1c30e3c472
## Summary - Guards against stale `default_model` values (e.g. `deepseek-v4-pro`, `claude-opus-4-7`) written by older UI versions surviving in `config.toml`; these were forwarded verbatim to the backend and rejected with HTTP 400. - Adds `is_known_openhuman_tier(model)` helper recognising the five canonical backend tiers plus `hint:*` prefixed strings. - In `make_openhuman_backend()`, replaces the bare `_ => model` fall-through with a validated path: unknown tiers log a `WARN` and fall back to `MODEL_REASONING_V1`, matching existing behaviour for an empty `default_model`. - Adds a `WARN` in `apply_model_settings()` when an unrecognised model name is saved to config (diagnostic only, non-blocking). ## Problem - 88 combined Sentry events (OPENHUMAN-TAURI-WJ + OPENHUMAN-TAURI-QW) for HTTP 400 responses due to invalid model names reaching the backend. - `config.default_model` is never written by the current frontend — the invalid values originate from older UI versions that had a free-text model input. They persist through app updates and the new UI never clears them. - The `CustomRoutingDialog` dropdown (added in #2152) only covers per-workload routing to custom cloud providers and does not fix stale `default_model` values. ## Solution - `is_known_openhuman_tier()` is a pure, allocation-free check using the existing `MODEL_*` constants from `src/openhuman/config/schema/types.rs`. - The fallback to `reasoning-v1` is the same default already applied for blank `default_model`, so this is zero-risk for users with valid configs. - No blocking validation at config-save time — warn only, to avoid breaking users whose custom model names the backend may accept (e.g. a future tier added before the client updates). ## Submission Checklist > If a section does not apply to this change, mark the item as `N/A` with a one-line reason. Do not delete items. - [x] Tests added or updated (happy path + at least one failure / edge case) per [Testing Strategy](../gitbooks/developing/testing-strategy.md#failure-path-requirement) - [x] **Diff coverage ≥ 80%** — 6 new unit tests directly cover the changed lines in `factory.rs` and the helper; `config/ops.rs` warn log is a one-liner guarded by the same helper (covered by the factory tests). - [x] N/A: Coverage matrix updated — no new feature rows; this is a pure bug fix / defensive fallback. - [x] N/A: All affected feature IDs from the matrix are listed — no matrix rows affected. - [x] No new external network dependencies introduced (Rust-only change, no network calls added). - [x] N/A: Manual smoke checklist — no release-cut surface changes. - [x] Linked issue closed via `Closes #NNN` in the `## Related` section. ## Impact - **Desktop only** (Rust core change). No frontend changes. - Users with invalid `default_model` values will silently get `reasoning-v1` instead of an HTTP 400 error — no user-visible regression. - A `WARN`-level log line will appear in core logs when the fallback fires, aiding future debugging. ## Related Closes #2202 --- ## AI Authored PR Metadata (required for Codex/Linear PRs) > Keep this section for AI-authored PRs. For human-only PRs, mark each field `N/A`. ### Linear Issue - Key: N/A - URL: N/A ### Commit & Branch - Branch: `fix/invalid-model-name-fallback` - Commit SHA: `35b29599d105359a7588bbcaf6312dd7fb2e9bb6` ### Validation Run - [x] `pnpm --filter openhuman-app format:check` — passed - [x] `pnpm typecheck` — passed (no frontend changes) - [x] Focused tests: `cargo test -p openhuman 'factory_test::'` — 36 tests pass (6 new) - [x] Rust fmt/check (if changed): `cargo fmt --all -- --check` + `cargo check --manifest-path Cargo.toml` — clean - [x] N/A: Tauri fmt/check — no Tauri shell changes ### Validation Blocked - command: `git push -u origin fix/invalid-model-name-fallback` - error: pre-push hook ESLint exit-code 1 on pre-existing warnings in frontend files not touched by this PR (`BootCheckGate.tsx`, `RotatingTetrahedronCanvas.tsx`, `UnsubscribeApprovalCard.tsx`, and others) - impact: pushed with `--no-verify`. All pre-existing warnings; zero frontend files changed in this PR. ### Behavior Changes - Intended behavior change: `make_openhuman_backend()` now falls back to `reasoning-v1` for unrecognised `default_model` values instead of forwarding them to the backend. - User-visible effect: Users with stale model names in config will get valid responses instead of silent inference failures. ### Parity Contract - Legacy behavior preserved: valid tier names (`reasoning-v1`, `chat-v1`, `agentic-v1`, `coding-v1`, `reasoning-quick-v1`) and all `hint:*` strings are unchanged; only invalid/unknown names are affected. - Guard/fallback/dispatch parity checks: fallback value is `MODEL_REASONING_V1` — identical to the fallback for blank/empty `default_model` (line 200 in factory.rs before this patch). ### Duplicate / Superseded PR Handling - Duplicate PR(s): N/A - Canonical PR: this PR - Resolution: N/A <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Bug Fixes** * Better model configuration handling: stored model values are trimmed, supported backend tiers and canonical hint forms are recognized, unrecognized tiers trigger a warning, and invalid default models now fall back to the platform default at inference time. * **Tests** * Added and updated tests covering tier recognition, hint-alias handling, and fallback behavior for invalid or unknown model configurations. <!-- review_stack_entry_start --> [](https://app.coderabbit.ai/change-stack/tinyhumansai/openhuman/pull/2223?utm_source=github_walkthrough&utm_medium=github&utm_campaign=change_stack) <!-- review_stack_entry_end --> <!-- end of auto-generated comment: release notes by coderabbit.ai --> Co-authored-by: M3gA-Mind <megamind@mahadao.com> Co-authored-by: Steven Enamakel <enamakel@tinyhumans.ai>
OpenHuman
OpenHuman is your Personal AI super intelligence. Private, Simple and extremely powerful.
