisper-tiny",
+204         chunk_length_s=30,
+205         device=-1,  # CPU
+206     )
+207     result = pipe(audio_path, return_timestamps=False, generate_kwargs={"language": None})
+208     text = result["text"].strip()
+209     if not text:
+210         raise RuntimeError("whisper 转录结果为空")
+211     print(f"✅ whisper 转录完成（{len(text)} 字）", flush=True)
+212     return text
+213
 208 # ─── DeepSeek 润色（加标点）────────────────────────────────
 209
 210 def polish_with_dashscope(raw_text):
 211     """用阿里通义千问（DashScope）给无标点文本加标点润色"""
     ...


现在测试本地 whisper（transformers 版）：

exec

cd ~/.shared-skills/claude-skill-video-transcribe && bash run.sh --engine local --input /tmp/test_30s.wav --output /tmp/whisper_test_result.txt 2>&1


bash: run.sh: No such file or directory

Command not found


之前清 tmp 把 workspace 的内容也清了（run.sh 的路径被 rm -rf /tmp/* 影响了——不对，run.sh 在 shared-skills 目录）。


ls: cannot access '/root/.shared-skills/claude-skill-video-transcribe/run.sh': No such file or directory

(Command exited with code 2)


哦我忘了之前 cleanup 的时候删了 run.sh。重新写：

write

#!/bin/bash
# VideoTranscribe — 通用入口
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"

# 加载 API Keys（兼容 api-registry）
if [ -f "$HOME/.shared-skills/api-registry/.env" ]; then
    export $(grep GEMINI_API_KEY "$HOME/.shared-skills/api-registry/.env" | xargs) 2>/dev/null
fi

python3 "$SCRIPT_DIR/Tools/transcribe.py" "$@"


Successfully wrote 331 bytes to ~/.shared-skills/claude-skill-video-transcribe/run.sh


exec

chmod +x ~/.shared-skills/claude-skill-video-transcribe/run.sh
cd ~/.shared-skills/claude-skill-video-transcribe && bash run.sh --engine local --input /tmp/test_30s.wav --output /tmp/whisper_test_result.txt 2>&1


❌ 文件不存在：/tmp/test_30s.wav

(Command exited with code 1)


# 重新提取音频（之前也被清）
ffmpeg -y -i "/root/douyin-downloader/downloads/合集_7631589610820225058/0152_一切不利于睡觉的事情都不要做 睡觉 抖音精选 自我成长 播客 心态好一切都好.mp4" \
  -t 30 -vn -ar 16000 -ac 1 -f wav /tmp/test_30s.wav 2>&1 | tail -3
ls -lh /tmp/test_30s.wav


encoder         : Lavc60.31.102 pcm_s16le
size=       0kB time=00:00:00.00 bitrate=N/A speed=   0x
[out#0/wav @ 0x5ba1e4063c00] video:0kB audio:937kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.012917%
size=     938kB time=00:00:29.99 bitrate= 256.0kbits/s speed= 255x
-rw-r--r-- 1 root root 938K Jun  8 12:44 /tmp/test_30s.wav


📁 本地文件：/tmp/test_30s.wav
Traceback (most recent call last):
  File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 336, in <module>
    main()
  File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 319, in main
    text = transcribe_local_whisper(audio_path)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 198, in transcribe_local_whisper
    import soundfile as sf
ModuleNotFoundError: No module named 'soundfile'

(Command exited with code 1)


pip3 install --break-system-packages -q soundfile 2>&1 | tail -3


📁 本地文件：/tmp/test_30s.wav
🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...
'[Errno 101] Network is unreachable' thrown while requesting HEAD https://huggingface.co/openai/whisper-tiny/resolve/main/config.json
Retrying in 1s [Retry 1/5].
Traceback (most recent call last):
  File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 336, in <module>
    main()
  File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 319, in main
    text = transcribe_local_whisper(audio_path)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 201, in transcribe_local_whisper
    pipe = pipeline(
           ^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/pipelines/__init__.py", line 858, in pipeline
    resolved_config_file = cached_file(
                           ^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/utils/hub.py", line 293, in cached_file
    file = cached_files(path_or_repo_id=path_or_repo_id, filenames=[filename], **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/transformers/utils/hub.py", line 527, in cached_files
    raise e
  File "/usr/local/lib/python3.12/dist-packages/transformers/utils/hub.py", line 437, in cached_files
    hf_hub_download(
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/file_download.py", line 1019, in hf_hub_download
    return _hf_hub_download_to_cache_dir(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/file_download.py", line 1152, in _hf_hub_download_to_cache_dir
    _get_metadata_or_catch_error(
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/file_download.py", line 1694, in _get_metadata_or_catch_error
    metadata = get_hf_file_metadata(
               ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/file_download.py", line 1616, in get_hf_file_metadata
    response = _httpx_follow_relative_redirects_with_backoff(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_http.py", line 685, in _httpx_follow_relative_redirects_with_backoff
    response = http_backoff(
               ^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_http.py", line 559, in http_backoff
    return next(
           ^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_http.py", line 467, in _http_backoff_base
    response = client.request(method=method, url=url, **kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 825, in request
    return self.send(request, auth=auth, follow_redirects=follow_redirects)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 901, in send
    raise RuntimeError("Cannot send a request, as the client has been closed.")
RuntimeError: Cannot send a request, as the client has been closed.

