Open-source GraphRAG Application with your own data
Hello. This is an easy-to-use application for exploring your own data with retrieval augmented generation (RAG) backed by txtai. txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows. txtai has a feature to automatically create knowledge graphs using semantic similarity. This enables running Graph RAG queries with path traversals. This RAG application generates a visual network to illustrate the path traversals and help understand the context from which answers are generated from. Embeddings databases are used as the knowledge store.…
Open-source GraphRAG Application with your own data launched on August 8, 2024 with 12 votes, #1,297 of 5,471 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
This open-source application lets users explore their own data using retrieval augmented generation backed by txtai, an embeddings database for semantic search and language model workflows. It automatically creates knowledge graphs from data and runs Graph RAG queries with path traversals, displaying results as visual networks to show how answers were derived. Users can start with a blank database or existing sources like Wikipedia, then add custom information using the textractor pipeline. The application extracts content from documents and stores it in an embeddings database for retrieval.
written from the facts on this page · September 2026
From the sources
This project is a Retrieval Augmented Generation (RAG) Streamlit application backed by txtai from hub.docker.com
In the maker’s words, at launch
Hello. This is an easy-to-use application for exploring your own data with retrieval augmented generation (RAG) backed by txtai. txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows. txtai has a feature to automatically create knowledge graphs using semantic…
Does a similar job
all alternatives →
txtai: open-source, production-focused vector search and RAG2024 · neuml.github.io · ▲12txtai is an all-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows
FastGraphRAG – Better RAG using good old PageRank2024 · github.com · ▲457Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
Turn any website into a knowledge base for LLMs2024 · embedding.io · ▲305I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
- IMI made a website to semantically search ArXiv papers2024 · papermatch.mitanshu.tech · ▲324
As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…
- IBIn-Browser Graph RAG with Kuzu-WASM and WebLLM2025 · blog.kuzudb.com · ▲158
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…
HelixDB – Open-source vector-graph database for AI applications (Rust)2025 · github.com · ▲237Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 21d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 30d ago · world.pixverse.video
Source: Show HN post ↗ · launch text quoted in part
Launched alongside, August 2024
the whole month →
Jupitrr AI▲1,195Jupitrr AI turns raw talking videos into scroll-stopping content for coaches and consultants. Research, script, record, edit, and publish in one app.
AI · 2024 · jupitrr.com
Hey there HN! We’re Joe and Stopa, and today we’re open sourcing InstantDB, a client-side database that makes it easy to build real-time and collaborative apps like Notion and Figma. Building modern apps these days involves a lot of schleps. For a basic CRUD app you need to spin up servers, wire up endpoints, integrate auth, add permissions, and then marshal data from the backend to the frontend and back again. If you want to deliver a buttery smooth user experience, you’ll need to add optimistic updates and rollbacks. We do these steps over and over for every feature we build, which can…
Dev tools · 2024 · github.com