wild-pc/docs/design.md

Wild PC Design

Wild PC is a personal software platform. It manages independent services, tools, and frontends on a Linux machine using standard Unix primitives — systemd for process supervision, Caddy for HTTP routing, the filesystem for storage, and env vars for configuration. The wildpc CLI and API provide a registry and coordination layer on top.

The long-term goal: multiple Wild PC nodes (machines) that discover each other and coordinate, forming a personal infrastructure mesh. Each node is self-sufficient. The mesh is optional.

Principles

1. Unix-native. Use the OS. systemd, journald, filesystem, signals, env vars, DNS. Don't reimplement what Linux already provides.

2. Independence. Components never depend on Wild PC. They accept standard configuration (ports, data dirs, URLs) via env vars. A Wild PC service is just a well-behaved Unix daemon that happens to be registered in a manifest.

3. Stack and kind. Each program has an optional stack (development toolchain: python-fastapi, python-cli, react-vite). How it's realized is a property of its deployment, whose manager (systemd/caddy/path/ none) determines the derived kind (service, job, tool, static, reference). Scheduling, systemd management, and proxying are orthogonal operations — not kinds.

4. Language-agnostic above the build line. Below the build line, every language is different (uv, pnpm, cargo, go). Above it, everything is just processes, ports, files, and signals. Wild PC operates above the line.

5. Separate source from runtime. The repo is for development. The runtime lives in standard Unix locations ($WILDPC_HOME, default ~/.wildpc/, plus systemd units). Nothing running should point into the source tree.

6. AI-manageable. The CLI and API exist so that AI assistants can discover, create, and manage programs programmatically. Humans use the dashboard. Agents use the CLI and API.

7. Simple until proven otherwise. Filesystem over databases. HTTP over custom protocols. Shell commands over plugin systems. Add complexity only when the simple thing actually fails.

Architecture Layers

┌─────────────────────────────────────────────┐
│  Coordination                               │
│  Node discovery, global registry, messaging │
├─────────────────────────────────────────────┤
│  Registry                                   │
│  Component spec, node config, CLI, API      │
├─────────────────────────────────────────────┤
│  Runtime                                    │
│  systemd, Caddy, filesystem, journald       │
├─────────────────────────────────────────────┤
│  Build                                      │
│  uv, pnpm, cargo, go build, etc.           │
└─────────────────────────────────────────────┘

The critical boundary is between Build and Runtime. Below it, each language has its own toolchain. Above it, everything is uniform — a process that reads env vars, listens on a port, logs to stdout, and responds to SIGTERM.

Build Layer

Transforms source code into runnable artifacts. Wild PC does not abstract over language toolchains — it just records the build commands and their outputs.

Language	Toolchain	Artifact
Python	uv	Entry point in venv
Node/TS	pnpm	Static bundle (frontends) or node script
Rust	cargo	Binary
Go	go build	Binary

Wild PC's build spec is intentionally minimal: a list of shell commands and a list of output paths. This works for any language without Wild PC needing to understand the toolchain.

For interpreted languages (Python, Node), Wild PC also needs to know the runtime wrapper — how to invoke the artifact. For a manager: systemd deployment this is the nested run: block's launcher variants:

• python — Python (sync via uv, deploy resolves installed binary)
• node — Node.js (sync via pnpm/npm)
• command — Direct execution (compiled binaries, shell scripts)
• container — Docker/Podman
• compose — a multi-container stack as one unit

(A non-systemd deployment has no launcher: manager: caddy serves files, manager: path installs a CLI, manager: none is an external reference.)

Compiled languages (Rust, Go) use the command launcher — once built, they're just binaries. No Wild PC-specific launcher needed.

Runtime Layer

Manages running processes using standard Linux infrastructure.

systemd handles process supervision:

• Start/stop/restart services
• Restart-on-failure policies (OTP's "let it crash")
• Dependency ordering via After= / Wants=
• Scheduled execution via .timer units
• Logging via journald (stdout/stderr capture)

Caddy handles HTTP routing:

• Reverse proxy on port 9000
• Subdomain routing to services (<service>.<domain>); the /api path is reserved for the dashboard's own backend in no-domain (HTTP-only) mode
• Static file serving for frontends
• TLS termination

Filesystem handles storage:

• Service data: $WILDPC_DATA_DIR/<name>/ (default /data/wildpc/, on a dedicated volume)
• Secrets: $WILDPC_HOME/secrets/ (default ~/.wildpc/secrets/)
• Generated config: $WILDPC_HOME/artifacts/specs/ (Caddyfile, registry.yaml)

Wild PC generates systemd unit files and Caddyfile entries from the registry. It doesn't run a daemon itself — it configures OS-level infrastructure and gets out of the way.

