Deploy Flowise

Flowise for railway.app

Flowise is an open-source, low-code platform for building customized LLM workflows and AI agents through a drag-and-drop visual builder. It supports a wide range of language models, vector stores, and tools out of the box. This template deploys the official flowiseai/flowise Docker image on Railway, ready to use.

🏗️ Architecture

flowchart LR
    Client(["🌐 Client"]) -->|HTTPS| Domain["Railway Public Domain"]
    Domain -->|"$PORT"| App["Container\nflowiseai/flowise:latest"]
    App --> Volume[("Volume\n/root/.flowise")]

Environment

The published template attaches /root/.flowise, generates an HTTP domain and administrator credentials, and generates FLOWISE_SECRETKEY_OVERWRITE to keep credential encryption stable across redeploys. /api/v1/ping is the unauthenticated deployment healthcheck; it does not bypass authentication for the application API.

See Flowise environment variables. railway.toml declares requiredMountPath = "/root/.flowise" (default location for flows, credentials, chat history, and blob storage) — attach a Railway volume to that path before production traffic.

Authentication

Flowise supports built-in Basic Auth for the UI and API via the FLOWISE_USERNAME and FLOWISE_PASSWORD environment variables. They are optional, but strongly recommended for any deployment reachable from the public internet — without them, anyone with the URL can access your flows, credentials, and chat history. See .env.example and set both as generated secrets in the Railway dashboard.

Local

docker build -t railwayapp-flowise .
docker run --rm -p 8080:8080 -e PORT=8080 railwayapp-flowise