ai-parrot

v0.25.6 safe
3.0
Low Risk

Framework for building AI agents for Navigator

🤖 AI Analysis

Final verdict: SAFE

The package appears to be legitimate with no clear signs of malicious intent. While there are some indications of obfuscation and incomplete metadata, these do not strongly suggest a supply-chain attack.

  • moderate obfuscation risk
  • incomplete maintainer metadata
Per-check LLM notes
  • Network: The use of aiohttp.ClientSession indicates the package is making network requests, which is common for packages interacting with APIs or web services.
  • Shell: No shell execution patterns detected.
  • Obfuscation: The use of base64 decoding suggests some level of obfuscation, but it could also be for legitimate purposes such as handling binary files.
  • Credentials: No suspicious patterns indicating credential harvesting were found.
  • Metadata: The maintainer has an incomplete profile and only one published package, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/phenobarbital/ai-parrot/
  • Detailed PyPI description (27009 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

  • Classifier: Typing :: Typed
  • Type checker (mypy / pyright / pytype) referenced in project
  • 500 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in phenobarbital/ai-parrot
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

  • : self._session = aiohttp.ClientSession( timeout=self.timeout, heade
  • t.headers async with aiohttp.ClientSession(timeout=timeout, headers=headers) as session: if
  • sed: self._http = aiohttp.ClientSession( timeout=aiohttp.ClientTimeout(total=30),
⚠ Code Obfuscation score 4.0

Found 2 obfuscation pattern(s)

  • part.file_bytes = base64.b64decode(file_data["fileWithBytes"]) part.file_media_type
  • g. _OPTIMIZE_PRIORITY_RE = re.compile( r'\bexplain\s+analyze\b' r'|\bquery\s+plan\b' r'|\bexecution\s+plan\b' r'|\bplan\s+de\s+ejecuci[oó]n\b' r'|
✓ 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: phenobarbital.info>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository phenobarbital/ai-parrot appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 ai-parrot 
Create a mini-application named 'AI Navig8r' that leverages the 'ai-parrot' package to develop an intelligent navigation assistant for indoor spaces like malls or airports. This application will guide users from their current location to their desired destination using voice commands and real-time updates. Here's a detailed plan on how to proceed:

1. **Setup Environment**: Ensure you have Python installed along with the necessary packages including 'ai-parrot'.
2. **Define the Navigation Space**: Create a digital map of the indoor space (e.g., floor plans of a mall). This map should include key points of interest such as shops, restrooms, and exits.
3. **Integrate ai-parrot**: Use 'ai-parrot' to set up an AI agent capable of understanding natural language queries about directions and providing accurate responses based on the predefined map data.
4. **Voice Command Integration**: Implement voice command recognition so that users can interact with the app verbally. This could involve integrating third-party services for speech-to-text processing.
5. **Real-Time Updates**: Incorporate mechanisms for real-time updates in case of any changes in the environment (e.g., closed shops).
6. **User Interface**: Develop a simple yet intuitive user interface where users can input their starting point and destination either via voice command or manually through the app.
7. **Testing and Iteration**: Test the application thoroughly in a simulated environment before deploying it in a real-world scenario. Gather feedback and make necessary improvements.

Suggested Features:
- Voice-guided navigation
- Interactive map display
- Real-time notifications for service disruptions or closures
- Integration with local amenities (food courts, ATMs)
- Offline mode support

How 'ai-parrot' is Utilized:
- For setting up the AI agent that understands and responds to user queries.
- To handle complex navigation logic and provide step-by-step directions.
- For enhancing the conversational experience by enabling more natural interactions between the user and the app.