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license: apache-2.0
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license: apache-2.0
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**Code Repository:** [GitHub - BridgeLang](https://github.com/jjwbarrett-jpg/BridgeLang)

# BridgeLang (v0.1 Alpha)


# BridgeLang (v0.1 Alpha)
**A Hybrid NLU Interceptor for Deterministic Agent Control**

## 🚀 Overview
BridgeLang is a middleware architecture designed to solve the "Stochastic Control Problem" in AI Agents. It combines the flexibility of Neural Networks with the safety of deterministic code.

- **The Problem:** LLMs are powerful but probabilistic. Asking an AI to "Stop System" might result in a conversational response rather than an immediate halt.
- **The Solution:** BridgeLang intercepts critical commands at the `Tier Core (tc)` layer, executing them immediately via hard-coded logic, while passing nuanced context (`Tier 1`) to a fine-tuned FLAN-T5 model.

## 🧠 Architecture
1.  **User Input:** Natural Language ("System, stop the process immediately.")
2.  **Interceptor Layer (BridgeLang Core):** Scans for `tc` keywords.
    - Detected: `Stop` -> `tc.cmd.stop` (Priority: CRITICAL)
3.  **Neural Layer (Context Engine):** Passes remaining context to AI.
    - Detected: `process` -> `t1.task.action.process`
4.  **Executor Layer:** deterministic execution of the SIGS protocol.

## 📂 Repository Structure
- `core-logic/`: Python interceptors and executors.
- `models/`: Fine-tuned FLAN-T5 model for SIGS protocol translation.
- `data/`: Master Lexicon (v2.0).

## 🛠️ Usage
```bash
# Run the Interceptor
python core-logic/bridge_lang_interceptor.py

# Run the Executor (Simulated Robot)
python core-logic/bridge_lang_executor.py