🧠 NeuroCode – Modular Cognitive AI for Code Understanding

An open intellectual initiative to reimagine how machines understand code — inspired by the human brain.

📘 About the Project

NeuroCode is a cognitively inspired framework for understanding source code.
It simulates a neural memory system for machines by extracting lightweight "code neurons" from source code, documentation, and usage patterns.

These code neurons are:

• Activated only when relevant
• Forgotten when unused (simulating memory decay)
• Context-weighted based on frequency and recency
• Organized to mimic human cognitive behavior (contextual recall, associative memory, long-term consolidation)

🎯 The ultimate goal:
To reduce reliance on constant full LLM inference by emulating selective memory recall — the way the human brain activates specific memory pathways depending on the task.

🧩 Why Pluggable Knowledge Matters

In many domains, it's impractical or impossible to pretrain on proprietary or evolving data (e.g., private source code, stories in progress, custom ontologies).
NeuroCode offers a new model: treating knowledge as modular and pluggable.

• You can inject dynamic code or domain-specific memory on the fly.
• The system decides which neurons to activate, ignore, or decay — just like adaptive cognitive memory.
• This makes NeuroCode useful for real-time, domain-specific, or privacy-critical environments.

📄 Full Concept Document

Read the full open-initiative concept PDF here:
👉 initiative.pdf

Includes theoretical foundation, design principles, and architecture.

⚙️ What's Included

• 🧠 Code neuron extractor & semantic linker
• 🧩 Modular analyzers for generating cognitive embeddings
• 🔁 Context-aware recall simulation
• 🧪 Entry point script: main.py

🚫 What's Not Included

To keep the repo minimal:

• No pretrained data
• No saved models
• No test sets

Refer to docstrings in each module to simulate your own experiments.

🚀 Quick Start

```bash

Clone and install

git clone https://github.com/FalahMsi/neurocode.git cd neurocode

python -m venv .venv .venv\Scripts\activate # On Windows pip install -r requirements.txt

python main.py 🙋 Looking for Adoption

This is a public, open-source intellectual initiative. Due to personal resource constraints, I cannot continue development alone.

If you’re a developer, researcher, or organization interested in expanding or building upon this concept — you’re welcome to fork, adapt, or reach out.

📫 Email: info.alharbi94@gmail.com 🤝 Contributions and collaborations are highly encouraged.