add dora_ulite6 standalone node with command lifecycle status
Migrates the ulite6 Python dora node from dora_littlehand into a
self-contained repository following the dora-zed structure. Adds
command lifecycle state ("started"/"done"/"failed") and type
("command"/"error") to the status output so coordinator nodes can
reliably sequence robot actions without polling.
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# AGENTS.md
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This file provides guidance to AI coding assistants when working with code in this repository.
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## What this is
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A dora-rs Python node that interfaces with a UFactory Lite6 robot arm. On each tick it reads joint angles and TCP pose from the robot and publishes them as dora outputs. It also accepts JSON commands (home, move_to, move_to_pose, vacuum_on/off) via a `command` input. A FastAPI REST server with a web UI runs in a background thread for manual control. The robot control wrapper lives in `dora_ulite6/main.py` as the `ULite6Helper` class, and the dora event loop is the `main()` function in the same file.
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## Build
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```bash
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uv pip install -e .
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```
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Requirements: Python >=3.8, uv, and network access to the UFactory Lite6 robot.
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## Run
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```bash
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dora up
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dora start dataflow.yml
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```
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Robot behavior is configured through environment variables (see README.md for the full list: ROBOT_IP, DEFAULT_SPEED, DEFAULT_UNITS, API_HOST, API_PORT, VACUUM_ENABLED, INIT_MODE, etc.).
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## Architecture
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- **`dora_ulite6/main.py`** -- Single-file implementation containing:
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- `ULite6Helper`: Wraps the xArm Python SDK for motion control (go_home, move_to_pose, get_current_position, get_joint_angles_deg, get_pose_matrix, vacuum gripper, status, reset).
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- `MoveToRequest` / `MoveToPoseRequest`: Pydantic models for API validation.
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- `create_api()`: FastAPI app factory with REST endpoints and embedded HTML/JS web UI for manual control.
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- `main()`: Dora event loop. Starts FastAPI in a daemon thread, then processes `tick` (publishes joint_pose and tcp_pose) and `command` (executes robot actions and publishes status) inputs.
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- **`dora_ulite6/__init__.py`** -- Package marker.
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- **`pyproject.toml`** -- Package metadata, dependencies, and entry point.
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- **`dataflow.yml`** -- Example dora dataflow using the git: source format.
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## Key APIs
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- **dora Python API** (`dora`): `Node()`, `node.send_output()`, event iteration via `for event in node`.
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- **xArm SDK** (`xarm.wrapper.XArmAPI`): `connect()`, `motion_enable()`, `set_mode()`, `set_state()`, `set_position()`, `move_gohome()`, `get_position()`, `get_servo_angle()`, `set_vacuum_gripper()`.
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- Output data is sent as PyArrow arrays with metadata dicts.
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## Tools
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- **Issue tracker:** Gitea. Use the Gitea MCP tools (`mcp__gitea__*`) to read and manage issues, pull requests, and other repository operations.
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## Rules
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- Do not mention AI tools in commit messages or documentation.
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- This controls a real robot. Test changes carefully and preserve safety checks.
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