ai-agent-book/cursor-chats/20251003_235310_Traceback_(most_recent_call_last).md

Cursor Chat: ai-agent-book

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• Project: ai-agent-book
• Path: /Users/boj
• Date: 2025-10-03 23:53:10
• Session ID: 033185f2-73c0-4e9e-a12a-172a80b42f7e

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👤 You

Traceback (most recent call last): File "/root/sesame.py", line 163, in processed_ds = raw_ds.map( preprocess_example, remove_columns=raw_ds.column_names, desc="Preprocessing dataset", ) File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/arrow_dataset.py", line 562, in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) ~~~~^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/arrow_dataset.py", line 3327, in map for rank, done, content in Dataset._map_single(**unprocessed_kwargs): ~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/arrow_dataset.py", line 3659, in _map_single for i, example in iter_outputs(shard_iterable): ~~~~~~~~~~~~^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/arrow_dataset.py", line 3633, in iter_outputs yield i, apply_function(example, i, offset=offset) ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/arrow_dataset.py", line 3556, in apply_function processed_inputs = function(*fn_args, *additional_args, **fn_kwargs) File "/root/sesame.py", line 116, in preprocess_example {"type": "audio", "path": example["audio"]["array"]}, ~~~~~~~^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/formatting/formatting.py", line 285, in getitem value = self.format(key) File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/formatting/formatting.py", line 380, in format return self.formatter.format_column(self.pa_table.select([key]))[0] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/formatting/formatting.py", line 465, in format_column column = self.python_features_decoder.decode_column(column, pa_table.column_names[0]) File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/formatting/formatting.py", line 228, in decode_column self.features.decode_column(column, column_name, token_per_repo_id=self.token_per_repo_id) ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/features/features.py", line 2121, in decode_column decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id) ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/features/features.py", line 1409, in decode_nested_example return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/features/audio.py", line 179, in decode_example from ._torchcodec import AudioDecoder File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/datasets/features/_torchcodec.py", line 2, in from torchcodec.decoders import AudioDecoder as _AudioDecoder File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/__init__.py", line 10, in from . import decoders, samplers # noqa ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/decoders/__init__.py", line 7, in from .._core import AudioStreamMetadata, VideoStreamMetadata File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/_core/__init__.py", line 8, in from ._metadata import ( ...<5 lines>... ) File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/_core/_metadata.py", line 16, in from torchcodec._core.ops import ( ...<3 lines>... ) File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/_core/ops.py", line 84, in load_torchcodec_shared_libraries() ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^ File "/root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/_core/ops.py", line 69, in load_torchcodec_shared_libraries raise RuntimeError( ...<11 lines>... ) RuntimeError: Could not load libtorchcodec. Likely causes: 1. FFmpeg is not properly installed in your environment. We support versions 4, 5, 6 and 7. 2. The PyTorch version (2.8.0+cu128) is not compatible with this version of TorchCodec. Refer to the version compatibility table: https://github.com/pytorch/torchcodec?tab=readme-ov-file#installing-torchcodec. 3. Another runtime dependency; see exceptions below. The following exceptions were raised as we tried to load libtorchcodec:

[start of libtorchcodec loading traceback] FFmpeg version 7: libavutil.so.59: cannot open shared object file: No such file or directory FFmpeg version 6: /root/miniconda3/envs/sesame/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by /usr/lib/x86_64-linux-gnu/libavfilter.so.9) FFmpeg version 5: libavutil.so.57: cannot open shared object file: No such file or directory FFmpeg version 4: libavutil.so.56: cannot open shared object file: No such file or directory [end of libtorchcodec loading traceback]. (sesame) root@C.26412100:~$ ffmpeg --version ffmpeg version 6.1.1-3ubuntu5 Copyright (c) 2000-2023 the FFmpeg developers built with gcc 13 (Ubuntu 13.2.0-23ubuntu3)

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🤖 Cursor Assistant

This is a library compatibility issue between your conda environment and the system FFmpeg installation. The system FFmpeg 6 requires GLIBCXX_3.4.32, but your conda environment has an older version of libstdc++.

