Instruments that deal with diagrams as code, comparable to PlantUML, are invaluable for speaking
advanced system habits. Their text-based format simplifies versioning, automation, and
evolving architectural diagrams alongside code. In my work explaining distributed
methods, PlantUML’s sequence diagrams are significantly helpful for capturing interactions
exactly.
Nonetheless, I typically wished for an extension to stroll by these diagrams step-by-step,
revealing interactions sequentially reasonably than displaying the complete advanced circulate at
as soon as—like a slideshow for execution paths. This want displays a standard developer
state of affairs: wanting customized extensions or inside instruments for their very own wants.
But, extending established instruments like PlantUML typically entails vital preliminary
setup—parsing hooks, construct scripts, viewer code, packaging—sufficient “plumbing” to
deter speedy prototyping. The preliminary funding required to start can suppress good
concepts.
That is the place Massive Language Fashions (LLMs) show helpful. They’ll deal with boilerplate
duties, liberating builders to concentrate on design and core logic. This text particulars how I
used an LLM to construct PlantUMLSteps
, a small extension including step-wise
playback to PlantUML sequence diagrams. The objective is not simply the software itself, however
illustrating the method how syntax design, parsing, SVG era, construct automation,
and an HTML viewer have been iteratively developed by a dialog with an LLM,
turning tedious duties into manageable steps.
Diagram as code – A PlantUML primer
Earlier than diving into the event course of, let’s briefly introduce PlantUML
for individuals who is likely to be unfamiliar. PlantUML is an open-source software that enables
you to create UML diagrams from a easy text-based description language. It
helps
numerous diagram varieties together with sequence, class, exercise, element, and state
diagrams.
The facility of PlantUML lies in its capability to model management diagrams
as plain textual content, combine with documentation methods, and automate diagram
era inside improvement pipelines. That is significantly priceless for
technical documentation that should evolve alongside code.
Here is a easy instance of a sequence diagram in PlantUML syntax:
@startuml disguise footbox actor Consumer participant System participant Database Consumer -> System: Login Request System --> Consumer: Login Kind Consumer -> System: Submit Credentials System -> Database: Confirm Credentials Database --> System: Validation Consequence System --> Consumer: Authentication Consequence Consumer -> System: Request Dashboard System -> Database: Fetch Consumer Knowledge Database --> System: Consumer Knowledge System --> Consumer: Dashboard View @enduml
When processed by PlantUML, this textual content generates a visible sequence diagram displaying the
interplay between elements.

The code-like nature of PlantUML makes
it straightforward to study and use, particularly for builders who’re already snug
with text-based instruments.
This simplicity is what makes PlantUML an ideal candidate for extension. With the
proper tooling, we are able to improve its capabilities whereas sustaining its text-based
workflow.
Our objective for this challenge is to create a software which may divide the
sequence diagram into steps and generate a step-by-step view of the diagram.
So for the above diagram, we must always have the ability to view login, authentication and
dashboard
steps one after the other.
Step 2: Constructing the Parser Logic (and Debugging)
“Now we have to parse the plantuml recordsdata and separate out step. Each time we
encounter a step marker, we create a step object and hold including the subsequent strains
to it till we encounter one other step marker or finish of file. In case we
encounter one other step counter, we create new step object, it ought to have all
the consists of, actors and individuals from the earlier step. It also needs to
have all of the content material of the earlier step, except the step metadata has
‘newPage’ attribute. If there are not any step markers encountered, which is the case
the place we have now recordsdata with out steps, it ought to create a default step. Create a
StepParser to parse given puml recordsdata and create listing of steps.”
Claude generated the preliminary code for a StepParser class and a Step mannequin class to
deal with parsing PlantUML recordsdata with step markers. The preliminary implementation had some
logical points:
- Incorrect dealing with of step content material inheritance when newPage attribute was false
- Improper dealing with of declarations (actors, individuals) showing earlier than the
first step marker - Points with making a default step for recordsdata with out markers
The Cursor editor was working in Agent mode, so after working exams and figuring out
these points by the failure messages, Claude offered a corrected model that
correctly dealt with:
- Content material collected earlier than step one marker
- Inheritance of content material from the instantly previous step
- World monitoring of declarations throughout steps
- Correct creation of a default step for recordsdata with out markers
With these corrections, the parser efficiently handed all exams.
The subsequent step was to generate a gradle activity.
We want gradle activity which may course of puml recordsdata in src/diagrams and its sub
folders. For every file it ought to create a listing with the identify of the file the place
it generates legitimate puml file for every step. It will probably generate that by simply including
@startuml in the beginning and @enduml on the finish of the step content material.
