Aiko Ai Waifu
Collection
AI Waifu project.
An AI companion with persistent memory, voice, and a live 3D VRM avatar - model under 32B params served via Modal. • 2 items • Updated • 1
OppaAI
OppaAI
AI & ML interests
Local AI implementation, Agentic AI workflows, AI Autonomous Robot
Recent Activity
updated a bucket 1 day ago
OppaAI/Aiko-data posted an update 3 days ago
Yesterday I said I wanna make a UI for users to draw DAG workflow so my AI Waifu can use these workflows to run automated agentic tasks for me, so I ask Grok to make something that looks like the image shown in the demo.
I wish I have the time and skill to make it like n8n-style and look more professional. Right now there are only 5 nodes to choose from and will as I need for my own workflow. But at least right now I can see if the graphs in my code are properly setup.
This could potentially be a enterprise-level product, I just don't have the time and skills to scale it to a bigger level.
I have just pushed this in my code yet. Not tested yet.
Probably need sometimes to polish it.
Github: https://github.com/OppaAI/Aiko-chan/ posted an update 4 days ago
So many ideas, so little time and energy:
Another idea pops up today after spending the past weekend polishing the DAG Agentic workflow system of my AI Waifu system.
These past few days, as I was building workflows for my AI Waifu, the patterns and basic building blocks look very similar and probably can recycle for each workflow. So I propose a 5-layers Graph Engine to generalize all my workflows:
(I'm sure there are apps like that in the market, only the scale, complexity and price differs. But if f there is a generic app that can use local AI to let people construct workflows to run automated tasks, non-tech users or small companies can benefit from this.)
1) Planning - Users writes a detailed a spec of the workflow they want. Or even draws it in a n8n-like environment, defining each building block + args + queries, moving them around, arranging them to run in parallel/sequence, format the output, destination of the output, etc.
2) Orchestrating: AI system then interprets the spec, organizing the nodes into workflows, verified and tested by humans, then run the workflows and do the works. Reduce coding to the minimum for users.
3) Executing: Node is the basic building block of the graph and can be customizable, and sharable among different workflows; each node will call the registered tools or skills to do the work.
4) Tools and skills: exposed to AI system just like what we have right now.
5) Outputs: Generate reports of WIP and final results and users choose to get notified
With enough time and effort, and fund to invest, this and many other components of my AI system could potentially be a startup idea. Unfortunately I have neither the time, energy, fund, or talent to build productivity tools to benefit others, I can only build the components just good enough for my own use, and provide the source codes to other people to make the ideas scalable to production environment if they want.Organizations
upvoted a collection 2 months ago