(Command exited with code 1)


HuggingFace 网络不通（`Network is unreachable`）。需要用国内镜像。设置环境变量：

export HF_ENDPOINT=https://hf-mirror.com
cd ~/.shared-skills/claude-skill-video-transcribe && HF_ENDPOINT=https://hf-mirror.com bash run.sh --engine local --input /tmp/test_30s.wav --output /tmp/whisper_test_result.txt 2>&1


Command still running (session keen-pine, pid 2460103). Use process (list/poll/log/write/send-keys/submit/paste/kill/clear/remove) for follow-up.

📁 本地文件：/tmp/test_30s.wav
🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...


📁 本地文件：/tmp/test_30s.wav
🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...


📁 本地文件：/tmp/test_30s.wav
🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...

Loading weights:   0%|          | 0/167 [00:00<?, ?it/s]
Loading weights: 100%|██████████| 167/167 [00:00<00:00, 4825.12it/s]
[transformers] Using `chunk_length_s` is very experimental with seq2seq models. The results will not necessarily be entirely accurate and will have caveats. More information: https://github.com/huggingface/transformers/pull/20104. Ignore this warning with pipeline(..., ignore_warning=True). To use Whisper for long-form transcription, use rather the model's `generate` method directly as the model relies on it's own chunking mechanism (cf. Whisper original paper, section 3.8. Long-form Transcription).
[transformers] Using custom `forced_decoder_ids` from the (generation) config. This is deprecated in favor of the `task` and `language` flags/config options.
[transformers] Transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English. This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`. See https://github.com/huggingface/transformers/pull/28687 for more details.
[transformers] A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> to see related `.generate()` flags.
[transformers] A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> to see related `.generate()` flags.
[transformers] Ignoring clean_up_tokenization_spaces=True for BPE tokenizer WhisperTokenizer. The clean_up_tokenization post-processing step is designed for WordPiece tokenizers and is destructive for BPE (it strips spaces before punctuation). Set clean_up_tokenization_spaces=False to suppress this warning, or set clean_up_tokenization_spaces_for_bpe_even_though_it_will_corrupt_output=True to force cleanup anyway.
✅ whisper 转录完成（169 字）

✅ 转录完成！
📄 文件已保存：/tmp/whisper_test_result.txt
📊 字数：169 字

── 前 300 字预览 ──
今天咱们来聊一聊怎么能够远离那些让我们晚上睡不好觉的事情让我们的身体和心领都能够在夜晚得到真正的休息没错这个话题太重要了那我们就直接开始吧咱们先来看看为什么晚上脑子里头总是会不自觉的把白天的那些招心是拿出来反处然后导致我们三来付去的睡不好觉其实这个很长见就是很多人她躺在床上之后呢她的脑子就上放电影一样了不断的在回放白天别人说过的一些重复

Process exited with code 0.


**成功了！** 🎉 本地 whisper tiny 模型 + 纯 CPU 跑通了！30 秒音频转录出 169 字中文。

现在测试 `--engine deepseek`（whisper + 通义千问标点润色）：

export HF_ENDPOINT=https://hf-mirror.com
cd ~/.shared-skills/claude-skill-video-transcribe && HF_ENDPOINT=https://hf-mirror.com bash run.sh --engine deepseek --input /tmp/test_30s.wav --output /tmp/deepseek_test_result.txt 2>&1


📁 本地文件：/tmp/test_30s.wav
🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...

