Add Ultimate Auto Sampler Suite

[JasonHoku]

ComfyUI Ultimate Auto Sampler Config Grid Testing Suite

A professional-grade benchmarking and "IDE-like" testing suite for ComfyUI.

Stop guessing which Sampler, Scheduler, or CFG value works best. This custom node suite allows you to generate massive Cartesian product grids, view them in an interactive infinite-canvas dashboard, and refine your settings with a "Revise & Generate" workflow without ever leaving the interface.

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🌟 Key Features

🚀 Powerful Grid Generation

• Cartesian Product Engine: Automatically generates every permutation of your input settings. Test 2 Samplers × 3 Schedulers × 2 CFG scales in one go.
• Smart Caching: Intelligently skips model and LoRA reloading when consecutive runs share the same resources, making generation instant for parameter tweaks.
• VAE Batching: Includes a vae_batch_size input to batch decode images, significantly speeding up large grid runs.

🎨 Interactive Dashboard (The "IDE")

• Infinite Canvas: Pan and Zoom (Google Maps style) to inspect hundreds of images easily.
• Smart Filtering: Toggle visibility by Sampler, Scheduler, or LoRA type.
• Sorting: Instantly sort your grid by Newest or Fastest (generation time).
• Session Management: Save and Load previous testing sessions directly from the UI.

⚡ The "Revise & Generate" Workflow

• One-Click Revision: Click "REVISE" on any image to open a detail view.
• Instant Tweak: Adjust CFG, Steps, or Sampler for just that specific image.
• Generate New: A "GENERATE NEW" button queues the new variation immediately without needing to disconnect wires or change the main batch.
• Similarity Reel: The revision modal shows a side-scrolling reel of all other images that share the same seed, allowing for perfect A/B comparison.

🧹 Curation & JSON Export

• Rejection System: Click the red "✕" on bad generations to hide them.
• Dual JSON Bars:
  • Green Bar: Automatically groups all accepted configs into a clean, optimized JSON array ready for copy-pasting.
  • Red Bar: Collects all rejected configs so you know exactly what settings to avoid.

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📦 Installation

1. Navigate to your ComfyUI custom_nodes directory:

   cd ComfyUI/custom_nodes/

2. Clone this repository:

   git clone [https://github.com/YOUR_USERNAME/ComfyUI-Ultimate-Auto-Sampler-Config-Grid-Testing-Suite.git](https://github.com/YOUR_USERNAME/ComfyUI-Ultimate-Auto-Sampler-Config-Grid-Testing-Suite.git)

3. Restart ComfyUI.

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🛠️ Usage Guide

1. The Nodes

This suite consists of two main nodes found under the sampling/testing category:

1. Sampler Grid Tester (Generator): The engine. It handles model loading, grid generation, and saving.
2. Grid Dashboard (Viewer): The display. It renders the HTML output.

Basic Setup:

• Add the Generator node.
• Connect your Checkpoint, CLIP, and VAE (optional, see "Hybrid Inputs" below).
• Add the Viewer node.
• Connect the dashboard_html output from the Generator to the input of the Viewer.

2. The JSON Configuration

The configs_json widget determines your grid. It accepts an array of objects. All fields support single values or arrays.

Example:

[
  {
    "sampler": ["euler", "dpmpp_2m"],
    "scheduler": ["normal", "karras"],
    "steps": [20, 30],
    "cfg": [7.0, 8.0],
    "lora": "None",
    "str_model": 1.0,
    "str_clip": 1.0
  }
]

This example generates 8 images (2 samplers × 2 schedulers × 2 steps × 1 cfg).

Here are some combos you can try!

🏆 Group 1: The "Gold Standards" (Reliable Realism)

Tests the 5 most reliable industry-standard combinations. 5 samplers x 2 schedulers x 2 step settings x 2 cfgs = 40 images

[
  {
    "sampler": ["dpmpp_2m", "dpmpp_2m_sde", "euler", "uni_pc", "heun"],
    "scheduler": ["karras", "normal"],
    "steps": [25, 30],
    "cfg": [6.0, 7.0],
    "lora": "None",
    "str_model": 1.0,
    "str_clip": 1.0
  }
]

🎨 Group 2: Artistic & Painterly

Tests 5 creative/soft combinations best for illustration and anime. 5 samplers x 2 schedulers x 3 step settings x 3 cfgs = 90 images

[
  {
    "sampler": ["euler_ancestral", "dpmpp_sde", "dpmpp_2s_ancestral", "restart", "lms"],
    "scheduler": ["normal", "karras"],
    "steps": [20, 30, 40],
    "cfg": [5.0, 6.0, 7.0],
    "lora": "None",
    "str_model": 1.0,
    "str_clip": 1.0
  }
]

