# ResiNet-LLM-topology

This repository contains the implementation for the submission:

> **An LLM-Based Framework for Intent-Driven Network Topology Design**
> *(CNSM submission)*



## Purpose

`ResiNet-LLM-topology` provides the evaluation pipeline used in our work for comparing generated network topologies against reference designs.

It includes:

- node-level F1 evaluation
- edge-level F1 evaluation
- scenario data and reference topologies used for evaluation

## Folder layout

```
requirements.txt
README.md
data/
  ├─ results/
  ├─ scenarios/
  ├─ topology_scenario_1.json
  ├─ topology_scenario_2.json
  ├─ topology_scenario_3.json
  └─ topology_scenario_4.json

f1_nodes_functions.py
f1_nodes_main.py
f1_edges_functions.py
f1_edges_main.py
resinet_llm_prompt.py
evaluate_connectivity.py
draw_topology.py
```

## Installation

Install the dependencies with:

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

## Quick start

### Node F1 evaluation

```bash
python f1_nodes_main.py --gen <generated-json-or-folder> --ref <reference.json>
```

### Edge F1 evaluation

```bash
python f1_edges_main.py --gen <generated-json-or-folder> --ref <reference.json>
```

The scripts produce detailed evaluation logs and summary `.txt` outputs in the local `results/` path next to the evaluated files.

## File descriptions

- `f1_nodes_functions.py` — helper functions for node normalization, mapping, and F1 calculation.
- `f1_nodes_main.py` — driver script for node-based evaluation and overall summary generation.
- `f1_edges_functions.py` — helper functions for edge cleanup, structural remapping, and edge F1 scoring.
- `f1_edges_main.py` — driver script for edge-based evaluation and final metrics.
- `resinet_llm_prompt.py` — prompt utilities for intent-driven topology generation.
- `evaluate_connectivity.py` — connectivity and resilience measurement helpers.
- `draw_topology.py` — graph drawing utilities.
- `requirements.txt` — Python package dependencies.

## Repository usage 

This package is designed to let users:

1. inspect the evaluation logic used in the paper,
2. reproduce node and edge F1 scoring on generated topologies with LLMs using the previous prompts,
3. compare generated outputs with reference topologies,


## Notes for publication

- This repository is intended as a reproducibility artifact