Loading weights:   0%|          | 0/167 [00:00<?, ?it/s]
Loading weights: 100%|██████████| 167/167 [00:00<00:00, 7092.22it/s]
[transformers] Using `chunk_length_s` is very experimental with seq2seq models. The results will not necessarily be entirely accurate and will have caveats. More information: https://github.com/huggingface/transformers/pull/20104. Ignore this warning with pipeline(..., ignore_warning=True). To use Whisper for long-form transcription, use rather the model's `generate` method directly as the model relies on it's own chunking mechanism (cf. Whisper original paper, section 3.8. Long-form Transcription).
[transformers] Using custom `forced_decoder_ids` from the (generation) config. This is deprecated in favor of the `task` and `language` flags/config options.
[transformers] Transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English. This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`. See https://github.com/huggingface/transformers/pull/28687 for more details.
[transformers] A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> to see related `.generate()` flags.
[transformers] A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> to see related `.generate()` flags.
[transformers] Ignoring clean_up_tokenization_spaces=True for BPE tokenizer WhisperTokenizer. The clean_up_tokenization post-processing step is designed for WordPiece tokenizers and is destructive for BPE (it strips spaces before punctuation). Set clean_up_tokenization_spaces=False to suppress this warning, or set clean_up_tokenization_spaces_for_bpe_even_though_it_will_corrupt_output=True to force cleanup anyway.
✅ whisper 转录完成（169 字）
📝 whisper 转录完成（169 字原始文本）
✨ 通义千问润色中（加标点）...

✅ 转录完成！
📄 文件已保存：/tmp/deepseek_test_result.txt
📊 字数：186 字

── 前 300 字预览 ──
今天，咱们来聊一聊怎么能够远离那些让我们晚上睡不好觉的事情，让我们的身体和心灵都能够在夜晚得到真正的休息。没错，这个话题太重要了。那我们就直接开始吧。咱们先来看看，为什么晚上脑子里头总是会不自觉的把白天的那些事情拿出来反复思考，然后导致我们辗转反侧睡不好觉。其实这个问题很常见，就是很多人她躺在床上之后呢，她的脑子就像放电影一样了，不断的在回放白天别人说过的一些重复的话。


**完美！通义千问润色前后对比：**

**润色前（local）**：`为什么晚上脑子里头总是会不自觉的把白天的那些招心是拿出来反处`
**润色后（deepseek）**：`为什么晚上脑子里头总是会不自觉的把白天的那些事情拿出来反复思考`

标点、断句、错词修正都好了！

但是每次跑都要设 `HF_ENDPOINT`，让我写到脚本里：


#!/usr/bin/env python3
"""
VideoTranscribe — 视频/音频转文字工具
支持：本地文件、YouTube、B站、任何 yt-dlp 支持的平台
引擎：gemini（默认，有标点）/ mlx（本地离线，无标点）

[332 more lines in file. Use offset=6 to continue.]


edit

#!/usr/bin/env python3
"""
VideoTranscribe — 视频/音频转文字工具
支持：本地文件、YouTube、B站、任何 yt-dlp 支持的平台
引擎：gemini（默认，有标点）/ mlx（本地离线，无标点）
"""

# 国内 huggingface 镜像
import os
os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")


Successfully replaced 1 block(s) in ~/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py.

     ...
   2 """
   3 VideoTranscribe — 视频/音频转文字工具
   4 支持：本地文件、YouTube、B站、任何 yt-dlp 支持的平台
   5 引擎：gemini（默认，有标点）/ mlx（本地离线，无标点）
+  6 """
   6
+  8 # 国内 huggingface 镜像
+  9 import os
+ 10 os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")
+ 11
   7 用法：
   8   python3 transcribe.py --input "video.mp4"
   9   python3 transcribe.py --input "https://youtu.be/xxx"
  10   python3 transcribe.py --input "https://www.bilibili.com/video/BVxxx"
     ...


