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:
- 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
- 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