Wide Research Web UI Tutorial

This tutorial demonstrates how to use the ToolUniverse Wide Research Web UI, a powerful web-based interface that provides intelligent literature search and analysis capabilities across multiple academic databases.

Overview

The Wide Research Web UI is a comprehensive web application that combines:

  • Multi-database search across 11+ academic databases

  • AI-powered query expansion for better search results

  • Intelligent summarization with temporal and thematic analysis

  • Modern web interface with paper card display

  • Real-time search status and tool usage tracking

Key Features

  • Unified Search Interface: Search across ArXiv, PubMed, Crossref, Semantic Scholar, OpenAlex, DBLP, DOAJ, Europe PMC, HAL, MedRxiv, and Unpaywall

  • Smart Query Processing: AI-powered query expansion to generate multiple search terms

  • Intelligent Analysis: Comprehensive literature review generation with: - Research overview and scope analysis - Temporal analysis of research trends - Thematic analysis of research areas - Key contributions identification - Research gaps and future directions

  • Paper Card Display: Modern, responsive interface showing papers with source identification

  • Real-time Status: Live updates on tool usage and search progress

Quick Start

Starting the Web UI

The easiest way to start the Wide Research Web UI is using the command-line tool:

tooluniverse-wide-research

This will start the web server and display:

🚀 Starting ToolUniverse Wide Research Web UI...
📚 Available tools: ArXiv, PubMed, Crossref, Semantic Scholar, OpenAlex, DBLP, DOAJ, Europe PMC, HAL, MedRxiv, Unpaywall
🌐 Web interface will be available at: http://localhost:5001
🔍 API endpoint: http://localhost:5001/api/search
📖 Documentation: http://localhost:5001/api/tools
============================================================
Press Ctrl+C to stop the server
============================================================

Access the web interface by opening http://localhost:5001 in your browser.

Alternative Startup Methods

You can also start the web UI directly:

# Method 1: Direct Python execution
cd /path/to/ToolUniverse/src/tooluniverse/web_tools/literature_search_ui
python simple_app.py

# Method 2: Using Python module
python -m tooluniverse.web_tools.literature_search_ui.simple_app

Using the Web Interface

Understanding the Results

The web interface displays results in several sections:

Search Status - Real-time updates on which tools are being used - Success/failure status for each database - Total number of papers found

Paper Cards Each paper is displayed as a card showing: - Title and Authors - Publication year and Source database - Abstract (truncated with expand option) - Journal/Venue information - DOI and Direct links - Source badge with color-coded identification

Intelligent Summary (when enabled) - Research Overview: Scope, recent activity, data sources - Research Timeline: Temporal analysis of publication trends - Research Themes: Primary research areas and methodological approaches - Key Contributions: Notable papers and their significance - Research Trends: Collaboration patterns and emerging patterns - Research Gaps: Identified gaps and future opportunities - Methodology: Information about the search process

Advanced Features

AI Query Expansion

When “AI Query Split” is enabled, the system automatically:

  1. Analyzes your query to identify key concepts

  2. Generates related terms and synonyms

  3. Creates multiple search variations for comprehensive coverage

  4. Searches each variation across all databases

Example: - Input: “machine learning” - Expanded queries: [“machine learning”, “deep learning”, “neural networks”, “AI applications”]

Intelligent Summarization

The AI summary provides comprehensive analysis including:

Temporal Analysis - Recent developments (2021+) - Historical context by decade - Publication trends over time - Key papers from each period

Thematic Analysis - Primary research areas (Machine Learning, Computer Vision, NLP, etc.) - Methodological approaches (Deep Learning, Statistical Methods, etc.) - Research focus distribution

Key Contributions - Most important papers identified - Author collaboration patterns - Source diversity analysis

Research Gaps & Future Directions - Emerging trends and patterns - Identified research gaps - Future research opportunities

API Usage

The web UI also provides RESTful API endpoints for programmatic access:

Search Endpoint

POST http://localhost:5001/api/search
Content-Type: application/json

{
    "query": "machine learning",
    "use_ai_split": true,
    "use_ai_summary": true,
    "limit": 10
}

Response format:

