How do I deploy lightrag on Railway?

You can deploy lightrag on Railway by clicking the "Deploy Now" button on this page. Railway will automatically set up all the necessary services and configurations for you.

What are the system requirements?

Railway handles all the infrastructure requirements. You only need a web browser to deploy and manage your application.

Is this template free to use?

Yes, this template is free to use within your existing Railway account.

Can I customize this template?

Yes, you can fully customize this template. After deployment, you will have full control of what you've deployed in your Railway project.

How do I get support for this template?

You can get support through our community forum: lightrag-2a040f0c, or join our Discord community for more assistance.

Deploy and Host LightRAG on Railway

One-click deployment of LightRAG - the most popular Graph RAG framework with 25K+ GitHub stars. Featured in EMNLP 2025.

About Hosting LightRAG

LightRAG is a graph-based Retrieval-Augmented Generation system that outperforms traditional RAG by building knowledge graphs from your documents. Unlike simple vector search, LightRAG understands relationships between entities, delivering smarter and more contextual answers.

This template includes the full LightRAG server with a built-in Web UI for document management, chat interface, and interactive knowledge graph visualization.

Why Deploy LightRAG on Railway

One-click setup: No Docker configuration or server management required
Built-in Web UI: Upload documents, chat, and visualize your knowledge graph instantly
Smarter than traditional RAG: Graph-based retrieval captures entity relationships, not just text similarity
Multiple LLM providers: Works with OpenAI, Groq, OpenRouter, Azure, and AWS Bedrock
Production ready: Health checks, automatic restarts, and scalable infrastructure
Cost effective: Pay only for what you use with Railway's usage-based pricing

Common Use Cases

Research & Academia: Analyze research papers and discover connections across literature
Documentation Q&A: Build intelligent search for technical documentation
Legal Document Review: Extract entities and relationships from contracts and legal texts
Customer Support: Create knowledge bases that understand context and relationships
Business Intelligence: Query company documents with natural language
Personal Knowledge Management: Organize and query your notes, books, and articles

Dependencies for LightRAG

LightRAG requires an LLM provider for text generation and embeddings. The template supports multiple providers out of the box.

Deployment Dependencies

LLM Provider (Required): OpenAI API key recommended. Also supports Groq, OpenRouter, Azure OpenAI, and AWS Bedrock
Embedding Model (Required): Uses OpenAI text-embedding-3-small by default (1536 dimensions)
Storage: Railway provides ephemeral storage. Add a Railway Volume mounted to /app/data for persistent storage
Memory: Minimum 512MB RAM recommended, 1GB+ for larger document collections

Environment Variables

Variable	Required	Default	Description
LLM_BINDING_API_KEY	Yes	-	Your LLM provider API key
LLM_MODEL	No	gpt-4o-mini	Model for text generation
EMBEDDING_MODEL	No	text-embedding-3-small	Model for embeddings
EMBEDDING_DIM	No	1536	Embedding dimensions

Quick Start

Deploy this template
Set your LLM_BINDING_API_KEY environment variable
Generate a public domain in Settings → Networking
Access the Web UI and upload your first document