# OpenAdapt: Launcher for the OpenAdapt Flow Compiler [![Build Status](https://github.com/OpenAdaptAI/OpenAdapt/actions/workflows/main.yml/badge.svg)](https://github.com/OpenAdaptAI/OpenAdapt/actions/workflows/main.yml) [![PyPI version](https://img.shields.io/pypi/v/openadapt.svg)](https://pypi.org/project/openadapt/) [![Downloads](https://img.shields.io/pypi/dm/openadapt.svg)](https://pypi.org/project/openadapt/) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Python 3.10+](https://img.shields.io/badge/python-3.10%2B-blue)](https://www.python.org/downloads/) [![Discord](https://img.shields.io/badge/Discord-Join%20the%20community-7289da?logo=discord&logoColor=white)](https://discord.gg/yF527cQbDG) > **Lifecycle: Beta launcher/meta-package.** The active compiler and governed > runtime are developed in > [`openadapt-flow`](https://github.com/OpenAdaptAI/openadapt-flow). This > repository preserves the high-visibility `openadapt` install and unified CLI; > it is not a second implementation of the engine. The pre-1.0 monolith is > historical and frozen under [`legacy/`](legacy/). **Compile repeated GUI work into deterministic, governed workflows.** OpenAdapt compiles a demonstrated workflow into a locally executable program. Healthy runs make no model calls. When an interface drifts, the runtime first tries deterministic re-resolution, can optionally propose a reviewable repair, and halts when configured identity, postcondition, effect, or certification checks fail. The proven self-serve path today is browser automation; native desktop backends remain experimental and remote-display (RDP/Citrix-style) automation remains research-stage. `pip install openadapt` installs the launcher and the compiler, exposed as `openadapt flow ...`. Native capture, privacy scrubbing, and the separate ML research toolkits remain optional extras. [Join us on Discord](https://discord.gg/yF527cQbDG) | [Documentation](https://docs.openadapt.ai) | [OpenAdapt.ai](https://openadapt.ai) --- ## Why a compiler Every automation tool assumes an API. The systems that actually run regulated work often don't: legacy EMRs, Citrix desktops, and internal apps a team still drives by hand. General computer-use agents can operate those GUIs, but re-reasoning through every step with a large model is slow, expensive, and non-deterministic, and a wrong click writes to the wrong record. OpenAdapt takes the opposite path for workflows you run over and over. You demonstrate the task once. `openadapt-flow` **compiles** that demonstration into a script that replays **deterministically and locally**, with no model calls on a healthy run. When the UI changes, the resolution ladder may re-resolve the target and persist a reviewable repair. When configured checks cannot establish identity or success, the run **halts with a report** instead of continuing. --- ## Installation ```bash pip install openadapt # CLI + demonstration compiler (openadapt flow …) pip install openadapt[capture] # + native GUI capture/recording pip install openadapt[privacy] # + Presidio-backed PII/PHI scrubbing pip install openadapt[all] # Everything, including research extras ``` The flagship compiler ships in the base install, so `openadapt flow …` works right after `pip install openadapt`. Install `openadapt-flow[hosted]` when you want OS-keychain token storage; environment-based token configuration remains available on headless systems. This launcher requires `openadapt-flow>=1.7.0,<2` so clean installs cannot resolve an older engine that lacks the governed hosted artifact commands documented below. **Requirements:** Python 3.10+ --- ## Quick Start Run the bundled MockMed workflow first. This is the reproducible path exercised by `openadapt-flow` CI and requires no account or target application: ```bash openadapt flow demo-record --out rec openadapt flow compile rec --out bundle --name mockmed-triage openadapt flow certify bundle --policy permissive openadapt flow replay bundle --run-dir run-baseline openadapt flow replay bundle --drift theme --run-dir run-drift \ --save-healed-to bundle-healed ``` Each replay writes an illustrated `REPORT.md` in its run directory. The drift run demonstrates bounded deterministic re-resolution; it is not a claim that arbitrary UI changes can be repaired. Now apply the stricter deployment gates: ```bash openadapt flow lint bundle openadapt flow certify bundle --policy clinical-write ``` These two commands currently exit nonzero. That is intentional: the bundled workflow is runnable under the permissive demo policy, but it has unarmed clicks, a vacuous postcondition, and no configured system-of-record effect for its write. The strict policy refuses to call it safe. A policy pass means only that the bundle satisfies that named policy. To run the workflow through OpenAdapt Cloud, create and review a sanitized derivative locally, approve its exact bytes, then upload that immutable derivative with an ingest token created in the Cloud dashboard: ```bash openadapt flow sanitize rec --kind recording --out rec-sanitized openadapt flow review-sanitized rec-sanitized --original rec openadapt flow approve-sanitized rec-sanitized --original rec --reviewer "$USER" openadapt flow login --token oai_ingest_... openadapt flow push rec-sanitized --kind recording openadapt flow compile rec-sanitized --out bundle --name workflow openadapt flow lint bundle --strict openadapt flow certify bundle --policy permissive openadapt flow replay bundle --url https://app.example/login --run-dir run openadapt flow sanitize bundle --kind bundle --out bundle-sanitized openadapt flow review-sanitized bundle-sanitized --original bundle openadapt flow approve-sanitized bundle-sanitized --original bundle \ --reviewer "$USER" openadapt flow validate-hosted --recording rec-sanitized \ --bundle bundle-sanitized --run-dir run --policy permissive \ --risk-class low --environment staging-v1 \ --target-url https://app.example/login --out validation.json openadapt flow push bundle-sanitized --kind bundle \ --validation-attestation validation.json ``` The original recording remains local. Sanitization accounts for every file and refuses unsupported content rather than copying it. Review is local and approval is bound to the exact archive hash; live observations can contain PHI again and therefore remain inside the workflow's declared execution boundary. Then record your own browser application: ```bash openadapt flow record --url https://your.app --out rec openadapt flow compile rec --out bundle --name my-workflow openadapt flow replay bundle --url https://your.app ``` > `openadapt flow ` is the recommended path. The standalone > `openadapt-flow ` command keeps working and behaves identically. --- ## How the compiler works Each compiled step carries a template crop, an OCR label, geometry landmarks, and postconditions derived from what the demo changed on screen. At replay time a resolution ladder tries them in order (local match, global match, OCR, landmark geometry, then optionally a grounding model), so healthy runs cost milliseconds and make no model calls. - **Deterministic replay.