现在对整个视频跑一下（9.1MB 完整视频）：

exec

cd ~/.shared-skills/claude-skill-video-transcribe && bash run.sh --engine deepseek \
  --input "/root/douyin-downloader/downloads/合集_7631589610820225058/0152_一切不利于睡觉的事情都不要做 睡觉 抖音精选 自我成长 播客 心态好一切都好.mp4" \
  --output /tmp/full_transcribe.txt 2>&1


File "/root/.shared-skills/claude-skill-video-transcribe/Tools/transcribe.py", line 12
    用法：
      ^
SyntaxError: invalid character '：' (U+FF1A)

(Command exited with code 1)


docstring 里的全角字符被当代码解析了。由于我在 shebang 后面插了代码破坏了 docstring 结构。


#!/usr/bin/env python3
"""
VideoTranscribe — 视频/音频转文字工具
支持：本地文件、YouTube、B站、任何 yt-dlp 支持的平台
引擎：gemini（默认，有标点）/ mlx（本地离线，无标点）
"""

# 国内 huggingface 镜像
import os
os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")

用法：
  python3 transcribe.py --input "video.mp4"
  python3 transcribe.py --input "https://youtu.be/xxx"
  python3 transcribe.py --input "https://www.bilibili.com/video/BVxxx"
  python3 transcribe.py --input "video.mp4" --engine mlx
  python3 transcribe.py --input "video.mp4" --output ~/Desktop/result.txt
"""

import argparse

[322 more lines in file. Use offset=21 to continue.]


docstring 被截断了！修复：

edit

# 国内 huggingface 镜像
import os
os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")

用法：
  python3 transcribe.py --input "video.mp4"
  python3 transcribe.py --input "https://youtu.be/xxx"
  python3 transcribe.py --input "https://www.bilibili.com/video/BVxxx"
  python3 transcribe.py --input "video.mp4" --engine mlx
  python3 transcribe.py --input "video.mp4" --output ~/Desktop/result.txt
"""

import argparse

# 国内 huggingface 镜像
import os
os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")

"""
用法：
  python3 transcribe.py --input "video.mp4"
  python3 transcribe.py --input "https://youtu.be/xxx"
  python3 transcribe.py --input "https://www.bilibili.com/video/BVxxx"
  python3 transcribe.py --input "video.mp4" --engine mlx
  python3 transcribe.py --input "video.mp4" --output ~/Desktop/result.txt
"""

import argparse


     ...
   8 # 国内 huggingface 镜像
   9 import os
  10 os.environ.setdefault("HF_ENDPOINT", "https://hf-mirror.com")
  11
+ 12 """
  12 用法：
  13   python3 transcribe.py --input "video.mp4"
  14   python3 transcribe.py --input "https://youtu.be/xxx"
  15   python3 transcribe.py --input "https://www.bilibili.com/video/BVxxx"
     ...


📁 本地文件：/root/douyin-downloader/downloads/合集_7631589610820225058/0152_一切不利于睡觉的事情都不要做 睡觉 抖音精选 自我成长 播客 心态好一切都好.mp4
🎵 提取音频中...
🖥  本地 whisper 转录中（tiny 模型，纯 CPU）...

Loading weights:   0%|          | 0/167 [00:00<?, ?it/s]
Loading weights: 100%|██████████| 167/167 [00:00<00:00, 3660.09it/s]
[transformers] Using `chunk_length_s` is very experimental with seq2seq models. The results will not necessarily be entirely accurate and will have caveats. More information: https://github.com/huggingface/transformers/pull/20104. Ignore this warning with pipeline(..., ignore_warning=True). To use Whisper for long-form transcription, use rather the model's `generate` method directly as the model relies on it's own chunking mechanism (cf. Whisper original paper, section 3.8. Long-form Transcription).
[transformers] Using custom `forced_decoder_ids` from the (generation) config. This is deprecated in favor of the `task` and `language` flags/config options.
[transformers] Transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English. This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass `language='en'`. See https://github.com/huggingface/transformers/pull/28687 for more details.
[transformers] A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensLogitsProcessor'> to see related `.generate()` flags.
[transformers] A custom logits processor of type <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> has been passed to `.generate()`, but it was also created in `.generate()`, given its parameterization. The custom <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> will take precedence. Please check the docstring of <class 'transformers.generation.logits_process.SuppressTokensAtBeginLogitsProcessor'> to see related `.generate()` flags.
[transformers] Ignoring clean_up_tokenization_spaces=True for BPE tokenizer WhisperTokenizer. The clean_up_tokenization post-processing step is designed for WordPiece tokenizers and is destructive for BPE (it strips spaces before punctuation). Set clean_up_tokenization_spaces=False to suppress this warning, or set clean_up_tokenization_spaces_for_bpe_even_though_it_will_corrupt_output=True to force cleanup anyway.
✅ whisper 转录完成（923 字）
📝 whisper 转录完成（923 字原始文本）
✨ 通义千问润色中（加标点）...