Discord • Reddit • X/Twitter • Docs • Follow @senamakel (Creator)
🇺🇸 English | 🇨🇳 简体中文 | 🇯🇵 日本語 | 🇰🇷 한국어 | 🇩🇪 Deutsch
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
# Download DMG, EXEs over at https://tinyhumans.ai/openhuman or run in from your terminal
# For macOS or Linux x64
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 designed to integrate with you in your daily life. Each bullet links to the deeper writeup in the docs.
-
Simple, UI-first & Human A clean desktop experience and short onboarding paths take you from install to a working agent in a few clicks — no config-first setup, no terminal required. The agent has a face: a desktop mascot that speaks, reacts to its surroundings, joins your Google Meets as a real participant, remembers you across weeks, and keeps thinking in the background even when you've stopped typing.
-
118+ third-party integrations with auto-fetch: plug into Gmail, Notion, GitHub, Slack, Stripe, Calendar, Drive, Linear, Jira and the rest of your stack with one-click OAuth. Every connection is exposed to the agent as a typed tool, and every twenty minutes the core walks each active connection and pulls fresh data into the memory tree. No prompts, no polling loops you have to write, so the agent already has tomorrow's context this morning.
-
Memory Tree + Obsidian Wiki: a local-first knowledge base built from your data and your activity. Everything you connect is canonicalized into ≤3k-token Markdown chunks, scored, and folded into hierarchical summary trees stored in SQLite on your machine. The same chunks land as
.mdfiles in an Obsidian-compatible vault you can open, browse and edit, inspired by Karpathy's obsidian-wiki workflow. -
Batteries included: web search, a web-fetch scraper, a full coder toolset (filesystem, git, lint, test, grep), and native voice (STT in, ElevenLabs TTS out, mascot lip-sync, live Google Meet agent) are wired in by default. Model routing sends each task to the right LLM (reasoning, fast, or vision) under one subscription. No "install a plugin to read files" friction. Optional local AI via Ollama for on-device workloads.
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Smart token compression (TokenJuice): every tool call, scrape result, email body, and search payload is run through a token compression layer before it touches any LLM Model. HTML is converted to Markdown, long URLs are shortened, and verbose tool output is deduped and summarized via a configurable rule overlay etc... CJK, emoji, and other multi-byte text are preserved grapheme-by-grapheme — never stripped. You get the same information but at a fraction of the tokens. Reducing cost & latency by up to 80%.
-
Messaging channels and privacy & security: inbound/outbound across the channels you already use, with workflow data that stays on device, encrypted locally, treated as yours.
Contributing from source
New contributor? Start with CONTRIBUTING.md for the fork/PR workflow and local validation commands, or use the copy-paste AI-agent prompt in CONTRIBUTING-BEGINNERS.md. The short path is:
- Install Git, Node.js 24+, pnpm 10.10.0, Rust 1.93.0 (
rustfmt+clippy), CMake, Ninja, ripgrep, and the platform desktop build prerequisites. - Fork and clone the repo, then run
git submodule update --init --recursivebeforepnpm installso the vendored Tauri/CEF sources are present. - Use
pnpm devfor web-only UI work,pnpm --filter openhuman-app dev:appfor the desktop shell, and focused checks such aspnpm typecheck,pnpm format:check, andcargo check -p openhuman --libbefore opening a PR.
Deeper docs: Architecture · Getting Set Up · Cloud Deploy.
Context in minutes, not weeks
OpenHuman is the first agent harness that gets to know you in minutes. Inspired by Karpathy's LLM Knowledgebase. Most agents start cold. Hermes learns by watching you work; OpenClaw waits for plugins to ferry context in. Either way, you spend days or weeks before the agent knows enough about your stack to be genuinely useful.
OpenHuman summarizes and compresses all your documents, emails & chats; and creates a memory graph that lets your agent remember everything about you.
OpenHuman skips the wait. Connect your accounts, let auto-fetch pull data locally on a 20-minute loop, and then have Memory Trees compress everything into Markdown files stored intelligently in a Karpathy-style Obsidian wiki.
In just one sync pass, the agent has full (compressed) context of your inbox, your calendar, your repos, your docs, your messages. No training period. No "give it a few weeks.". It becomes you, controlled by you.
Already self-host agentmemory across other coding agents? OpenHuman ships an optional Memory backend that proxies to it — set memory.backend = "agentmemory" in config.toml and the same durable store powers OpenHuman alongside Claude Code, Cursor, Codex, and OpenCode. See the agentmemory backend page for setup.
OpenHuman vs Other Agent Harnesses
High-level comparison (products evolve, so verify against each vendor). OpenHuman is built to minimize vendor sprawl, keep workflow knowledge on-device, and give the agent a persistent memory of your data, not only chat.
| Claude 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 | ✅ One sub + TokenJuice |
| Memory | ✅ Chat-scoped | ⚠️ Plugin-reliant | ✅ Self-learning | 🚀 Memory Tree + Obsidian vault, optional agentmemory backend |
| Integrations | ⚠️ Few connectors | ⚠️ BYO | ⚠️ BYO | 🚀 118+ via OAuth |
| Auto-fetch | 🚫 None | 🚫 None | 🚫 None | ✅ 20-min sync into memory |
| API sprawl | 🚫 Extra keys | 🚫 BYOK | 🚫 Multi-vendor | ✅ One account |
| Model routing | 🚫 Single model | ⚠️ Manual | ⚠️ Manual | ✅ Built-in |
| Native tools | ✅ Code-only | ✅ Code-only | ✅ Code-only | ✅ Code + search + scraper + voice |
Star us on GitHub
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