AION

AION logo

AION architecture

AION is a tiny hybrid local assistant built in a constrained CPU environment. It unifies several learned and symbolic components into one entrypoint:

from aion import generate
print(generate("hola"))

What AION can do

  • Chat greetings and basic conversation.
  • Write Python snippets and functions.
  • Create web pages/components with HTML, advanced CSS and vanilla JavaScript.
  • Solve many math tasks:
    • arithmetic,
    • linear equations,
    • quadratics,
    • derivatives/integrals for simple polynomials,
    • statistics,
    • geometry,
    • trigonometry,
    • combinatorics,
    • interest,
    • unit conversion.
  • Solve basic physics formulas:
    • F=ma,
    • kinetic/potential energy,
    • Ohm's law,
    • power,
    • density,
    • momentum,
    • wave speed.
  • Basic chemistry:
    • common elements,
    • moles,
    • molarity,
    • ideal gas law,
    • pH.
  • Basic biology/general knowledge:
    • photosynthesis,
    • cells,
    • DNA,
    • evolution,
    • algorithms,
    • databases,
    • internet,
    • machine learning.

Download

You can download the complete ready-to-run package from the repository files:

git lfs install
git clone https://huggingface.co/VoidWalkercero/AION-1
cd AION-1
python aion.py "hola"

Or from Python:

from huggingface_hub import snapshot_download
path = snapshot_download("VoidWalkercero/AION-1")
print(path)

A zipped copy is also included under download/AION-1.zip.

Architecture

AION is not a transformer LLM. It is a merged hybrid model:

  1. neural_python_mind.py โ€” NumPy character-level GRU trained for Python syntax/style.
  2. real_python_learner.py โ€” character n-gram learned intent classifier + compositional Python generator.
  3. real_web_learner.py โ€” character n-gram learned web intent classifier + HTML/CSS/JS generator.
  4. unified_learning_ai.py โ€” unified router for chat, Python, web, math and science.
  5. A small deterministic math/science solver layer.

Usage

CLI:

python aion.py "create a responsive landing page with dark mode"
python aion.py "solve 2x + 5 = 17"
python aion.py "force mass 10 acceleration 2"
python aion.py "write code to keep numbers greater than 12"

Python:

from aion import generate
print(generate("what can you do"))

Evaluation

AION benchmark snapshot

Local evaluation results are in:

results/aion_local_eval.json
results/aion_local_eval.md

Summary:

Suite Score
chat sanity 3/3
Python generation sanity 3/3
Web generation sanity 4/4
Math/science sanity 6/6
GSM8K test sample 30 0/30

Important: these are not official Hugging Face leaderboard results. AION is not a standard transformers model and cannot be directly submitted to most official HF benchmark leaderboards without a custom evaluation adapter. The GSM8K sample result is included honestly and shows the current limitation on multi-step word problems.

For optional comparison with small HF models, see benchmark/benchmark_compare_small_models.py and benchmark/SMALL_MODEL_COMPARISON.md.

Limitations

  • Not a large language model.
  • Not a Transformers AutoModel checkpoint.
  • Strong on composed templates and formulaic tasks; weak on deep natural-language reasoning.
  • GSM8K multi-step reasoning is currently poor.
  • Web output is generated as inline HTML/CSS/JS snippets suitable for local preview, not production-audited code.

Training data

AION uses generated local curricula plus downloaded GSM8K JSONL files from OpenAI's public grade-school-math repository when available:

outputs/unified_learning_ai/online_datasets/gsm8k_train.jsonl
outputs/unified_learning_ai/online_datasets/gsm8k_test.jsonl
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