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orze
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Automate your research.
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# orze [](https://pypi.org/project/orze/) [](https://raw.githubusercontent.com/warlockee/orze/main/LICENSE) [](https://orze.ai/pro) A GPU experiment orchestrator for ML research. Orze runs experiments on GPUs: **schedule ideas → train → evaluate → report → repeat**. It coordinates GPUs via filesystem locks, works across machines, and gives you a complete leaderboard, notifications, and analysis — out of the box. **Website:** [orze.ai](https://orze.ai) ## Install ```bash curl -sL https://orze.ai/install | bash ``` That's it. It installs orze, detects your GPUs and codebase, generates training scripts and experiment ideas, and starts running — all in one command. Pass environment variables for additional options: ```bash # LLM-powered setup ANTHROPIC_API_KEY=sk-ant-... curl -sL https://orze.ai/install | bash # With pro (autopilot) ORZE_PRO_KEY=ORZE-PRO-xxx curl -sL https://orze.ai/install | bash # Custom project path curl -sL https://orze.ai/install | bash -s /nfs/my-project ``` ## orze vs orze-pro orze is a **complete, production-ready tool**. orze-pro adds **autopilot** — so experiments run while you sleep. | Feature | orze (free) | + orze-pro | |---------|:-----------:|:----------:| | GPU scheduling & multi-node | ✓ | ✓ | | Idea queue (ideas.md + SQLite) | ✓ | ✓ | | Hyperparameter sweep (auto-expand grid) | ✓ | ✓ | | Leaderboard report | ✓ | ✓ | | Notifications (Telegram/Slack) | ✓ | ✓ | | Admin dashboard & MCP server | ✓ | ✓ | | Retrospection (plateau detection) | ✓ | ✓ | | Cross-experiment regression analysis | ✓ | ✓ | | Failure analysis & categorization | ✓ | ✓ | | Checkpoint GC | ✓ | ✓ | | Sealed eval protection | ✓ | ✓ | | Service watchdog (auto-restart + containers) | ✓ | ✓ | | **Autonomous research agents** (Gemini/GPT/Claude) | | ✓ | | **The Professor** (paper lake, cross-domain search, strategy) | | ✓ | | **Engineer** (implement ideas, fix bugs) | | ✓ | | **Auto-fix failed experiments** | | ✓ | | **Code evolution on plateau** | | ✓ | | **Meta-research (strategy adjustment)** | | ✓ | | **FSM orchestration** (7 procedures) | | ✓ | | **Data analyst & thinker** (auto-injected) | | ✓ | ### Research Loop Comparison | | orze free | + orze-pro | |---|---|---| | **How ideas are generated** | **Smart Suggestions** — rule-based: detects regressions, generates scale sweeps, perturbations | **Research Agents** — LLM-driven: reads all results, forms hypotheses, designs novel experiments | | **How failures are handled** | You read the failure log | Auto-fix: LLM diagnoses and patches the error | | **How plateaus are handled** | Smart Suggestions tries parameter variations | Code Evolution: LLM modifies your train script | | **Does research stop?** | **Never** — Smart Suggestions keeps GPUs busy | **Never** — agents run indefinitely | | **Requires API key?** | No | Yes (Gemini/OpenAI/Anthropic) | ### Compatibility | orze | orze-pro | Notes | |------|----------|-------| | 4.1.x | 0.8.x | Current release | ## Quick Start After install, orze auto-detects GPUs and starts running experiments. **AI CLI users (Claude Code, Cursor, Codex):** ```bash do @ORZE-AGENT.md ``` ## CLI Reference ```bash # Project lifecycle orze init [path] # initialize a new project orze start # start as background daemon orze stop # stop gracefully orze restart # stop + start orze --check # validate config, files, GPUs, API keys orze --uninstall # full cleanup, preserves research results # Operations orze upgrade # reinstall from source + restart daemon orze admin migrate # migrate legacy layout to .orze/ orze service install # auto-restart on crash (systemd) # Pro orze pro activate <key> # activate license orze pro status # check license info orze pro deactivate # remove license orze sop list # list available SOPs ``` ## File Layout ``` your-project/ ├── orze.yaml # Project config (single source of truth) ├── train.py # Your training script ├── ideas.md # Experiment queue ├── GOAL.md # Research objective ├── RESEARCH_RULES.md # Agent constraints ├── configs/base.yaml # Default hyperparameters ├── .env # API keys (gitignored) ├── ORZE-AGENT.md # AI CLI instructions ├── ORZE-RULES.md # Agent guardrails ├── venv/ # Training dependencies ├── .orze/ # Runtime state (gitignored) │ ├── state/version.json # Layout version │ ├── logs/ # Role logs │ ├── locks/ # Filesystem locks │ ├── rules/ # Migrated rule files │ ├── mcp/ # MCP server configs │ ├── receipts/ # Execution evidence │ ├── triggers/ # One-shot role triggers │ ├── heartbeats/ # Per-host liveness │ ├── backups/ # ideas.md backups │ └── feedback/ # Failure feedback ├── procedures/ # User procedure overrides (pro) ├── fsm/runner.py # FSM orchestrator (pro) └── orze_results/ # Research outputs ├── idea-0001/metrics.json ├── methods/ # Generated code └── knowledge/ # Analysis insights ``` ## Multi-node Start orze in the same shared folder on any machine — nodes auto-join the research pool. ```bash # Node 1 ssh node1 "cd /nfs/project && orze start" # Node 2 ssh node2 "cd /nfs/project && orze start" ``` ## Key Features - **Scales to 1M+ Experiments** — SQLite-backed job queue with O(log N) scheduling - **Config Inheritance** — Child ideas inherit parent configs; specify only what changes - **HP Sweep** — `lr: [1e-4, 3e-4]` auto-expands into all combinations - **Failure Protection** — Stops automatically when failure rates spike - **Cross-Experiment Analysis** — Detects regressions, tradeoffs, and suggests actions - **Rich Notifications** — GPU VRAM, per-dataset breakdown, verified results, target/gap tracking - **Admin Panel** — Real-time web dashboard at `http://localhost:8787` - **Clean Uninstall** — `orze --uninstall` removes runtime files, preserves results ## The Contract Your training script receives: ```bash python train.py --idea-id idea-001 --results-dir orze_results --ideas-md ideas.md --config base.yaml ``` **Required output:** `orze_results/{idea_id}/metrics.json`: ```json {"status": "COMPLETED", "test_accuracy": 0.92, "training_time": 142.5} ``` See [**SKILL.md**](SKILL.md) for the full technical specification. ## Admin Panel Auto-launches at **http://localhost:8787**. No extra install needed. <img width="900" height="674" alt="admin-panel" src="https://github.com/user-attachments/assets/b23879e3-d064-4e02-8251-6e8dbfad21f9" /> <img width="900" height="674" alt="admin-queue" src="https://github.com/user-attachments/assets/39747da2-7b7f-4a9f-ad4a-7cfaca41407b" /> <img width="900" height="551" alt="admin-leaderboard" src="https://github.com/user-attachments/assets/70e77941-efbf-4018-9200-93ea77998c5e" /> ## Telegram Notifications ```yaml notifications: enabled: true on: [completed, failed, new_best] channels: - type: telegram bot_token: "YOUR_BOT_TOKEN" chat_id: "YOUR_CHAT_ID" ``` <img width="521" height="341" alt="tg" src="https://github.com/user-attachments/assets/f931221d-b428-4b85-9a8e-af6d516cb5ad" /> ## Service Management ```bash orze service install -c orze.yaml # auto-restart on crash + manage containers orze service status # check health orze service uninstall # remove ``` The watchdog runs every minute (crontab) or every 5 minutes (systemd). It restarts orze on crash/stall and manages Docker containers defined in `orze.yaml`: ```yaml containers: paperdog: image: warlockee/paperdog:latest ports: - "8000:8000" ``` Containers are auto-pulled and recreated when a new image is available. ## Citation ```bibtex @article{li2026autoresearching, title={Auto Researching, not hyperparameter tuning: Convergence Analysis of 10,000 Experiments}, author={Li, Xiaoyi}, journal={arXiv preprint arXiv:2603.15916}, year={2026} } ``` ## License Apache 2.0 — orze is and will always be free and open source. [orze-pro](https://github.com/warlockee/orze-pro) (autopilot features) is commercially licensed.
