audio-clean-booster

v0.1.3 safe
4.0
Medium Risk

Recommended no-reference speech cleanup pipeline using MossFormer2 plus post-processing.

🤖 AI Analysis

Final verdict: SAFE

The package exhibits minimal risk indicators with no network calls, shell executions, or obfuscations. However, the lack of a git repository and a new maintainer account slightly elevate metadata risk.

  • No network calls or shell executions detected
  • New maintainer account and missing git repository
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution detected, indicating no direct system command invocations.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows some red flags due to the missing git repository and a new maintainer account, but there's no direct evidence of malicious intent.

📦 Package Quality Overall: Low (2.8/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (1138 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 27 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "audio-clean-booster contributors" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with audio-clean-booster 
Create a Python-based mini-application called 'VoiceCleaner' that leverages the 'audio-clean-booster' package to enhance the quality of audio recordings by removing noise and boosting speech clarity. The application should allow users to upload an audio file, process it using the 'audio-clean-booster' package, and then download the cleaned-up version of their audio file. Here are the key steps and features to include in your project:

1. **User Interface**: Develop a simple web interface using Flask or Django where users can upload their audio files.
2. **Audio Processing**: Utilize the 'audio-clean-booster' package to clean up the uploaded audio files. This involves loading the audio data, applying the MossFormer2 model for speech cleanup, and then conducting post-processing as described in the package documentation.
3. **Progress Indicator**: Implement a progress bar or status indicator to show the user how long the processing will take.
4. **Download Feature**: After processing, provide a button for users to download the cleaned audio file.
5. **Error Handling**: Ensure that the application gracefully handles errors such as unsupported file formats, large file sizes, or processing failures.
6. **Documentation**: Write comprehensive documentation on how to use the application, including installation instructions, usage examples, and troubleshooting tips.
7. **Testing**: Conduct thorough testing to ensure the application works as expected across different types of audio files.

The 'audio-clean-booster' package should be integrated in a way that allows for easy updates to the underlying models and algorithms without requiring significant changes to the application code. Additionally, consider adding a feature to allow users to preview the processed audio before downloading it.

💬 Discussion Feed

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