Daguerra turns a RunPod pod into a complete image studio. Launch the template, paste your license key and start creating.
Illustrative frames. Your own prompts produce your own images.
Deploy on RunPod with a 24 GB GPU or more, and attach an 80 GB volume.
Daguerra checks the license on the pod, offline. Add your Civitai token once.
Missing nodes and models download on first boot and are verified by hash.
Daguerra unlocks as soon as the pipeline is ready. Open port 3000.
Pick a scene and press Generate to see how a frame develops. This is a preview of the interface with illustrative frames, not a live generation.
Write your own prompts on your own GPU.
Live previews show the composition settling, so you can stop a weak run early and keep your GPU time for the good ones.
Drop a reference image and Daguerra writes a detailed prompt from it, or press Enhance to turn a short idea into a full description of framing, camera, light and setting. Read it, edit it, undo it.
Framing and subject: vertical 3:4 view of a still mountain lake at first light, low sun behind layered ridges. Camera: full-frame body, 35 mm equivalent, deep depth of field. Lighting: soft low sun with warm haze above the ridges. Finish: muted tones, light sensor grain, not glossy.
Upload a LoRA or pick one already on your volume. Set its strength and trigger word once, and keep the same look across a whole series of images.
One button under a finished image gives it the look of a phone, a compact or a DSLR. Slide across the picture to compare before and after, and download either version.
Every result lands in a history strip under the viewer. Move between images with the arrow keys, download, copy the prompt or reuse the settings.
The interface adapts to small screens, with ComfyUI and JupyterLab one tap away. A News page in the app lists what changed in every release.
The template requires CUDA 12.8 or newer. First boot takes roughly 10 to 30 minutes while models download.
Written by people who use Daguerra. Every review is read before it is published.
No. The pod runs in your own RunPod account, so RunPod bills you directly. A license covers the Daguerra software.
You receive a key by email after purchase and paste it into Daguerra, or set it as LICENSE_KEY on the template. It is verified on the pod, with no license server.
From their original sources, Civitai and Hugging Face, with your own tokens. Each model keeps its own licence, which you accept with your own account.
Yes. ComfyUI and JupyterLab run on the same pod and are linked from the Daguerra header.
They are generated and stored on your pod, in your volume. Daguerra does not upload them anywhere.
The template does not depend on a datacenter. Pick another GPU or region on RunPod and attach a volume in that region.
Get a license key and deploy the template on your RunPod account.