AI Analysis
Final verdict: SAFE
The package is deemed safe as it lacks network calls and shell executions, indicating no immediate runtime risks. However, metadata risks slightly elevate its score due to a single maintainer and a non-HTTPS link.
- Single maintainer with only one package.
- Non-HTTPS link in package metadata.
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution detected, indicating the package does not execute system commands.
- Metadata: The package has a single maintainer with one package and contains a non-HTTPS link, which could indicate a lack of maintenance or oversight.
Package Quality Overall: Low (4.6/10)
○ 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 (995 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
7.0
Partial type annotation coverage
Type checker (mypy / pyright / pytype) referenced in project39 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
6.0
Limited contributor diversity
2 unique contributor(s) across 100 commits in alipay/antchain-openapi-prod-sdkTwo distinct contributors found
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
score 2.0
Found 1 obfuscation pattern(s)
n-openapi-prod-sdk" VERSION = __import__(PACKAGE).__version__ REQUIRES = [ "antchain_alipay_util>=1.0.1,
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: alibabacloud.com
Suspicious Page Links
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.apache.org/licenses/LICENSE-2.0
Git Repository History
Repository alipay/antchain-openapi-prod-sdk appears legitimate
Maintainer History
score 2.0
1 maintainer concern(s) found
Author "Ant Chain SDK" 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 antchain-aigc
Create a fully functional mini-application that leverages the AntChain AIGC SDK for Python to generate personalized content recommendations based on user interests. This application will serve as a proof of concept for integrating AI-generated content into a real-world scenario. Here’s a detailed breakdown of what the application should achieve and how it utilizes the 'antchain-aigc' package: 1. **User Registration & Profile Setup**: Users can register and set up their profiles, including basic information and preferences (e.g., favorite genres, topics of interest). 2. **Content Recommendation Engine**: Utilize the 'antchain-aigc' package to analyze user data and generate tailored content recommendations. This could include articles, videos, or other media types. 3. **Real-time Updates**: Implement a feature where the application can fetch and process new content from external sources (such as news feeds or blogs) using APIs or web scraping techniques, and then use 'antchain-aigc' to recommend relevant items to users in real-time. 4. **Feedback Loop**: Allow users to provide feedback on the recommended content (e.g., like/dislike, share). Use this feedback to refine future recommendations through continuous learning mechanisms provided by 'antchain-aigc'. 5. **Analytics Dashboard**: Develop a simple analytics dashboard that shows key performance indicators such as engagement rates, recommendation accuracy, and user satisfaction. 6. **Security and Privacy Compliance**: Ensure that all user data is handled securely and complies with privacy regulations. Use best practices in data handling and storage. **How to Utilize 'antchain-aigc':** - For generating personalized content recommendations, utilize the AI models within the 'antchain-aigc' package to predict and suggest content based on user profiles and historical interactions. - Integrate the SDK’s API calls to fetch and process new content dynamically, ensuring that recommendations remain fresh and relevant. - Leverage any machine learning capabilities within 'antchain-aigc' to improve recommendation quality over time by incorporating user feedback. - Explore any documentation or examples provided by the package to understand its full potential and how it can enhance the application's core functionalities.
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