axio-transport-openai

v0.9.7 safe
3.0
Low Risk

OpenAI-compatible transport for Axio

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk with no signs of malicious intent or supply-chain attack. It uses standard libraries and practices without any unusual behavior.

  • Low network and obfuscation risks
  • No evidence of shell execution or credential harvesting
Per-check LLM notes
  • Network: The detected network patterns are typical for a package that uses aiohttp for making HTTP requests, likely for API interactions.
  • Shell: No shell execution patterns were detected.
  • Obfuscation: The base64 decoding is likely used for data processing rather than obfuscation.
  • Credentials: No suspicious patterns indicating credential harvesting were found.
  • Metadata: Low risk due to lack of suspicious indicators, but concerns about low-effort metadata suggest caution.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 7 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.axio-agent.com
  • Detailed PyPI description (10133 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

  • 150 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 100 commits in mosquito/axio-agent
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 6.0

Found 4 network call pattern(s)

  • self.http_session = aiohttp.ClientSession() own_session = True url = f"{self.base_
  • _make_spec()]) async with aiohttp.ClientSession() as session: t = OpenAICompatibleTransport(base_url
  • = fake_server async with aiohttp.ClientSession() as session: yield NebiusTransport(base_url=base_ur
  • chunks("ok")) async with aiohttp.ClientSession() as session: t = NebiusTransport( base_
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • lta( data=base64.b64decode(ev["delta"]), media_type=self.output_aud
✓ 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

Repository mosquito/axio-agent appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 axio-transport-openai 
Create a Python-based command-line tool that leverages the 'axio-transport-openai' package to interact with OpenAI's API for generating text completions. This tool will allow users to input a text prompt and receive a response from an AI model hosted on OpenAI. The application should have the following functionalities:

1. User Input: Allow users to input their own prompts through the command line.
2. Response Generation: Use the 'axio-transport-openai' package to send these prompts to an OpenAI API endpoint and retrieve the generated text completion.
3. Error Handling: Implement error handling to manage potential issues such as network errors, invalid inputs, or API rate limits.
4. Logging: Include logging capabilities to record interactions, including user inputs and received responses.
5. Configuration: Provide a configuration file where users can specify their API key and other settings.
6. Help Documentation: Offer a help menu accessible via command-line options that explains how to use the tool and provides examples of valid inputs.
7. Output Customization: Allow customization of the output format (e.g., plain text, markdown).
8. Interactive Mode: Support an interactive mode where users can continuously input prompts without exiting the program.

To utilize the 'axio-transport-openai' package, you will need to install it using pip. Then, set up your main script to initialize the transport object with the appropriate configuration (such as API key and endpoint). Use this transport object to make requests to the OpenAI API and handle the responses appropriately within your application.

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