I am going to allow you to create a Gradle activity to course of PlantUML recordsdata and generate
step-by-step diagrams. First, let’s create the duty in
construct.gradle:
// Course of every .puml file within the enter listing and its subdirectories fileTree(inputDir).embrace('**/*.puml').every { pumlFile -> def relativePath = inputDir.toPath().relativize(pumlFile.toPath()).toString() def fileName = pumlFile.identify.exchange('.puml', '') def stepOutputDir = new File(outputDir, fileName) if (!stepOutputDir.exists()) { stepOutputDir.mkdirs() } // Run the generator for this file javaexec { classpath = sourceSets.foremost.runtimeClasspath mainClass = 'com.instance.StepDiagramGenerator' args = [pumlFile.absolutePath, stepOutputDir.absolutePath] }
Claude additionally helped producing a easy plantuml sequence diagram to check the gradle
activity. The identical one which we used at the start of the article.
The gradle activity wanted a category PlantUMLGenerator which
can generate SVGs for every step.
Cursor within the Agent mode generated the code for the category.
It then ran the construct to confirm the duty.
Let's run a check to substantiate our implementation works: cd /Customers/unmeshjoshi/work/plantumlsequence && ./gradlew clear construct Job :generateStepDiagrams Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-01-step-1-user-login.puml Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-02-step-2-authentication.puml Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-03-step-3-dashboard.puml Generated step circulate abstract: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/abstract.puml BUILD SUCCESSFUL in 543ms 3 actionable duties: 3 executed
Step 3: Producing HTML Viewer for Step Sequence
The subsequent step was to generate a easy HTML viewer that can be utilized to view the step
sequence.
Now we have to generate a HTML viewer for the step recordsdata to be proven one after the other.
The HTML viewer can have a view space the place we present the svg picture generated for every
step with the step identify within the metadata for that step. We are able to have subsequent and former
buttons to point out subsequent and former step picture.
I am going to allow you to create an HTML viewer for the step diagrams. We’ll must: Generate
SVG recordsdata from the PlantUML recordsdata Create an HTML viewer with navigation controls
Replace the Gradle activity to generate each PlantUML and SVG recordsdata, together with the HTML
viewer First, let’s create a easy HTML template for the viewer:
….
The agent mode discovered a couple of points with the template however auto-fixed it by
working some corrective actions.
This setup allowed us to shortly generate step diagrams from a single PlantUML file,
and look at them in a step-by-step method. So the above diagram might be seen as a
sequence of following steps:



The Code is the Supply of Fact
The place to go from right here?
Whereas the prompts and the LLM assistant (on this case, interacting in an agent-like
mode, using fashions like Claude Sonnet) offered a remarkably efficient option to
generate a working first model of PlantUMLSteps
, it is essential to
acknowledge the character of this generated output.
- Prompts are usually not Deterministic: The prompts utilized in our dialog have been
efficient for this interplay, however they can’t be handled as the last word
‘supply of reality’. The identical prompts given to a special mannequin, and even the identical
mannequin at a later date, are usually not assured to supply the very same output due
to the inherent variability in LLM era. - Code Requires Administration: The generated code is the supply of reality for
the software’s performance. As such, it must be handled like every other
software program artifact – checked into model management, reviewed, examined, and
maintained. - Evaluate for Habitability: It is important to revisit the LLM-generated code
after the preliminary creation section. Is it ‘liveable’? That’s, is it moderately
straightforward to learn, perceive, and modify by a human developer? Whereas the LLM helped
overcome preliminary hurdles and boilerplate, making certain the long-term maintainability
and readability of the codebase typically requires human assessment and potential
refactoring. The objective is code that not solely works however will also be advanced
successfully over time.
Prompting in pure language (like English) to generate code works nicely within the
early phases of improvement—once you’re exploring concepts, scaffolding performance,
or getting acquainted with a brand new software or framework. However as your system begins to take
form, the bounds of imprecise or broad prompts turn into obvious. At this stage, what’s
wanted just isn’t extra code era, however conceptual modeling—utilizing the constructs of
your programming language or expertise stack to precisely signify the area.
This stage wants deeper pondering to construct abstractions, and an alignment between
code construction and area ideas—one thing solely achievable by considerate
design, not simply prompting. If prompt-based code era with out
assessment known as “vibe coding,” then the extra disciplined strategy might be
known as “AI-assisted structured coding.”.
Past Code Technology: The Developer Perception in Refactoring
The subsequent step was to refactor the code to make it extra readable and maintainable.
Initially, the parse technique was a protracted, monolithic operate that dealt with every little thing
from
detecting step markers to managing declarations and content material. The code was tough
to
perceive and preserve.
The complete code is offered in
this preliminary commit on GitHub.
The `StepParser.java` parse technique wants refactoring. It ought to signify ideas
used within the requirement or area ideas and observe commonplace clear code practices
with intentional technique names and code that reads like a DSL.
This preliminary request was open-ended, indicating that the developer acknowledged the
want for enchancment however was on the lookout for steering on the way to strategy it.
