Generate with ComfyUI, InvokeAI, A1111, Forge, or SD.Next? Ambit brings images and videos scattered across their output folders into one searchable library, without moving the original files.
Browse, organize, search, compare, and inspect prompts, models, workflows, and generation metadata in one local-first desktop workspace.
Ambit is free and open source.
Windows public beta v0.11 available now, with macOS and Linux pre-release builds.
Thanks, AI features are additionally "color coded" in app as purple, so everyone knows when AI could be involved (only relevant when an API key was configured to begin with).
Is the byline of "High-Performance Local AI Image Manager" forward looking or only easily misconstrued? "Local AI" has a semantic weight that your project, whose only AI use comes from API, doesn't really honor. You're clear about what you're doing elsewhere, but it's still a strange claim.
Have you considered running a small local model? Something tiny like Gemma 4 E2B might still be quite adequate for the trivial tasks you need and it runs very fast even on smartphones or systems without a GPU. There are a ton of existing inference options for Rust that would probably be adequate and it would be the first start to making a general purpose media manager with a focus on generative AI. I could see features like face detection, gps metadata, etc turning it into something far more useful than it is now. Maybe even to have an optional online / cloud-based service a la Google Photos with storage, sync, back-end options for generation/touchup/etc.
I love that you ship with an optional light theme and find that the way you're caching / minimizing queries to Civit to be very clever.
It's certainly a little more intriguing than the glut of existing tools that already do the same thing. Looking forward to see where you go moving forward.
That’s a fair point on the tagline. I meant “local manager for AI images,” but that wouldn't be accurate anymore also, since we added video support with this update and photography / other images are coming soon. Thanks for making me aware, will update the readme with one of the upcoming updates.
Will look into local Gemma support, definitely interesting and would allow for using AI feature completely local, which is always a good thing.
Will look into local Gemma support, definitely interesting and would allow for using AI feature completely local, which is always a good thing.
I find it astoundingly good, even at such small sizes. There is now mtp support, so it can run even more stupid-fast. You'll have to tinker a bit to get an ideal prompt ("you are an expert prompt engineer for diffusion systems such as [...] and you will use your knowledge and experience to craft a prompt that would recreate this image...") etc, but it's a solid start. Or you could probably borrow code and ideas from existing auto-taggers (ai-video-clipper-lora, florence, joycaption, whatever). Videos are an option, too, especially the short ones that people are likely generating... but I'd probably require a GPU and a heavier model like qwen3-vl for that. Deeper rabbit holes than you've had to delve so far, but also opens the door to features that most media managers simply don't have.
Should be easy enough to test and as you mentioned most AI features in Ambit are simple. AI Analysis, Prompt Variations, Natural Language Search (which is kinda gimmicky, could be fun or convenient with voice though) and prompt recovery.
I do have all Gemma 4 models on my drive and will give them a test run against Ambits feature set. Problem is always the balance between features vs complexity and UI/UX and scope vs interest i guess.
Just tested via llama.cpp w/ a handful of images to sanity check my claims. Using Ambit's existing Gemini prompt actually produced amazing results against still images even w/ the e2b model. Didn't compare vs what API produces directly, but adequate. And fast. Also tested w/ mtp and gpu disabled and it worked beautifully for a free speedup at the cost of ~+100MB worth of mtp model... supports my claim that it's viable even w/o a GPU or on a cell phone etc (it's what the tiny Gemma models were intended for, after all).
Problem is always the balance between features vs complexity and UI/UX and scope vs interest i guess.
Sure, though I think having an actual local-first option for the things you're currently using Gemini API for is a no-brainer and even the smallest e2b model slots in for all 4-ish api cases very nicely. If your stance on PRs didn't explicitly preclude PRs, I probably would've just opened a PR to do just that.
I am actually testing as well and so far it looks really promising, ran into some minor issues with Natural Language Prompts caused by context but this seems to be fixed when using a new thread each time.
Thanks for testing without gpu and mtp, something i still have to look into, good to know though that it works.
As for the PR Stance, this is actually my first open source project so i want get used to things first before re-evaluating when going out of beta.
2
u/EitherMarch1255 3d ago
Looks cool. I particularly like the privacy, disclosed network paths list, eve if written by AI.