autogen-dakera

v0.2.0 safe
3.0
Low Risk

AutoGen integration for the Dakera AI memory platform

🤖 AI Analysis

Final verdict: SAFE

The package autogen-dakera v0.2.0 shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential risks. However, the metadata risk is slightly elevated due to the maintainer having only one package.

  • No network calls
  • Single package by maintainer
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 risk of unauthorized command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

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

Some documentation present

  • Documentation URL: "Documentation" -> https://docs.dakera.ai/integrations/autogen
  • Detailed PyPI description (6318 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 29 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 3 unique contributor(s) across 30 commits in dakera-ai/dakera-autogen
  • Small but multi-author team (3–4 contributors)

🔬 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

Repository dakera-ai/dakera-autogen appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Dakera Team" 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 autogen-dakera 
Create a fully-functional mini-application that integrates the 'autogen-dakera' Python package to facilitate seamless interaction between users and the Dakera AI memory platform. Your task is to develop a chatbot application that allows users to store, retrieve, and manage memories using natural language queries. This application will serve as a personal digital diary, enabling users to engage with their memories in a conversational manner. Here’s a detailed breakdown of the requirements and functionalities:

1. **User Authentication**: Implement a simple user authentication system to ensure that each user has a private space to store and manage their memories.
2. **Memory Storage**: Users should be able to input text-based memories using natural language. The application should utilize the 'autogen-dakera' package to automatically categorize these memories based on context and sentiment analysis.
3. **Memory Retrieval**: Users should be able to query their memories using natural language. The application should leverage the 'autogen-dakera' package to understand the intent behind the query and retrieve relevant memories.
4. **Memory Management**: Provide functionalities for users to edit, delete, or tag memories. The 'autogen-dakera' package should be used to enhance these operations by suggesting tags or providing insights into the content of the memories.
5. **Sentiment Analysis**: Integrate the sentiment analysis capabilities of the 'autogen-dakera' package to allow users to view trends in their emotional state over time.
6. **Chat Interface**: Design a user-friendly chat interface where users can interact with the application. The chatbot should respond naturally, guiding users through the process of managing their memories.
7. **Integration Testing**: Ensure that the application is thoroughly tested for integration with the 'autogen-dakera' package, verifying that all features function as expected.

This project aims to demonstrate the power of combining human-like conversation with advanced memory management capabilities, making it easier for individuals to keep track of their personal experiences and emotions.

💬 Discussion Feed

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