Local Lora Gallery

If you have more than a dozen LoRAs, you already know the exact pain this node kills. The stock LoraLoader gives you a dropdown, so every time you want a character, a style, or a look, you scroll a list of filenames and hope the name tells you anything. The Local Lora Gallery replaces that dropdown with a card browser: your LoRAs show up as tiles with preview images, tags, search, and a stack you can pile as many LoRAs onto as you want, each with its own strength. It launched to a warm welcome on r/comfyui in August 2025, and the pitch is simple - visualization and simplicity, not feature bloat.

Why you'd reach for it

LoRAs are the dominant way to bolt a style or character onto a checkpoint - small adapter files that patch the model's cross-attention layers, stackable and weight-adjustable. The default ComfyUI experience for managing them is a text dropdown and nothing else. If you collect LoRAs the way some people collect fonts, that stops working fast. This node is the fix for "I have 400 of these and I remember three by name."

The honest caveat, from the author's own mouth: it's not the most feature-complete LoRA manager around (that title belongs to heavier tools like ComfyUI-Lora-Manager). Its advantage is that you see your library. For most people that's the part that actually matters.

How it works

The gallery is a JS frontend that reads your models/loras folder and renders a card per LoRA. Previews come from files that share the LoRA's filename - character_v3.safetensors plus character_v3.png (or a video) in the same folder. No preview file, no picture on the card, which is the single most common "it doesn't work" moment.

Your selection isn't lost between runs: it's serialized into a hidden selection_data widget that travels with the workflow JSON, and each gallery node mints its own unique ID so two workflows don't collide. When you queue, load_loras walks your stack in order and applies each enabled LoRA through ComfyUI's own LoraLoader, with per-card model and clip strengths (both default to 1.0; entries toggled off or at strength 0 are skipped). If the connected model is a Nunchaku-accelerated wrapper (Flux, Qwen, Z-Image), it transparently swaps in the Nunchaku loader instead.

Inputs and outputs

Only two required inputs - model and clip, straight from your checkpoint loader. Three outputs:

• MODEL and CLIP - wire these into your sampler / conditioning chain exactly as you would from a LoraLoader.
• trigger_words (STRING) - concatenates the trigger words of every enabled LoRA that has them. Connect it into your prompt or CLIPTextEncode so your own words don't have to carry the load.

The three things a beginner actually sets:

1. Click a card to add it to the stack, click again to remove.
2. Per-card strength - remember that 1.0 is often too hot; 0.5–0.8 is the common range.
3. Filters - name search, tag multi-select with OR/AND, and Ctrl+click the pencil to batch-edit tags.

Drag to reorder the stack (order matters when LoRAs interact), and presets save whole stacks for one-click reload.

Installing it

ComfyUI Manager is easiest: search "Local Lora Gallery" in Custom Nodes Manager and install. Manual way:

cd ComfyUI/custom_nodes
git clone https://github.com/Firetheft/ComfyUI_Local_Lora_Gallery.git

Restart ComfyUI. There's no extra Python dependency - it wraps ComfyUI's built-in LoraLoader, and it reads whatever LoRAs you already have. The optional comfyui-nunchaku plugin only adds acceleration for Nunchaku-compatible models; skip it unless you run quantized FLUX.

Troubleshooting

• No previews on any card. Add same-named image/video files next to each LoRA, or click the ☁️ sync button once per card - it computes the SHA256, looks the model up on Civitai, and downloads a 450px preview plus trigger words and the model's page URL. Needs network.
• Empty trigger_words output. Nothing's there until you sync or hand-edit the trigger words.
• Stack doesn't apply. Make sure you saved/reloaded the workflow so selection_data persisted, and that the MODEL/CLIP outputs are actually wired onward.
• Nunchaku not kicking in. It only activates when the model connected to the node is genuinely a Nunchaku wrapper; otherwise you get the standard loader, which is fine.

If your LoRA folder is big and you live in ComfyUI, this is the one you'll actually reach for. If you need deep metadata management, look at the heavier managers - but for "what did that one look like again?", nothing beats seeing it.