RAG e conhecimento
infigraph
AST-powered code intelligence engine — graph database plus hybrid semantic search across 62 languages, zero LLM dependency.
★ 91 estrelasNOASSERTION
Ver o guia →quivr é um projeto de RAG e conhecimento de código aberto de The-Vibe-Company (The-Vibe-Company/quivr no GitHub). Tem 39.575 estrelas no GitHub e 3.739 forks, é publicado sob a licença MIT e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.
Open-source engine turning continuous content streams into search, monitoring and alerts
Decide what you want from quivr and check the README and requirements to confirm it fits your setup and Go environment.
Clone the repository from GitHub (github.com/The-Vibe-Company/quivr) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
Durable ingestion of continuous content streams rather than one-off uploads.
Hybrid search across the ingested content for retrieval and monitoring.
Alerting on new or matching content as it arrives.
Plugins for formats, models and business rules extend the engine.
The V2 engine is written in Go with Docker Compose and Railway deployment options.
`make dev` starts dependencies, runs migrations and launches the API and worker.
Start by getting the source and entering the project directory.
git clone https://github.com/The-Vibe-Company/quivr.git
cd quivrRequirements include Go, Docker with Compose v2 and Python 3; make dev brings the stack up.
make devRun the end-to-end verification journeys on an isolated stack.
make verifyIt is maintained by The-Vibe-Company and contributors on GitHub, where the repository github.com/The-Vibe-Company/quivr is the canonical home for code, issues and releases.
Yes — it is open source under the MIT license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
Model access depends on the plugins you configure; the engine itself is self-hosted and key-free.
Compared with classic Quivr 'second brain' apps: Quivr V2 is an engine for streams, search and alerts, rather than a single-user chat-with-documents app.
Clone github.com/The-Vibe-Company/quivr, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
AST-powered code intelligence engine — graph database plus hybrid semantic search across 62 languages, zero LLM dependency.
Semantic search engine designed for files and code.
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
Meta's library for efficient similarity search and clustering of dense vectors, in C++ and Python
Vector similarity search inside Postgres - store embeddings next to your data
Air-gapped, open-source NotebookLM alternative that turns local documents into briefings, decks and podcasts.
Os outros projetos de RAG e conhecimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se quivr não for o ideal para você.
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Projetos de RAG e conhecimento próximos no catálogo, os mais próximos em estrelas de quivr: continue explorando dos dois lados dele.
Marker — converts PDFs to Markdown and JSON quickly and accurately, with layout, tables and math intact, Apache-2.0
PageIndex: vectorless, reasoning-based RAG that indexes documents like a human expert would
Meta's library for efficient similarity search and clustering of dense vectors, in C++ and Python
Local knowledge-base RAG and agent app built on LangChain with ChatGLM, Qwen and Llama models
Complete API layer for private AI apps on local models: RAG, skills, tools, MCP and text-to-SQL
Microsoft's graph-based RAG: index a corpus into a knowledge graph, then query it with an LLM
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.