From Local RAG Bot to a Cloud-Native Chatbot
How I moved a personal RAG chatbot to Cloud Run with PostgreSQL, session-aware retrieval, and Vertex AI.
Writing
Notes from the workbench.
Experiments, systems, mistakes, and the parts worth remembering.
From Local Scripts to a Serverless Data Collection Pipeline
How I moved a local Python data collector to Google Cloud so a teammate could trigger it remotely through Telegram.
A Modular Video Translation Pipeline with Whisper
I separated transcription, translation, and subtitle rendering to make a personal video translation pipeline easier to debug.
From Terminal to Browser: Giving My Multi-Agent Chatbot a Face
I wrapped my multi-agent chatbot in Docker and FastAPI so I could use it through a simple browser interface.
Making My Personal AI Assistant Safer and More Reliable
I added safety checks, retrieval ranking, and response editing to make my personal assistant more reliable.
Building a Personal AI Assistant from My Notes
I built a personal assistant around my Obsidian notes to learn how retrieval, agents, and personal knowledge can work together.
A Half-Day Return to Machine Learning with Fraud Detection
A short fraud-detection project helped me revisit class imbalance, Random Forest, SMOTETomek, and precision-recall metrics.
Why I Switched My AI Newsroom from CrewAI to LangGraph
I moved my AI newsroom from CrewAI to LangGraph to gain clearer state, workflow control, and more consistent output.
Building a Weekly AI Digest with an Agentic Workflow
I built a small AI newsroom with CrewAI to collect, filter, and summarize the AI news I actually want to read.
Using Apps Script and Gemini to Triage Gmail
I used Google Apps Script and Gemini to classify incoming Gmail messages and make a crowded inbox easier to scan.
Automating a Mobile App with an Android Emulator
I used Python, an Android emulator, and OCR to automate a repetitive in-app card-spinning workflow.
What LLM Agent Frameworks Actually Add
A practical introduction to agent workflows, using a CrewAI newsroom example to explain roles, loops, and trade-offs.
How to Write Better Prompts for LLMs
Four practical ways to give language models clearer instructions, better context, and smaller tasks.
怎樣才能寫好提示詞？
四個實用方法：講清楚任務、補充背景、要求檢查，再把大任務拆小。