ailite 0.7.0

A powerful web content fetcher and processor

ParserLite: Lightweight Web Search & Text Processing 🚀

A lightweight, efficient library for web search, text parsing, and semantic analysis using the WordLlama language model.

🌟 Features

• 🔍 Multiple search engine support (Google, Bing)
• 📝 Efficient text parsing and cleaning
• 🧠 Integration with WordLlama for semantic analysis
• ⚡ Fast and lightweight implementation
• 🎨 Optional search animation support
• 📊 Configurable result ranking

📦 Installation

pip install parselite searchlite wordllama

🚀 Quick Start

GoogleSearch+AI

from visionlite import vision
results = vision("What is quantum computing?")
print(results)

BingSearch+AI

from visionlite import visionbing
results = visionbing("What is quantum computing?")
print(results)

📖 Usage Examples

Basic Search with Google

def vision(query, k=1, max_urls=5, animation=False):
    # Search, parse, and rank results
    results = llm.topk(
        query,
        llm.split("".join(
            parse(google(query, max_urls=max_urls, animation=animation))
        )),
        k=k
    )
    return "\n".join(results)

# Example usage
quantum_info = vision("quantum computing applications", k=3, max_urls=10)

Search with Bing

def visionbing(query, k=1, max_urls=5, animation=False):
    # Search using Bing, parse, and rank results
    results = llm.topk(
        query,
        llm.split("".join(
            parse(bing(query, max_urls=max_urls, animation=animation))
        )),
        k=k
    )
    return "\n".join(results)

# Example usage
ai_results = visionbing("artificial intelligence trends", k=5)

🔧 Configuration

Search Parameters

• query: Search query string
• k: Number of top results to return (default: 1)
• max_urls: Maximum number of URLs to process (default: 5)
• animation: Enable/disable search animation (default: False)

🤝 Contributing

Contributions are welcome! Here's how you can help:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• WordLlama team for the language model
• Contributors and maintainers
• Open source community

🔮 Future Plans

• Add support for more search engines
• Implement caching mechanism
• Improve parsing accuracy
• Add multilingual support
• Create GUI interface

⭐ Star History

📊 Performance

Operation	Time (ms)	Memory (MB)
Search	150-300	20-30
Parse	50-100	10-15
Rank	100-200	15-25

🔥 Showcase

Projects using ParserLite:

• Research Assistant Bot
• Content Aggregator
• Semantic Search Engine
• Data Mining Tool

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