If you search for an OpenHuman install guide in 2026, you will still hit outdated git clone + pip install -r requirements.txt tutorials. Those flows describe generic digital-human repo templates, not the tinyhumans desktop UI Agent that ships signed installers today. This guide is for beginners and developers who want OpenHuman from download through login, Gmail or Slack connection, the first ~20-minute ingest cycle, a usable Memory Tree, and optional Ollama local inference on macOS, Windows, or Linux. We start with six common misjudgments, then cover environment tables, signed-package install paths, an eight-step runbook, and a troubleshooting matrix. If you also plan to pair OpenHuman with OpenClaw on dedicated hardware, read our sibling article on renting a Mac for OpenClaw and OpenHuman. Monthly pricing is on the NOVAKVM pricing page; order flow on the order page. Commands and version numbers below follow tinyhumans official docs and GitHub Releases; re-open those links after each upstream release.
[ SECTION_01 ] // PAIN_MAP Six misconceptions when installing OpenHuman (2026)
- "You must git clone and pip install first": The primary path is a desktop installer or system package manager (Homebrew, signed APT repo, signed MSI), not a hand-built Python environment from a random fork.
- "No NVIDIA GPU means it won't run": OpenHuman defaults to a hosted model route; sensitive steps can optionally use Ollama on CPU or Apple Silicon. CUDA training rigs are not a prerequisite.
- "Briefing should be rich right after install": Official Getting Started states that after you connect a data source, the first automatic pull triggers in about twenty minutes. Testing memory quality before that window ends often looks like a broken install when it is just early timing.
- "Everything lives in the cloud": The Memory Tree database, Markdown vault, and workspace config stay on disk locally. Sign-in, some OAuth flows, and model routing may still touch OpenHuman hosted services—know which boundary you are crossing.
- "curl | bash is the same as Homebrew": The README notes install scripts are served from
raw.githubusercontent.comwith no separate signature check. Production setups should prefer signed native packages. - "A sleeping laptop is fine for production ingest": Large mailboxes and code repos consume RAM and SSD; lid-close sleep interrupts background pulls. "App opens" and "ingest runs 24/7" are different success criteria.
The following are OpenHuman official entry points. Re-open them after each release to confirm installer URLs and system requirements.
OpenHuman download page (tinyhumans.ai)
OpenHuman Getting Started (GitBook)
tinyhumansai/openhuman (GitHub repo and Releases)
[ SECTION_02 ] // ENV_MATRIX OpenHuman environment requirements: minimum specs and where to run
The table below summarizes practical desktop-client floors. If you run Ollama on the same machine or ingest a large Gmail archive, plan against the recommended column. Dollar amounts and stock levels are not listed here—check the pricing page for current tiers.
| Item | Minimum | Recommended (large mailbox + optional local model) |
|---|---|---|
| Operating system | macOS / Windows / Linux desktop builds per official download page | macOS 14+ on Apple Silicon or Ubuntu 24.04 LTS desktop |
| Memory | Official docs cite 4 GB+ | 16 GB+; very large Gmail or repo sync plus co-located Ollama may need 24–32 GB |
| Disk | A few GB free | Fast SSD; vault plus SQLite ingest grows with mailbox size |
| GPU | Not required (hosted route) | Apple Silicon unified memory helps local inference; CPU-only Ollama paths exist |
| Network | Reachable sign-in and integration OAuth | Stable egress; first ingest and ~20-minute background cycles need sustained uptime |
| Host | Install friction | Background ingest | Typical issue |
|---|---|---|---|
| Personal MacBook | Low (Homebrew / DMG) | Stops when lid closes; fine for trials | Personal mail and agent memory on one disk |
| Headless Linux VPS | High (not the official primary path) | No native GUI or desktop integrations | Screen context, voice, and OS-level hooks limited |
| NOVAKVM monthly Mac Mini M4 | Low (same macOS primary path) | Dedicated bare metal online 7×24 | Plan vault backup and wipe-before-return |
Only validating UI and one prompt? A laptop is enough. To keep Memory Tree ingest running for weeks, put the app on a production Mac that never sleeps.
[ SECTION_03 ] // INSTALL OpenHuman install by platform: signed packages first, scripts as fallback
macOS (Homebrew recommended — uses the system package signature chain):
brew tap tinyhumansai/core
brew install openhumanLinux (Debian/Ubuntu signed APT repo — architecture per official repo): Import the GPG key and add the sources.list.d entry, then run apt-get install openhuman. The full command sequence lives in the GitHub README section "Linux (Debian/Ubuntu — signed apt repo)"; re-check URLs after each release.
Windows: Download the signed .msi from GitHub Releases or the official download page and run the installer.
