agentforge-openai

v0.2.4 suspicious
5.0
Medium Risk

OpenAI LLM + embeddings provider for AgentForge — gpt-4o / o-series + text-embedding-3-*

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of network, shell, obfuscation, and credential handling. However, the metadata risk score is elevated due to missing repository information and a new maintainer account, which raises suspicion.

  • Metadata risk due to missing repository
  • New maintainer account
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require external API interactions.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: Suspicious due to missing repository and new maintainer account.

🔬 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 "The AgentForge Authors" 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 agentforge-openai
Create a personalized note-taking and summarization app using the 'agentforge-openai' Python package. This app will allow users to input their notes and receive summaries generated by an advanced AI model, enhancing productivity and comprehension. Here’s a detailed plan on how to develop this app:

1. **Project Setup**: Initialize a new Python environment and install necessary packages including 'agentforge-openai', 'Flask' for web server, and 'sqlite3' for local database.
2. **Database Design**: Design a simple database schema to store user information (username, password hash) and notes (title, content, summary).
3. **User Authentication**: Implement basic user authentication functionality (sign-up, sign-in, sign-out) to ensure only registered users can access their notes.
4. **Note Input & Storage**: Develop a feature where users can input their notes through a web interface. Upon submission, these notes should be stored in the database along with a timestamp.
5. **AI-Powered Summarization**: Utilize the 'agentforge-openai' package to generate summaries of the notes. Users should have the option to request a summary for any of their notes.
6. **Display Summaries**: Show both the original notes and their corresponding summaries on a dedicated page. Ensure that the display is user-friendly and easy to navigate.
7. **Search Functionality**: Allow users to search for specific notes based on keywords found within the notes or summaries.
8. **Advanced Features**: Consider adding features such as sentiment analysis on the notes, categorization of notes into different topics, and integration with calendar apps for scheduling reminders.
9. **Security Measures**: Implement basic security measures such as HTTPS for secure data transmission and hashing passwords before storing them in the database.
10. **Testing & Deployment**: Thoroughly test all functionalities before deploying the app on a cloud platform like Heroku or AWS.

The 'agentforge-openai' package is crucial for generating high-quality summaries of user notes using advanced AI models provided by OpenAI. It simplifies the process of integrating these powerful tools into your application.

💬 Discussion Feed

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