The LLM responded with a complete refactoring that launched a number of new
lessons and strategies:
- Launched `PlantUmlDocument` to signify the doc being parsed - Smaller, extra centered strategies with intention-revealing names - Higher encapsulation of associated behaviors - Extra expressive variable and technique names /** * Represents a PlantUML doc being parsed, managing state throughout parsing */ personal class PlantUmlDocument { personal ultimate Recordsteps = new ArrayList<>(); personal ultimate Record declarations = new ArrayList<>(); personal ultimate Record contentBeforeFirstStep = new ArrayList<>(); personal Step currentStep = null; personal boolean hasStepMarkers = false; public void beginNewStep(StepMetadata metadata) { hasStepMarkers = true; // Save the present step if it exists if (currentStep != null) { steps.add(currentStep); } // Create a brand new step currentStep = new Step(metadata.getName(), metadata.isNewPage(), metadata.getAttributes()); // Add all declarations to the brand new step currentStep.addAllDeclarations(declarations); // If this is not a brand new web page and we have now earlier steps, copy all content material from earlier steps if (!metadata.isNewPage() && !steps.isEmpty()) { carryOverPreviousStepsContent(); } } personal void carryOverPreviousStepsContent() { for (Step previousStep : steps) { for (String contentLine : previousStep.getContent()) { currentStep.addContent(contentLine); } } } public void addDeclaration(String line) { declarations.add(line); if (currentStep != null) { currentStep.addDeclaration(line); } else { contentBeforeFirstStep.add(line); } } public void addContentLine(String line) { if (currentStep != null) { currentStep.addContent(line); } else if (!line.trim().isEmpty()) { contentBeforeFirstStep.add(line); } } public void finalizeDocument() { // Add the final step if it exists and hasn't been added but if (currentStep != null) { steps.add(currentStep); } }
The complete code is offered in
this commit on GitHub.
The `contentBeforeFirstStep` in `PlantUmlDocument.java` is used just for creating
default step when there are not any step markers?
So we are able to probably
do two go processing the place we first verify if there are step markers.. if there
are.. we do step-based processing. Or else we simply create a default step and add all
declarations and content material. That may take away the necessity to have `contentBeforeFirstStep`
We are able to additionally possibily identify PlantUmlDocument as `ParsedPumlFile` which represents
the parsed puml file.
The LLM applied this suggestion with a two-pass strategy. It additionally renamed the
PlantUmlDocument as ParsedPumlFile.
The complete code is offered in
this commit on GitHub.
`ParsedPumlFile` might be higher represented as builder sample.
`StepBuilder` is usually a builder for `Step` objects.
This perception demonstrated the developer’s capability to acknowledge design patterns,
noting that the refactored class adopted the Builder sample.
The ultimate refactoring represents a major enchancment over the unique code:
class StepBuilder { personal ultimate Record<Step> steps = new ArrayList<>(); personal ultimate Record<String> globalDeclarations = new ArrayList<>(); personal Step currentStep = null; public void startNewStep(StepMetadata metadata) { if (currentStep != null) { steps.add(currentStep); } currentStep = new Step(metadata); currentStep.addAllDeclarations(globalDeclarations); if (!metadata.isNewPage() && !steps.isEmpty()) { // Copy content material from the earlier step Step previousStep = steps.get(steps.dimension() - 1); for (String contentLine : previousStep.getContent()) { currentStep.addContent(contentLine); } } } public void addDeclaration(String declaration) { globalDeclarations.add(declaration); if (currentStep != null) { currentStep.addDeclaration(declaration); } } public void addContent(String content material) { // If no step has been began but, create a default step if (currentStep == null) { StepMetadata metadata = new StepMetadata("Default Step", false, new HashMap<>()); startNewStep(metadata); } currentStep.addContent(content material); } public Record<Step> construct() { if (currentStep != null) { steps.add(currentStep); } return new ArrayList<>(steps); } }
The complete code is offered in
this commit on GitHub.
There are extra enhancements attainable,
however I’ve included a couple of to exhibit the character of collaboration between LLMs
and builders.
Conclusion
Every a part of this extension—remark syntax, Java parsing logic, HTML viewer, and
Gradle wiring—began with a centered LLM immediate. Some components required some professional
developer steering to LLM, however the important thing profit was with the ability to discover and
validate concepts with out getting slowed down in boilerplate. LLMs are significantly
useful when you’ve a design in thoughts however are usually not getting began due to
the efforts wanted for organising the scaffolding to strive it out. They will help
you generate working glue code, combine libraries, and generate small
UIs—leaving you to concentrate on whether or not the thought itself works.
After the preliminary working model, it was necessary to have a developer to information
the LLM to enhance the code, to make it extra maintainable. It was important
for builders to:
- Ask insightful questions
- Problem proposed implementations
- Recommend various approaches
- Apply software program design rules
This collaboration between the developer and the LLM is essential to constructing
maintainable and scalable methods. The LLM will help generate working code,
however the developer is the one who could make it extra readable, maintainable and
scalable.