KMH158-QLU/test_dataset_final

UI Automation Dataset (Multi-Video)

107 examples from 1 videos - UI automation tasks from screen recordings.

Dataset Structure

Each entry contains:

• video_id: Sequential ID for each video (video_001, video_002, etc.)
• step: Step number within that video (0, 1, 2, ...)
• system: System prompt for the GUI agent
• user: Task instruction + previous actions
• assistant: Model's reasoning and action
• image: Screenshot of the UI state

Usage

from datasets import load_dataset

ds = load_dataset("KMH158-QLU/test_dataset_final")

# Access by video
for video_id in set(ds['train']['video_id']):
    video_data = ds['train'].filter(lambda x: x['video_id'] == video_id)
    print(f"Video {video_id}: {len(video_data)} steps")

# Or iterate all examples
for item in ds['train']:
    print(f"{item['video_id']} - Step {item['step']}: {item['assistant'][:50]}...")

Growing Dataset

This dataset supports multiple videos. Each video gets a unique ID (video_001, video_002, etc.). New videos are automatically appended with the next available ID.