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Introducing RAGFlow: Enabling Smarter Research with AI-Powered Search

A new open-source application is now available on UCloud, designed for students, researchers, and educators working with complex data and artificial intelligence. RAGFlow – short for Retrieval-Augmented Generation – combines powerful language models with your own academic materials, offering an intelligent way to search, explore, and interact with content.

Whether you’re conducting a literature review, developing a teaching assistant, or building a domain-specific chatbot, RAGFlow provides an intuitive pipeline that transforms unstructured documents into a searchable, AI-ready knowledge base. But RAGFlow is more than just question-answering. It supports the creation of custom workflows and intelligent agents, enabling advanced interactions, data processing, and tool integration – all within a flexible and transparent environment.

What can you do with RAGFlow?

RAGFlow helps large language models (LLMs) generate accurate answers based on real data – not just pre-trained knowledge. It’s built to close the gap between raw academic material and useful insight.

RAGFlow is designed with both beginners and advanced users in mind. At its simplest, you can just upload documents and start asking questions. The interface guides you through the basics, so you can get useful results straight away.

As your needs grow, you can delve deeper into advanced features such as custom chunking, retrieval tests, datasets, and programmable workflows. Comprehensive documentation and tutorials are available, allowing you to learn at your own pace and expand your use of the platform over time.

Key Features:
  • Data Ingestion & Chunking:
    Upload PDFs, text files, webpages and more. RAGFlow automatically breaks them into manageable parts.
  • Embedding & Indexing:
    These chunks are converted into vector representations so they can be searched by meaning, not just keywords.
  • Smart Retrieval:
    When you ask a question, the system finds the most relevant information.
  • Contextual Generation:
    An LLM uses this context to generate well-informed responses.
  • Cited Sources:
    All answers come with grounded citations, showing where the information came from — supporting transparency and academic rigour.

This process improves the quality of responses and significantly reduces the risk of hallucinated or misleading answers.

From Search to Workflow: Introducing Agents

Beyond document search, RAGFlow also allows you to build and customise your own AI-powered agents. These agents can search, analyse, and use tools on your behalf – forming a pipeline tailored to your specific research needs.

So, what is an agent?

Think of an agent as a specialised AI assistant. You might create one to retrieve data from a source, another to analyse it, and a third to generate a written summary or report. These agents can be chained together into a programmable pipeline – a step-by-step flow where each agent passes its output to the next.

For example, you could build a research assistant that:

  • Searches for academic papers on a topic
  • Extracts and summarises the most relevant findings
  • Runs basic statistical analysis
  • Outputs the results as a draft report

Unlike typical ‘black-box’ AI tools, which conceal their inner workings, RAGFlow provides full transparency, allowing you to understand exactly how your AI operates. You can inspect, adjust, and understand every stage – from document chunking to embedding, retrieval, and agent reasoning. It’s a flexible and reproducible platform where your agents can be saved, re-run, or even shared with colleagues.

Why use RAGFlow on UCloud?

RAGFlow is available directly on UCloud. This offers several key advantages:

  • Academic Use Cases:
    Build assistants for teaching, research discovery, or even entire knowledge bases for your institute or research centre.
  • No Installation Required:
    Launch RAGFlow on UCloud with everything preconfigured and ready to use.
  • Flexible AI Model Support:
    Choose from models hosted on Hugging Face, Ollama, or take advantage of GPU-accelerated inference with vLLM – all accessible via an API key.
  • Easy Document Management:
    Upload and manage a wide range of formats, including PDFs, scanned documents, spreadsheets, and HTML.
Learn more 

Guides and technical details:
RAGFlow Guide
RAGFlow documentation on UCloud

A recorded tutorial will also be available shortly. Sign up for the newsletter to receive updates on this and other Interactive HPC news.