I’m building a tool that scans through Figma documents in a workspace to locate specific node types. I’m using a Node.js library that wraps the Figma REST API calls.
The issue happens when I try to fetch really big Figma files using the file retrieval endpoint. The API returns a 400 status code with this error message:
const designApi = new FigmaClient({ token: process.env.FIGMA_TOKEN });
try {
const documentData = await designApi.getDocument(largeFileKey);
console.log('Document loaded:', documentData);
} catch (error) {
console.error('Failed to load document:', error.message);
// Error: Request failed with status code 400
// Response: "Render timeout, try requesting fewer or smaller images"
}
The weird part is that this error mentions images and rendering, but I’m just trying to get the document structure as JSON data. There’s a separate image export endpoint for actually getting image files.
Has anyone found a workaround for this? I’m wondering if there’s a way to fetch large documents in smaller pieces or if there are any API parameters that might help. Right now I’m just using the basic document endpoint and expecting to get back the full node tree structure.
I faced a similar issue with large Figma files, and I discovered that the misleading error message about images was actually related to document complexity. A useful workaround is to use the ids parameter in your request. By fetching specific pages or frames individually instead of the entire document, you can significantly reduce the payload size and avoid timeouts. Additionally, consider starting with the basic file metadata before pulling specific pages using their node IDs. This approach helps manage the size of your requests effectively. Implementing geometry=paths can also be beneficial for optimizing vector data. Lastly, ensure you have retry logic with exponential backoff in place, as large files can lead to unpredictable response times.
weird it’s mentioning images when ur just pulling JSON. I’ve hit this b4 - Figma struggles with massive files even on basic calls. try adding ?depth=1 to limit how deep it digs into the tree structure. fixed it for me on some huge design system files.
Been there with oversized Figma files. The 400 error happens because Figma’s API tries to process all the document data at once, including preparing image references even for the JSON structure call.
Most people will tell you to use pagination or break down your requests manually, but that’s a pain to code and maintain. You end up writing tons of retry logic and rate limiting code.
I hit this exact problem last year when scanning design systems across multiple large files. What solved it was setting up an automation workflow that handles the heavy lifting.
The workflow breaks down large Figma requests automatically, manages rate limits, and reassembles the data. It also caches responses so you don’t hit the same timeouts repeatedly. Plus it runs the scanning logic without blocking your main application.
Saved me weeks of coding custom retry mechanisms and error handling. The automation approach scales way better than trying to handle this stuff in your Node.js app directly.
Hit this same issue 6 months back with massive enterprise Figma files - hundreds of components everywhere. That timeout error’s misleading - it’s not about image rendering, it’s the API choking on the entire document tree at once. Here’s what fixed it: use the depth parameter to limit how deep the request goes. Skip fetching the complete structure and start with depth=1 or depth=2 instead. Then make separate calls for the specific pages or frames you actually need. More API calls, but no more timeouts. Also check if your files are loaded with embedded assets or external components - that stuff creates processing overhead. Files with tons of imported libraries hit this limit even when they don’t look that big in Figma’s interface.
ohh, i totally feel ya! big files can be a pain. try using geometry=paths to reduce data size or just grab specific page IDs! it really helps to get past those limits.