backboard-sdk

v1.5.15 safe
4.0
Medium Risk

Python SDK for the Backboard API - Build conversational AI applications with persistent memory and intelligent document processing

🤖 AI Analysis

Final verdict: SAFE

The package is considered safe despite the metadata risk due to lack of evidence of malicious activities such as network, shell, or obfuscation risks.

  • Low network risk typical for SDKs
  • No signs of shell execution or obfuscation
  • No credential harvesting attempts detected
Per-check LLM notes
  • Network: The package makes network calls using an API key, which is typical for SDKs communicating with backend services.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The repository is not found and the maintainer has only one package, which may indicate suspicious activity.

📦 Package Quality Overall: Low (4.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_live_reasoning.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://app.backboard.io/docs
  • Detailed PyPI description (13608 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 84 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • client self._client = httpx.AsyncClient( headers={ "X-API-Key": self.api
✓ 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: backboard.io>

✓ 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 "Backboard" 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 backboard-sdk 
Create a mini-application named 'ConvoDocBot' that leverages the 'backboard-sdk' package to process and manage user interactions around documents. This application will serve as a conversational assistant that can understand, store, and retrieve information from various documents, providing a seamless user experience. Here’s a detailed breakdown of the application's functionality and steps to implement it:

1. **Setup Environment**: Begin by setting up your development environment with Python and installing the 'backboard-sdk'. Ensure you have access to the Backboard API credentials necessary for authentication.

2. **User Interaction Module**: Develop a module that allows users to interact with the application through natural language inputs. Users should be able to ask questions about the content of their documents, request specific pieces of information, or seek summaries.

3. **Document Processing**: Utilize the 'backboard-sdk' to integrate document processing capabilities. The application should support multiple file formats (e.g., PDF, DOCX, TXT) and be able to extract key information from these documents.

4. **Persistent Memory**: Implement a feature where the application remembers previous interactions and document-related queries. Use the 'backboard-sdk' to manage this persistent memory, ensuring that users receive contextually relevant responses based on past conversations.

5. **Intelligent Summarization**: Incorporate a summarization feature that uses the 'backboard-sdk' to generate concise summaries of longer documents. This could be particularly useful for quick overviews or when users need a brief summary of a document's main points.

6. **Integration with Chat Platforms**: Optionally, extend the application to work within popular chat platforms (like Slack or Discord) using webhooks or APIs provided by these platforms. This would allow users to interact with 'ConvoDocBot' directly within their preferred communication channels.

7. **Security and Privacy Compliance**: Ensure that all data handling complies with relevant privacy regulations. Use secure methods for storing and transmitting data, and ensure that only authorized users can access the application and its stored data.

8. **Testing and Documentation**: Finally, thoroughly test the application to ensure reliability and accuracy. Document the setup process, usage instructions, and any troubleshooting tips for future maintenance and updates.

By following these steps and utilizing the 'backboard-sdk', you'll create a powerful tool that enhances document management and retrieval through conversational AI.

💬 Discussion Feed

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