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I built this POC to test if complete RAG pipelines could run entirely client-side using WebGPU.
Key difference: zero server dependency. PDF parsing, embeddings, vector search, and LLM inference all happen in your browser.
Select a model (Llama, Phi-3, Mistral), upload a PDF, ask questions. Documents stay local in IndexedDB. Works offline once models are cached.
Integrated WeInfer optimization achieving ~3.76x speedup over standard WebLLM through buffer reuse and async pipeline processing.
WebPizza AI - Private PDF ChatPOC: Private PDF AI using only your browser with WebGPU
Emanuele Strazzulloleft a comment
Hey everyone, I’m Emanuele, and I built WebPizza AI to see if browser-based RAG could actually work — and to rethink how much we trust cloud AI tools with our data. Most “chat with your docs” apps work like this: upload your PDF → processed on their servers → chat with results. That’s fine, but it means your files live somewhere you can’t control. I wanted to flip that idea. What if everything...
WebPizza AI - Private PDF ChatPOC: Private PDF AI using only your browser with WebGPU
I built mcl to simplify my daily terminal workflow.
It lets you create custom shortcuts for your most-used commands locally or globally using a simple JSON config.
It’s still early, but I plan to add auto-completion, plugin support, and command chaining soon.
MCLLightweight CLI tool for local & global commands
Emanuele Strazzulloleft a comment
Hi everyone! 👋 I built mcl to make my terminal workflow faster and cleaner. It lets you define local and global commands in a simple JSON file — and run them anywhere with just mcl . It’s open source, still in its early stage, and I’d love your feedback 🙌 🔗 GitHub: https://github.com/stramanu/mcl-...
MCLLightweight CLI tool for local & global commands