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The JWT signature verification failed. Check the signing key and the algorithm.
Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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The LAION-DISCO-12M dataset contains 12M links to music on YouTube, inspired by the methodology of DISCO-10M. It contains song metadata (song_id, title, artist_names, artist_ids, album_name, album_id, isExplicit, views, duration) and YouTube URL, pointing to the original song on the public web. It does not contain any original audio samples and is thus an index dataset.

Starting from an initial seed list of artists, we can discover new artists by recursively exploring the artists listed in the "Fans might also like" section. We explore the related artists graph for as long as we are able to find new artists. For a given artist, we can extract their metadata, such as their name and number of subscribers, as well as a list of all of their songs and music videos. Importantly, each song or music video is associated with a YouTube URL (obtained from its ID). The collected metadata fields are: song_id, title, artist_names, artist_ids, album_name, album_id, isExplicit, views, duration.

The authors of DISCO-10M used a seed list of 18 artists, chosen to represent a variety of genres. However, we found that this is not sufficient for exploring the artist graph of YouTube Music. Starting from this seed list, we were able to discover only 90,007 artists and 5,399,389 songs.

We therefore compiled a larger seed list by considering the artists that appear on YouTube Music charts of top songs by country and genre playlists. This resulted in an initial list of 45,218 artists. The artist graph exploration starting from this seed list resulted in 250,516 artists and 12,648,485 songs.

This work was inspired by DISCO-10M, consider citing them if you use this dataset.

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