--- tags: - gguf-connector --- ## chat - gpt-like dialogue interaction workflow (demonstration) - simple but amazing multi-agent plus multi-modal implementation - prepare your llm model (replaceable; can be serverless api endpoint) - prepare your multimedia model(s), i.e., image, video (replaceable as well) - call the specific agent/model by adding @ symbol ahead (tag the name/agent like you tag anyone in any social media app) ## frontend (static webpage or localhost) - https://chat.gguf.org ## backend (serverless api or localhost) - run it with `gguf-connector` - activate the backend(s) in console/terminal - 1) llm chat model selection ``` ggc e4 ``` > >GGUF available. Select which one to use: > >1. llm-q4_0.gguf <<<<<<<<<< opt this one first >2. picture-iq4_xs.gguf (image model example) >3. video-iq4_nl.gguf (video model example) > >Enter your choice (1 to 3): _ - 2) picture model (opt the second one above; you should open a new terminal) ``` ggc w8 ``` - 3) video model (opt the third one above; you need another terminal probably) ``` ggc e5 ``` - make sure your endpoint(s) dosen't break by double checking each others - since `ggc w8` or/and `ggc e5` will create a .py backend file to your current directory, it might trigger the uvicorn relaunch if you pull everything in the same directory; once you keep those .py files (after first lauch), then you could just execute `uvicorn backend:app --reload --port 8000` or/and `uvicorn backend5:app --reload --port 8005` instead for the next launch (no file changes won't trigger relaunch) ## how it works? - if you ask anything, i.e., just to say `hi`; everybody (llm agent(s)) will response ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo1.png) - you could tag a specific agent by @ for single response (see below) ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo2.png) - for functional agent(s), you should always call with tag @ - let's say, if you wanna call image agent/model, type `@image` first ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo3.png) - then image agent will work for you like example below ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo4.png) - for video agent, in this case, you should prompt a picture (drag and drop) with text instruction like below ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo5.png) - then video agent will work for you like the example shown ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo6.png) ## more settings - check and click the `Settings` on top right corner - you should be able to: - change/reset the particular api/endpoint(s) - for multimedia model(s) - adjust the parameters for image and/or video agent/model(s); i.e., sampling rate (step), length (fps/frame), etc. - for llm (text response model - openai compatible standard) - add/delete agent(s) - assign/disable vision for your agent(s), but it based on the model you opt (with vision or not) ![screenshot](https://raw.githubusercontent.com/calcuis/gguf-pack/master/chat-demo7.png) Happy Chatting!