anosys-sdk-openai

v1.0.13 suspicious
4.0
Medium Risk

AnoSys SDK for OpenAI - Automatic instrumentation and logging for OpenAI API calls

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network, shell, obfuscation, and credential usage. However, the metadata risk score is moderately high due to incomplete author information and a potentially new or inactive account, raising concerns about its legitimacy.

  • Incomplete author information
  • Potentially new or inactive author account
Per-check LLM notes
  • Network: The network call is likely for logging or telemetry purposes.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of code being hidden maliciously.
  • Credentials: No credential harvesting patterns detected, suggesting the package does not aim to steal secrets.
  • Metadata: The author's information is incomplete and the account seems new or inactive, which could indicate potential risk.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_openai.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.anosys.ai
  • Detailed PyPI description (2737 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 9 type-annotated function signatures (partial)
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 85 commits in anosys-ai/anosys-sdk
  • Two distinct contributors found

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • ) response = requests.post(_log_api_url, json=data, timeout=5) response
✓ 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

Email domain looks legitimate: anosys.ai>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository anosys-ai/anosys-sdk 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 anosys-sdk-openai 
Your task is to develop a Python-based mini-application named 'ChatLogAnalyzer' that leverages the 'anosys-sdk-openai' package for enhanced logging and monitoring of interactions with the OpenAI API. This tool will serve as a valuable resource for developers and researchers who frequently use the OpenAI API for tasks such as generating text, translating languages, or summarizing content. Here’s a detailed breakdown of the project requirements and steps to get you started:

1. **Project Setup**: Begin by setting up your Python environment. Ensure you have Python 3.8 or higher installed. Next, install the necessary packages including 'anosys-sdk-openai', 'openai', and any other dependencies you deem necessary.

2. **Core Functionality**: The main feature of 'ChatLogAnalyzer' will be to log every interaction with the OpenAI API, including details like request parameters, response data, timestamps, and more. Use 'anosys-sdk-openai' to automatically instrument these API calls, ensuring comprehensive and automatic logging without manual intervention.

3. **User Interface**: Design a simple command-line interface (CLI) for users to interact with the application. Users should be able to input their API key securely, select from predefined API endpoints (e.g., 'create_completion', 'translate_text'), and provide necessary parameters for their requests.

4. **Data Visualization**: Implement basic data visualization capabilities using libraries like Matplotlib or Plotly. Visualize trends in API usage over time, frequency of different types of requests, and other relevant metrics derived from the logged data.

5. **Advanced Features**: Consider adding advanced features such as real-time alerts for unusual activity patterns, integration with external databases for long-term storage of logs, or even a web interface for more interactive analysis.

6. **Security Measures**: Since 'ChatLogAnalyzer' will handle sensitive information like API keys, ensure robust security measures are in place. This includes encrypting stored data, validating user inputs, and handling exceptions gracefully.

7. **Documentation**: Finally, create comprehensive documentation for both end-users and developers. Include setup instructions, examples of how to use 'ChatLogAnalyzer', and explanations of how 'anosys-sdk-openai' enhances the application's functionality.

By following these steps, you'll create a powerful yet user-friendly tool that not only streamlines the process of interacting with the OpenAI API but also provides valuable insights into its usage through detailed logging and analytics.

💬 Discussion Feed

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