Introduction:

The Human-Centric Programming Language (HCL) bridges this gap by prioritizing intuitive, readable instructions over verbose boilerplate code. As an early prototype, HCL enables users to express ideas in everyday English sentences while generating reliable Python code behind the scenes.

Problem Statement:

The lack of a programming language that allows users to write code using simple, natural English sentences while maintaining reliability, advanced data structures, and seamless execution creates a steep learning barrier for beginners and non-programmers. Traditional languages force users to focus on rigid syntax, brackets, indentation, and boilerplate code instead of solving actual problems.

Objective:

The main objective of this project is to develop a Human-Centric Programming Language (HCL) that enables users to write programs using everyday English sentences (e.g., “set age to 42” or “create empty avl tree scores”) instead of complex syntax rules. The system uses a robust rule-based pattern-matching engine powered by actions.jsonl combined with a custom AST generator to convert these natural language instructions into correct, executable Python code. The standalone compiler (Compiler.exe) provides a modern notebook-style interface and automatically downloads a fine-tuned hybrid AI model from Hugging Face on first run, ensuring a lightweight yet powerful development experience.

Key Features:

  1. Modern Notebook Interface: A clean, tabbed notebook-style IDE with block-based editing, real-time output, and interactive terminal support.
  2. Multi-Language Execution Engine: Supports execution of Python, C, C++, and the custom HCL language within the same environment.
  3. AI Integration:Integrated with a locally hoste d Large Language Model using llama.cpp for future intelligent assistance.
  4. Dynamic Model Downloader:Automatically downloads the required AI model (~4 GB) from Hugging Face on first launch with progress tracking.
  5. Actions System & Parser:A robust actions.jsonl-based pattern matching system with a custom parser that converts natural language commands into Python Abstract Syntax Tree (AST) for execution.
  6. Professional Build & Distribution:Compiled as a standalone executable using Nuitka and packaged with a professional installer created using Inno Setup.
  7. User Experience:Features include dark/light theme support, folder tree navigation, auto-resizing blocks, save/load functionality, and an intuitive REPL mode.

Technical Architecture:

  1. Frontend: Custom Tkinter-based GUI with modern styling
  2. Backend: Custom AST Generator and execution engine (parser.py + run.py)
  3. AI Engine: llama.cpp with GGUF quantized model
  4. Build System: Nuitka (for standalone .exe)
  5. Installer: Inno Setup