{
    "success": true,
    "query": "machine learning",
    "search_terms": ["machine learning", "deep learning", "neural networks"],
    "total_results": 25,
    "tools_used": ["ArXiv_search_papers", "PubMed_search_articles", "Crossref_search_works"],
    "results": [
        {
            "query": "machine learning",
            "total_results": 8,
            "tools_used": ["ArXiv_search_papers"],
            "results_by_tool": {
                "ArXiv_search_papers": {
                    "status": "success",
                    "results": [...],
                    "count": 8
                }
            }
        }
    ],
    "summary": "# Literature Review: machine learning\n\n## 📊 Research Overview\n..."
}

Tool Information Endpoint

GET http://localhost:5001/api/tools
```

Returns information about available search tools and their capabilities.

Search History Endpoint

GET http://localhost:5001/api/history
```

Returns the last 10 search queries and their results.

Configuration

Environment Detection

The web UI automatically detects your ToolUniverse environment:

  • Full Mode: When ToolUniverse is available, uses all integrated tools

  • Demo Mode: When ToolUniverse is not available, uses simulated data

You can check the mode in the startup messages or by calling the tools endpoint.

Customization

The web UI can be customized by modifying:

  • Port: Change the default port (5001) in simple_app.py

  • Result limits: Adjust default limits in the interface

  • Database selection: Enable/disable specific databases

  • UI styling: Modify the HTML/CSS templates

Troubleshooting

Common Issues

Port Already in Use - The default port 5001 is already occupied - Solution: Kill the process using the port or change the port in the code

ToolUniverse Not Found - ToolUniverse is not properly installed or configured - Solution: Install ToolUniverse or run in demo mode

No Results Found - Search query might be too specific - Try broader terms or enable AI query expansion - Check if databases are accessible

Slow Performance - Large result sets or many databases can slow down searches - Reduce the result limit - Disable some databases if not needed

API Errors - Check network connectivity - Verify API endpoints are accessible - Check for rate limiting

Best Practices

Search Optimization

  1. Use specific, relevant keywords

  2. Enable AI query expansion for comprehensive coverage

  3. Start with moderate result limits (5-10) for faster searches

  4. Use the intelligent summary to understand research landscape

Result Analysis

  1. Review the paper cards for relevant publications

  2. Read the intelligent summary for research insights

  3. Check source diversity to ensure comprehensive coverage

  4. Use the timeline analysis to understand research evolution

Workflow Integration

  1. Start with broad searches to understand the field

  2. Refine queries based on initial results

  3. Use multiple search sessions for different aspects

  4. Export results for further analysis

Example Workflows

Literature Review Preparation

  1. Initial broad search: “artificial intelligence”

  2. Enable AI expansion and summary

  3. Review thematic analysis to identify key areas

  4. Focus on specific themes: “computer vision”, “natural language processing”

  5. Use temporal analysis to understand recent developments

  6. Identify research gaps for your contribution

Research Gap Analysis

  1. Search your research area: “quantum machine learning”

  2. Enable intelligent summary to see research gaps

  3. Review recent papers (last 2-3 years)

  4. Analyze collaboration patterns for potential partnerships

  5. Identify future directions mentioned in the summary

Competitive Analysis

  1. Search for key researchers in your field

  2. Use author names in search queries

  3. Review recent publications from competitors

  4. Analyze research trends to understand market direction

  5. Identify emerging areas for early entry

Complete Example

Here’s a complete example of using the Wide Research Web UI:

  1. Start the web UI:

    tooluniverse-wide-research

  2. Open your browser and go to http://localhost:5001

  3. Perform a search: - Query: “deep learning computer vision” - Enable AI Query Split: ✓ - Enable AI Summary: ✓ - Limit: 5

  4. Review the results: - Check the paper cards for relevant publications - Read the intelligent summary for insights - Note the research timeline and themes

  5. Refine your search: - Try more specific terms: “object detection deep learning” - Focus on recent papers: adjust date filters - Explore related themes from the summary

  6. Export results: - Use the API to programmatically access results - Save interesting papers for further reading - Use the summary for your literature review

This tutorial provides a comprehensive guide to using the ToolUniverse Wide Research Web UI. The interface combines the power of multiple academic databases with intelligent analysis to provide a complete literature research solution.

For more information about individual tools, see the literature search tools tutorial.

For API reference, see the API documentation.