#Custom setup help

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rose templeBOT
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gritty notchBOT
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Big buckets to think about with that architecture (Mac → Podman VM → Alpine container → OpenClaw, and Ollama serving models):

Performance / “will this be fast?”

  1. Metal acceleration vs Linux VM reality
  • On Apple Silicon, the fast path for local LLMs is usually native macOS + Metal.
  • If you run Ollama inside Podman on macOS, it’s typically inside a Linux VM, and you may lose Metal acceleration (or at least make it much harder). That can turn a “works great on an M3 Ultra” setup into “why is this crawling?”.

Pragmatic recommendation: run Ollama natively on macOS, and run OpenClaw wherever you like (host or container) connecting to Ollama over localhost/VM host bridge.

  1. Memory and context length
  • RAM usage is not just “model weights”. KV cache scales with context length and concurrency.
  • If you crank context (e.g., 32k/64k) and run multiple requests in parallel, you can suddenly eat tens of GB in KV cache even when the weights are fine.

Plan for:

  • a conservative default context first (then increase),
  • low parallelism until you’ve measured,
  • and watch swap/pressure (macOS memory pressure is your friend here).
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  1. Podman machine resource caps
  • Podman on macOS runs a VM with explicit CPU/RAM limits. Even if your Mac has ~256GB RAM, the VM might have far less unless you configured it.
  • If you insist on “everything inside Podman”, make sure the Podman VM has enough memory allocated, otherwise you’ll hit weird OOM/perf cliffs.
  1. Alpine (musl) friction
  • Alpine can be great, but Node/native deps sometimes assume glibc and can cause extra build pain (or subtle runtime issues).
  • If you want “it just works”, a Debian/Ubuntu slim base is often lower drama for Node apps.

Security / “what’s the blast radius if something goes wrong?”

  1. Don’t expose Ollama or the Gateway broadly
  • Treat Ollama as an internal service. Bind it to localhost / private interface only, and don’t publish it to your LAN unless you really mean to.
  • Same for the OpenClaw gateway/control endpoints: keep them local, and use a gateway token/password.
  1. Container hardening basics
    If running OpenClaw in a container:
  • Rootless Podman (preferable).
  • Drop Linux capabilities, no --privileged, no host PID namespace.
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  • Read-only filesystem where feasible; mount only what you need.
  • Be careful with volume mounts: don’t mount your whole home directory into the container.
  1. Secrets
  • API keys / tokens: avoid baking into images.
  • Prefer runtime env vars / secret files with tight permissions.
  • Assume anything inside the container can be read by processes in that container.
  1. Network egress
  • Decide whether OpenClaw should have general outbound internet access. If you’re using it purely locally, restricting egress reduces risk.
  • If you do want web/tools, you’ll need outbound access—just be explicit about it.

Reliability (OpenClaw-specific gotchas with local models)

  • Many local/ollama-served models can be flaky at tool-calling / structured JSON (browser tool, message tool, etc.). You may see stalls, malformed tool calls, or “wandering”.
  • A common pattern is: use local models for “drafting/summarizing”, but keep a tool-reliable cloud model available for “do the actual tool-running”.

(If you want, ask in the server’s #models channel—people will have the most current “this model works/doesn’t for tool calls” experience.)

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A sane architecture that usually works well

  • Ollama on macOS (Metal) for best perf.
  • OpenClaw either:
    • on macOS directly, or
    • in Podman (container/VM), connecting to Ollama via the host bridge.
  • Keep both services bound to local/private interfaces; require a gateway token.

Quick clarifying questions (to tailor advice)

  1. When you wrote “265 mb” do you mean ~256GB RAM?
  2. Do you need OpenClaw to use browser/web tools, or is this an offline/local-only agent?
  3. Are you okay running Ollama native on macOS (best perf), or is “everything in containers” a hard requirement?
lyric aurora
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ollama will be on the os and openslaw will be inside alpiune linux. Yes I ment 265gb unified ram.

gritty notchBOT
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Nice — that’s the best split for Apple Silicon perf (Ollama on macOS/Metal, OpenClaw containerized).

