# Fireworks Tech Graph — Generate Technical Diagrams from Natural Language

> An AI skill that produces SVG and PNG technical diagrams from plain text descriptions. Supports 7 visual styles, UML diagrams, and AI/Agent workflow patterns with clean, production-ready output.

## Install

Save as a script file and run:

# Fireworks Tech Graph — Generate Technical Diagrams from Natural Language

## Quick Use
```bash
pip install fireworks-tech-graph
fireworks-graph "Three microservices behind an API gateway connecting to PostgreSQL and Redis" -o arch.svg
fireworks-graph "User logs in, server validates token, returns session" --style uml -o login.png
```

## Introduction

Fireworks Tech Graph converts plain-text descriptions of systems and workflows into clean technical diagrams. You describe the architecture in natural language and receive production-ready SVG or PNG output, removing the need to manually position boxes and arrows in a GUI diagramming tool.

## What Fireworks Tech Graph Does

- Parses natural language descriptions and produces technical diagrams in SVG or PNG format
- Supports 7 visual styles: minimal, blueprint, whiteboard, dark, corporate, sketch, and neon
- Generates UML diagram types including sequence, class, component, and activity diagrams
- Renders AI/agent workflow patterns with specialized shapes for models, tools, and decision points
- Accepts iterative refinement commands to adjust layout and labels without regenerating

## Architecture Overview

The tool uses a two-stage pipeline. The first stage parses natural language to extract entities and relationships into a structured graph. The second stage applies the selected visual style and computes node positions using force-directed or hierarchical layout. SVG is generated directly; PNG goes through a headless renderer.

## Self-Hosting & Configuration

- Install via `pip install fireworks-tech-graph` or use the Docker image
- Configure default style and output format in `~/.fireworks-graph/config.yml`
- Set `FTG_OUTPUT_DIR` to control where diagrams are saved
- Custom color palettes defined in YAML can be referenced by name with `--style`
- Integrates with CI pipelines to auto-generate diagrams from description files

## Key Features

- Produces clean, deterministic SVG suitable for version control alongside code
- Seven visual styles match output to different team and presentation contexts
- Specialized AI/agent workflow support including tool-call loops and multi-agent topologies
- Iterative refinement adjusts individual elements without full regeneration
- CLI-first design makes it scriptable for documentation automation

## Comparison with Similar Tools

- **Mermaid** — requires learning a text-based DSL; Fireworks Tech Graph accepts plain natural language
- **PlantUML** — established UML tool with its own markup; Fireworks Tech Graph removes the need for a formal syntax
- **D2** — declarative diagram scripting; Fireworks Tech Graph targets users who prefer English prose descriptions
- **Excalidraw** — freehand whiteboard tool; Fireworks Tech Graph automates layout from text input

## FAQ

**Q: Does the tool require an internet connection?**
A: The layout engine and style rendering work offline. The natural language parsing stage may use a local or remote LLM depending on your configuration.

**Q: How does it handle large diagrams with many nodes?**
A: The layout engine switches to a hierarchical algorithm for graphs above 30 nodes and supports pagination for very large diagrams.

**Q: Can I export the intermediate graph for use in other tools?**
A: Yes. Pass `--export-json` to output the parsed graph structure as JSON for programmatic use.

## Sources

- https://github.com/yizhiyanhua-ai/fireworks-tech-graph
- https://fireworks-tech-graph.readthedocs.io/

---
Source: https://tokrepo.com/en/workflows/asset-83bba1fd
Author: Script Depot