[Snyk] Fix for 5 vulnerabilities

[q1blue]

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

Snyk changed the following file(s):

• requirements.txt

⚠️ Warning

tyro 0.9.17 requires backports-cached-property, which is not installed.
trl 0.9.4 requires accelerate, which is not installed.
trl 0.9.4 requires transformers, which is not installed.
trl 0.9.4 requires torch, which is not installed.
pyzstd 0.18.0 has requirement typing-extensions>=4.13.2, but you have typing-extensions 4.7.1.
py7zr 0.21.0 requires pyppmd, which is not installed.
py7zr 0.21.0 requires inflate64, which is not installed.
invisible-watermark 0.2.0 requires torch, which is not installed.
datasets 2.13.2 has requirement dill<0.3.7,>=0.3.0, but you have dill 0.3.7.

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Important

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• Max score is 1000. Note that the real score may have changed since the PR was raised.
• This PR was automatically created by Snyk using the credentials of a real user.
• 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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EntelligenceAI PR Summary

This PR updates Python dependencies in requirements.txt for security patches and version upgrades.

• Upgraded sentencepiece from version 0.2.0 to 0.2.1
• Added torch>=2.10.0 dependency (Snyk security fix)
• Added wheel>=0.46.2 dependency (Snyk security fix)
• Added trailing newline to requirements.txt for proper formatting

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[gemini-code-assist]

Summary of Changes

Hello @q1blue, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request, automatically generated by Snyk, aims to resolve five identified security vulnerabilities within the project's Python dependencies. It achieves this by updating specific package versions and introducing new version constraints for indirect dependencies in the requirements.txt file to ensure a more secure dependency tree.

Highlights

• Dependency Upgrades: The sentencepiece dependency has been upgraded from version 0.2.0 to 0.2.1 to address a security vulnerability.
• New Dependency Pins for Vulnerability Mitigation: New version pins have been added for torch (>=2.10.0) and wheel (>=0.46.2). These packages were not direct dependencies but were pinned by Snyk to avoid identified vulnerabilities.

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[entelligence-ai-pr-reviews]

Walkthrough

This PR focuses on dependency management improvements for security and stability. The sentencepiece package receives a minor version upgrade from 0.2.0 to 0.2.1. Two critical security updates are introduced: torch is pinned to version 2.10.0 or higher, and wheel is pinned to version 0.46.2 or higher. Both security-related dependencies were added based on Snyk vulnerability recommendations. Additionally, a minor formatting improvement adds a trailing newline to the requirements file for better compliance with standard file formatting conventions.

Changes

File(s)	Summary
requirements.txt	Upgraded sentencepiece from 0.2.0 to 0.2.1; added torch>=2.10.0 and wheel>=0.46.2 dependencies pinned by Snyk for security vulnerability fixes; added trailing newline for proper file formatting.

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[gemini-code-assist]

Code Review

This pull request from Snyk addresses 5 identified vulnerabilities by updating dependencies in requirements.txt. The changes include upgrading sentencepiece to version 0.2.1 and introducing minimum version requirements for torch (>=2.10.0) and wheel (>=0.46.2). While these updates are crucial for enhancing security, a potential version conflict for torch has been identified due to its existing installation method in the Dockerfile.

[gemini-code-assist]

The addition of torch>=2.10.0 in requirements.txt is a positive step for addressing a vulnerability. However, the Dockerfile (line 70) explicitly installs pytorch==2.3.0 via conda. This creates a version conflict, as pytorch==2.3.0 does not satisfy the torch>=2.10.0 requirement. This discrepancy could lead to pip attempting to upgrade torch after conda has installed it, potentially causing environment instability or build failures. It is recommended to update the conda installation command in the Dockerfile to a pytorch version that satisfies torch>=2.10.0 to ensure consistency and security.

[snyk-io]

✅ Snyk checks have passed. No issues have been found so far.

Status	Scanner	Critical	High	Medium	Low	Total (0)
✅	Open Source Security	0	0	0	0	0 issues

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