---
license: mit
tags:
  - modular-intelligence
  - reasoning
  - structure
  - transformers
  - experimental
base_model: openai-community/gpt2
pipeline_tag: text-generation
language: en
---

# Modular Intelligence

Modular Intelligence is a lightweight reasoning framework built on top of a language model.  
It provides **Modules** (task-specific lenses), **Checkers** (second-pass reviewers), **Contracts** (structured output sections), and optional **Routing** (automatic module selection).

The base model is GPT-2, but the architecture is model-agnostic—any LLM can be plugged in.

---

## Features

### Modules
Task-specific reasoning modes.  
Examples:
- **Analysis Note** – explanation and breakdown of concepts  
- **Document Explainer** – summaries of contracts, policies, articles  
- **Strategy Memo** – Options → Recommendation → Risks → Next Steps  
- **System Blueprint** – workflow / system design  
- **Brainstorm** – structured idea generation  
- **Message Reply** – concise responses for emails, posts, chats  

### Checkers
A second pass that evaluates:
- correctness  
- clarity  
- missing pieces  
- contradictions  

### Contracts
Every module produces a fixed output template.  
This ensures reproducible structure and reduces variance.

### Router
Optional automatic module selection based on prompt classification.

---

## Usage

### Python

```python
from app import run_module

result = run_module(
    module="StrategyMemo",
    prompt="Should we expand operations to Region X next quarter?"
)

print(result)