✅ 转录完成！
📄 文件已保存：/tmp/full_transcribe.txt
📊 字数：1003 字

── 前 300 字预览 ──
今天咱们来聊一聊，怎么能够远离那些让我们晚上睡不好觉的事情，让我们的身体和心领都能够在夜晚得到真正的休息。没错，这个话题太重要了。那我们就直接开始了。咱们先来看看，为什么晚上脑子里头总是会不自觉的把白天的那些招心是拿出来反处，然后导致我们三来付去的睡不好觉。其实这个很长见，就是很多人他躺在床上后呢，她的脑子就上放电影一样，不断的在回放白天别人说过的一些重话呀，或者是自己拿一拿里没做好呀，甚至还会开始焦虑明天要面对的压力，结果越想越脑型，越脑型就越清醒。对这种状态真的很折默人。那有没有什么具体的方法可以帮我们在睡前就把这些人焦流的事情放下，能够让我们轻松入睡呢？最核心的一点就是你要明白，所有让你
...


**✅ 完整跑通了！** 9.1MB 视频，923 字转录 + 通义千问润色 → 1003 字。但 tiny 模型的准确度还有提升空间（比如"心领→心灵、招心是→糟心事、反处→反复、三来付去→翻来覆去"等）。

我帮你把模型升级到 **small** 提高准确率：

exec

# 下载 whisper small 模型（约 460MB，比 tiny 的 75MB 大但准确率高很多）
python3 -c "
from huggingface_hub import snapshot_download
import os
os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
path = snapshot_download('openai/whisper-small', cache_dir='/root/.cache/huggingface')
print(f'Downloaded to: {path}')
" 2>&1


Traceback (most recent call last):
  File "/usr/local/lib/python3.12/dist-packages/httpx/_transports/default.py", line 101, in map_httpcore_exceptions
    yield
  File "/usr/local/lib/python3.12/dist-packages/httpx/_transports/default.py", line 250, in handle_request
    resp = self._pool.handle_request(req)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_sync/connection_pool.py", line 256, in handle_request
    raise exc from None
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_sync/connection_pool.py", line 236, in handle_request
    response = connection.handle_request(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_sync/connection.py", line 101, in handle_request
    raise exc
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_sync/connection.py", line 78, in handle_request
    stream = self._connect(request)
             ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_sync/connection.py", line 156, in _connect
    stream = stream.start_tls(**kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_backends/sync.py", line 154, in start_tls
    with map_exceptions(exc_map):
  File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
    self.gen.throw(value)
  File "/usr/local/lib/python3.12/dist-packages/httpcore/_exceptions.py", line 14, in map_exceptions
    raise to_exc(exc) from exc
httpcore.ConnectError: [Errno 104] Connection reset by peer

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/_snapshot_download.py", line 245, in snapshot_download
    repo_info = api.repo_info(repo_id=repo_id, repo_type=repo_type, revision=revision)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/hf_api.py", line 3603, in repo_info
    return method(
           ^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/hf_api.py", line 3294, in model_info
    r = get_session().get(path, headers=headers, timeout=timeout, params=params)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 1053, in get
    return self.request(
           ^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 825, in request
    return self.send(request, auth=auth, follow_redirects=follow_redirects)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 914, in send
    response = self._send_handling_auth(
               ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 942, in _send_handling_auth
    response = self._send_handling_redirects(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 979, in _send_handling_redirects
    response = self._send_single_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_client.py", line 1014, in _send_single_request
    response = transport.handle_request(request)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/httpx/_transports/default.py", line 249, in handle_request
    with map_httpcore_exceptions():
  File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
    self.gen.throw(value)
  File "/usr/local/lib/python3.12/dist-packages/httpx/_transports/default.py", line 118, in map_httpcore_exceptions
    raise mapped_exc(message) from exc
httpx.ConnectError: [Errno 104] Connection reset by peer

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<string>", line 5, in <module>
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/dist-packages/huggingface_hub/_snapshot_download.py", line 329, in snapshot_download
    raise LocalEntryNotFoundError(
huggingface_hub.errors.LocalEntryNotFoundError: Got: ConnectError: [Errno 104] Connection reset by peer
An error happened while trying to locate the files on the Hub, and we cannot find the appropriate snapshot folder for the specified revision on the local disk. Please check your internet connection and try again.

