agentmemry

v0.1.1 safe
1.0
Low Risk

Local-first memory for AI agents. SQLite + local embeddings. No cloud required.

🤖 AI Analysis

Final verdict: SAFE

The package does not exhibit any risky behaviors such as network calls, shell executions, or code obfuscation. It appears to be a straightforward local-first memory solution using SQLite.

  • No network calls
  • No shell execution
  • No obfuscation
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external communication.
  • Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of code obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret or credential theft.

🔬 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

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 7.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • Very few commits: 1 total
  • Single contributor with only 1 commit(s) — possibly throwaway account
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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 agentmemry 
Create a personal knowledge management system using the 'agentmemry' Python package. This system will allow users to store, organize, and retrieve information locally without relying on cloud services. The application should include the following features:

1. **User Interface**: Develop a simple and intuitive command-line interface (CLI) for users to interact with the system.
2. **Data Entry**: Allow users to input various types of data such as text notes, links, images, and other files.
3. **Search Functionality**: Implement a search feature that leverages 'agentmemry' to find stored data based on user queries. Utilize local embeddings for semantic search capabilities.
4. **Organization Tools**: Enable users to categorize their entries into different tags or folders for better organization.
5. **Backup and Restore**: Provide options for backing up and restoring the local database to ensure data safety.
6. **Privacy Focus**: Emphasize the privacy aspect by highlighting that all data is stored locally, ensuring user data remains private and secure.

**How to Use 'agentmemry':** 
- Initialize a local SQLite database using 'agentmemry' to store user data.
- Utilize the embedding functionality provided by 'agentmemry' to create semantic representations of the data for advanced search capabilities.
- Implement a mechanism within your application to update and manage these embeddings as new data is added or existing data is modified.

Your goal is to build a fully functional mini-app that demonstrates the power and flexibility of 'agentmemry' while providing a useful tool for managing personal information.