COMMAND.md

name	new-dataflow
description	Create a new dora dataflow project with common templates

/new-dataflow Command

Create a new dora dataflow project with pre-configured templates.

Usage

/new-dataflow <name> [--type <template>] [--lang <language>]

Arguments

Argument	Description	Default
<name>	Project name	required
--type	Template type	basic
--lang	Language	python

Templates

basic

Simple camera + visualization:

nodes:
  - id: camera
  - id: visualize

vision

Object detection pipeline:

nodes:
  - id: camera
  - id: detector
  - id: visualize

audio

Speech-to-speech pipeline:

nodes:
  - id: microphone
  - id: vad
  - id: whisper
  - id: llm
  - id: tts
  - id: speaker

robot

Robot teleoperation:

nodes:
  - id: leader
  - id: follower
  - id: camera
  - id: recorder

vlm

Vision-language interaction:

nodes:
  - id: camera
  - id: vlm
  - id: visualize

Workflow

1. Create project directory
2. Generate dataflow.yml from template
3. Create custom node stubs if needed
4. Print next steps

Example

/new-dataflow my-robot --type vision

Creates:

my-robot/
├── dataflow.yml
└── README.md

With dataflow.yml:

nodes:
  - id: camera
    build: pip install opencv-video-capture
    path: opencv-video-capture
    inputs:
      tick: dora/timer/millis/33
    outputs:
      - image
    env:
      CAPTURE_PATH: "0"
      IMAGE_WIDTH: "640"
      IMAGE_HEIGHT: "480"

  - id: detector
    build: pip install dora-yolo
    path: dora-yolo
    inputs:
      image: camera/image
    outputs:
      - bbox
    env:
      MODEL: yolov8n.pt

  - id: visualize
    build: pip install dora-rerun
    path: dora-rerun
    inputs:
      image: camera/image
      boxes2d: detector/bbox

Next Steps

After creating:

cd my-robot
dora build dataflow.yml --uv
dora run dataflow.yml

Custom Templates

Create custom templates by modifying the generated dataflow.yml:

1. Add/remove nodes
2. Adjust environment variables
3. Change connections
4. Add custom nodes