Fireworks Tech Graph — Generate Technical Diagrams from Natural Language

Introduction

Fireworks Tech Graph transforms plain English descriptions into polished technical diagrams. Instead of wrestling with diagramming tools or learning DOT syntax, developers describe what they want and receive publication-ready SVG or PNG output suitable for documentation, presentations, and architecture reviews.

What Fireworks Tech Graph Does

• Converts natural language into SVG and PNG technical diagrams
• Supports 7 visual styles from minimal wireframe to polished corporate
• Generates UML diagrams including sequence, class, and activity types
• Renders AI and agent workflow patterns with specialized node types
• Produces deterministic output suitable for version control

Architecture Overview

The tool uses a Python CLI that parses natural language input, maps it to an intermediate graph representation, and then renders it through a layout engine. The LLM interprets the description and produces structured JSON describing nodes, edges, and groupings. A rendering pipeline applies the selected visual style, handles automatic layout with collision avoidance, and exports the final SVG or rasterized PNG.

Self-Hosting & Configuration

• Install via pip with Python 3.10+
• Requires an LLM API key (OpenAI, Anthropic, or compatible local endpoint)
• Configure default style, output format, and model in ~/.fireworks-graph/config.yaml
• Supports batch mode for generating multiple diagrams from a manifest file
• No external services required beyond the LLM provider

Key Features

• Seven distinct visual styles from technical to presentation-ready
• First-class UML support with correct notation and layout rules
• Agent workflow patterns with specialized nodes for tools, models, and memory
• Deterministic rendering for consistent output across runs
• CLI and Python API for integration into documentation pipelines

Comparison with Similar Tools

• Mermaid — text DSL for diagrams; Fireworks uses natural language, no syntax to learn
• Excalidraw — manual drawing tool; Fireworks auto-generates from descriptions
• PlantUML — structured UML markup; Fireworks accepts plain English input
• D2 — declarative diagram language; Fireworks eliminates the need for a custom DSL

FAQ

Q: Can I customize the visual styles? A: Yes, styles are defined as JSON theme files. You can modify colors, fonts, spacing, and node shapes to match your brand.

Q: Does it handle large diagrams well? A: The layout engine handles diagrams with up to 50-60 nodes comfortably. For very large architectures, breaking into sub-diagrams is recommended.

Q: Can I use it without a cloud LLM? A: Yes, point it at any OpenAI-compatible local endpoint such as Ollama or vLLM for fully offline operation.

Q: Is the SVG output accessible? A: Generated SVGs include title and description metadata. Adding full ARIA labels is on the roadmap.

Sources

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