Bohrium Paper Search Tool

English | 简体中文

Author: dp
Version: 0.0.2 Type: tool

Description

bohrium-tool-paper is a powerful academic paper retrieval tool plugin that offers multiple search modes to meet various research needs. This tool supports keyword search, semantic search, and other advanced retrieval methods, helping researchers efficiently access academic resources.

Key Features

• Multiple Search Modes:

  • Keyword Search: Ideal for precise author name or keyword searches
  • Enhanced Search: Provides more powerful retrieval capabilities
  • Pro Search 1.0: Enhanced semantic understanding
  • Pro Search 2.0: State-of-the-art semantic retrieval

• Rich Filtering Options:

  • Time range filtering
  • Author search
  • Support for both English and Chinese queries

Requirements

• Valid API access key (access_key)
• Python 3.12 runtime environment
• Memory requirement: minimum 256MB

Installation

1. Ensure your system meets the running requirements
2. Configure a valid API access key
3. Follow the standard plugin installation process

API Response Data

The tool returns data including the following main fields:

• Paper DOI
• Paper title (English and Chinese)
• Abstract (English and Chinese)
• Author information
• Publication date
• Citation count
• Impact factor
• Other academic metrics

Supported Languages

• English (en_US)
• Simplified Chinese (zh_Hans)
• Portuguese (pt_BR)

Usage Example

# Example query parameters
{
    "query": "artificial intelligence",
    "search_type": 3,  # Pro Search 2.0
    "start_time": "2023-01-01",
    "end_time": "2024-03-21"
}

Response Format

{
    "success": true,
    "data": [
        {
            "doi": "...",
            "paperId": "...",
            "enName": "Paper Title",
            "authors": [...],
            "enAbstract": "...",
            "citationNums": 0,
            "impactFactor": 0.0
        }
    ],
    "search_info": {
        "type": 3,
        "search_type": "Pro Search 2.0",
        "total_results": 50
    }
}

Error Handling

The plugin provides clear error messages for common issues:

• Invalid API key
• Network connection problems
• Invalid search parameters
• API rate limiting

Best Practices

1. Use Pro Search 2.0 for semantic understanding
2. Use Keyword Search for exact author matches
3. Specify date ranges for more focused results
4. Utilize both English and Chinese search capabilities for comprehensive results

Development

The plugin is built with:

• Python 3.12
• RESTful API integration
• JSON response format
• Secure API key handling

Contributing

We welcome contributions to improve the plugin. Please follow these steps:

1. Fork the repository
2. Create your feature branch
3. Submit a pull request

Technical Support

For any technical issues or suggestions, please contact us through: huangzhenting@dp.tech

License

MIT License

Acknowledgments

• Thanks to the DP Tech API service
• All contributors and users of this plugin

For more detailed information about privacy policy, please refer to PRIVACY.md.