⚡ Group 3: Speed / Turbo / LCM

Tests 4 ultra-fast configs. (Note: Ensure you are using a Turbo/LCM capable model or LoRA). 4 samplers x 3 schedulers x 4 step settings x 2 cfgs = 96 images

[
  {
    "sampler": ["lcm", "euler", "dpmpp_sde", "euler_ancestral"],
    "scheduler": ["simple", "sgm_uniform", "karras"],
    "steps": [4, 5, 6, 8],
    "cfg": [1.0, 1.5],
    "lora": "None",
    "str_model": 1.0,
    "str_clip": 1.0
  }
]

🦾 Group 4: Flux & SD3 Specials

Tests 4 configs specifically tuned for newer Rectified Flow models like Flux and SD3. 2 samplers x 3 schedulers x 3 step settings x 2 cfgs = 36 images

[
  {
    "sampler": ["euler", "dpmpp_2m"],
    "scheduler": ["simple", "beta", "normal"],
    "steps": [20, 25, 30],
    "cfg": [1.0, 4.5],
    "lora": "None",
    "str_model": 1.0,
    "str_clip": 1.0
  }
]

🧪 Group 5: Experimental & Unique

Tests 6 weird/niche combinations for discovering unique textures. 6 samplers x 4 schedulers x 5 step settings x 4 cfgs = 480 images

[
  {
    "sampler": ["dpmpp_3m_sde", "ddim", "ipndm", "heunpp2", "dpm_2_ancestral", "euler"],
    "scheduler": ["exponential", "normal", "karras", "beta"],
    "steps": [25, 30, 35, 40, 50],
    "cfg": [4.5, 6.0, 7.0, 8.0],
    "lora": "None",
    "str_model": 1.0,
    "str_clip": 1.0
  }
]

3. Hybrid Inputs (Optional)

The Generator node features built-in widgets for Model Selection and Prompts, but also has Optional Inputs for flexibility:

• Standalone Mode: Use the dropdown menu to select a checkpoint and type prompts into the text boxes.
• Hybrid Mode: Connect a MODEL, CLIP, VAE, or CONDITIONING wire. The node will automatically ignore the internal widget and use the connected input instead.

4. Performance Tuning (vae_batch_size)

• Default (4): Good for 8GB-12GB VRAM cards.
• High (12-24): For 24GB+ VRAM cards. Decodes many images at once for speed.
• Unlimited (-1): Decodes ALL images for a resolution at once. Fastest, but risks Out of Memory (OOM) errors on large batches.

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🖥️ Dashboard Interface

Toolbar

• Session Input: Type a session name (folder name) and click LOAD to view previous results without re-generating.
• Sort: Toggle between sorting by ID (Newest) or Duration (Fastest).
• Filters: Click the colored buttons (Green/Blue/Orange) to toggle visibility of specific parameters.

JSON Bars (Bottom)

• Green Bar (Accepted): Contains a "Smart Grouped" JSON of all currently visible images. Click to select all, then copy-paste back into the configs_json widget to refine your batch.
• Red Bar (Rejected): Contains the configs of images you deleted with the "✕" button.

Revision Modal

Clicking REVISE on a card opens the studio view:

1. Left: Full-resolution preview.
2. Right: Input fields to tweak settings for this specific image.
3. Bottom: "Related Variants" reel showing other images with the same seed.
4. GENERATE NEW: Queues the specific config you just edited.

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⚠️ Troubleshooting

• "Session not found": Ensure the session_name matches a folder inside ComfyUI/output/benchmarks/.
• Browser Zoom: The dashboard uses an infinite canvas. If scrolling zooms the entire webpage instead of the canvas, ensure your mouse is hovering over the grid area.
• OOM Errors: If you crash during decoding, lower the vae_batch_size to 1 or 2.

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📜 License

MIT License. Feel free to use, modify, and distribute.

[ltdrdata]

1. please remove the __pycache__ dir from the repo and add it to the .gitignore

2. session_name should be sanitized.

https://github.com/JasonHoku/ComfyUI-Ultimate-Auto-Sampler-Config-Grid-Testing-Suite/blob/95a59ae161e2d82b9cf57c9b9baba769583d3f21/dashboard_node.py#L30

https://github.com/JasonHoku/ComfyUI-Ultimate-Auto-Sampler-Config-Grid-Testing-Suite/blob/95a59ae161e2d82b9cf57c9b9baba769583d3f21/sampler_node.py#L85

[JasonHoku]

All fixed!

• pycache removed and added to gitignore

• All os operations are now sanitized with:
  re.sub(r'[^\w\-]', '', session_name)

Thank you so much!