🤖 AI Analysis

Final verdict: SAFE

The package is deemed safe with no signs of obfuscation or credential harvesting. However, the metadata risk score suggests lower activity from the maintainer.

No obfuscation detected
No credential harvesting patterns found

Per-check LLM notes

Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has only one package and lacks PyPI classifiers, suggesting low activity or effort.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (14559 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

35 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "Shloimy Wiesel" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with ai-sdk-stream-python

Create a real-time sentiment analysis web application using the 'ai-sdk-stream-python' package. This application will allow users to input text streams (such as live chat messages, social media posts, or blog comments) and instantly receive sentiment scores indicating whether the content is positive, negative, or neutral. The app should have a user-friendly interface where users can paste their text stream into a textarea and see the sentiment analysis results displayed dynamically as they type.

Key Features:
1. Real-time Streaming Input: Users can paste or type in text streams continuously, and the app should analyze each piece of text as it comes in.
2. Sentiment Analysis Output: Display the sentiment score next to each analyzed piece of text, updating in real-time.
3. Visualization: Use color coding to visually represent the sentiment (green for positive, red for negative, and yellow for neutral).
4. Historical Data View: Provide a feature to view past sentiment analysis results in a chart or graph format.
5. Export Results: Allow users to export the sentiment analysis data in CSV or JSON format for further analysis.

How to Utilize 'ai-sdk-stream-python':
- Integrate the package for handling the streaming of text data efficiently.
- Use its functionalities to process and analyze the incoming text streams for sentiment.
- Implement real-time updates based on the streaming capabilities provided by the package.
- Explore any additional utilities or tools within the package that could enhance the real-time processing and analysis.