---
language:
- en
license: apache-2.0
pipeline_tag: graph-ml
tags:
- intent-detection
- graph-learning
- agent
- workflow
- nlp
library_name: python
task_categories:
- text-processing
model-index:
- name: intentgraph-lm
  results: []
---

# IntentGraphLM 🚀

**IntentGraphLM** is an open-source language model pipeline that converts raw natural language into **dynamic intent graphs**, enabling smarter agents, workflow orchestration, and multi-step task planning.

This project is designed to be **lightweight, extensible, and Hugging Face–ready**, with strong future scope in agentic AI systems.

---

## 🔍 What Problem Does It Solve?

Traditional intent detection returns flat labels.  
IntentGraphLM goes further by:

- Extracting **multiple intents**
- Modeling **relationships between intents**
- Representing them as a **directed graph**
- Enabling **dynamic updates** during conversations

---

## ✨ Key Features

- 🧠 Intent extraction from raw text  
- 🕸️ Graph-based intent representation  
- 🔁 Dynamic intent graph updates  
- ⚡ Lightweight, dependency-minimal design  
- 🤗 Hugging Face–compatible inference pipeline  
- 🧩 Modular and extensible architecture  

---

## 📂 Project Structure

```
intentgraph-lm/
├── config/
├── data/
├── src/
├── training/
├── scripts/
├── tests/
├── notebooks/
├── README.md
├── model_card.md
├── requirements.txt
└── LICENSE
```

---

## ⚙️ Installation

```bash
pip install -r requirements.txt
```

---

## 🚀 Quick Usage

```python
from src import IntentGraphPipeline

pipeline = IntentGraphPipeline()

output = pipeline("Book a flight and then reserve a hotel")

print(output)
```

---

## 🧠 How It Works

1. Tokenization  
2. Intent Extraction  
3. Graph Building  
4. Dynamic Updates  

---

## 🧪 Testing

```bash
pytest tests/
```