Use manually-entered and AI-generated descriptions to build organized photo albums, multimedia portfolios, and meme pages.
- Simple utility. Creates searchable media captions, in browser.
- Offline and private. Or optionally use OpenAI or Google.
- Internet-ready. Can publish album/portfolio as a website.
- Light wight. Does not require torch. 4GiB VRAM.
- Free and open-source. NO WARRANTIES. See LICENSE.
Who doesn't have a folder of their favorite memes? But it becomes tedious scrolling through pages and pages of memes, photos, and audio clips to find the right one for every occasion.
New Features.
- Omni support - Generate AI captions for audio files as well as images.
aichat.pyserver - supports multimodal text, image, and audio input.
Enjoying it so far, or want more features? Support development. (PayPal donation link).
git clone https://github.com/themanyone/FindAImage.git
cd FindAImageOr, if it's already downloaded, git pull.
To keep requirements from potentially messing up your default python setup, and to speed things up, you might want to install and use uv to create a virtual environment.
sudo dnf -y install uv
uv venv -p python3.13 .venv
source .venv/bin/activate
uv pip install -r requirements.txtExport OPENAI_API_KEY to enable ChatGPT. Edit .bashrc, or another startup file to make it permanent.
export OPENAI_API_KEY=<my API key>- Sign up for a GOOGLE_API_KEY
pip install -q -U google-generativeaiexport GENAI_KEY=<YOUR API_KEY>
A local server is our preferred way to generate captions, avoid censorship, and keep everything private. Let's build a local GPU-accelerated AI model server.
Build llama.cpp according to their instructions. Compile it with the type of acceleration that supports your hardware, if possible. Prefer CUDA for Nvidia GPU cards.
If you have more than 4GB VRAM, you can remove -ngl option to offload all layers to GPU. We are using a different port than normal for this dedicated server. Feel free to change it, and modify the chat clients with the new port.
- Text & image (Download any GGUF. We are using IQ4_NL quantized model, about 3GiB).
- We use -a "model-alias" with "llava", "vision", "vox" or "omni" to tell our program to use those capabilities.
- We also limit token generation to 200 to prevent these models from running on and overheating.
Vision/LLAVA. Caption your images.
llama-server -ngl 16 -hf unsloth/Qwen2.5-VL-3B-Instruct-GGUF:IQ4_NL --port 8087 -n 200 -a "Qwen2.5-vision"
Text & audio. Caption audio, not images. (just over 2GiB download).
llama-server -ngl 17 -hf ggml-org/ultravox-v0_5-llama-3_2-1b-GGUF --port 8087 -n 200 -a "Ultravox"
Omni models. Support both image & audio captions.
llama-server -ngl 16 -hf ggml-org/Qwen2.5-Omni-3B-GGUF:Q4_K_M --port 8087 -n 200 -a "Qwen2.5-Omni"
Multimodal text & video (Video may not be supported by llama-server yet but link has good info & scripts).
If you have several AI models, you might want to try llama-server's router mode, that serves up all the models in your /models directory. Then our apps can choose among them.
Omni model crashes. If you use llama.cpp's router with Omni model, it crash with a message to the effect that it requires ub >= c. This might not always be the case, but just a FYI. We had to use -ub option or put ub into the configuration in our .models.ini:
[Qwen2.5-Omni-7B-IQ4_XS]
ngl = 29
c = 16384
ub = 16384
python aichat.py
This starts a chat server (yes, yet another server--a web server this time) so, if port 7860 is open on your firewall, anyone on your wifi can interact with llama-server via our chat app. Upload or capture pictures from a webcam (for models that support them), read and translate text in images, or ask questions about them. Right now, ours is the only chat app, that we know of, that can prompt an omni model with text, audio, and images simultaneously. Try speaking your prompt into the recorded audio and see!
Update. Now that llama.cpp also has a chat server of their own, you may want to try that. Theirs doesn't record audio or handle multimodal prompts as well as ours yet. But it might later.
Up/down voting. Now that aichat.py's up and down-voting works, you can rank which models you like best. The rankings will appear in a file, votes.json. If you have downloaded several models, you could use that data later to decide which models to keep.
Canvas mode. You can edit questions, code, and responses right in the interface by clicking twice on the text. A button will appear to submit a new query with your edits, comments, or annotations.
Test captioning photos in the memes directory. This will launch a server to host the photo album builder. The builder then creates a web page that will be the photo album or media portfolio.
./album_create.py memes
You should see a URL for the photo album builder. Ctrl+click it to open it. Or type it into your browser. Monitor memory usage with nvtop.
The link might look something like this. http://localhost:9165
If there is an existing index.html in the image folder, it will import captions from there. If not, it will scan the image metadata for keywords. If the photos were already tagged with keywords using a tool like LLavaImageTagger it will display those. (You must install LLavaImageTagger to make that work).
When Omni model is selected, the photo album builder can also caption audio files!
Supervise children. Be aware that these models are under active development. Their output, though usually fine, may not always be safe for all ages.
Once you open the link, and see the browser interface,
- select a vision model from the drop-down in the upper-left,
- click buttons to generate captions,
- click inside text boxes to manually edit captions,
- and save the annotated photo album.
The saved abum will go into your Downloads folder. Move the downloaded index.html back into the directory where the images are. Launch it with a browser (or double click it in your file manager) any time you want to search images. Feel free to customize it, add CSS styles, etc.
Now try making albums/portfolios in your other image folders.
./album_create.py ~/Pictures/2026Rename the album to something creative. Launch the album in the default web browser.
xdg-open album.html
Create a link to your album on the desktop. While viewing the album, simply drag the link in the address bar to the desktop. Or create a simlink from the command line.
ln -s album.html ~/Desktop/
Search for text captions in the browser by pressing CTRL+F. It will scroll to the image in question. Right click on your mug shots to copy them, paste them to social media, etc. You could also publish the album on a web server, github pages, or google drive. Or good old-fashioned lftp to your server box.
There is some JavaScript to alternately show and hide groups of images based on what you type into a search bar. For an example of this, look in the memes directory. You may use this so long as it doesn't become part of a commercial product that denies proper credit and royalties to the author.
Well, that's it. We built llama.cpp, made AI image descriptions locally, and built a photo album. We made a searchable web page, with AI-generated image captions. And we created a shortcut on the Desktop. What else could we be doing with the help of AI?
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Copyright (C) 2024-2026 Henry Kroll III, www.thenerdshow.com. See LICENSE for details.