# VisionLite: Lightweight Web Search With AI 🚀

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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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

```bash
pip install parselite searchlite wordllama
```

## 🚀 Quick Start

### GoogleSearch+AI
```python
from visionlite import vision
results = vision("What is quantum computing?")
print(results)
```
### BingSearch+AI
```python
from visionlite import visionbing
results = visionbing("What is quantum computing?")
print(results)
```

## 📖 Usage Examples

### Basic Search with Google

```python
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

```python
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](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

[![Star History Chart](https://api.star-history.com/svg?repos=YourUsername/parselite&type=Date)](https://star-history.com/#YourUsername/parselite&Date)

## 📊 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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