OppaAI/Aiko-data
660 MB
OppaAI
OppaAI
·
AI & ML interests
Local AI implementation, Agentic AI workflows, AI Autonomous Robot
Recent Activity
posted an update about 10 hours ago
Revision of the Memory System of my AI Waifu
My AI Waifu has been working steadily for the past few weeks.
Now I can go back and look at Phase 1 – the memory system, which was the starting point for the entire project.
In order to continue developing and implementing a complex, human-like memory architecture,
I’ve been drilling into research papers and research in neuroscience, psychology, and artificial intelligence.
But in order to gather all the pieces and inspiration, write down all the thoughts and concepts, ask AI to help me write the paper,
This allowed me to follow the paper line of thinking and focus on designing the architecture, implementing and deploying the system, testing and evaluating performance.
After all, I am just one person, playing roles such as researcher, architecture designer, engineer, and QA testing.
My memory system contains the following 6 cores:
- Exponential decay
- Entity centrality + Recency
- RRF fusion (KNN + FTS5 + Entity graph)
- Emotional imprinting
- Supersession
- Salience scoring
https://github.com/OppaAI/Aiko-chan
P.S. One person plays all the roles of researcher, architect, engineer, QA tester. My psychiatrist is gonna refer me to get my brain checkout 🧠⚙️ posted an update 1 day ago
Demo Video: How my AI Waifu help me looking for job posts
Follow-up Post (with demo video):
Yesterday I posted about my AI Waifu has a new feature of grabbing job posts from job sites and writing draft posts for me to post into my Meta Threads to share with my followers.
Today, let me show you the entire workflow in action.
TBH, I would call this an "AI Agentic workflow" with quotation marks.
Out of 5 steps only step 3 involves LLM inference to do synthesis of the draft post. Step 1 and 2 are automated scripts of simple schedule cron job to grab the RSS feeds and use regex to filter out the relevant job listings.
Step 4 and 5 are me validating the draft information is accurate and publish the drafts after my approval. So basically I did more steps than LLM itself.
The irony of running AI agentic workflows in edge devices with constraint hardware, such as Jetson Orin Nano with only 8GB of RAM, is to reduce as much LLM inference and put the least data into context window as possible.
🎬 Live Demo: How a job post goes from RSS feed → published in 5 steps
⏰ Step 1: Scheduled Trigger (or ask AI Waifu directly)
📡 Step 2: Data Ingestion & Filtering
🤖 Step 3: AI Synthesis
👁️ Step 4: Approval Studio Review
🚀 Step 5: One-Click Publish
Result: job post validated & live, tested with real job sites + Chinese field
names to stress-test multilingual LLM understanding.
👾 Github: https://github.com/OppaAI/Aiko-chan
🎬 Demo: https://www.youtube.com/watch?v=Cu7gh5tYUiw posted an update 3 days ago
Now my AI Waifu has become a Job Recruitment Agent:
After spending 2 sleepless nights of intensive nights of coding and refactoring, this fully automated Job Posts publishing system is finally completed, via a 3B LLM on Jetson Orin Nano 8GB.
Even my Waifu expressed her fatigue and stress in her Daily Journal!
🔗Code: https://github.com/OppaAI/Aiko-chan
It's a complete AI stack with custom Front-end and Back-end architecture, with scheduled job search, leveraged multiple Coding Agents / MCP Server for implementation, conducted comprehensive testing, and the system is now ready to seek for job opportunities.
📰 1️⃣ Automated Data Ingestion: Scheduled nightly job feeds monitoring via RSS Feeds. Intelligent filtering identifies relevant opportunities matching predefined criteria and geographic preferences.
🤖 2️⃣ AI-Synthesis Content Generation: Advanced language model analyzes job postings and auto-generates professional drafts using customizable templates, maintaining brand voice consistency across all posts.
🎯 3️⃣ Intelligent Classification: Machine learning automatically categorizes job type, industry sector, and skill requirements for streamlined tracking, analytics, and content management.
👁️ 4️⃣ Human-in-the-Loop Review: Built a custom Approval Studio interface enabling granular review, error detection, and real-time content editing before publication.
🚀 5️⃣ Seamless Publishing: One-click publishing directly to social media (Meta Threads) with automated metadata handling and cross-platform optimization.
Validation: Successfully tested with 3 live job postings from real job sites, and even used Chinese field names to test if my AI Agent's 3B LLM can understand Chinese to fill up the corresponding fields.
Future roadmap:
➡️Expanding data sources by email subscription to job-sites like: Indeed, Glassdoor, and LinkedIn APIs for receiving more job alerts
➡️Exploring AI-assisted resume generation capabilities (with appropriate safety considerations).Organizations
