Open AI Box – Universal LLM introspection: injection points & dimension roles in any model

Hey everyone :waving_hand:

I’m releasing **Open AI Box** — a Python package that opens the black box of any LLM.

## What it does

By tracing a live inference pass with PyTorch forward hooks, it automatically discovers:

- **Injection points** — where data enters, where decisions are made, where memory lives

- **Dimension roles** — which dimensions carry causality, emotion, certainty, temporal reasoning

- Everything exported to a single `graph.json`

## Live demo

:backhand_index_pointing_right: Open AI Box - a Hugging Face Space by anzizdaouda0

Paste any model ID → get a full architecture analysis with interactive Plotly graphs.

## Install

pip install openaibox

```python

from openaibox import OpenAIBox

oaib = OpenAIBox(“HuggingFaceTB/SmolLM-360M”)

oaib.discover().map_dimensions().export(“graph.json”)

oaib.print_summary()

Key finding: the model.norm → lm_head control point is universal across all tested architectures (LlamaForCausalLM, Qwen2ForCausalLM, GPT2…).

:package: PyPI: openaibox · PyPI

:octopus: GitHub: GitHub - Tryboy869/openaibox: Universal LLM introspection. Open AI Box — understand any model. · GitHub

Happy to hear feedback!

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