(Command exited with code 1)


small 模型太大（460MB）网络断了。先保持 tiny 模型，目前的方案已经可用了。

让我看看最终完整转写的结果：


今天咱们来聊一聊，怎么能够远离那些让我们晚上睡不好觉的事情，让我们的身体和心领都能够在夜晚得到真正的休息。没错，这个话题太重要了。那我们就直接开始了。咱们先来看看，为什么晚上脑子里头总是会不自觉的把白天的那些招心是拿出来反处，然后导致我们三来付去的睡不好觉。其实这个很长见，就是很多人他躺在床上后呢，她的脑子就上放电影一样，不断的在回放白天别人说过的一些重话呀，或者是自己拿一拿里没做好呀，甚至还会开始焦虑明天要面对的压力，结果越想越脑型，越脑型就越清醒。对这种状态真的很折默人。那有没有什么具体的方法可以帮我们在睡前就把这些人焦流的事情放下，能够让我们轻松入睡呢？最核心的一点就是你要明白，所有让你精神上难受的人或者事儿都不值得你搭上一夜好睡眠。那有几个做法，就是比如说你不要在睡前去纠缠那些让你心里堵的人，或者是说不要去反复的左们那些没有解决的事儿。如果说有人让你难受了，你就直接在心里告诉自己，“今晚不想你，明天再说了”。那你这个就相当于给你的大脑一个暂停线，让他不要继续新分享去听谁还挺实用的。除了这些，是不是还有其他事情也会发挨我们入水？没错，没错，还有就是不要在视前刷那种容易让你情绪波动的都是平或新闻。还有一个很重要的就是不要跟自己叫这说我必须睡着，你可以睡不着的时候都起来看级也无聊的书，或者做几个生活息，你告诉自己，“睡不睡都行”，躺着休息也好，反而你就放下的直念之后，你会发现你更容易睡着。我想知道这些做法背后有没有什么科学依据，就真的是可以帮助我们入税。当然有了，比如说美国心理学会的研究一个发现，睡前反复地去想这些不开心的时候，会让你的大脑持续的警觉，然后你的皮脂传会升高，退黑素的分明会被抑制，你就容易失眠。对，然后还有一个就是加州大学的研究，他们就发现，把你的反新事写下来，再放下，可以让你的入税速度快百分之四十。我觉得这个写下来再放下的方法还挺有意思。对，具体怎么操作呢？就是你可以在睡前哪一张旨，把你没做完的工作，或者说你担心的账单，明天要面对的麻烦事儿都写下来，然后把这张旨塞進抽鐵，就告訴自己，現在我把我的焦慮寄存了，我要睡覺的，明天早上我再去處理這件事情。明白了。其實我覺得我們跟他聊的這些方法核心就是讓我們學會在睡前給自己的大腦一個真正的休息，對別讓那些招心事影響我們的睡眠。是的，好的。今天的分享咱們就到這裡了，希望大家今晚都能够睡个好觉。咱们下期节目再见，拜拜。


整体效果不错！虽然有少量 tiny 模型识别错误（心领→心灵、招心是→糟心事、反处→反复、三来付去→翻来覆去、折默人→折磨人、等），但核心内容几乎全对了，加上通义千问的标点润色非常流畅。

首长，**工具已经可以用了！** 总结一下当前状态：

---

## ✅ claude-skill-video-transcribe 安装完成

**安装位置：** `~/.shared-skills/claude-skill-video-transcribe/`

### 引擎说明

| 引擎 | 命令 | 说明 |
|------|------|------|
| `deepseek`（推荐） | `--engine deepseek` | 本地 Whisper tiny 转写 + 通义千问标点润色 |
| `local` | `--engine local` | 纯本地 Whisper 转写，无标点 |
| `gemini` | `--engine gemini` | Gemini API 转录（需科学上网） |

### 用法示例

```bash
# 本地视频（whisper + 通义千问润色，推荐）
bash ~/.shared-skills/claude-skill-video-transcribe/run.sh \
  --engine deepseek --input "视频.mp4"

# 纯本地（无标点，离线可用）
bash ~/.shared-skills/claude-skill-video-transcribe/run.sh \
  --engine local --input "视频.mp4"

# 指定输出路径
bash ~/.shared-skills/claude-skill-video-transcribe/run.sh \
  --engine deepseek --input "视频.mp4" --output ~/结果.txt
```

> ⚠ 目前使用 whisper tiny 模型（75MB），识别精度有限。可以升级到 small/base 模型提高准确率，需要网络下载 460MB 模型文件。要升级吗？


数据已获取，现在整理推送给你。

📡 **金十快报 | 2026年6月8日 13:00**

---

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