Here are the solutions, in order of preference:

Solution 1: Install FFmpeg in the conda environment (Recommended)

This ensures all libraries are compatible within the same environment:

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👤 You

The following NEW packages will be INSTALLED:

aom conda-forge/linux-64::aom-3.3.0-h27087fc_1 ffmpeg conda-forge/linux-64::ffmpeg-5.0.1-h964e5f1_2 freetype pkgs/main/linux-64::freetype-2.13.3-h4a9f257_0 gmp conda-forge/linux-64::gmp-6.2.1-h58526e2_0 gnutls conda-forge/linux-64::gnutls-3.6.13-h85f3911_1 icu pkgs/main/linux-64::icu-73.1-h6a678d5_0 lame conda-forge/linux-64::lame-3.100-h7f98852_1001 libdrm pkgs/main/linux-64::libdrm-2.4.124-h5eee18b_0 libpciaccess pkgs/main/linux-64::libpciaccess-0.18-h5eee18b_0 libpng pkgs/main/linux-64::libpng-1.6.39-h5eee18b_0 libva conda-forge/linux-64::libva-2.21.0-hd590300_0 libvpx conda-forge/linux-64::libvpx-1.11.0-h9c3ff4c_3 libxml2 pkgs/main/linux-64::libxml2-2.13.8-hfdd30dd_0 nettle conda-forge/linux-64::nettle-3.6-he412f7d_0 openh264 pkgs/main/linux-64::openh264-2.1.1-h4ff587b_0 svt-av1 conda-forge/linux-64::svt-av1-1.1.0-h27087fc_1 x264 conda-forge/linux-64::x264-1!161.3030-h7f98852_1 x265 conda-forge/linux-64::x265-3.5-h924138e_3 xorg-libxext pkgs/main/linux-64::xorg-libxext-1.3.6-h9b100fa_0 xorg-libxfixes pkgs/main/linux-64::xorg-libxfixes-6.0.1-h9b100fa_0

Downloading and Extracting Packages:

Preparing transaction: done Verifying transaction: done Executing transaction: done (sesame) root@C.26412100:$ ffmpeg --version ffmpeg: error while loading shared libraries: libiconv.so.2: cannot open shared object file: No such file or directory (sesame) root@C.26412100:$ which ffmpeg /root/miniconda3/envs/sesame/bin/ffmpeg

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🤖 Cursor Assistant

The FFmpeg installation is missing the libiconv library dependency. Let's install it:

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👤 You

) RuntimeError: Could not load libtorchcodec. Likely causes: 1. FFmpeg is not properly installed in your environment. We support versions 4, 5, 6 and 7. 2. The PyTorch version (2.8.0+cu128) is not compatible with this version of TorchCodec. Refer to the version compatibility table: https://github.com/pytorch/torchcodec?tab=readme-ov-file#installing-torchcodec. 3. Another runtime dependency; see exceptions below. The following exceptions were raised as we tried to load libtorchcodec:

[start of libtorchcodec loading traceback] FFmpeg version 7: libavutil.so.59: cannot open shared object file: No such file or directory FFmpeg version 6: /root/miniconda3/envs/sesame/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by /usr/lib/x86_64-linux-gnu/libavfilter.so.9) FFmpeg version 5: /root/miniconda3/envs/sesame/lib/python3.13/site-packages/torchcodec/libtorchcodec_core5.so: undefined symbol: av_channel_layout_default, version LIBAVUTIL_57 FFmpeg version 4: libavutil.so.56: cannot open shared object file: No such file or directory [end of libtorchcodec loading traceback].

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🤖 Cursor Assistant

I see the issue now. The conda FFmpeg 5 has a symbol compatibility problem with torchcodec. You need to install a newer FFmpeg version (6 or 7) in your conda environment. Since you're on a remote Linux server, here are the commands you should run:

Solution: Install FFmpeg 6 or 7 in conda

Try FFmpeg 6 first (should work with your torchcodec version):

conda install -c conda-forge "ffmpeg>=6.0" -y

If that doesn't resolve it, you may also need to update libstdc++ to get the required GLIBCXX version:

conda install -c conda-forge libstdcxx-ng -y

Alternative: Install libiconv and upgrade FFmpeg

Since FFmpeg is also missing libiconv, install both together:

conda install -c conda-forge libiconv "ffmpeg>=6.0" libstdcxx-ng -y

If conda approach doesn't work: Downgrade to avoid torchcodec

The audio decoding issue comes from the datasets library trying to use torchcodec. You can work around this by:

1. Downgrade datasets to a version that doesn't require torchcodec:

   pip install "datasets<3.0.0"
   

2. Or disable audio decoding in your code by modifying how you load the dataset. Looking at your script, change the dataset loading to avoid decoding audio automatically:

   raw_ds = load_dataset("...", split="...", streaming=False)
   # Set decode=False for audio to avoid torchcodec
   raw_ds = raw_ds.cast_column("audio", datasets.Audio(decode=False))
   

Recommendation: Try the first approach (install FFmpeg 6+ and libstdcxx-ng in conda) as it's the cleanest solution that addresses all the library compatibility issues at once.

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