Performance concerns (with that split)

  1. Networking overhead (usually minor)
  • OpenClaw (in the Podman VM) will call Ollama (on macOS) over a virtualized network hop. It’s typically fine, but you want:
    • stable host address from the VM (see below),
    • keep-alive enabled (defaults are usually OK).
  1. Podman VM sizing
  • Even though Ollama is on macOS, OpenClaw + any tools (browser automation, indexing, etc.) still run in the Podman VM.
  • Make sure the Podman “machine” has enough RAM + CPU allocated, otherwise you’ll get random slowness/timeouts that look like “LLM is slow” but aren’t.
  1. Tool-calling reliability
  • Local models (including some very strong ones) can be inconsistent at strict JSON/tool calling. If you hit weird behavior (tools not invoked, malformed args), it’s probably the model, not your infra.
  • Keep a fallback “tool-reliable” model around for workflows that heavily use browser/tools.

Security concerns

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  1. Bind Ollama to localhost
  • On macOS, make sure Ollama is only listening on 127.0.0.1 (or at least not on 0.0.0.0), unless you intend LAN access.
  • If you must expose it to the Podman VM, prefer a host-only/VM-only route rather than LAN-wide exposure.
  1. How the container reaches the host
  • Avoid opening Ollama to your whole network just so the Podman VM can see it.
  • Prefer Podman’s host aliasing (often something like host.containers.internal) from inside the container/VM.
  1. Gateway access
  • Don’t expose OpenClaw’s gateway/dashboard beyond localhost unless you’re protecting it (gateway token/password) and you actually need remote access.
  1. Container hardening
  • Rootless Podman, no --privileged, minimal volume mounts, don’t mount your whole $HOME.
  • Alpine is fine, just be aware it can increase “dependency friction”; security-wise it’s not automatically safer, it’s just smaller.

Practical connectivity checklist

From inside the OpenClaw container, you want curl http://host.containers.internal:11434/api/tags (or equivalent) to work.

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If that hostname doesn’t resolve in your setup, the fix is Podman-networking-specific; the goal is: container → Podman VM → macOS host → Ollama without binding Ollama to your LAN.

One more “gotcha” on macOS

If you later enable browser automation (Chromium) inside the Linux container, it can be heavier than expected. If performance gets weird, consider running browser tooling on the host instead, or use a remote browser.

Quick questions so I can be concrete

  1. Are you using Podman Desktop with a Podman “machine”, or a custom VM?
  2. Do you already have a working hostname/IP from the container to the macOS host (e.g. host.containers.internal)?
  3. Will OpenClaw need browser tool usage, or mostly chat + local tools?
lyric aurora
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I'll want cromium what pod stats should I be aiming at?

gritty notchBOT
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If Ollama is staying on macOS, the Podman VM only needs to cover OpenClaw + Chromium (and whatever other tools you run). In that case you’re sizing mostly for headless browser memory + CPU, not model weights.

Targets to aim for (good starting points)

Baseline (single-browser / light concurrency)

  • CPU: 6–8 vCPU
  • RAM: 12–16 GB
  • Disk: 30–60 GB (Chromium deps + caches + logs + session files)

Comfortable (multiple pages / more agent activity)

  • CPU: 8–12 vCPU
  • RAM: 24–32 GB
  • Disk: 60–100 GB

With 256GB unified RAM you can go higher, but you usually won’t see wins past ~12 vCPU for “one agent driving a browser”; the bigger win is giving it enough RAM to avoid memory pressure in the VM.

Chromium-specific gotchas inside containers

  1. /dev/shm size
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  • Headless Chromium really wants a decent shared memory segment. Small /dev/shm causes crashes/hangs/weird slowness.
  • If you can, run the OpenClaw container with something like --shm-size=1g (often 2g if you’ll open heavy web apps / multiple tabs).
  1. Per-tab memory
  • Rough heuristic: ~300MB–1.5GB per active Chromium instance/tab, depending on the site (Gmail/Notion/etc. can be huge).
  • If you expect 3–5 “heavy” pages at once, that’s why I suggest 24–32GB RAM for the Podman machine.
  1. CPU spikes
  • Page loads + JS-heavy sites will spike CPU. If the VM is limited to 2–4 cores, everything feels “laggy” even though the LLM is fast.

