Fiber: High-Performance Neuro-Symbolic IDE

Official Visual Studio Code extension for the Fiber programming language. Fiber is a next-generation "batteries-included" language designed for seamless integration of Neural Networks and Symbolic Logic.

🚀 Features

• 🌈 Gold-Standard Syntax Highlighting: Precisely colorized keywords, operators, and Fiber-specific types (tensor, expr, struct, enum, match).
• 🏗️ One-Click Standalone Build: Right-click any Fiber file to compile it into a production-ready Windows .exe instantly.
• 🛡️ Bytecode Integration: Native support for Fiber Compiled Bytecode (.fibc) visualization and distribution.
• 🧠 Expert Snippets:
  • fneural: Instantly scaffold a modular Sequential neural network.
  • fexpr: Create and differentiate symbolic expressions.
  • fmatch: Professional pattern-matching boilerplate.
• 🌑 Fiber Branded Dark Theme: A premium, custom-designed dark theme optimized for neuro-symbolic development.
• 🎨 Professional Terminal UI & Themes: Built-in libraries (terminal.fib, theme.fib) for creating colored console applications and high-visibility report systems.
• ⚙️ Integrated Language Support: Auto-bracket matching, indentation rules, and intelligent comment toggling.

🛠️ Getting Started

1. Download Fiber: Get the latest fiber.exe from the Official Releases.
2. Install Extension: Search for Fiber in the Marketplace and click Install.
3. Configure Path:
   • Open VS Code Settings (Ctrl+,).
   • Search for Fiber Path.
   • Paste the path to your fiber.exe (e.g., C:\Tools\fiber.exe).
4. Select Theme: Open any .fib file and switch to the official theme: Ctrl+K, Ctrl+T -> Fiber Branded Dark.

🏗️ Running Code

• Option 1 (Built-in): Right-click any .fib file in the explorer and select "Build to Executable (EXE)".
• Option 2 (Code Runner): If you have the Code Runner extension, add the following to your settings.json for 1-click execution:

"code-runner.executorMap": {
    "fiber": "cd $dir && fiber $fileName"
}

🧩 Fiber at a Glance

# Symbolic Differentiation
var e = expr("x**2 + 5*x")
print diff(e, "x")

# Neural Architecture
from neural import Linear, ReLU, Sequential
var model = Sequential([
    Linear(10, 32),
    ReLU(),
    Linear(32, 1)
])

📜 License

This extension is licensed under the MIT License.

Developed by daksh-gehlot