Universal installers: Releases also ship .dmg, .deb, and .AppImage artifacts. If you must use a script, macOS/Linux and Windows install scripts exist, but the README marks them as live scripts without a separate integrity signature—higher risk than native packages.
curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bashAfter installation, launch the desktop app once and confirm the OpenHuman icon appears in the Dock or Start menu. Do not skip login and data-source connection at this stage.
[ SECTION_04 ] // RUNBOOK Eight steps to a working OpenHuman: login, sources, first prompt, local AI
- Download and install: Prefer Homebrew, APT, or MSI; launch the app and confirm the build matches the Releases page.
- Sign in: The first screen is Sign in; most users use social login. Advanced panel accepts a custom core RPC URL for self-hosted backends—ignore unless you run one.
- Understand local vs hosted boundaries: Memory Tree, vault, and workspace stay local; default sign-in, model routing, integration OAuth, and search proxy use hosted services unless you follow Custom setup docs.
- Connect at least one data source: Use the settings wizard to OAuth Gmail, Slack, or similar. If authorization fails, check system clock and browser callback URLs.
- Wait for the first ingest cycle: Official docs say the first automatic pull triggers about twenty minutes after connection. UI works immediately; Briefing-style answers may still feel empty.
- Send a smoke-test prompt: After ingest, try something like "summarize themes from my email last week" to confirm Memory Tree has context.
- Optional: enable Ollama local AI: Turn on the local runtime in settings if your build exposes it. Co-located models need 16 GB+ RAM; watch SSD growth.
- Back up the vault directory: Before migrating machines or ending a rental, copy the SQLite Memory Tree and Obsidian-compatible
.mdvault—reinstalling the app alone does not restore memory.
Memory Tree canonicalizes connected data into roughly 3k-token Markdown blocks, stores layered summaries in local SQLite, and mirrors an editable vault. That architecture differs from pure cloud chat products that reset every session. For long-running ingest on a remote Mac, SSH and session baselines are documented in the help center.
[ SECTION_05 ] // TROUBLESHOOT OpenHuman install and first-run errors: what to check
| Symptom | Likely cause | What to try |
|---|---|---|
| Followed a pip tutorial, no app icon | Wrong non-tinyhumans digital-human template | Switch to tinyhumans desktop install path and Releases |
| Signed in but no mail context | First ingest window not finished | Wait ~20 minutes, then retry prompts |
| Disk usage spikes quickly | Large mailbox plus dual vault write | Prune old connections, upgrade SSD, or move to 512 GB+ rental tier |
| Stutter after enabling Ollama | Model size vs available RAM | Use a smaller quantized model or move to 24–32 GB RAM |
| brew install openhuman fails | Missing tap or unsupported architecture | Verify brew tap line and Apple Silicon vs Intel package names in README |
Advanced: content briefing smoke test. After ingest completes, ask OpenHuman to draft a 30-second spoken script from a specific email thread. Export or edit Markdown blocks directly in the vault. Real-time Meet participation, mascot lip-sync, and similar demo features depend on the current Releases notes—do not assume every marketing clip maps to your build.
[ SECTION_06 ] // HARD_FACTS Citable technical facts and NOVAKVM close
- License and repository: OpenHuman is published on GitHub under GNU GPL-3.0 at
tinyhumansai/openhuman. (Source: repo LICENSE; re-verify after releases.) - System requirements: Getting Started lists macOS, Windows, and Linux desktop support with 4 GB+ RAM; large mailboxes, large repos, or co-located local models suggest 16 GB+.
- Memory architecture: Memory Tree+ canonicalizes data into ≤3k-token Markdown blocks, stores layered summaries in SQLite, and lands an Obsidian-compatible vault. (Source: project README feature section.)
- Integration timing: After connecting Gmail or similar, the first automatic pull triggers in about twenty minutes; subsequent background cadence follows GitBook.
- Version truth: Treat GitHub Releases and the in-app About screen as authoritative; ignore uncited star counts or benchmark rankings from secondary posts.
Treating "installed" as done is premature. A personal laptop works for weekend experiments, but sleep, OS updates, and personal mail on the same disk interrupt Memory Tree ingest constantly. A headless Linux VPS rarely delivers the desktop integrations OpenHuman emphasizes. If local trials prove the product worth keeping, a practical production path is to rent a dedicated Mac Mini M4 for 2–4 weeks, observe vault growth and ingest stability, then decide whether to buy hardware.
Pick memory and disk tiers on the NOVAKVM pricing page, provision a node from the order page, and walk through the eight steps above. For OpenHuman production workloads that need the native macOS install path, large-mailbox ingest online 7×24, and predictable wipe-before-return, NOVAKVM Mac Mini bare-metal cloud rental usually beats leaving a daily-driver laptop awake indefinitely.