sanil-23andClaude Opus 4.7
8e55ddd71e
Phase 3a of the memory architecture (#711 umbrella). Lifts admitted leaves into a per-source hierarchy so Phase 4 retrieval has a tree to walk. ## What's in this PR * **Schema** — three new tables in `chunks.db` alongside Phase 1/2: `mem_tree_trees`, `mem_tree_summaries`, `mem_tree_buffers`. Plus a `parent_summary_id` backlink column on `mem_tree_chunks`. All migrations are additive and idempotent (`ALTER TABLE ADD COLUMN`, same pattern as Phase 2). * **`source_tree/` module** — isolated subdir; does not touch the legacy `openhuman::memory` layer. - `types.rs` — `Tree`, `SummaryNode`, `Buffer`, `TreeKind` (Source/Topic/Global), `TreeStatus`. Constants: `TOKEN_BUDGET = 10_000`, `DEFAULT_FLUSH_AGE_SECS = 7d`. - `store.rs` — CRUD for all three tables via the shared `with_connection` entry point. Writes are transactional; summary insert is idempotent on primary key (INSERT OR IGNORE). - `registry.rs` — `get_or_create_source_tree(scope)` — idempotent lookup keyed on `(kind, scope)`. - `bucket_seal.rs` — `append_leaf` + cascade: push a leaf into L0, seal when `token_sum >= TOKEN_BUDGET`, recurse upward. One seal = one transaction; children get a parent backlink (leaves via `parent_summary_id`, summaries via `parent_id`). Tree's `max_level` and `root_id` bump on root split. - `flush.rs` — `flush_stale_buffers(max_age)` force-seals any buffer whose `oldest_at` is older than `max_age`. Primitive only; wiring into a scheduler is out of scope. - `summariser/` — `Summariser` trait + `InertSummariser` fallback (concatenate children, union entities preserving first-seen order, hard-truncate to budget). Trait is async; Ollama implementation slots in later without breaking callers. * **Ingest wiring** — `tree/ingest.rs::persist` now calls `append_leaf` once per kept chunk after chunks + scores land. Failures are logged at warn level and do not fail the ingest — leaves are already persisted and the next flush can still rebuild the tree. ## Concurrency / LLM The async summariser call happens OUTSIDE any DB transaction, so a slow LLM never holds SQLite locks. Blocking DB calls inside `append_leaf` are acceptable for Phase 3a because the Inert summariser does no real I/O; when a networked summariser lands, wrap the DB calls in `tokio::task::spawn_blocking`. ## Tests (23 new, all green) * `types` — enum round-trips, buffer staleness predicates * `store` — tree insert + unique scope, summary insert + idempotence, buffer upsert/clear, stale-buffer ordering * `registry` — `get_or_create` idempotence, distinct scopes yield distinct trees, id prefix format * `summariser/inert` — provenance-prefixed concat, entity union with order preservation, budget truncation, empty-content skip * `bucket_seal` — append-below-budget is buffered only (no seal); 12k-token cross-over produces an L1 summary with correct `child_ids`, L0 cleared, L1 carries the new summary id, tree `max_level`/`root_id` updated, leaf → parent backlink populated * `flush` — stale buffer force-seals under budget; recent buffer is a no-op Broader `memory::tree` suite: 160 tests pass (23 new + 137 existing Phase 1/2), no regressions. ## Stacked on #775 This PR applies on top of `feat/708-memory-llm-ner` (PR #775, Phase 2 LLM-NER follow-up). Merge #775 first; this branch will rebase cleanly onto main. ## Out of scope (tracked separately) * **3b — Global activity digest tree** — time-aligned cross-source recap * **3c — Topic trees** — hotness-driven per-entity materialisation * **Phase 4 (#710)** — retrieval / query / gate Closes part of #709 (source-tree foundation). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
OpenHuman
The age of super intelligence is here. OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.
Discord • Reddit • X/Twitter • Docs
"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:
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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.
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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.
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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.
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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.
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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.
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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. Running from source: docs/install.md.
Highlights
- Neocortex — local-first knowledge base that learns from your data and activity, compounding context across tools and sessions.
- The Subconscious — background self-learning loops that turn everyday usage into workflow-aware intelligence.
- Screen Intelligence — the agent sees what's on your screen and feeds it into your local context.
- Inline Autocomplete — memory-aware keyboard autocomplete anywhere on your desktop.
- Voice (STT + TTS) — speak to OpenHuman and hear it reply, natively on the desktop.
- Skills & Integrations — one-click skills for Gmail, Slack, Notion and the rest of your stack, with local encryption and webhooks for instant feedback.
- Messaging Channels — inbound/outbound across the channels you already use, routed through your agent.
- Teams & Organizations — shared workspaces for collaborating with an agent across a team.
- Rewards & Achievements — gamified progression as your agent grows with you.
- Privacy & Security — workflow data stays on device, encrypted locally, and treated as yours.
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 | 🚫 Proprietary | ✅ MIT | ✅ MIT | ✅ GNU |
| Simple to start | ✅ Desktop + CLI | ⚠️ Terminal-first | ⚠️ Terminal-first | ✅ Clean UI, minutes |
| Cost | ⚠️ Sub + add-ons | ⚠️ BYO models | ⚠️ BYO models | ✅ Local-friendly |
| Memory & KB | ✅ Chat-scoped | ⚠️ Plugin-reliant | ✅ Self-learning | 🚀 Local KB + learning |
| API sprawl | 🚫 Extra keys | 🚫 BYOK | 🚫 Multi-vendor | ✅ One account |
| Extensibility | ✅ MCP | ✅ SKILL.md | ✅ SKILL.md | 🚀 Rich Skills |
| Desktop integration | ⚠️ Basic | ⚠️ Light | ⚠️ Light | ✅ STT/TTS/screen/more |
Contributors Hall of Fame
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