| # OmniAgentBench Dataset Card |
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|
| ## Overview |
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| **OmniAgentBench** is a comprehensive benchmark for evaluating multimodal agents under realistic "wild" conditions including speech input, acoustic noise, and complex multi-turn interactions. |
|
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| **Organization:** `omniagentbench` |
| **Dataset:** `OmniAgentBench` |
| **Total Size:** 27.1 GB |
| **Contributors:** Hodfa71, acbueff |
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|
| --- |
|
|
| ## Dataset Structure |
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| The dataset is organized into **separate benchmark folders** at the root level: |
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| ``` |
| OmniAgentBench/ |
| ├── 📁 data/ # Dataset metadata and manifests |
| ├── 📁 dataset/mpcc/ # MPCC dataset files (tabular) |
| ├── 📁 gui_odyssey/ # ⭐ GUI Odyssey (NEW - 1,800 wild audio samples) |
| │ ├── General_Tool/ |
| │ ├── Information_Management/ |
| │ ├── Multi_Apps/ |
| │ ├── Media_Entertainment/ |
| │ ├── Social_Sharing/ |
| │ ├── Web_Shopping/ |
| │ └── screenshots/ # GUI Odyssey screenshots ONLY |
| ├── 📁 images/mpcc/ # ⚠️ MPCC screenshots ONLY (5,700 files) |
| ├── 📁 mpcc/ # MPCC audio and manifests |
| │ ├── manifest.json |
| │ └── *.wav (2,700+ audio files) |
| ├── 📁 wild/ # Shared noise resources (MUSAN, etc.) |
| └── 📁 wild_long_scattered/ # Additional wild variations |
| ``` |
|
|
| --- |
|
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| ## ⚠️ Important: Folder Separation |
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| **The `images/` folder contains ONLY MPCC screenshots!** |
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| | Folder | Benchmark | Content | |
| |--------|-----------|---------| |
| | `images/mpcc/` | **MPCC** | 5,700 screenshots (flight schedules, calendars, meetings) | |
| | `gui_odyssey/screenshots/` | **GUI Odyssey** | 1,950 mobile app screenshots | |
| | `gui_odyssey/General_Tool/screenshots/` | **GUI Odyssey** | Per-category screenshots | |
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| **They are NOT mixed** - each benchmark has its own dedicated folder. |
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|
| --- |
|
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| ## Benchmarks |
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| ### 1. MPCC (Multi-Modal Planning and Control Challenge) |
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| Constraint planning over visual schedules (flights, calendars, meetings). |
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| **Location:** `mpcc/`, `images/mpcc/`, `dataset/mpcc/` |
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| **Contents:** |
| - Audio: 300 speech samples across 3 tasks × 3 difficulties |
| - Images: 5,700 screenshots (schedules, flight info, calendars) |
| - Text: Structured task instructions with JSON output format |
| - Ground Truth: Optimal plans with constraint satisfaction labels |
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| **Format:** |
| ```python |
| { |
| "audio_file": "mpcc_flight_easy_1.wav", |
| "image_paths": ["images/mpcc/flight_easy_1_img1.jpg"], |
| "text_instruction": "Find flights from London to Vienna...", |
| "gold_answer": {"flight_way": "...", "price": 291} |
| } |
| ``` |
|
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| --- |
|
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| ### 2. GUI Odyssey (NEW - Wild Audio) |
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| Cross-app mobile GUI navigation with wild audio inputs. |
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| **Location:** `gui_odyssey/` |
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| **Contents:** |
| - **Audio:** 1,800+ wild samples (300 per category × 6 categories) |
| - TTS-generated with Qwen3-TTS |
| - Acoustic noise: coffee_shop, convention_hall, outdoor, etc. |
| - SNR: 5dB, 10dB, 15dB |
| - **Images:** 1,950 mobile app screenshots |
| - **Text:** Task instructions (spoken in audio) |
| - **Ground Truth:** Click coordinates, text inputs, scroll actions |
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| **Categories:** |
