openhuman/gitbooks/developing/README.md

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Contributor-facing documentation for OpenHuman — how to build, test, ship, and extend the app and core.	code-branch

Overview

OpenHuman is open source under GNU GPL3 and lives at github.com/tinyhumansai/openhuman. This section is for contributors and people running OpenHuman from source.

Where things live

Path	What's there
app/	Yarn workspace openhuman-app — Vite + React frontend (app/src/) and the Tauri desktop host (app/src-tauri/).
src/	Rust crate openhuman_core and the openhuman CLI binary — domains, MCP routing, JSON-RPC.
docs/	Remaining deep developer reference (memory pipeline diagrams, telegram-login, sentry, agent flows, etc.).
gitbooks/	Public-facing documentation — this site.

The high-level shape lives in Architecture. The deep developer architecture lives in Architecture.

Start here

• Getting Set Up — building from source, toolchain, vendored Tauri CLI, sidecar staging.
• Testing Strategy — Vitest, cargo test, WDIO E2E. Where each test goes.
• E2E Testing — running end-to-end specs locally and in CI.
• Release Policy — release cadence, version policy, OAuth-and-installer rules.

Building features

• Skills — how skills are discovered, fetched, installed, initialized, executed and synced.
• Subconscious Loop — background task evaluation against the workspace.
• Conscious Loop — actionable-item extraction from the memory tree.
• Webview Integration — adding a new third-party webview-based integration.

Working with agents

• Coding Harness — the agent's code-focused tool surface and how to extend it.
• Agent Observability — the artifact-capture layer that makes E2E tests debuggable.

Other contributor docs

Anything not yet migrated lives under docs/ in the repo. Notable references:

• Architecture — canonical architecture.
• Memory Context Window — long-term memory injection presets.
• docs/PROMPT_INJECTION_GUARD.md — security model.
• Frontend chapter docs — React app structure (app/src/).
• Tauri shell chapter docs — desktop host (app/src-tauri/).

CLAUDE.md is the source of truth for AI agents working on the codebase, with the same rules contributors are expected to follow.