Hey there!
In this guide, you’ll build a web app that converts plain English into visual diagrams. The app uses a React frontend, a FastAPI backend and the Kroki API to turn generated diagram code into SVG or PNG images.

By the end, you’ll have a clean interface where users type a description, choose a diagram type and instantly see a rendered diagram. It’s fast, lean and surprisingly simple once you understand the flow.

Exact Prompt to Use

Paste this directly into Emergent:

Build a Natural Language to Diagram Generator web app.

Use React 19 with Tailwind and shadcn/ui for the frontend. 
Create a layout that includes a text input panel, a diagram type selector, a preview area and a code view tab. 
Add a dark/light theme toggle and toast notifications using Sonner.

Use FastAPI for the backend. 
Add a POST /api/generate-diagram endpoint that takes a natural language string and a diagram type (graphviz, mermaid or plantuml). 
Parse the text using simple regex, remove filler words and generate valid diagram code. 
Return the code and the appropriate Kroki type.

On the frontend, send the returned code to the Kroki API (https://kroki.io) to render SVG for preview and PNG for export. 
Implement error handling, CORS, theme persistence and responsive layout.

Deliverables: working NLP-to-diagram flow, SVG preview, PNG export, code viewer and theme toggle

System Overview

The frontend runs on React with Tailwind and shadcn/ui, giving you a fast, modern interface.
The backend runs on FastAPI and handles all text parsing.
Kroki does the heavy lifting by converting diagram code into images.

Flow:

1. The user types a description.

2. The backend generates diagram code.

3. The frontend sends the code to Kroki.

4. Kroki returns an SVG.

5. The preview updates instantly.

Core Features

The interface includes a text panel for natural language input, a dropdown to select GraphViz, Mermaid or PlantUML and a preview window that displays the rendered SVG. Users can switch between preview and raw code, zoom into diagrams, toggle themes and export to PNG by re-calling Kroki’s PNG endpoint.

The backend handles all parsing. Start with simple regex: split sentences, detect “if…then…” patterns and sanitize labels. Convert the cleaned structure into diagram syntax and return it. Each diagram type needs its own small generator function.

Implementation Notes

• Make sure you only read the fetch response body once on the frontend.

• Always use return after sending a FastAPI response to avoid hitting fallback logic.

• Escape quotes and remove special characters before generating diagram code.

• If SVGs show up with zero width or height, override those styles with CSS.

• And don’t forget CORS—your frontend won’t reach the API without it.

Common Issues

You may see spacing issues with Select components in shadcn/ui; reduce padding or simplify the label.
If your diagram fails to render, test the generated code directly on Kroki—it’s the fastest way to find syntax errors.
If theme toggling doesn’t persist, store it in localStorage and apply it on initial load.
Make sure the layout adapts to mobile by using Tailwind responsive utilities.

Optional Improvements

You can extend the app with more diagram types, autosave, side-by-side editing, or real-time previews as the user types. Once the core flow works, it’s easy to iterate.

Wrapping Up

That is it.
You now have a well structured Natural Language to Diagram Generator running on Emergent.

You described the requirements and Emergent generated:

• the backend parsing logic

• the diagram code generator

• the React interface

• the Kroki rendering workflow

• the export tools

Once deployed, your generator is live and ready to explore. Check out our published app at https://textflow-74.emergent.host/