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langflow-ai/openrag — OpenRAG is a comprehensive, single package Retrieval-Augmented Generation platform built on Langflow…

Description and use

Here's a 2-3 sentence summary of the project:

OpenRAG is an open-source Retrieval-Augmented Generation platform that enables the creation of searchable knowledge bases, allowing internal knowledge to be easily accessible and usable by assistants. This platform, built on Langflow, Docling, and Opensearch, can be integrated with various use cases such as indexing knowledge bases, improving search over documents, and grounding assistant answers. With its high production readiness and strong ecosystem signals, OpenRAG is suitable for a serious pilot, making it a valuable tool for organizations looking to leverage AI-driven knowledge management.

**Value:**
The primary value proposition of OpenRAG lies in its ability to make internal knowledge searchable and usable by assistants, revolutionizing the way organizations approach knowledge management. By leveraging the power of Retrieval-Augmented Generation, OpenRAG enables the creation of a comprehensive and easily accessible knowledge base, which can be used to improve search, ground assistant answers, and index knowledge bases.

**Practical Adoption Path:**
To adopt OpenRAG, organizations can start by evaluating its feasibility through a small proof of concept and reviewing the README documentation. This will help them understand the platform's capabilities and requirements. Once the feasibility is established, organizations can proceed with a more extensive pilot to test the

Problem

langflow-ai/openrag helps make internal knowledge searchable and usable by assistants.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

  • index knowledge bases
  • improve search over documents
  • ground assistant answers

Evidence

OpenRAG is a comprehensive, single package Retrieval-Augmented Generation platform built on Langflow, Docling, and Opensearch.

Source

  • Record date: 2026-09-11T06:12:44.144Z