OpenRAG

Free#18 of 26 in Retrieval-Augmented Generation ToolsLLM Application Development Frameworks

OpenRAG: OpenRAG combines multimodal parsing, hybrid retrieval, citations, and self-hosted control. Ranked #18 of 26 in Retrieval-Augmented Generation Tools by our editors (7.3/10); pricing: Free plan; best for open-source multimodal RAG deployments.

7.3/10★★★★☆Editor score

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At a glance

• Editor score
  7.3 / 10
• Pricing
  Free plan
• Best for
  Open-source multimodal RAG deployments
• Free plan
  Yes
• Paid from
  None
• Source citations
  Yes
• Founded
  2000
• Facts checked
  22 Sep 2026

• Where it wins

  • Hybrid semantic and BM25 search with multilingual reranking
  • OCR, image captioning, and audio transcription support
  • Page-level citations, partitioned knowledge bases, and APIs

• Where it doesn't

  • Self-hosted deployments require your team to manage infrastructure
  • Configuring model, embedder, reranker, and VLM endpoints adds decisions
  • The framework is focused on document-grounded AI systems

Our verdict on OpenRAG

OpenRAG is an open-source Retrieval-Augmented Generation framework from LINAGORA for teams building document-grounded AI systems. It supports web, API, and self-hosted deployments, with control over infrastructure, data, models, and the retrieval pipeline. Public and private organizations can use it to combine document ingestion, retrieval, reranking, citations, and generation in one modular system. Its scope is especially relevant to teams that need multimodal knowledge access rather than a basic text-only question-answering layer.

The retrieval and parsing stack is the main strength. OpenRAG combines semantic search with BM25 keyword search, then supports multilingual result reranking. Answers can include document- and page-level citations, while multimodal parsing covers OCR, image captioning, and audio transcription. Partitioned knowledge bases support separation by user or team. Teams can configure their own LLM, embedder, reranker, and VLM endpoints, and the React administration console covers documents, jobs, users, models, and presets. Horizontal processing with Ray gives the architecture a path for larger workloads.

OpenRAG is free and open source, and its OpenAI-compatible API supports integration with Open WebUI, LangChain, n8n, and Twake.ai. The separately scoped managed service uses usage-based or fixed-fee billing. Self-hosted control is a strong fit for organizations that need infrastructure and model flexibility, but it also places deployment and operational responsibility on the adopting team. Choose OpenRAG for open-source, multimodal, citation-aware RAG deployments with configurable components; teams seeking a narrowly packaged hosted product may prefer a simpler alternative.

OpenRAG pricing

OpenRAG fact sheet

OpenRAG integrations

OpenRAG lists 4 integrations on its own site.

• Open WebUI
• LangChain
• n8n
• Twake.ai

Alternatives to OpenRAG

• Amazon Bedrock Knowledge BasesA deep, AWS-centered toolkit for production RAG over enterprise and structured data.9.3
• HaystackA modular Python framework for customizable RAG pipelines, agents, and semantic search.9.2
• LangChainA flexible foundation for developers building programmable RAG and agent applications.9.1

See all OpenRAG alternatives →

Also listed in

• LLM Application Development Frameworks

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update