[Snyk] Fix for 5 vulnerabilities

[sestinj]

Snyk has created this PR to fix 5 vulnerabilities in the pip dependencies of this project.

Snyk changed the following file(s):

• manual-testing-sandbox/requirements.txt

⚠️ Warning

typer 0.3.2 has requirement click<7.2.0,>=7.1.1, but you have click 8.1.8.
thinc 8.0.17 requires murmurhash, which is not installed.
thinc 8.0.17 requires preshed, which is not installed.
thinc 8.0.17 requires cymem, which is not installed.
spacy 3.1.2 requires murmurhash, which is not installed.
spacy 3.1.2 requires preshed, which is not installed.
spacy 3.1.2 requires cymem, which is not installed.
qtconsole 5.4.4 requires pyzmq, which is not installed.
notebook 6.5.7 requires pyzmq, which is not installed.
jupyter-server 1.24.0 requires pyzmq, which is not installed.
jupyter-console 6.6.3 requires pyzmq, which is not installed.
jupyter-client 7.4.9 requires pyzmq, which is not installed.
ipykernel 6.16.2 requires pyzmq, which is not installed.
exceptiongroup 1.3.1 has requirement typing-extensions>=4.6.0; python_version < "3.13", but you have typing-extensions 3.10.0.2.

Breaking Change Risk

Notice: This assessment is enhanced by AI.

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Important

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• Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

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[sestinj]

This upgrade involves a major, high-risk update to keras and a medium-risk update to nltk.

keras@2.6.0 → keras@3.12.3

Risk: HIGH

The upgrade from Keras 2 to Keras 3 is a major rewrite with significant breaking changes. Keras 3 has been redesigned as a multi-backend framework that can run on top of TensorFlow, JAX, and PyTorch.

Key Breaking Changes:

• Package Imports: Code must be migrated from tensorflow.keras to the new standalone keras package. For example, from tensorflow.keras import layers must be changed to from keras import layers.
• Backend Configuration: A backend must be explicitly configured (e.g., via the KERAS_BACKEND environment variable) before importing Keras.
• API Changes: To achieve multi-backend compatibility, code using TensorFlow-specific operations (e.g., tf.nn.relu) should be replaced with backend-agnostic alternatives like keras.ops.relu.
• Model Saving: The default model-saving format has changed to .keras v3. While older models can often be loaded, re-saving them in the new format is recommended.

Recommendation:
This is a significant migration that requires careful code modification and testing. Developers must review the official migration guide to update import paths and replace any backend-specific code. Due to the scale of these changes, this upgrade should be handled in a dedicated effort.

nltk@3.6.3 → nltk@3.10.0

Risk: MEDIUM

This upgrade spans several minor versions and includes environment and behavioral changes.

Key Changes:

• Python Version Support: NLTK 3.7, included in this range, drops support for Python 3.6.
• Behavioral Change: As of version 3.6.5, METEOR evaluation now requires pre-tokenized input, which may affect existing implementations using this metric.
• Enhancements: The versions include numerous bug fixes, performance improvements, and support for newer Python versions like 3.10 and 3.11.

Recommendation:
Verify that your project's runtime environment is newer than Python 3.6. If you use METEOR for evaluation, ensure your input is pre-tokenized to avoid issues.

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