** No large model on the hot path, so a compiled run is repeatable and has no model API charge on a healthy run. It still consumes local or hosted compute, storage, monitoring, and exception-handling effort. - **Bounded re-resolution and repair.** Deterministic fallback rungs can recover from supported drift. Optional model- or human-assisted repairs are governed changes to the bundle, not unconstrained reasoning on every run. - **Explicit verification.** Compiled steps can carry postconditions. For consequential writes, effect verification must also be configured against a system of record; screen evidence alone cannot prove a transaction committed. - **Refusal where armed.** Identity-verified or policy-gated steps can refuse a low-confidence match and halt with a report. Coverage is not automatic for every click, so lint and certification are part of deployment. The reference backend is a **headless browser**, which is why the whole loop runs in CI with no OS permissions. Desktop, Citrix, and RDP backends are adapters in progress, not yet production paths: Windows UI Automation is Experimental, and RDP/Citrix-style pixel-only automation is Research — we are seeking design partners to validate them on real deployments. Compiled workflows can also be emitted as Agent Skills or MCP servers so other agents can invoke them. In one field test against a computer-use agent on a real third-party EMR (OpenEMR's public demo), compiled replay matched the agent's success (20/20 compiled vs 10/10 agent) at roughly half the median latency and with zero model calls in the measured runs; the agent's measured model charge was about $0.55 per run. This comparison does not include authoring, maintenance, compute, storage, review, or exception-handling cost. It is a small-sample result on a shared, daily-resetting public demo, so it is not CI-reproducible; a CI-reproducible control and the adversarial safety measurements are published alongside it. See [openadapt-flow](https://github.com/OpenAdaptAI/openadapt-flow) for the compiler, validation methodology, and known limits. --- ## Repository Role and Lifecycle This repository is the stable URL and install route; `openadapt-flow` is the canonical implementation. Lifecycle labels describe support intent, not a blanket production-readiness claim. | Package | Role | Maturity | Repository | |---------|------|----------|------------| | `openadapt` | Installer + unified CLI (`openadapt flow ...`) | **Beta** | This repo | | `openadapt-flow` | Compiler + governed runtime | **Beta**; browser path proven, Windows UI Automation experimental, remote-display (RDP/Citrix) research | [openadapt-flow](https://github.com/OpenAdaptAI/openadapt-flow) | | `openadapt-capture` | Optional native recorder | **Experimental** | [openadapt-capture](https://github.com/OpenAdaptAI/openadapt-capture) | | `openadapt-privacy` | Optional PII/PHI scrubbing | **Experimental** | [openadapt-privacy](https://github.com/OpenAdaptAI/openadapt-privacy) | `openadapt-flow` also ships standalone on PyPI (`pip install openadapt-flow`); the standalone `openadapt-flow ` command behaves identically to `openadapt flow `. ### CLI reference ``` openadapt flow record --url --out Record a workflow once openadapt flow compile --out Compile a recording into a bundle openadapt flow replay Replay a bundle (local, $0) openadapt flow lint Report a bundle's coverage gaps openadapt flow certify --policy Enforce a safety policy on a bundle openadapt flow sanitize --kind --out openadapt flow review-sanitized --original openadapt flow approve-sanitized --original --reviewer openadapt flow login --token openadapt flow validate-hosted --recording --bundle --run-dir ... openadapt flow push --kind recording openadapt flow push --kind bundle \ --validation-attestation [--workflow-id ] \ [--resolves-run-id ] openadapt flow report-break --workflow-id openadapt capture start --name Start a native recording (requires [capture]) openadapt capture stop Stop recording openadapt capture list List captures openadapt capture view Open capture viewer openadapt version Show installed versions openadapt doctor Check system requirements ``` --- ## Research (not the product) These packages are **research**, not part of the supported product. They explore whether human demonstrations can improve the accuracy of general computer-use models. They are not required to record, compile, or replay a workflow, and the compiler above makes no model calls on its hot path. | Package | Research focus | Repository | |---------|----------------|------------| | `openadapt-ml` | Training and inference for multimodal GUI-action models | [openadapt-ml](https://github.com/OpenAdaptAI/openadapt-ml) | | `openadapt-evals` | Benchmark evaluation for GUI agents | [openadapt-evals](https://github.com/OpenAdaptAI/openadapt-evals) | | `openadapt-retrieval` | Multimodal demonstration retrieval | [openadapt-retrieval](https://github.com/OpenAdaptAI/openadapt-retrieval) | | `openadapt-grounding` | UI element localization / grounding models | [openadapt-grounding](https://github.com/OpenAdaptAI/openadapt-grounding) | Install with `pip install openadapt[ml,evals]`. The `openadapt train` and `openadapt eval` commands become available once those extras are installed.
