In-Browser Graph RAG with Kuzu-WASM and WebLLM
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…
In plain words
This project demonstrates a fully in-browser chatbot that performs Graph RAG by combining Kuzu, an embedded graph database compiled to WebAssembly, with WebLLM for on-device language model inference. The system translates user questions into Cypher queries to retrieve relevant graph data, which the LLM then uses to generate responses. It is designed for developers exploring how modern graph databases and language models can work together entirely within the browser without server dependencies.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of the performance limitations we see currently may not be as much of a problem in the future. We will soon also be releasing a vector index as part of Kuzu that you can also use in the browser to build traditional RAG or Graph RAG that retrieves from both vectors and graphs. The system has come a long way since we open sourced it about 2 years ago, so please give us feedback about how it can be more useful!
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