da5fe9260b fix(local_ai): hard-override to disabled until explicit opt-in (#573) (#637)
* refactor(local_ai): default to opt-in on all devices (#573)

Local AI now defaults to disabled whenever the user has not explicitly
picked a tier, regardless of device RAM. The onboarding flow and
Settings panel remain the only ways to turn it on. Previously the
bootstrap only disabled local AI on <8 GB devices and auto-applied a
recommended preset on larger hosts; this flip completes the MVP goal
of cloud-first defaults with a single, opt-in local model.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* style(local_ai): apply cargo fmt to bootstrap tests (#573)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(onboarding): present cloud AI as default on sufficient-RAM path (#573)

Flips the LocalAIStep sufficient-RAM screen so the primary button is
"Continue with Cloud" and local AI appears as an explicit opt-in
("Use local AI instead"). This aligns onboarding with the new opt-in
bootstrap: every device now starts on cloud unless the user chooses
local AI. The low-RAM cloud-fallback screen is unchanged.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* test(onboarding): cover opt-in local AI semantics in LocalAIStep (#573)

Updates the sufficient-RAM path tests to match the cloud-primary UI:
the default "Continue with Cloud" click advances without triggering
local AI bootstrap, and the secondary "Use local AI instead" opt-in
still starts the recommended-preset bootstrap and propagates errors.
Low-RAM cloud-fallback tests are unchanged.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* feat(local_ai): add opt_in_confirmed marker to local AI config (#573)

Bootstrap will hard-override `enabled=false` unless this marker is true,
ensuring existing installs with a stale `selected_tier` from the pre-MVP
default-on era fall back to cloud until the user explicitly re-opts in.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* fix(local_ai): hard-override local AI to disabled until explicit opt-in (#573)

Every bootstrap path now returns `enabled=false` unless `opt_in_confirmed`
is true, regardless of device RAM or `selected_tier`. This closes the
regression where upgrading users with a persisted `selected_tier` bypassed
the onboarding opt-in and started local AI without consent.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* refactor(local_ai): set opt_in_confirmed on apply_preset and surface MVP tier only (#573)

`apply_preset` is the single source of truth for the opt-in marker: any
non-disabled tier flips it true, `disabled` clears it. The preset RPC now
returns `mvp_presets()` so the Settings UI exposes only the allowlisted
`ram_2_4gb` tier, matching the MVP scope already enforced on the
onboarding path.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

* revert(local_ai): keep full preset catalog in presets RPC (#573)

Revert the `mvp_presets()` swap in `handle_local_ai_presets`. PR #588
already renders all 5 tier cards in Settings with non-MVP tiers shown
as "Coming soon" / non-selectable, and that roadmap visibility is the
intended UX. Returning only the MVP tier from the RPC hid the other 4
cards entirely and broke that signal.

The opt-in gate still holds: `apply_preset` remains the single writer
of `opt_in_confirmed`, the RPC guard continues to reject non-MVP
apply_preset calls, and the bootstrap hard-override still clamps
stale configs. This commit only rolls back the UI catalog surface.

Fixes failing `json_rpc_local_ai_device_profile_and_presets` integration
test which expects 5 presets.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-17 13:03:34 -07:00
2026-03-26 17:04:46 -07:00
2026-04-17 04:03:11 +00:00
2026-02-20 13:03:15 +04:00
2026-02-20 13:03:15 +04:00

OpenHuman

The age of super intelligence is here. OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.

DiscordRedditX/TwitterDocs

Early Beta Platforms: desktop only Latest Release

The Tet

"The Tet. What a brilliant machine" — Morgan Freeman as he reminisces about alien superintelligence in the movie Oblivion

Early Beta — Under active development. Expect rough edges.

To install or get started, either download from the website over at tinyhumans.ai/openhuman or run

# For MacOS/Linux
curl -fsSL https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.sh | bash

# For Windows
irm https://raw.githubusercontent.com/tinyhumansai/openhuman/main/scripts/install.ps1 | iex

What is OpenHuman?

