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RAG & Knowledge Systems

Lightningrag

Lightningrag is an open-source Vue and Gin full-stack starter for building retrieval-augmented generation applications. It provides document knowledge-base workflows, vector and other retrieval methods, configurable model and storage integrations, and a canvas for orchestrating retrieval, language-model calls, tools and control flow.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Lightningrag — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Lightningrag when building a self-managed RAG application calls for control over document ingestion, retrieval methods, provider configuration or visual agent orchestration. Optional webhook connectors suit projects that also want to bind published agents to messaging channels.

Who it is for

  • Developers building a document-grounded chat or knowledge-base application.
  • Teams that need to configure LLM, embedding, vector-store or reranking providers.
  • Builders designing multi-step or branching agent workflows around retrieval and tools.
  • Developers connecting published agents to messaging services through webhooks.

Documented uses

  • Ingest, parse and chunk documents, then embed them into a configured vector store.
  • Retrieve knowledge using vector, keyword, PageIndex or related retriever types.
  • Build chat workflows with streaming responses and optional references.
  • Compose agent flows from retrieval, LLM, message and tool-enabled agent nodes.
  • Bind published agents to supported messaging channels using webhook connectors.
Before you choose

Requirements & limits

  • The documented frontend and backend use Vue and Gin; the technology selection also lists MySQL and Redis.
  • The README sets Node.js above 18.16.0 and Go at 1.22 or later for its development setup.
  • Provider integrations are described as pluggable, but the specific provider options should be checked in the project documentation.
  • The README describes the online demo as not yet deployed.
  • The Apache-2.0 license is specified in the repository.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Start the server and web app locally

Follow the README's separate development commands to launch the backend and frontend.

Before you start

  • Node.js version above 18.16.0
  • Go version 1.22 or later
  • A local copy of the LightningRAG repository

Steps

  1. Clone the repository using the documented Git command.

  2. In the server directory, run the command below, then the command below.

    Documented command
    go generate
    Documented command
    go run .

  3. In the web directory, run the command below, then the command below.

    Documented command
    npm install
    Documented command
    npm run serve

Expected outcome

The README provides commands to start the server and web app as separate development processes.

Guide limitations

  • The instructions describe separate server and web workflows; they do not establish that a particular local environment will run successfully.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Retrieval-augmented applications

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
LightningragIngest, parse and chunk documents, then embed them into a configured vector store.Self-hosted, Server, Web
LangsearchCrawl website or local data for a knowledge base.CLI, Self-hosted, Server
Hybrid Search RagCombine document retrieval and language-model generation in a configurable workflow.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
9 October 2026
Original website title
LightningRAG/LightningRAG · Official homepage title · retained in its source language
How we review sourcesSuggest a correction