agentloop-py-openai

v0.3.0 safe
4.0
Medium Risk

Drop-in OpenAI SDK wrapper for AgentLoop — adds memory retrieval and turn logging to chat.completions.create calls. Supports streaming.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no signs of network or shell abuse, obfuscation, or credential mishandling. The metadata risk, though elevated due to the maintainer's limited presence, does not conclusively point towards a supply-chain attack.

  • No network or shell execution risks
  • Low obfuscation and credential risk
  • Single package from the maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external communications.
  • Shell: No shell execution patterns detected, indicating the package does not attempt to execute commands on the host system.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating safe handling of sensitive information.
  • Metadata: The repository is not found and the maintainer has only one package, which could indicate potential risk.

🔬 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 score 3.0

Repository not found (deleted or private)

  • Repository not found (deleted or private)
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "AgentLoop" 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 agentloop-py-openai 
Create a personal AI assistant application using the 'agentloop-py-openai' Python package. This application will serve as a command-line interface where users can interact with an AI assistant that leverages OpenAI's API capabilities while adding unique features such as conversation history and contextual memory retrieval. Here’s a detailed breakdown of the steps and features to implement:

1. **Setup Environment**: Begin by setting up your Python environment and installing the necessary packages including 'agentloop-py-openai', 'openai', and any other dependencies required.
2. **Authentication**: Integrate OpenAI API keys securely into your application so it can communicate with OpenAI's servers.
3. **Core Functionality**: Implement the main interaction loop where the user can type commands or questions, and the AI responds based on these inputs. Utilize 'agentloop-py-openai' to enhance the OpenAI API responses by incorporating memory retrieval and turn logging.
4. **Conversation History**: Design a feature that allows the AI to remember previous conversations with the user, enabling context-aware responses. Use 'agentloop-py-openai' to manage the storage and retrieval of this data efficiently.
5. **Contextual Memory Retrieval**: Enhance the AI's ability to recall specific pieces of information from past interactions to provide more accurate and relevant answers.
6. **Streamed Responses**: Enable real-time updates from the AI as it processes requests, allowing for a smoother and more interactive experience.
7. **User Interface**: Although this is a command-line application, consider implementing basic formatting and color-coding to make the output more engaging and readable.
8. **Error Handling**: Ensure robust error handling to manage unexpected situations gracefully, providing useful feedback to the user.
9. **Testing**: Thoroughly test the application with various inputs to ensure reliability and responsiveness.
10. **Documentation**: Provide clear instructions on how to install and use the application, along with examples of common use cases.

This project aims to demonstrate the power and flexibility of integrating 'agentloop-py-openai' into applications that require enhanced AI interaction capabilities.