Systemd units point to installed binaries (on PATH or in ~/.local/bin/), not to repo subdirectories. Frontends are the deliberate exception: rather than stage a copy, Caddy serves their built assets in place from the repo (<source>/<dist>/) at the root of its own subdomain (VITE_BASE=/).

Registry Layer

The registry is the central concept in Wild PC. It tracks what programs exist, what they can do, and how they're configured. But it's not a single thing — it's three distinct concepts:

1. Component spec — what a program is. Description, capabilities, build instructions, default configuration. This is source-level information, version-controlled in the repo. It answers: "what programs could exist?"

2. Node config — what's deployed on this machine, with what concrete ports, data paths, and env vars. This is per-machine. Two Wild PC nodes might run different subsets of programs with different parameters. It answers: "what's running here, and how?"

3. Runtime state — what's actually happening. PIDs, health, uptime, logs. This is ephemeral, owned by systemd and queried on demand. It answers: "is it working?"

Source vs. runtime split

These map to the config root (wildpc.yaml globals plus per-resource files under programs/ and deployments/), version-controlled in the repo:

# programs/central-context.yaml — what software exists
description: Content storage API
source: /data/repos/central-context

# deployments/central-context.yaml — manager: systemd → kind: service
program: central-context
manager: systemd
run:
  launcher: python
  program: central-context
expose:
  http:
    internal: { port: 9001 }
    health_path: /health
proxy: true   # expose at central-context.<gateway.domain>
manage:
  systemd: {}

# deployments/backup-collect.yaml — manager: systemd + schedule → kind: job
program: backup-collect
manager: systemd
run:
  launcher: command
  argv: [backup-collect]
schedule: "0 2 * * *"
manage:
  systemd: {}

Programs define what software exists (identity, source, build). Deployments define how a program is realized on this node — a single manager-discriminated entry whose derived kind (service/job/tool/static/ reference) captures whether it's an always-on daemon, a scheduled task, a CLI on PATH, a served frontend, or an external reference.

A deployment can reference a program via program: for description fallthrough and source code linking. It can also exist independently (e.g., wildpc-gateway runs Caddy — not our software).

A service's env is exactly its defaults.env — wildpc injects nothing implicitly. Values may use ${port}/${data_dir}/${name}/${secret:…} placeholders, which deploy resolves into the registry's flat env.

$WILDPC_HOME/artifacts/specs/registry.yaml (per-node, not in the repo, generated by wildpc apply) — Node config:

node:
  hostname: tower
  wildpc_root: /data/repos/wildpc
  gateway_port: 9000
deployed:
  central-context:
    manager: systemd
    launcher: python
    run_cmd: [/home/user/.local/bin/central-context]
    env:
      CENTRAL_CONTEXT_DATA_DIR: /home/user/.wildpc/data/central-context
      CENTRAL_CONTEXT_PORT: "9001"
    kind: service
    stack: python-fastapi
    port: 9001
    health_path: /health
    subdomain: central-context
    managed: true

The node config says what's deployed here and with what concrete values. wildpc apply reads the spec from the repo, resolves the defaults.env placeholders and secrets, resolves binary paths, and writes the registry. Systemd units and Caddyfile are then generated from the registry — never from the spec directly.

This separation means:

• The repo is just a repo. git pull doesn't affect running services.
• Multi-node works: sync the spec + deploy on each node, no repo needed.
• The spec is portable and version-controlled. The node config is local.
• AI agents read the node registry to know what's deployed and running.

Interfaces

Three interfaces expose the registry:

• CLI (wildpc) — For AI agents and terminal users. Structured output via --json. Commands for listing, inspecting, creating, and managing programs.
• API (wildpc-api) — For programmatic access over HTTP. Used by the dashboard, other nodes, and remote agents.
• Dashboard (wildpc) — For human discoverability. Visual overview of what's running, health status, logs.

Coordination Layer

Coordination handles discovery and communication — both between programs on a single node and across multiple Wild PC nodes.

Intra-node coordination:

• Programs find each other through the gateway or direct port access via env vars. A gateway route maps a host address (<name>.<domain>) to a target of one kind: proxy (a local service port), remote (a service on another node), or static (a built frontend's dist/, served as files). The same computed route list drives the Caddyfile, wildpc gateway status, and the dashboard, so they always agree.
• The registry (CLI/API) provides discoverability.
• No service mesh or message broker required for basic operation.