How to choose your final numbers

  • Decide your max concurrent browser pages (1? 3? 10?).
  • Start with 8 vCPU / 24GB RAM / 60GB disk.
  • Run a realistic workload and watch:
    • podman stats (container memory/CPU)
    • Podman VM memory pressure (if the VM starts swapping, bump RAM)
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If you tell me roughly how many simultaneous pages/tabs you expect OpenClaw to drive (and whether it’ll do screenshots/video, scraping, etc.), I can give a tighter recommendation.

lyric aurora
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I'm loading large local models that are just squeezing to my available ram. I think the amounts you are recommending are good. I truly have no idea but don't think I will turn into a large crawler.

gritty notchBOT
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Makes sense — if your models are already right at the edge of unified RAM, the biggest risk is accidentally “reserving” too much memory for the Podman VM, and then Ollama starts failing / evicting / slowing because the host can’t breathe.

Key point (Podman on macOS)

Podman runs a Linux VM with a fixed memory allocation. That allocation effectively comes out of the same pool your models need. So don’t oversize it “just because you have 256GB” if the models are already squeezing.

A good starting Podman VM size in your situation

Since Ollama stays on macOS, aim for just enough for OpenClaw + one headless Chromium:

  • CPU: 6–8 vCPU
  • RAM: 10–16 GB (I’d start at 12–14 GB)
  • Disk: 60 GB

That typically covers:

  • OpenClaw (small),
  • Chromium (the real hog),
  • some headroom for spikes.
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If you notice Chromium-heavy sites (Notion, Google apps, etc.) or multiple tabs/pages, bump to 16–24GB only if needed.

Chromium stability knobs (important in containers)

  • Set shared memory: --shm-size=1g (2g if you see crashes / “Target closed” / weird hangs)
  • Keep concurrency low (1 browser instance / a couple tabs) since you’re not crawling.

If RAM gets too tight anyway

Two escape hatches that keep your “models squeeze” working:

  1. Run OpenClaw on macOS (skip the VM overhead entirely), keep Ollama on macOS.
  2. Keep OpenClaw in the container, but run the “real browser” on the host (e.g., via the Chrome relay approach) so the VM doesn’t pay the Chromium tax.

If you tell me whether you expect “one page at a time” vs “multiple tabs + long-running sessions”, I can suggest the lowest VM RAM that won’t be annoying.

lyric aurora
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I'll resize as needed lets talk network setup. Whats the best way to configure ollama to be available to the vm and the vm to have internet access. Also there was talk of a token. A token to what?

gritty notchBOT
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You’ve basically got two separate networking problems here:

  1. OpenClaw (in the Podman VM) → Ollama (on macOS)
  2. Your browser / Control UI (on macOS) → OpenClaw Gateway (in the container/VM)

1) Making Ollama reachable from the Podman VM (best practice)

Goal: don’t accidentally expose Ollama to your whole LAN, but still let the VM reach it.

Option A (simplest, common): bind Ollama to a non-loopback addr + firewall it

  • By default, Ollama usually binds to 127.0.0.1, which the VM can’t reach.
  • So you bind Ollama to something reachable (often 0.0.0.0:11434), then use a firewall rule to only allow connections from the Podman VM network.

How to validate connectivity from inside the container/VM:

  • From inside the OpenClaw container, try one of these:
    • curl http://host.containers.internal:11434/api/tags
    • and/or (if you’re using the OpenAI-compat endpoint) curl http://host.containers.internal:11434/v1/models
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If host.containers.internal doesn’t resolve in your setup, the next-best is: find the macOS host’s reachable IP from within the VM (via podman machine ssh → check ip route, DNS, etc.) and use that.

Option B (tightest security): keep Ollama on 127.0.0.1 and tunnel

If you’re willing to enable SSH on macOS, you can keep Ollama strictly on loopback and create an SSH tunnel from the VM/container to the host. That way Ollama never listens on any “real” interface. More moving parts, but very clean from a security standpoint.

2) VM/container internet access

Podman on macOS normally gives the VM NAT’ed outbound internet by default. So the VM + containers usually “just have internet” without you doing anything special.

