---
title: "Deploy Local Deep Research"
description: "AI deep-research assistant with citations and private SearXNG, behind auth"
category: "AI/ML"
url: https://railway.com/deploy/local-deep-research
---

# Deploy Local Deep Research

AI deep-research assistant with citations and private SearXNG, behind auth

**[Deploy Local Deep Research on Railway](https://railway.com/template/local-deep-research)**

Machine-readable deploy manifest (JSON, validated by TemplateCI): https://railway.com/deploy/local-deep-research/manifest.json

- **Creator:** Youssef Siam
- **Category:** AI/ML

## Template content

### ldr

- **Image:** localdeepresearch/local-deep-research:1.10.7

### searxng

- **Image:** ghcr.io/youssefsiam38/ldr-railway-searxng:1.0.0

### caddy

- **Image:** ghcr.io/youssefsiam38/ldr-railway-caddy:1.0.0
- **Health check:** /api/v1/health
- **Public domain:** Yes

## Documentation

# Deploy and Host Local Deep Research on Railway

Local Deep Research (LDR) is an open-source AI research assistant: give it a question and it runs multi-step web
research across many sources and writes a report with citations, using the LLM of your choice and a private
search engine. This is a community-maintained template; it is not affiliated with the Local Deep Research or
SearXNG projects.

## About Hosting Local Deep Research

LDR is a multi-user application that encrypts each user's data with their own password, and it needs a search
engine (SearXNG) alongside it, with SearXNG's JSON API enabled. Out of the box LDR's user registration is open
and, behind a TLS-terminating proxy, it needs the right forwarded headers or its real-time features break.

This template runs the whole thing on Railway as three services behind one password: LDR itself, a private
SearXNG with the JSON API turned on, and a Caddy front-door that adds HTTP basic authentication so the instance
is private by default and forwards the browser's HTTPS scheme so LDR's WebSocket progress streaming works. Bring
your own LLM key (OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible endpoint), configured inside LDR after
you sign in.

## Common Use Cases

- A private deep-research assistant for your team, behind a shared password.
- Cited literature and web research reports generated with your own LLM key.
- A self-hosted alternative to hosted "deep research" tools, with your data encrypted per user.

## Dependencies for Local Deep Research Hosting

- An LLM: OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible endpoint (configured in LDR's settings).
- Nothing else — SearXNG is bundled and private.

### Deployment Dependencies

- Local Deep Research: https://github.com/LearningCircuit/local-deep-research (MIT)
- SearXNG: https://github.com/searxng/searxng (AGPL-3.0)
- Caddy: https://caddyserver.com (Apache-2.0)
- Template repository, images and tests: https://github.com/youssefsiam38/ldr-railway

### Implementation Details

LDR runs upstream's own published image, pinned by digest (its maintainers already build non-root,
capability-dropped, with pinned dependencies). SearXNG runs the stock image with only its JSON output format and
secret configured. A Caddy front-door adds HTTP basic authentication over everything except the health check,
routes to LDR, and forces the HTTPS scheme LDR needs for secure cookies and its WebSocket same-origin check.
Ollama (local models) is omitted as impractical on CPU instances.

Tested in CI and on a live deployment of this template: all three services start, authentication gates the app,
LDR is reachable through the front-door, SearXNG's JSON API answers, the Socket.IO WebSocket connects through
basic auth, and a redeploy keeps the data volume.

The deploy form generates `OWNER_PASSWORD` (front-door username `owner`). Copy it from the caddy service's
variables, open the domain, then create your LDR account and add an LLM key inside the app.

## Why Deploy Local Deep Research on Railway?

Railway is a singular platform to deploy your infrastructure stack. Railway will host your
infrastructure so you don't have to deal with configuration, while allowing you to vertically and
horizontally scale it.

By deploying Local Deep Research on Railway, you are one step closer to supporting a complete full-stack
application with minimal burden. Host your servers, databases, AI agents, and more on Railway.


## Similar templates

- [Chat Chat](https://railway.com/deploy/-WWW5r) — Chat Chat, your own unified chat and search to AI platform.
- [stella](https://railway.com/deploy/stella) — Self-host stella with web, API, Postgres, Redis, and object storage.
- [Hermes Agent | OpenClaw Alternative with Dashboard](https://railway.com/deploy/hermes-agent-or-openclaw-alternative-wit) — Self-Hosted Hermes AI Agent for Telegram, Discord & Slack

Open this page in a browser: https://railway.com/deploy/local-deep-research