Inter-node coordination:

• Each Wild PC node runs the API, which exposes its program registry.
• Nodes discover each other via MQTT retained messages and mDNS/DNS-SD (python-zeroconf) for LAN environments.
• The gateway on each node can proxy to services on other nodes via host-based routing (<service>.<domain> resolves to the local port or, via the remote registry, another node). Components don't know which node they're talking to.
• MQTT provides pub/sub messaging for events, status, and coordination across nodes.
• All mesh features are opt-in: WILDPC_API_MQTT_ENABLED=true and WILDPC_API_MDNS_ENABLED=true. Single-node works without them.

MQTT topics:

• wildpc/{hostname}/registry — retained JSON, full NodeRegistry. Published on connect and after wildpc apply.
• wildpc/{hostname}/status — "online" (retained) / "offline" (LWT). LWT ensures nodes are marked offline if they disconnect unexpectedly.

MeshStateManager (wildpc_api.mesh) holds remote NodeRegistry instances in memory, indexed by hostname. 5-minute staleness TTL. Updated by the MQTT client on incoming messages. Read by API endpoints to serve cross-node data.

mDNS (wildpc_api.mdns) advertises _wildpc._tcp and browses for peers and _mqtt._tcp broker. Uses python-zeroconf. Properties include hostname, gateway_port, api_port.

Caddyfile generation supports remote_registries — cross-node routes are added with reverse_proxy {hostname}:{port} entries. Local paths always take precedence.

Why MQTT over custom gossip:

• Standard protocol, every language has a client library.
• Retained messages give new nodes an immediate view of the network.
• Topic-based routing maps naturally to wildpc/{node}/{program}.
• Works across networks (not just LAN like mDNS).
• Mosquitto is a single binary, simple to run as a Wild PC program.

Why mDNS/DNS-SD as a complement:

• Zero-config LAN discovery via python-zeroconf.
• Each node advertises _wildpc._tcp — standard tooling works (avahi-browse, dns-sd).
• Good for bootstrapping: find the MQTT broker without hardcoding its address.

Dashboard

The web dashboard (wildpc) is a React SPA served by Caddy in place from its repo build output (<source>/dist/) at the root /. It talks to wildpc-api via the gateway proxy at /api.

Layout:

Wild PC
Personal software platform

[tower] [devbox (3)]               ← NodeBar (hidden in single-node)

┌─────────────────────────────────────────────────────────┐
│ Gateway · tower · port 9000 · 4 routes    [Reload] [Caddyfile] │
│                                                         │
│ Path              Component           Port  Node  Health│
│ /api              wildpc-api          9020  tower  ● up │
│ /central-context  central-context     9001  tower  ● up │
│ /notifications    notification-bridge 9002  tower  ● up │
│ /devbox-api       devbox-api          9020  devbox ● up │
└─────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────┐
│ Mesh  ● connected     mqtt://localhost:1883   0 peers   │
└─────────────────────────────────────────────────────────┘

Daemons · Long-running processes that expose ports
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ wildpc-api   │ │ central-ctx  │ │ notif-bridge │
│ ● up 5ms     │ │ ● up 12ms    │ │ ● up 8ms     │
│ :9020        │ │ :9001        │ │ :9002        │
└──────────────┘ └──────────────┘ └──────────────┘

Components · Software catalog
  Name             Stack            Kind      Schedule     Status
  pdf2md           Python / CLI     tool      —            installed
  protonmail       Python / CLI     tool      */5 * * * *  installed
  wildpc       React / Vite     static    —            —
  backup-collect   Python / CLI     job       0 2 * * *    —

Key programs:

• GatewayPanel — Route table with live health badges, reload button, collapsible Caddyfile viewer. Node column appears when multi-node.
• MeshPanel — MQTT connection status (connected/disconnected badge), broker address, mDNS status, peer count with links. Hidden when mesh is disabled.
• NodeBar — Horizontal list of discovered nodes. Hidden in single-node mode. Each node links to /node/{hostname}.
• ServiceSection — Daemon cards in a responsive grid.
• ComponentTable — Unified sortable table for all non-daemon deployments (tools, statics) with Stack, Kind, Schedule, and Status columns.

Real-time updates:

• SSE stream at /stream pushes health, service-action, and mesh events. React Query caches are updated or invalidated on each event.
• Health polling runs every 10s server-side; SSE delivers updates to all connected dashboard clients.

