Add support for python 3.13 + 3.14

[mdeyell-valid-mind]

Pull Request Description

What and why?

Add support for python 3.13 and 3.14.

How to test

poetry env use python3.13
  poetry install --all-extras
  poetry run python -m ipykernel install --user --name validmind-py313 --display-name "ValidMind (Py 3.13)"
  poetry run jupyter lab

I tested this by running the following poorly hacked together snippet on python 3.13 and 3.14

import validmind as vm
import uuid
from validmind.api_client import log_metric
from datetime import datetime, timedelta
import secrets

rand_num = secrets.randbits(53) / (1 << 53) # float in [0,1)
vm.init(
    api_host="http://localhost:5000/api/v1/tracking",
    api_key="",
    api_secret="",
    document="documentation", # requires library >=2.12.0
    model="cmmwm2e6k00ek0ip4iyudr7gs",
)
NUM_DAYS = 10
REFERENCE_DATE = datetime(2024, 1, 1)  # Fixed date: January 1st, 2024
base_date = REFERENCE_DATE - timedelta(days=NUM_DAYS)
recorded_at = base_date + timedelta(days=1)
metric_name = str(uuid.uuid4()) 
log_metric(
    key=metric_name,
    value=rand_num,
    recorded_at=recorded_at.isoformat()
)

I verified that the metrics appears in the inventory_model_metrics table.

What needs special review?

Dependencies, breaking changes, and deployment notes

Release notes

Add support for python 3.13 and 3.14.

Checklist

• What and why
• Screenshots or videos (Frontend)
• How to test
• What needs special review
• Dependencies, breaking changes, and deployment notes
• Labels applied
• PR linked to Shortcut
• Unit tests added (Backend)
• Tested locally
• Documentation updated (if required)
• Environment variable additions/changes documented (if required)

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[github-actions]

PR Summary

This PR broadens the supported Python versions across the project by extending the recommended range from Python 3.11 to Python 3.14. The changes include updates to multiple notebook files (and other documentation) and GitHub workflow configuration files to reflect the new range (e.g., "Python 3.8 <= x <= 3.14" instead of 3.11). Additionally, the pyproject.toml has been updated to a new version (2.12.3) with adjustments to dependency constraints for libraries such as numpy, pyarrow, datasets, and others. These dependency rules now include conditional specifiers based on the Python version to ensure compatibility across all supported platforms. Overall, these changes help ensure that the library remains compatible with newer Python versions and that dependency resolution is accurate for those versions.

Test Suggestions

• Run the full test suite on Python versions 3.8, 3.9, 3.10, 3.11, 3.13, and 3.14 to confirm baseline functionality.
• Verify that GitHub actions and dependency testing workflows pass in the expanded matrix.
• Execute all updated notebooks to ensure they run successfully and that the updated recommended versions display correctly.
• Perform integration tests to validate that dependency resolution works as expected with the new constraints in pyproject.toml.

[cachafla]

Very nice