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View guide →LibreAI / RAG & Knowledge / rag.computer
// rag · bigint/rag.computer
rag.computer
rag.computer is an open-source rag & knowledge project by bigint (bigint/rag.computer on GitHub). It has 100 GitHub stars and 11 forks, is released under the MIT license, and was last updated on GitHub on 4 October 2026.
Rag.computer — self-hostable rag platform - document ingestion, embedd, open-source.
💎 Hidden gem★ 100 stars⑂ 11 forksMITupdated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
so here's a placeholder. The guide below is complete regardless.
// project facts
Project facts
- Repository
- bigint/rag.computer
- GitHub stars
- 100
- Forks
- 11
- License
- MIT
- Last updated on GitHub
- 4 October 2026
- Category
- RAG & Knowledge
- Listing
- Hidden gem — a shorter page for a lesser-known project
- Official site
- Official site
// how it works
How it works
- Clone the repository
Fetch the source code onto your machine.
- Install dependencies
Set up the Python environment the project needs.
- Configure the project
Copy the sample config or env file and adjust it.
- Run it
Start the app from the source directory.
// features
Why people love it
Ai
Built around ai for a focused workflow.
Embeddings
Built around embeddings for a focused workflow.
Rag
Built around rag for a focused workflow.
Rag Pipeline
Built around rag pipeline for a focused workflow.
Open source
Inspect, fork, and modify every line of the code.
Self-hosted
Run it on your own machine — no account lock-in.
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// run it
Run it yourself
- Clone
Get the source on your machine.
git clone https://github.com/bigint/rag.computer.git - Install
Set up Python dependencies.
cd rag.computer && pip install -r requirements.txt - Start
Launch the application.
cd rag.computer && python main.py
// use cases
What you can build
- Contributing fixes back to the project
- Forking and customizing for your own needs
- Teaching or studying rag & knowledge patterns
- Self-hosting instead of paying for SaaS
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// faq
Questions, answered
What does rag.computer do?
It self-hostable RAG platform - document ingestion, embedding, and vector search behind a simple REST API, giving you a working starting point you can run and adapt.
Is rag.computer free to use?
Yes — the code is open-source, so you can use and modify it without a license fee.
How do I install rag.computer?
Clone the GitHub repository and follow the README; the typical flow is install dependencies, configure, and run.
What is rag.computer written in?
It is primarily written in Python, so you will need that toolchain to build or extend it.
Where can I get help with rag.computer?
The GitHub repository is the hub: open issues for bugs and check the README and discussions for guidance.
// keep exploring
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View guide →// alternatives
Alternatives in RAG & Knowledge
The most-starred other RAG & Knowledge projects in the LibreAI catalogue — the realistic shortlist if rag.computer is not the right fit.
- MarkItDown★ 193.5k
MarkItDown — Microsoft tool that converts PDFs, Office files, images and more to clean Markdown for LLMs, MIT
- Dify★ 157.8k
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
- ragflow★ 91.6k
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
- PaddleOCR★ 90.8k
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
- MinerU★ 82.5k
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
// more in rag
More in RAG & Knowledge
Nearby RAG & Knowledge projects in the catalogue, closest in stars to rag.computer — keep exploring the shelf either side of it.
- autonomie★ 103
Open rag & knowledge for "autonomie" is a highly semantic, responsive, accessibl.
- docs-mcp★ 97
Self-hosted rag & knowledge: cometchat docs search + implementation bundles: add cha.
- textbook-to-note★ 104
Self-hosted rag & knowledge: turn your own pdf textbooks into an ai-searchable knowl.
- infigraph★ 91
AST-powered code intelligence engine — graph database plus hybrid semantic search across 62 languages, zero LLM dependency.
- dstoolkit-text2sql-and-imageprocessing★ 105
Open rag & knowledge for this repo accelerates development of rag applications w.
- codealive-mcp★ 90
Codealive-mcp, in Python — built for context engine for large codebases, exposed throug...
Get rag.computer
Free and open — grab the source, star the repo, and start creating.