OpenDiagram is Rupam Golui’s open-source attempt to make AI-generated diagrams easier to read and revise: instead of asking a model to produce Mermaid text or an image, it has the model describe diagram content and uses a layout engine and renderer to place that content on an editable Excalidraw canvas. That separation can help avoid some familiar Mermaid frustrations, but it does not guarantee that a generated diagram is complete or technically correct.
Why build another AI diagram generator?
Golui describes the starting problem as a mismatch between a useful prompt and the diagram it produces. Mermaid code may fail to parse, or it may render as a crowded result that is difficult to edit. In his account, the issue is not just how a diagram looks: a text-based or image-like output can also make revisions awkward.
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OpenDiagram is his proposed alternative for software architecture and related diagrams. The project’s central idea is to make the AI describe what belongs in the diagram while software, rather than the model, determines where the elements go.
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How OpenDiagram says it generates a diagram
According to Golui’s project article, the model returns a typed semantic specification. The project then uses ELK for layout, a custom edge router for connections, and a themed renderer to create native Excalidraw elements. The author summarizes the approach this way: “The AI decides what’s in the system. It never decides where anything goes.”
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He also says, “The model never outputs Mermaid, and it never outputs pixels.” The distinction is about the generation pipeline: the AI supplies semantic content, while the application turns it into a canvas. It is not evidence that every result will be well organized, accurate, or complete.
What kinds of diagrams can it make?
The project describes support for several software and systems diagram categories. Its repository lists architecture, cloud, sequence, ER, flowchart, network, and infrastructure diagrams. The article illustrates those categories with an author-presented URL shortener, an AWS image-processing pipeline, an OAuth authorization-code sequence, an e-commerce ERD, and a larger commerce architecture prompt. These examples are the project’s own demonstrations, not independently reproduced results.
Can you edit the result after generation?
OpenDiagram describes its output as editable Excalidraw elements rather than a flattened image. The project says users can move shapes, restyle them, add notes, and ask the agent to revise a diagram. The repository also describes a persistent project workspace. That makes the canvas a starting point for human editing, not a substitute for checking the underlying system.
What the examples do—and do not—show
The Mermaid parsing anecdote
Golui reports that, for one URL-shortener prompt, two of five Mermaid outputs from ChatGPT and Gemini did not parse. He attributes those failures to {shortCode} in an edge label. This is a small, self-reported example from one prompt, not a benchmark or a general failure rate for AI-generated diagrams.
The complex-prompt omission
In another example, a prompt describing around 30 components led to a diagram that omitted disaster recovery, cross-region failover, and circuit breakers. That result makes an important limitation concrete: a diagram can look readable while leaving out requirements the prompt asked for. Treat generated diagrams as drafts and check their components, connections, and failure paths against the system and the original request.
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The article and repository describe OpenDiagram as open source under the AGPL-3.0 license and as self-hostable. The repository lists Bun 1.3+ and PostgreSQL as self-hosting prerequisites. Golui’s article describes the hosted service as free during beta and says it can be used in guest mode; its FAQ says users may optionally provide keys for OpenAI, Anthropic, Google, or OpenRouter. Hosted access, pricing, provider availability, and deployment instructions can change, so check the project repository and current service information before relying on those details.
Who should consider trying it?
OpenDiagram is worth considering if you want an AI-assisted first draft that remains an editable Excalidraw canvas, or if you want to inspect a workflow that separates semantic generation from layout and rendering. It is not a reason to skip technical review: verify that the diagram includes every required component and relationship, and correct any misleading structure before using it as documentation or a design artifact.
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