Why Livebound

A collection that grows brings the same problems back, over and over: folders you have lost track of, images you are not sure you already posted, a model you can no longer identify months later. Nineteen of them are below, each with what Livebound actually does about it.

I have so many images that I lose track of my own collection

Problem. I keep generating images over days or weeks. Eventually I have hundreds of folders and thousands of files on disk, and I no longer know exactly what is there or which images I still wanted to publish.

Livebound. Livebound scans the image folders you choose and presents the collection as a local gallery. You do not have to open every folder separately. Search, filters and monitored folders help you find new and relevant images again, then turn a selection into a post.

I probably have duplicates or near-duplicates in my collection

Problem. The larger my collection becomes, the easier it is for duplicate files, identical images in different folders or very similar variants to accumulate. Cleaning that up manually becomes tedious.

Livebound. The Duplicate Finder helps you identify and compare exact and likely duplicate images. You can permanently delete an image, or move it to your configured trash first. Permanent deletion cannot be undone. An image in trash can be restored as long as it has not been permanently deleted.

I sometimes do not remember whether I already posted an image

Problem. When I publish regularly, I eventually lose track of which images have already appeared on CivitAI and which have not. File names and folders are not enough to answer that reliably.

Livebound. Livebound links local images to their publishing history. You can see whether an image has already been used, which local post used it and which CivitAI image or post it belongs to.

I repeat the same steps when I prepare many posts

Problem. When I prepare several posts, I keep repeating the same routine: inspect images, clean metadata, write titles and descriptions, set tags, assign resources and choose publication times.

Livebound. Livebound keeps that preparation local and brings the steps into one workflow. You can edit metadata for multiple images, apply recurring exclusions, clean prompts, prepare titles, descriptions and tags, and optionally use local LLM assistance. Posts can be prepared through Ready, then multiple completed posts can be pushed to CivitAI and scheduled as a batch.

If I notice a mistake later, I do not want to fix the same thing across many posts by hand

Problem. Sometimes I notice only after preparing several posts that I want metadata, prompt fragments, tags or another repeated detail handled differently. Repeating the same correction across many images and posts is exactly the work I want to avoid.

Livebound. You can define global metadata and prompt exclusions in Settings. When one of those rules changes, it is applied again when already prepared images are materialised for a later upload. For targeted changes, you can also edit metadata and prompts across a selected group of images and preview the result before applying it. Post tags and other post-level values remain editable on the local post.

For example, a prompt exclusion can remove LoRA syntax from the public prompt while a LoRA that was already recognised, including its weight, remains available as a separate resource attribution. The original image file is not rewritten and an exclusion does not retroactively edit content that has already been uploaded.

I want to prepare posts completely before anything is uploaded to CivitAI

Problem. If part of my work lives locally and another part already exists remotely, it quickly becomes unclear what is actually finished when I am preparing several posts at once.

Livebound. Livebound lets you keep the preparation local first. You can review images, metadata, title, description, tags, resources and timing before CivitAI is involved. When the post is genuinely ready, move it to Ready and start the push from there.

I want to know before an upload whether I forgot something

Problem. With several prepared posts, I do not want to discover halfway through an upload that a file is missing, a setting is invalid or the post was not actually ready.

Livebound. Livebound runs a preflight before the push. You see blockers and relevant warnings before remote changes are made, so a problem can be fixed while the post is still local.

My images come from different generators and their metadata all looks different

Problem. Depending on whether I use ComfyUI, Automatic1111, Forge, Fooocus or another tool, prompts, seeds, models, LoRAs and other generation data arrive in different shapes. The more tools I use, the harder that becomes to reason about consistently.

Livebound. Livebound reads multiple generator families and normalises their generation data for the publishing workflow. You get upload metadata in a shape CivitAI can parse more consistently, concrete model and LoRA attribution kept separate from prompt presentation, and public-facing text you can clean without rewriting the source image. Supported inputs include Automatic1111 / Forge, ComfyUI, CivitAI, SwarmUI, Fooocus variants, InvokeAI, NovelAI, TensorArt and Hugging Face Spaces. When a value cannot be identified reliably, Livebound keeps it unknown instead of inventing an attribution for you.

With older images I often no longer know which exact model or LoRA version I used

Problem. Months later, the metadata may contain only a local file name or a short reference. That does not necessarily tell me which concrete CivitAI model version it came from.

Livebound. Livebound can scan your local model and LoRA directories, identify files by hash and bind them to concrete CivitAI model versions. Ambiguous matches stay visible so you can bind them manually instead of having Livebound guess. That gives your later resource attribution a specific version rather than only a remembered name.

My prompts contain technical fragments that I do not want in the published prompt

Problem. A generation prompt can contain technical syntax such as <lora:...> that mattered to the generator but does not necessarily belong in the text I want to present publicly.

Livebound. You can clean those fragments from the prompt used for the upload while keeping already recognised model or LoRA assignments and weights separately available as resource attribution.

