AnythingLLM PDF Upload Failed? Fix File Size Error Now
AnythingLLM PDF upload failing or processing hanging?
Compress your PDF instantly using the tool below — fixes hosted CPU limits, NGINX upload caps, and embedding errors.
🔒 Files never leave your device⚡ Instant processing in browser💸 100% free — no signup
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Drop your PDF here to fix upload errors
or click to select file — PDF only
Target size (optional)
or leave blank to compress as much as possible
⚡ File Size Limits (Quick Fix)
•Docker deployments of AnythingLLM behind an NGINX reverse proxy default to a 1MB upload limit, which will silently drop larger files.
👉 Fix: Compress your file below the required limit using the tool above.
About this tool
AnythingLLM upload failures have three common causes: CPU exhaustion on the hosted tier, NGINX's default 1MB upload cap on Docker deployments, or the embedder model running out of resources on large local files. Compressing the PDF addresses all three by reducing the processing load.
How to use this tool
Select or drag and drop your file into the tool above.
Adjust the settings or target size as needed for your specific requirement.
Wait a moment while your file is processed directly in your browser.
Download the final file safely to your device.
💡 Good to know
→AnythingLLM hosted Starter tier recommends a maximum of 10,000 words per PDF file to avoid CPU exhaustion and 502 errors.GitHub ↗
→Docker deployments of AnythingLLM behind an NGINX reverse proxy default to a 1MB upload limit, which will silently drop larger files.GitHub ↗
→Local and Docker installs of AnythingLLM have no enforced file size limit, but very large PDFs can exhaust CPU or RAM and cause the process to crash.GitHub ↗
→Converting large PDFs to Markdown before uploading to AnythingLLM improves embedding performance, as PDFs are less efficient to parse than plain text formats.GitHub ↗
Three common causes: (1) CPU exhaustion on the hosted Starter tier for files over 10k words, (2) NGINX's default 1MB upload cap on Docker deployments, (3) embedder model running out of RAM on large local files. Compress the PDF to reduce load.Source: GitHub ↗
How do I fix the NGINX 1MB upload limit in AnythingLLM Docker?+
Add or increase the client_max_body_size directive in your NGINX config (e.g. client_max_body_size 100M;) and reload NGINX. This raises the upload cap for your Docker deployment.Source: GitHub ↗
Why is AnythingLLM processing hanging on a large PDF?+
Large PDFs overwhelm the embedder model, causing the process to hang or crash. Compress the PDF, split it into chapters, or convert it to Markdown for faster, more reliable embedding.Source: GitHub ↗
Should I convert my PDF to Markdown for AnythingLLM?+
Yes, for large documents. Markdown is faster to parse and embed than PDF, and produces better AI responses. Use a PDF-to-Markdown converter for text-heavy research papers and documentation.Source: GitHub ↗
What is the most reliable fix for AnythingLLM upload failures?+
Split the PDF into smaller chapters (under 10k words each for hosted Starter), compress each part, and upload separately. This avoids CPU exhaustion, NGINX limits, and embedder memory issues simultaneously.Source: GitHub ↗
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