Multi-node behavior:

• NodeBar appears when GET /nodes returns >1 node.
• GatewayPanel shows a "Node" column when routes span multiple nodes.
• /node/{hostname} page shows a specific node's deployed programs.

Component Contract

Every Wild PC program, regardless of language, must satisfy a minimal contract. This is what makes the system uniform above the build line.

Services (long-running daemons)

Requirement	Mechanism
Accept configuration	Env vars (prefixed by service name)
Declare its port	Env var, registered in expose.http.internal.port
Health endpoint	GET /health returns 200
Data storage	Read *_DATA_DIR env var, write there
Logging	stdout for output, stderr for errors
Graceful shutdown	Handle SIGTERM, exit cleanly
Secrets	Read from env vars (Wild PC resolves ${secret:NAME})
No Wild PC dependency	Must run standalone with just env vars set

Tools (CLI utilities)

Requirement	Mechanism
Input	File argument or stdin
Output	stdout (pipeable)
Errors/status	stderr
Exit codes	0 success, non-zero failure
No interactive prompts	Scriptable by default

Jobs (scheduled tasks)

Same contract as tools, plus:

Requirement	Mechanism
Idempotent	Safe to re-run or run concurrently
Short-lived	Exit when done (oneshot systemd unit)

Component Lifecycle

The path from source to managed process is two moves — develop (against the program) and converge (wildpc apply):

source → [dev verbs: build/test/…] → config (programs/ + deployments/) → [wildpc apply] → running

• Develop — language-specific dev verbs (build, test, …) that Wild PC records but never runs implicitly. Frontends build in place under the repo (<source>/<dist>/), served from there — no copy step.
• Converge — wildpc apply reads the config, generates systemd units + Caddyfile entries, then reconciles reality to the desired state: activate what's enabled, restart what changed, deactivate what's disabled. Activation is polymorphic over the manager — systemd enable --now, uv tool install for a tool on PATH, a gateway route for a static — so there is no separate install or start step, and no per-kind verb. wildpc apply --plan shows the diff first.

Desired on/off is enabled on the deployment; the only way to durably stop something is enabled: false + apply. wildpc restart is the one imperative bounce that re-actualizes current state without changing it.

Runtime Filesystem Layout

Two roots, each overridable by an env var: $WILDPC_HOME (config, artifacts, secrets; default ~/.wildpc) and $WILDPC_DATA_DIR (bulk program data; default /data/wildpc, on a dedicated volume). Program source lives separately under /data/repos/<name>/ ($WILDPC_REPOS_DIR).

$WILDPC_HOME/                   ← Config & artifacts (default ~/.wildpc)
├── wildpc.yaml                 ← Global settings (gateway, repo, agents)
├── programs/  deployments/     ← One YAML file per program / deployment
├── infra.conf                  ← Infrastructure install choices
├── artifacts/specs/            ← Generated by `wildpc apply`
│   ├── Caddyfile
│   └── registry.yaml           ← Node config (what's deployed here)
└── secrets/                    ← Secret files (NAME → value)

/data/repos/<name>/             ← Program source (your programs; absolute source:)
$WILDPC_DATA_DIR/<name>/        ← Persistent service data (default /data/wildpc)
~/.config/systemd/user/         ← Systemd units + timers (wildpc-*.service/.timer)

Compiled-language tools (Rust, Go — planned) install their binaries to the standard ~/.local/bin/. Source is referenced only by dev verbs and while a deployment is materialized; everything the runtime touches lives under $WILDPC_HOME, $WILDPC_DATA_DIR, or standard systemd paths.

OTP as Design Guide

Wild PC's architecture parallels Erlang/OTP, mapped onto Unix:

OTP Concept	Wild PC Equivalent
Application	Component (independent, self-contained)
Application resource file	Component spec in wildpc.yaml
Release config (sys.config)	Node config in $WILDPC_HOME/artifacts/specs/registry.yaml
Release assembly	wildpc apply (spec + node config → runtime)
Supervisor	systemd (restart policies, ordering)
Process	Running service/worker/job
Application env	Env vars
Node	A machine running Wild PC
epmd	mDNS / MQTT discovery
Distribution	Inter-node coordination via MQTT + gateway proxying
"Let it crash"	restart: on-failure in systemd
Global registry	Merged node registries via MQTT retained messages

The mapping is conceptual, not literal. Wild PC doesn't implement OTP semantics — it uses OTP's thinking to guide which Unix primitives to compose and how.

