https://github.com/imass2550/token-visualizer
Token Visualizer helps you analyze and optimize your prompts for Large Language Models, saving you time and money. 🚀 With this tool, you can easily see token usage and improve your prompt efficiency. 💻
https://github.com/imass2550/token-visualizer
ai android api bubblemaps byte-pair-encoding docker gpt4 llm nodejs padding part-of-speech-tagger pixels playwright react textappearance tokens vercel word-segmentation
Last synced: 27 days ago
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Token Visualizer helps you analyze and optimize your prompts for Large Language Models, saving you time and money. 🚀 With this tool, you can easily see token usage and improve your prompt efficiency. 💻
- Host: GitHub
- URL: https://github.com/imass2550/token-visualizer
- Owner: imass2550
- Created: 2025-06-11T00:54:33.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-06-11T14:56:46.000Z (8 months ago)
- Last Synced: 2025-06-11T16:23:07.021Z (8 months ago)
- Topics: ai, android, api, bubblemaps, byte-pair-encoding, docker, gpt4, llm, nodejs, padding, part-of-speech-tagger, pixels, playwright, react, textappearance, tokens, vercel, word-segmentation
- Language: Python
- Size: 15.6 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Token Visualizer 🛠️
Welcome to the **Token Visualizer** repository! This tool is designed for anyone looking to analyze, visualize, and optimize prompts for large language models (LLMs). Whether you're a developer, researcher, or enthusiast, Token Visualizer will help you make the most of your interactions with models like OpenAI's ChatGPT.
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [How It Works](#how-it-works)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
## Introduction
In the age of artificial intelligence, understanding how to communicate effectively with LLMs is crucial. Token Visualizer provides a user-friendly interface to break down prompts, visualize token usage, and optimize interactions. This tool allows you to see how different prompts affect token consumption and model responses.
## Features
- **Analyze Prompts**: Gain insights into how your prompts are tokenized.
- **Visualize Token Usage**: See a clear representation of token distribution.
- **Optimize Interactions**: Get suggestions on how to refine your prompts for better results.
- **Supports Multiple Models**: Works seamlessly with various LLMs, including those from OpenAI.
- **User-Friendly Interface**: Designed for ease of use, even for those new to LLMs.
## Installation
To get started, you need to download the latest release of Token Visualizer. You can find it [here](https://github.com/imass2550/Token-Visualizer/releases). Download the appropriate file for your operating system, then follow the instructions below to install.
### For Windows
1. Download the Windows executable from the [Releases](https://github.com/imass2550/Token-Visualizer/releases) section.
2. Open the command prompt.
3. Navigate to the folder where you downloaded the file.
4. Run the executable.
### For macOS
1. Download the macOS package from the [Releases](https://github.com/imass2550/Token-Visualizer/releases) section.
2. Open the terminal.
3. Navigate to the downloaded file location.
4. Run the package.
### For Linux
1. Download the Linux binary from the [Releases](https://github.com/imass2550/Token-Visualizer/releases) section.
2. Open your terminal.
3. Navigate to the download directory.
4. Run the binary using the command: `./token-visualizer`.
## Usage
Once you have installed Token Visualizer, you can start using it right away. Here’s how:
1. **Open the Application**: Launch the Token Visualizer from your applications menu or command line.
2. **Input Your Prompt**: Enter the text you want to analyze in the input field.
3. **Analyze Tokens**: Click on the "Analyze" button to see the token breakdown.
4. **View Visualization**: The tool will generate a visual representation of your token usage.
5. **Optimize**: Use the suggestions provided to refine your prompt for better model responses.
### Example
Here’s a quick example of how you might use Token Visualizer:
- **Input**: "What are the benefits of using large language models?"
- **Output**: The tool shows how many tokens your prompt uses and suggests a more concise version, such as "Benefits of LLMs?"
## How It Works
Token Visualizer operates by breaking down your input into tokens, which are the basic units of meaning for language models. The tool uses OpenAI's API to fetch tokenization data and analyze how prompts are processed. Here’s a simplified overview of the process:
1. **Tokenization**: The input text is split into tokens based on the model's understanding.
2. **Analysis**: Each token is examined to determine its length and significance.
3. **Visualization**: The tool creates graphs and charts to represent token distribution and usage.
## Contributing
We welcome contributions to Token Visualizer! If you have ideas for features, improvements, or bug fixes, please follow these steps:
1. **Fork the Repository**: Click the "Fork" button at the top right of the page.
2. **Create a Branch**: Make a new branch for your changes.
3. **Make Changes**: Implement your features or fixes.
4. **Submit a Pull Request**: Push your changes and open a pull request.
### Code of Conduct
Please adhere to our code of conduct to ensure a welcoming environment for all contributors.
## License
Token Visualizer is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contact
For questions, feedback, or support, feel free to reach out:
- **Email**: support@tokenvisualizer.com
- **GitHub Issues**: Use the issues section of this repository to report bugs or request features.
## Conclusion
Thank you for using Token Visualizer! We hope this tool enhances your experience with large language models. Don't forget to check the [Releases](https://github.com/imass2550/Token-Visualizer/releases) section for updates and new features. Happy visualizing!