# 😺🚀 RoCat

RoCat is a Python library that provides a simple and user-friendly interface for integrating AI services into your projects. It supports various AI functionalities such as text summarization, YouTube transcript retrieval, audio transcription using OpenAI's Whisper, and web search using SerpAPI.

## Installation

You can install RoCat using pip:

~~~bash
pip install rocat
~~~

## Quick Start Guide

1. **Initialize RoCat**: Begin by creating a default configuration and example code to get started.

~~~bash
rocat init

Default configuration file and example code created.
- config.ini
- rocat_example.py
~~~

This command creates a default configuration file (config.ini) and an example script (rocat_example.py).

2. **Edit Configuration**: Open config.ini to add your API keys.

~~~ini
[API_KEYS]
openai = 
anthropic = 
serpapi =
naver_clovastudio =
naver_apigw =
~~~

3. **Write Your Code**: You can refer to the rocat_example.py file for sample usage of the library.

~~~python
# rocat_example.py
import rocat as rc

def main():
    # Initialize the library
    rc.initialize()
    
    # Write your code here.

if __name__ == "__main__":
    main()
~~~

## Example Usage

### Text Summarization

~~~python
def main():
    rc.initialize()
    
    # Get text from a web page
    url = "https://www.example.com/sample-page"
    text = rc.get_web(url)
    
    # Summarize the text
    summary = rc.ai_summarize(text, 3)
    
    # Print the summarized text
    print("\nAI Summary Test:")
    print(summary)

if __name__ == "__main__":
    main()
~~~

### YouTube Transcript Retrieval

~~~python
def main():
    rc.initialize()
    
    # Get captions from a YouTube video
    video_url = "https://www.youtube.com/watch?v=example-video-id"
    transcript = rc.get_youtube(video_url)
    
    # Print the caption text
    print("\nYouTube Caption Test:")
    print(transcript)

if __name__ == "__main__":
    main()
~~~

### Audio Transcription

~~~python
def main():
    rc.initialize()
    
    # Convert an audio file to text
    audio_file = "path/to/example/audio.mp3"
    transcription = rc.get_whisper(audio_file)
    
    # Print the converted text
    print("\nWhisper Recognition:")
    print(transcription)

if __name__ == "__main__":
    main()
~~~

### Web Search

~~~python
def main():
    rc.initialize()
    
    # Get Google search results
    query = "python"
    search_results = rc.get_search(query)
    for result in search_results:
        print(f"Title: {result['title']}")
        print(f"Link: {result['link']}")
        print(f"Snippet: {result['snippet']}")

if __name__ == "__main__":
    main()
~~~

## Features

- Text summarization using AI
- YouTube transcript retrieval
- Audio transcription using OpenAI's Whisper
- Web search using SerpAPI
- File utilities for handling various file formats (txt, xls, xlsx, doc, docx, ppt, pptx, csv, pdf, hwp, hwpx)
- Language model integration (GPT-3.5, GPT-4, Claude, Opus, Haiku, Sonnet)

## License

This project is licensed under the MIT License. See the LICENSE file for more information.

## Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository.

## Contact

If you have any questions or inquiries, please contact the author:

- Name: Faith6
- Email: root@yumeta.kr
