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FireCoder: Your Self-hosted AI Code Writing Assistant

FireCoder is your self-hosted AI assistant, purpose-built to optimize your coding experience directly on your local machine.

Feel free to share your feedback or report any issues on our GitHub repository.

FireCoder is currently a work in progress, and we appreciate your patience and support as we continue to enhance its capabilities.

Features

  • Easy Installation: Simply install extensions and start using FireCoder.
  • Completion Auto Mode: Enjoy the convenience of automatic code suggestions.
  • Manual Mode: Switch between auto mode and manual mode for code suggestions.
  • Chat Mode: Interact with FireCoder through natural language, receiving code suggestions and guidance tailored to your needs.
  • Multi-line Code Suggestions: Enhance your coding experience with multi-line code suggestions.
  • Platform Support: FireCoder supports Windows, Linux, and macOS.

New Experimental Features:

  • GPU Support: You can now utilize GPU support by adjusting the firecoder.experimental.useGpu settings in configuration.

Getting Started

  1. Download the VS Code extension for FireCoder.
  2. Wait for Server and Model Download.
  3. Start coding with the assistance of our AI-driven features.

Roadmap

  • Custom Commands
  • Generate Commit Descriptions
  • Easy GPU Support
  • Pull Request Reviews
  • Cloud Service
  • IntelliJ IDEA Support
  • Self-Hosting for Teams

We're committed to making FireCoder an indispensable part of your coding toolkit. Stay tuned for updates as we bring these exciting features to life!

System Requirements

Minimal Requirements

  • Disk Space: Minimum 2 GB of free disk space.
  • RAM: Minimum 1 GB of available memory.

These are the minimum specifications to run the FireCoder. The extension should function, but performance may be limited.

Optimal Requirements

  • Disk Space: 14 GB or more of free disk space.
  • RAM: 6 GB or more of available memory.

If you intend to utilize the high-power and large model features, it is advisable to use a system with enhanced specifications to achieve better performance.

Links

Release Notes

See Github Releases