Eric Visual Research

Agentic web research nodes for ComfyUI image generation.

Searches the web, retrieves visual references, and writes detailed grounded prompts. Platform agnostic - outputs wire into any generation model: Flux, SDXL, Qwen-Image, Hunyuan, or any node that accepts STRING and IMAGE inputs.

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Nodes

Eric Gen-Searcher

Sends your prompt to a running Gen-Searcher-8B model, which autonomously performs multi-hop web research - searching for text information, finding visual reference images, and browsing web pages - then synthesizes everything into a rich, detailed generation prompt.

Outputs:

• grounded_prompt - detailed text prompt ready for any generation node
• ref_image_1..4 - individual reference images at native aspect ratio
• reference_images - batch IMAGE tensor (all refs, letterboxed)
• search_log - human-readable record of searches performed

Eric Reference Describer

Converts reference images into text descriptions using a VL model, then merges those descriptions with the grounded prompt. Solves the "pixel contamination" problem when using web thumbnails with edit-mode models.

Outputs:

• combined_prompt - grounded prompt enriched with VL image descriptions
• descriptions_log - what the VL model said about each image

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Example Workflow

An example ComfyUI workflow is included in the workflows/ folder. Open workflows/workflow.png in ComfyUI to load it directly (the PNG embeds the full workflow JSON).

Full workflow overview

Prompting — Gen-Searcher research and grounded prompt

The Gen-Searcher node takes your brief subject description, performs multi-hop web research (text search, image search, optional page browsing), and outputs a rich grounded prompt along with up to four reference images.

Visual search results

Reference images retrieved from the web and returned as individual IMAGE outputs and a combined batch tensor.

Generation

The grounded prompt and (optionally) the combined reference description feed into the generation node of your choice.

Post-processing — sharpening and segmentation

Optional post-processing stage using Richardson-Lucy deconvolution, Smart Sharpening, subject segmentation masking (SAM + GroundingDINO), depth estimation, and metadata embedding before saving.

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Typical Workflows

With any text-to-image model

[EricGenSearcherNode]
  → grounded_prompt ──→ any text prompt input (Flux, SDXL, etc.)
  → ref_image_1..4  ──→ any image input (for reference/IP-adapter/etc.)

With pure text-to-image (no image input, maximum quality)

[EricGenSearcherNode]
  → grounded_prompt ──┐
  → ref_image_1..4  ──→ [EricReferenceDescriber] → combined_prompt → any t2i node

With Qwen-Image-Edit (reference-guided generation)

[EricGenSearcherNode]
  → grounded_prompt ──→ [EricQwenGroundedGenerate]
  → ref_image_1..4  ──→ [EricQwenGroundedGenerate]

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Requirements

• Python 3.10+ (included with ComfyUI)
• torch (included with ComfyUI)
• Pillow (included with ComfyUI)
• SGLang server running Gen-Searcher-8B - see docs/SERVER_SETUP.md
• Serper API key - free at https://serper.dev (2,500 queries/month free)
• (Optional) Jina API key - free tier at https://jina.ai/reader/
• (Optional) gallery-dl - for downloading from Pinterest, Flickr, etc.

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Installation

1. Clone into ComfyUI custom_nodes

cd ComfyUI/custom_nodes
git clone https://github.com/EricRollei/Eric_Visual_Research

2. Configure API keys

cd Eric_Visual_Research
cp api_keys.ini.example api_keys.ini
# Edit api_keys.ini and add your Serper key

Or set environment variables:

export SERPER_API_KEY=your-key-here
export JINA_API_KEY=your-key-here   # optional

3. Set up the Gen-Searcher server

See docs/SERVER_SETUP.md for full instructions covering:

• WSL2 setup (Windows)
• CUDA toolkit installation
• SGLang installation
• Model download (~17GB)
• Starting the server

4. Restart ComfyUI

Nodes appear under Eric/VisualResearch in the node menu.

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Configuration Reference

Edit api_keys.ini in the package directory:

[api_keys]
serper = your-serper-api-key     ; required
; jina = your-jina-api-key       ; optional

[gallery_dl]
; exe    = /path/to/gallery-dl   ; optional, auto-detected
; config = /path/to/config.json  ; optional

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Gen-Searcher Node Settings

| Setting | Default | Description | |---|---|---| | agent_api_url | http://localhost:30000 | SGLang server URL | | max_hops | 8 | Max search iterations (6-10 typical) | | ref_image_count | 4 | Number of reference images to download | | enable_browse | True | Allow reading full web pages via Jina | | use_instagram | False | ⚠ Enable with dummy account only | | use_facebook | False | ⚠ Enable with dummy account only |

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Reference Describer Node Settings

| Setting | Default | Description | |---|---|---| | vl_api_url | http://localhost:30000 | VL model server URL | | description_focus | auto | What to extract from each image | | synthesis_mode | synthesize | How to combine descriptions | | max_image_dim | 512 | Resolution sent to VL model |

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Credits

• Gen-Searcher-8B - tulerfeng/Gen-Searcher (fine-tuned from Qwen3-VL-8B by the Gen-Searcher team)
• Qwen3-VL - Qwen Team, Alibaba
• SGLang - sgl-project/sglang
• Serper - https://serper.dev
• Jina Reader - https://jina.ai

Node implementation by Eric Hiss (GitHub: EricRollei)

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License

CC BY-NC 4.0 / Commercial dual license - see LICENSE.txt