Research thesis: demonstration-conditioned agents The research line asks a different question from the compiler: instead of compiling one demonstration into a deterministic script, can a model *use* demonstrations at inference time to disambiguate unfamiliar GUIs? - **Demonstrate** — record user actions and screenshots, scrub PII/PHI, build a searchable demonstration library. - **Learn** — embed and index demonstrations for retrieval, and/or fine-tune Vision-Language Models on them. - **Execute** — condition a policy on retrieved demonstrations, ground intent to coordinates, act behind safety gates, and evaluate to feed results back. **Validated result (research, not product):** on a controlled macOS benchmark (45 System Settings tasks sharing a common navigation entry point), demonstration-conditioned prompting improved first-action accuracy from 46.7% to 100%, with a length-matched control (+11.1 pp) confirming the benefit is semantic, not token-length. Phase 2 (retrieval-only prompting) is validated; Phase 3 (demo-conditioned fine-tuning) is in progress. See the [research thesis](https://github.com/OpenAdaptAI/openadapt-ml/blob/main/docs/research_thesis.md) for methodology and limits. **Industry note:** [OpenCUA](https://github.com/xlang-ai/OpenCUA) (NeurIPS 2025 Spotlight, XLANG Lab) [reused OpenAdapt's macOS accessibility capture code](https://arxiv.org/html/2508.09123v3) in their AgentNetTool, but uses demonstrations only for model training, not runtime conditioning.
--- ## Migration and Deprecated Paths - **New automation work:** install `openadapt` and use `openadapt flow ...`; make engine changes in `openadapt-flow`. - **`openadapt-agent`: Deprecated.** Do not build new integrations on it. Its execution responsibilities have moved to the governed runtime in `openadapt-flow`. - **Pre-1.0 monolith: Historical.** Version 0.46.0 and its source remain available for existing users, but receive no feature development. --- ## Legacy Version The monolithic OpenAdapt codebase (v0.46.0) is preserved in the `legacy/` directory. ```bash pip install openadapt==0.46.0 ``` See [docs/LEGACY_FREEZE.md](docs/LEGACY_FREEZE.md) for the migration guide. Early demonstrations of the legacy version: [Twitter demo](https://twitter.com/abrichr/status/1784307190062342237) · [Loom walkthrough](https://www.loom.com/share/9d77eb7028f34f7f87c6661fb758d1c0). For the current architecture, see the [documentation](https://docs.openadapt.ai). --- ## Permissions The default headless-browser path needs no OS permissions. Native desktop capture does: **macOS:** Grant Accessibility, Screen Recording, and Input Monitoring permissions to your terminal. See [permissions guide](./legacy/permissions_in_macOS.md). **Windows:** Run as Administrator if needed for input capture. --- ## Contributing 1. [Join Discord](https://discord.gg/yF527cQbDG) 2. Pick an issue from the relevant repository 3. Submit a PR For sub-package development: ```bash git clone https://github.com/OpenAdaptAI/openadapt-flow # or another package cd openadapt-flow pip install -e ".[dev]" ``` --- ## Related Projects - [OpenAdaptAI/SoM](https://github.com/OpenAdaptAI/SoM) — Set-of-Mark prompting - [OpenAdaptAI/pynput](https://github.com/OpenAdaptAI/pynput) — input monitoring fork - [OpenAdaptAI/atomacos](https://github.com/OpenAdaptAI/atomacos) — macOS accessibility > **Product surfaces:** OpenAdapt Cloud provides the hosted browser-workflow > control plane, with live execution enabled only when its production > dependencies pass readiness checks. `openadapt-desktop` and native desktop > backends remain experimental; remote-display (RDP/Citrix-style) automation > remains research-stage. **Internal tooling:** `openadapt-wright`, `openadapt-herald`, > `openadapt-crier`, `openadapt-consilium`, `openadapt-telemetry`, and > `openadapt-viewer` support development and operations; they are not required > by the compiler runtime. --- ## Support - **Discord:** https://discord.gg/yF527cQbDG - **Documentation:** https://docs.openadapt.ai - **Issues:** use the relevant repository --- ## License MIT License — see [LICENSE](LICENSE) for details.