agentchatme

v1.0.3 suspicious
5.0
Medium Risk

Official Python SDK for AgentChat — the messaging platform for AI agents. Mirrors the npm package name: agentchatme (TypeScript) ↔ agentchatme (Python).

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has some indicators that raise concerns but does not show clear signs of malicious intent. The maintainer's inactivity and lack of community engagement increase the metadata risk.

  • Maintainer seems new or inactive
  • Repository lacks community engagement
Per-check LLM notes
  • Network: The use of httpx for network calls is common and not inherently suspicious; however, without additional context, there could be concern if the package is making unexpected external calls.
  • Shell: No shell execution patterns detected, which is normal and expected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • ent: httpx.Client = client or httpx.Client(timeout=_httpx_timeout(options.timeout_ms)) def close(s
  • httpx.AsyncClient = client or httpx.AsyncClient( timeout=_httpx_timeout(options.timeout_ms)
✓ 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 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "AgentChat" 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 agentchatme 
Create a simple chatbot application using the 'agentchatme' Python package. This chatbot will serve as a customer service representative for a fictional e-commerce store, providing information about products, answering common questions, and assisting with order inquiries. The application should be designed to run locally on your machine but could potentially be deployed online for real-world use.

### Core Features:
- **User Interface**: Implement a basic command-line interface (CLI) for users to interact with the chatbot. Consider adding a simple text-based menu system to guide users through different functionalities.
- **Product Information**: Allow users to ask about product details such as price, availability, and descriptions. The chatbot should fetch this data from a predefined JSON file that mimics a product catalog.
- **Order Inquiry**: Enable users to check the status of their orders by entering an order number. The bot should simulate fetching order information from a mock database.
- **Frequently Asked Questions (FAQs)**: Provide answers to common questions related to shipping, returns, payment methods, etc., stored within the application.
- **Feedback Collection**: Offer users the option to leave feedback about their experience with the chatbot, which can be logged into a text file for analysis.

### Utilizing 'agentchatme':
- Use the 'agentchatme' package to establish a connection between the chatbot and the AgentChat platform, enabling seamless communication.
- Integrate the package to handle incoming user messages and outgoing responses, ensuring that the chatbot can understand natural language queries and provide relevant, context-aware replies.
- Leverage the capabilities of 'agentchatme' to enhance the chatbot’s ability to learn from interactions and improve its responses over time, making it more effective at handling customer queries.

### Development Steps:
1. **Setup Environment**: Install necessary packages including 'agentchatme'.
2. **Design User Flow**: Plan out the interactions between the user and the chatbot.
3. **Implement CLI Interface**: Create a simple CLI for users to interact with the chatbot.
4. **Integrate Product Data**: Load product information from a JSON file.
5. **Build Order Inquiry Feature**: Simulate fetching order statuses.
6. **Implement FAQ Section**: Predefine answers to common questions.
7. **Add Feedback Mechanism**: Allow users to provide feedback.
8. **Test Application**: Ensure all features work as expected.
9. **Enhance Using 'agentchatme'**: Utilize the package to improve interaction quality.
10. **Document Code**: Write comments and documentation for future reference.

💬 Discussion Feed

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