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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CLAK Consulting Knowledge Graph Dataset

Graph-ML dataset for consulting knowledge representation learning.

Dataset Structure

Inspired by OGB (Open Graph Benchmark) format:

Field	Type	Description
node_feat	list[list[int]]	Node features (type, one-hot)
edge_index	list[tuple[int,int]]	Edge pairs (source, target)
edge_attr	list[int]	Edge types
y	list[float]	Target labels
num_nodes	int	Node count
domain	str	Consulting domain

Node Types

0: Framework (McKinsey 7S, Porter, etc.)
1: Capability (L3 AI/ML)
2: Process (L2)
3: Flow (L1)
4: Insight
5: Data Source

Edge Types

0: USES
1: PART_OF
2: REQUIRES
3: GENERATES
4: NEURAL_LINK

Tasks

Graph Classification: Predict success of framework implementation
Graph Regression: Predict quality scores
Link Prediction: Predict capability-process connections

Usage

from datasets import load_dataset
dataset = load_dataset("Kraft102/clak-consulting-graph-ml")

Citation

@misc{clak2026graph, title={CLAK Consulting Knowledge Graph Dataset}, author={CLAK Consulting AI}, year={2026} }

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