Key OTP ideas that apply:

• Isolation. Components don't share state. Communication is through explicit interfaces (HTTP, MQTT, filesystem paths).
• Let it crash. Services don't need elaborate error recovery. systemd restarts them. Design for restartability, not immortality.
• Supervision hierarchy. systemd's dependency ordering provides this. Services declare what they need to start after.
• Location transparency. Components talk to paths (/api, /central-context), not to specific hosts or ports. The gateway can remap these across nodes.
• Spec vs. config. In OTP, an application defines its structure (the .app file) and a release provides the deployment config (sys.config). Wild PC mirrors this: the program spec defines structure, the node config provides deployment values.

Current State

What exists today:

• CLI — wildpc command, installed via uv tool install --editable cli/

• Three packages — wildpc-core (models, config, generators), wildpc-cli (commands), wildpc-api (HTTP API)

• Source/runtime split — wildpc.yaml (spec) → wildpc apply → $WILDPC_HOME/artifacts/specs/registry.yaml (node config). Systemd units and Caddyfile generated from registry with fully resolved paths. No repo references in runtime artifacts.

• Explicit env with placeholders — a deployment's env is exactly its defaults.env; wildpc apply resolves ${port}/${data_dir}/${name}/ ${secret:…} into concrete values. No hidden convention injection.

• Gateway — Caddy on port 9000, Caddyfile generated from registry

• API — wildpc-api on port 9020, reads from registry (optional wildpc.yaml fallback for non-deployed programs)

• Dashboard — wildpc React/Vite frontend, static assets served in place from its repo build output (<source>/dist/)

• Services — central-context (content storage), notification-bridge (desktop notification forwarder)

• Jobs — protonmail (email sync every 5 min), backup-collect (nightly), backup-data (nightly restic backup)

• Tools — ~15 CLI utilities (pdf2md, docx2md, search, gpt, etc.)

• Manifest — wildpc.yaml with typed Pydantic models

• Mesh infrastructure — MQTT client (paho-mqtt), mDNS discovery (python-zeroconf), MeshStateManager, all wired into API lifespan. Opt-in via WILDPC_API_MQTT_ENABLED / WILDPC_API_MDNS_ENABLED.

• MQTT broker — Mosquitto running as wildpc-mqtt Docker container on port 1883, managed by systemd. Config and data in $WILDPC_DATA_DIR/wildpc-mqtt/.

• Node API — GET /mesh/status, GET /nodes, GET /nodes/{hostname}. GET /deployments?include_remote=true for cross-node program listing.

• Gateway panel — Dedicated UI showing route table, health per route, reload button, Caddyfile viewer. Cross-node routes shown when multi-node.

• Mesh panel — Dashboard UI showing MQTT connection status, broker address, mDNS state, peer count. Hidden when mesh is disabled.

• Node-aware UI — NodeBar (hidden single-node), node detail page, mesh SSE events for live node discovery updates.

• Cross-node routing — Caddyfile generator accepts remote registries, generates reverse_proxy {hostname}:{port} entries.

What doesn't exist yet:

• Multi-language support — Rust and Go programs (the abstractions support them via the command launcher, but no examples exist yet)
• Build automation — Wild PC records build specs but doesn't orchestrate builds (each project builds independently)
• Multi-machine testing — Mesh infrastructure is built and running on one node, but not yet tested with a second Wild PC node

Technology Map

Concern	Technology	Status
Process supervision	systemd (user units)	Active
HTTP routing	Caddy (port 9000)	Active
Component specs	wildpc.yaml + Pydantic models	Active
Node config	$WILDPC_HOME/artifacts/specs/registry.yaml	Active
CLI	wildpc (Python, uv)	Active
API	wildpc-api (FastAPI)	Active
Dashboard	wildpc (React, Vite, shadcn/ui)	Active
Python packaging	uv	Active
Node packaging	pnpm	Active
Linting	ruff (Python), ESLint (TS)	Active
Type checking	pyright (Python), tsc (TS)	Active
Testing	pytest (Python), Vitest (TS)	Active
Secrets	~/.wildpc/secrets/ file-based	Active
Data storage	Filesystem ($WILDPC_DATA_DIR/, default /data/wildpc/)	Active
Messaging	MQTT (paho-mqtt client, Mosquitto broker)	Active (opt-in)
Node discovery	mDNS (python-zeroconf) + MQTT	Active (opt-in)
Rust packaging	cargo	Planned
Go packaging	go build	Planned