README.md

---
license: cc-by-4.0
tags:
  - glyphic
  - symbolic-language
  - semantic-protocol
  - agent-cognition
  - drift-resistant
  - llm-training
  - interpreter
  - protocol
library_name: glyphic-language
language:
  - en
pretty_name: Glyphic Language
---

Glyphic Language

A symbolic language, semantic protocol, and training pipeline designed for drift‑resistant agent cognition.

Glyphic provides a deterministic structure for representing:

    Identity

    Intent

    Memory

    Behavior

    Safety

    State

    Thought

It is built for systems where consistency, structure, and long‑term stability matter more than free‑form natural language.

Glyphic is not a “constructed language.”
It is a protocol layer for intelligent systems.
Why Glyphic Exists

Modern LLMs are powerful but unstable:

    They drift over time

    They reinterpret instructions

    They lose identity

    They hallucinate structure

    They cannot maintain long‑term memory

    They treat meaning as prose instead of protocol

Glyphic solves these problems by introducing:
1. A deterministic symbolic language

Meaning is encoded as structured glyph sequences, not ambiguous sentences.
2. A strict grammar and syntax

Defined in BNF and enforced by validators.
3. A semantic dictionary

Concepts, actors, emotions, objects, modifiers, places, and contexts.
4. A CTX protocol layer

Identity, intent, memory, behavior, safety, state, and thought are explicit fields.
5. A training pipeline

Generate text↔glyph pairs, structured meaning, and CTX envelopes for LLM training.
6. A runtime envelope

Controllers wrap LLMs in deterministic Glyphic envelopes to eliminate drift.
Repository Overview
Code

glyphic-language/
├── data/                     # CTX layers + protocol definitions
├── dictionary/               # Ontology: concepts, actors, emotions, objects, etc.
├── docs/                     # Formal documentation + specifications
├── generator/                # Dataset generator + templates + training builder
├── interpreter/              # Encoder, decoder, validator, syntax engine
├── runtime/                  # Envelope builder for agent controllers
├── syntax/                   # Grammar rules, ordering rules, BNF
└── training/                 # Dataset formats, pipeline, evaluation

Quickstart
Install
bash

git clone https://github.com/GlyphicMind-Solutions/Glyphic-Language.git
cd glyphic-language
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt   # if present

Encode / Decode Glyphic
Encode text → structured meaning → glyph
python

from interpreter.glyph_encoder import encode_text

glyph = encode_text("The agent remembers a promise.")
print(glyph)

Decode glyph → meaning → text
python

from interpreter.glyph_decoder import decode_glyph

meaning = decode_glyph("<G:...>")
print(meaning)

See interpreter/README.md for full examples.
Generate a Dataset
Generate text↔glyph pairs
bash

python -m generator.run_generator

This produces:

    training/text_to_glyph.jsonl

    training/glyph_to_text.jsonl

    training/structured_meaning.jsonl

Dataset documentation is in:

    training/dataset_format.md

    training/dataset_generation_guide.md

Training an LLM on Glyphic

Glyphic includes a full training pipeline:

    generator/ — dataset builder

    training/ — formats, evaluation, fine‑tuning plan

    hf_finetune_glyphic.py — Hugging Face training script

Training flow

    Generate datasets

    Train a base model (LLaMA/Mistral/etc.) on Glyphic sequences

    Export as .gguf

    Use Glyphic envelopes at runtime to eliminate drift

A reference model will be available on Hugging Face:

    Model: GlyphicMind/glyphic-llm-v1

    Dataset: GlyphicMind/glyphic-dataset-v1

Why Glyphic Eliminates LLM Drift
1. Explicit structure

Identity, intent, memory, behavior, safety, and state are explicit CTX fields.
2. Protocol, not prose

The model learns a symbolic protocol with strict syntax.
3. Deterministic envelopes

Controllers build and validate envelopes; the LLM fills content but cannot alter structure.
4. Separation of concerns

Long‑term meaning lives in Glyphic structures.
The LLM becomes a stateless pattern engine.
5. Drift‑resistant memory

Memory is encoded symbolically, not as free‑form text.
Contributing to Glyphic

Glyphic is designed to be extensible, collaborative, and community‑driven.

See:

    CONTRIBUTING.md

    GOVERNANCE.md

You can contribute:

    new glyphs

    new dictionary entries

    new syntax rules

    new CTX fields

    new templates

    new training examples

All contributions must pass:

    dictionary validation

    syntax validation

    CTX protocol validation

Roadmap

See ROADMAP.md for full details.
v1 — Current

    Core dictionary

    Grammar + BNF

    Interpreter

    CTX protocol

    Dataset generator

    Training pipeline

v2 — Recursive Glyphs

    Compositional glyphs

    Glyph inheritance

    Polarity + intensity

v3 — Dynamic Glyph Generation

    On‑the‑fly glyph creation

    Glyph clustering

    Semantic compression

v4 — Multi‑Agent Glyphic Communication

    Agent‑to‑agent glyphic messaging

    Shared memory substrates

    Distributed glyphic cognition

License

This project is licensed under:

    Creative Commons Attribution 4.0 International (CC‑BY 4.0)  
    You may reuse, modify, and build upon this work with attribution.

See LICENSE for full terms.
Citation

If you use Glyphic in research or development:
Code

Glyphic Language (2026). GlyphicMind Solutions.
https://github.com/GlyphicMind-Solutions/Glyphic-Language