One useful global prompt exclusion is:

,\s*<lora:[^:>]+:[+-]?(?:\d+(?:\.\d+)?|\.\d+)>

For example, portrait, <lora:myLora_v7:0.8> becomes portrait. The recognised LoRA and its weight 0.8 remain separate from that prompt edit. Once the rule is stored in Settings, it is applied when matching images are prepared for upload, including images that were already prepared locally before the rule changed.

This expression deliberately expects a leading comma. A LoRA tag at the very start of the prompt without that comma is not matched by this example. Prompt cleaning changes the upload text, not the original image file and not content already uploaded to CivitAI.

Problem. Generation metadata is useful, but I may not want every field or every prompt fragment to be part of the upload. At the same time, I do not want a cleanup rule to silently destroy useful model or LoRA attribution.

Livebound. Treat three controls as separate decisions. Prompt exclusions clean the prompt text and, by themselves, keep already recognised resource assignments and weights. Metadata exclusions decide which fields are present in the upload copy at all; removing the evidence a resource mapping depends on can therefore remove that attribution too. CivitAI’s metadata visibility setting controls what CivitAI displays. These are different layers, so you can choose them deliberately instead of treating all metadata handling as one switch.

I spend too much time assigning models and LoRAs correctly

Problem. When I publish many images, I want the correct models and LoRAs linked so the right creators receive attribution. Checking every image and every model version manually takes time.

Livebound. Livebound can connect recognised resources to concrete CivitAI model versions and send those bindings as resource attribution during publishing. You can also bind a post directly to a CivitAI model page when that is part of the post you are preparing.

I want to plan several days or weeks ahead

Problem. My images may already be finished, but I do not want to publish them all at once or repeat the same publishing routine every day.

Livebound. Livebound supports absolute and relative publication times. You can prepare a series using fixed timestamps or offsets such as +1 day and +12 hours, then keep those posts ready for their intended schedule.

I lose track of the available times when I plan many posts

Problem. Once several posts are spread across different days, I find myself calculating which slot is free and when the next post should go out.

Livebound. The calendar shows your posts together with their publication times, so occupied days and upcoming posts remain visible in context. You can stagger several locally prepared posts from a chosen start with a fixed interval between them. Livebound previews the resulting times before you accept the plan, so you do not have to calculate every timestamp separately.

If an upload is interrupted, I do not always know what already happened on CivitAI

Problem. When a connection drops or CivitAI returns an error during a push, the uncomfortable question is whether a remote post was already created. Simply pressing the button again is not a safe answer if that could create a duplicate.

Livebound. Livebound records the progress of your push and can resume interrupted work. If creation may have happened but the result is uncertain, Livebound checks the actual CivitAI state before another post is created. Preflight, resume and reconciliation keep you from turning a failed request into a blind second attempt.

After scheduling I still keep checking whether everything really went live

Problem. Even after planning several posts ahead, I tend to check manually whether they were actually published and whether the remote state still matches what I expected.

Livebound. You can reconcile local posts with CivitAI again later. Changes such as Draft, Scheduled, Published, a missing remote post or another mismatch become visible locally so you do not have to open every post on CivitAI one by one.

Some of my older images now exist only on CivitAI

Problem. I may have generated images directly on CivitAI, lost local files or created older posts before I organised my local collection properly. Rebuilding that history by hand would be a lot of work.

Livebound. Livebound can discover and adopt existing posts from your own CivitAI account. Remote images can be fetched into the local location you choose and linked back to their publishing history and known resource assignments. Sync and adoption therefore help you bring remote-only history back into the same local workflow.

After publishing, I still have finished images mixed in with everything I am working on

Problem. Published images can remain in the same folders as new or unposted generations. Over time it becomes harder to tell what is finished and what still belongs to the active publishing backlog.

Livebound. After publication has been verified, you can ask Livebound to move the related files into your configured image archive by explicitly starting that archive action. Their publishing history stays linked while your active working folders can remain focused on current work.

Months later I cannot remember exactly what happened to an image

Problem. With older images I may need to answer several questions at once: Did I post it? Which post used it? Is the remote post still there? Did it change later? Does the local file still exist? Is this work already finished for me?

Livebound. Livebound keeps your local posts, images and remote counterparts connected so you can follow the history from the local library through publishing, later reconciliation and optional file archiving.

Two meanings of archive stay separate. An archived post is a Livebound post state that removes the post from your active board and calendar. The image archive is a folder on disk where files from verified published posts can be moved by an explicit archive run. One changes how your post is organised in Livebound; the other moves image files on disk.

The core idea

Livebound is built for the part of a creator’s workflow between “I have a large collection of finished images” and “these images are prepared, scheduled, published and still understandable months later.” Instead of treating folders, metadata, posts, scheduling, publishing history and remote state as separate jobs, Livebound connects them in one local publishing workflow.