OpenHuman is an open-source agentic assistant that is designed to integrate with you in your daily life. Here's what makes OpenHuman special:

  • Simple, UI-first — A clean desktop experience and short onboarding paths so you can go from install to a working agent in a few clicks, without a config-first setup. You don't need a terminal to run OpenHuman.

  • One subscription, many providers — You only need one account to get access to many agentic APIs (AI Models, Search, Webhooks/Tunnels and other 3rd party APIs etc..), simplifying the experience to get a powerful agent going.

  • Rich Skills — Plug into Gmail, Slack, Notion, and the rest of your stack via rich, feature-backed skills. Connections are typically one click through setup wizards instead of wiring APIs by hand. Workflow data is kept on device, encrypted locally, and treated as yours: encryption and sensitive context stay on your machine. Webhooks give instant feedback into the agent when external systems or skills emit events, so the loop stays tight without constant polling.

  • Local knowledge base — Built from your data and your activity. How you work across tools, sessions, and connected services—so the agent gets rich, workflow-aware context, not a one-off chat transcript. Everything is stored on your machine and compounding over time without becoming a cloud dossier. Channels, skills and ongoing conversations feed the same loop so day-to-day context does not reset every session.

  • Local AI model — The Rust core exposes local AI paths (and the desktop bundle can ship local/bundled runners where applicable) for the workloads above—vision snippets, speech helpers, summarization, tooling—so sensitive steps can stay off the cloud when you choose.

  • Deep desktop integrations — OpenHuman is a native desktop assistant, not a web-only chat: memory-aware keyboard autocomplete, voice (STT listening and TTS replies), screen intelligence that understands what is on screen and feeds your local context, plus windowing and OS-level permissions—so the agent meets you on the machine, not trapped in a browser tab.

Architecture: docs/ARCHITECTURE.md. Contributor orientation: CONTRIBUTING.md.

OpenHuman vs other agents

High-level comparison (products evolve—verify against each vendor). OpenHuman is built to minimize vendor sprawl, keep workflow knowledge on-device, and ship deep desktop features—not only chat.

Claude Code/Cowork OpenClaw Hermes Agent OpenHuman
Open-source: Is the codebase open to review? 🚫 Proprietary client MIT License MIT License GNU License
Simple: Is it simple to get started? Simple Desktop App + CLI ⚠️ Terminal first and often complex ⚠️ Terminal first and often complex Simple, Clean UI/UX. Get started within minutes
Cost: How expensive is to run? ⚠️ Subscription + add-on tool/API costs ⚠️ Tied to models & hosting you choose ⚠️ Tied to models & hosting you choose Cost optimized with the option to run many things locally for free
Memory & Knowledge Base (KB): Does the agent know you and your world? Built-in memory; mostly chat/session scoped ⚠️ Has a local memory but often needs plugins for richer behavior Self-learning / task loops (typical) 🚀 Local KB + Self-learning from your activity & data (GMail, Notion etc... via skills) & prompts
API spagetti: How complex is it to hook mulitple features together? 🚫 Claude bill + often extra keys for MCP/tools 🚫 BYOK / multi-vendor common 🚫 Multiple providers common One account get access to many bundled platform APIs
Extensibility: Can you add rich features into it? MCP (different model than sandboxed skills) Plugin Architecture (SKILL.md) Plugin Architecture (SKILL.md) 🚀 Rich Skills with ability to have realtime updates, local DB & more
Desktop integrations: Can it integrate into your desktop completely? ⚠️ Desktop app & access to folders ⚠️ Often lighter native surface ⚠️ Often lighter native surface STT, TTS, screen intelligence, memory-aware autocomplete and a whole lot more

Contributors Hall of Fame

Show some love and end up in the hall of fame

OpenHuman contributors
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