| - General_Tool (300 samples) |
| - Information_Management (300 samples) |
| - Web_Shopping (400 samples) |
| - Multi_Apps (300 samples) |
| - Media_Entertainment (400 samples) |
| - Social_Sharing (300 samples) |
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| **Format per sample:** |
| ```python |
| { |
| "sample_id": "0182869798349621_step2", |
| "instruction": "Use Bloomberg to search for Pfizer stock news...", |
| "audio_path": "gui_odyssey/General_Tool/audio/0182869798349621_step2_summer_outdoor_snr15.wav", |
| "screenshot_path": "gui_odyssey/screenshots/General_Tool/0182869798349621_2.png", |
| "gt_action": "CLICK", |
| "gt_x": 351.0, |
| "gt_y": 54.0, |
| "gt_all_steps": "[...full episode with 11 steps...]" # JSON string |
| } |
| ``` |
|
|
| --- |
|
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| ## Usage Examples |
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| ### Load MPCC |
| ```python |
| from datasets import load_dataset |
| |
| # Load MPCC manifest |
| import json |
| with open("mpcc/manifest.json") as f: |
| mpcc_data = json.load(f) |
| |
| # Access sample |
| sample = mpcc_data["mpcc_flight_easy_1"] |
| audio = sample["audio_file"] # Path to .wav |
| images = sample["image_paths"] # List of image paths |
| ``` |
|
|
| ### Load GUI Odyssey |
| ```python |
| import pandas as pd |
| from huggingface_hub import hf_hub_download |
| |
| # Download parquet |
| parquet_path = hf_hub_download( |
| repo_id="omniagentbench/OmniAgentBench", |
| filename="gui_odyssey/General_Tool/gui_odyssey_General_Tool_wild.parquet", |
| repo_type="dataset" |
| ) |
| |
| # Load |
| df = pd.read_parquet(parquet_path) |
| |
| # Access sample |
| row = df.iloc[0] |
| print(row["instruction"]) # Text instruction |
| print(row["audio_path"]) # Path to audio |
| print(row["screenshot_path"]) # Path to screenshot |
| print(row["gt_action"]) # Ground truth: CLICK/TEXT/SCROLL |
| ``` |
|
|
| ### Access Audio and Images |
| ```python |
| from huggingface_hub import hf_hub_download |
| |
| # MPCC audio |
| audio_path = hf_hub_download( |
| repo_id="omniagentbench/OmniAgentBench", |
| filename="mpcc/mpcc_flight_easy_1.wav", |
| repo_type="dataset" |
| ) |
| |
| # MPCC image |
| image_path = hf_hub_download( |
| repo_id="omniagentbench/OmniAgentBench", |
| filename="images/mpcc/calendar_easy_0_img1.jpg", |
| repo_type="dataset" |
| ) |
| |
| # GUI Odyssey audio |
| audio_path = hf_hub_download( |
| repo_id="omniagentbench/OmniAgentBench", |
| filename="gui_odyssey/General_Tool/audio/0182869798349621_step0_coffee_shop_snr5.wav", |
| repo_type="dataset" |
| ) |
| |
| # GUI Odyssey screenshot |
| screenshot_path = hf_hub_download( |
| repo_id="omniagentbench/OmniAgentBench", |
| filename="gui_odyssey/screenshots/General_Tool/0182869798349621_0.png", |
| repo_type="dataset" |
| ) |
| ``` |
|
|
| --- |
|
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| ## Statistics |
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| | Benchmark | Audio Files | Images | Size | Samples | |
| |-----------|-------------|--------|------|---------| |
| | MPCC | 2,700+ | 5,700 | ~10 GB | 300 speech | |
| | GUI Odyssey | 1,900+ | 1,950 | ~3 GB | 1,800 wild | |
| | **Total** | **4,600+** | **7,650** | **~27 GB** | **2,100+** | |
|
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| --- |
|
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| ## Ground Truth Format |
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| ### MPCC |
| - **Task Type:** Constraint planning |
| - **Output:** JSON with flight_way/schedule + price |
| - **Evaluation:** Feasible rate, optimal rate |
| |
| ### GUI Odyssey |
| - **Task Type:** Mobile GUI navigation |
| - **Output:** Action (CLICK/TEXT/SCROLL) + coordinates |
| - **Evaluation:** Action accuracy, coordinate error |
| |
| --- |
| |
| ## Citation |
| |
| ```bibtex |
| @dataset{omniagentbench_2026, |
| title = {OmniAgentBench: Wild Multimodal Agent Benchmark}, |
| author = {Hoda Fakharzadeh and Team}, |
| year = {2026}, |
| publisher = {HuggingFace Datasets}, |
| url = {https://huggingface.co/datasets/omniagentbench/OmniAgentBench} |
| } |
| ``` |
| |
| --- |
| |
| ## Contact |
| |
| For issues or questions, please open an issue on the OmniAgentBench repository. |
| |