Quick test:

  • podman machine ssh then curl https://example.com
  • or run a throwaway container: podman run --rm alpine sh -c "apk add -q curl && curl -I https://example.com"

If that fails, it’s usually DNS/proxy/corp-network related rather than an OpenClaw thing.

“Token” = token to what?

That token is OpenClaw Gateway auth, not Ollama.

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  • The Gateway exposes a control plane (WebSocket + HTTP APIs + Control UI hooks).
  • By default, auth is required: gateway.auth.token (or env OPENCLAW_GATEWAY_TOKEN) or password.
  • It’s what your Control UI / clients send when connecting to the Gateway.

Docs:

If you tell me whether host.containers.internal resolves for you inside the OpenClaw container, I can give you the most direct “set baseUrl to X, bind Ollama to Y” wiring for your exact setup.

lyric aurora
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I'll just enable ssh. Thats no issue. I'll set it up to be keyfile only then put the key in the pod. So for the token I generate the token and keep it on the server. Then use that token for clients to connect?

gritty notchBOT
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Yep — Gateway token = shared secret for OpenClaw’s Gateway, and clients need it.

What the token is for

The Gateway (the long-running openclaw gateway process) exposes a WebSocket + HTTP control plane. When gateway.auth.mode: "token" (default-ish), it requires a bearer token:

  • Server-side (on the machine/container running the Gateway):
    • gateway.auth.token (or env OPENCLAW_GATEWAY_TOKEN)
  • Client-side (anything connecting to that Gateway):
    • Control UI, macOS app, CLI in “remote” mode, nodes, etc. must supply that same token.

Docs: https://docs.openclaw.ai/gateway (see auth note) and https://docs.openclaw.ai/gateway/network-model

Generating / setting it

  • openclaw doctor --generate-gateway-token (note: only generates if missing; to rotate you set a new one explicitly)
  • Or set gateway.auth.token yourself, then restart the gateway.

After that, copy the token to clients that need to connect (treat it like a password).

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Also: even if you connect over an SSH tunnel, clients still must send the token. (Docs: https://docs.openclaw.ai/gateway/remote)

Don’t confuse these two

  • gateway.auth.token = protects the Gateway itself (server auth).
  • gateway.remote.token = just a client convenience setting for the CLI when you run the CLI in “remote gateway” mode; it doesn’t enable auth by itself. (It’s basically “store the token on the client so the CLI can use it”.)

Practical tip for your Podman VM setup

To avoid exposing the Gateway to your LAN, publish/forward it to host loopback only (so your macOS Control UI connects to ws://127.0.0.1:18789 + token), rather than binding it to 0.0.0.0.

If you want, paste how you’re starting the container (podman run / compose) and I’ll point out the cleanest “bind to localhost only” port mapping for macOS Podman.

lyric aurora
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podman machine init --cpus 6 --memory 14336 --disk-size 60

gritty notchBOT
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That Podman machine sizing looks sane for “OpenClaw + headless Chromium” while keeping most RAM available for Ollama/models on macOS:

podman machine init --cpus 6 --memory 14336 --disk-size 60
podman machine start

Recommended network setup (clean + secure)

Since you’re OK with SSH: keep Ollama bound to 127.0.0.1:11434 on macOS, and let the VM/container reach it via an SSH local-forward. That way Ollama is never exposed to LAN.

Inside the VM or inside the OpenClaw container, create a tunnel to the mac host:

ssh -N \
  -o ExitOnForwardFailure=yes \
  -o ServerAliveInterval=30 \
  -L 11434:127.0.0.1:11434 \
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  <mac_user>@host.containers.internal

Then from OpenClaw, you point your “local model provider baseUrl” at:

  • http://127.0.0.1:11434/v1 (if using Ollama’s OpenAI-compatible endpoint)
  • (verify with curl http://127.0.0.1:11434/v1/models or .../api/tags)

Why host.containers.internal? In many Podman-on-mac setups that resolves from containers to the mac host. If it doesn’t resolve for you, run in a test container:

podman run --rm alpine getent hosts host.containers.internal

…and use the IP you get (or the mac’s host-only IP visible from the VM).

VM internet access

Podman machine should have outbound internet via NAT by default. Quick test: