Deploy SRW — Helm values generator

Where it runs

One box, or a cluster you already have?

A single Linux machine becomes a cluster with k3s. An existing cluster brings its own ingress controller and storage, and the values adapt to what it has.

The runbook covers host preparation, volume storage and a private operator kubeconfig before installation.

Setup

Trying it out, or running it for real?

Evaluation keeps every credential in one values file. Production keeps them in Secrets you own and lets you swap any bundled service for one you already run.

Domain and TLS

Where will people reach it?

Use a domain with trusted TLS, or one IP/localhost address with a chart-owned self-signed certificate.

Base domain

ACME account e-mailHTTP-01 validation: port 80 must reach the ingress from the internet.

Services

Bundled, or bring your own?

The evaluation setup bundles everything. Switch to Production to bring your own Postgres, identity provider, git server or cloud storage.

Extras

Optional. The first three ship with the chart; the Dashboard is a separate install that install.sh does for you.

Neo4j knowledge graph. Project knowledge base. Community edition unless you bring an Enterprise license.pgAdmin. Database admin UI at pgadmin.<domain>, the SRW databases pre-registered. Login generated into the Secret.Dozzle. Live container logs at dozzle.<domain>. No login of its own, so keep that hostname on your VPN.Kubernetes Dashboard. A web view of pods, logs and events for anyone new to Kubernetes. Reached by port-forward with a token, never a public hostname.

Your account

Who will administer SRW?

Your first SRW login. Service and database credentials are generated separately.

Admin usernameChoose this for the initial installation. Existing accounts keep their username through upgrades.

Choose my own password. Otherwise a strong password is generated into your download.

Web research

Search the web and read pages?

The bundled research services need no external API key. AI models are configured separately after login.

Research packageSearXNG finds pages; Crawl4AI reads their content. Crawl4AI adds a 1 GiB memory request and a 4 GiB limit.

Models and capacity

How will you use AI models?

After installation, SRW guides you through connecting accounts, importing models and choosing defaults.

Use AI subscriptions. Install the model proxy, then connect a supported subscription in Settings → AI Subscriptions. Recommended for trying SRW. Connected accounts are shared across this installation.

Adds a 1 GiB auth volume, a 256 MiB memory request and a 2 GiB limit. Import models and choose defaults in Admin → Models after connecting. Some capabilities may need another model provider.

Max concurrent workersAgent pods that may run at once. Each needs roughly 1 vCPU and 1 GiB.

chevron_rightAdvanced: preconfigure model access

Preconfigure providers or an endpoint. Optional. You will still import models and choose defaults after login.

VM workspaces

How big is a VM, and how does the platform reach it?

Each VM boots from a golden image cloned onto its own root disk. install.sh installs KubeVirt and CDI matching your Kubernetes version; the runbook lists the hardware checks.

Root disk storage classRoot disk sizevCPU per VMMemory per VMMax VMs at once

SSH public key the platform uses to reach each VMssh-keygen -t ed25519 -f srw-vm -N "" — paste srw-vm.pub here; the private half goes into srw-secrets.yaml.

Pin VMs to labelled nodes. Required on a multi-node cluster with node-local storage (local-path): a root disk can only be mounted on the node that created it.

chevron_rightAdvanced — chart version, registry credential, secret values

Chart version (optional)Pin a version like 0.0.24, or leave empty.

Pull images with a registry credential. The images are public; tick this for a private mirror or a rate-limited network. install.sh then reads GHCR_USER and GHCR_TOKEN.

Your infrastructure,
your workforce