Tag: 학습
All the articles with the tag "학습".
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LangGraph Study #3 — Human-in-the-Loop (Approving Risky Tools) · Checkpoints and the Interrupt Mechanism
When an agent automatically calls risky tools like file deletion, sending emails, or payments, things go wrong. Implementing the HITL pattern using LangGraph's checkpoint + Interrupt mechanism to get human approval right before a risky tool call. An unexpected trap: the LLM's own safety guard can block execution before it ever reaches HITL. How to separate the system prompt from the HITL gate.
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FEMS Project #1 — Comparing Low-Spec Local Setup (Ollama + bge-m3 + Chroma) vs Claude API RAG
Building a RAG prototype while studying the FEMS (Factory Energy Management System) domain. Comparing local LLM inference (Ollama) on a low-spec environment (GTX1660 Super, 6GB VRAM) against calling the Claude / OpenAI APIs. Using bge-m3 for embeddings (strong Korean support) and Chroma as the vector DB. Ollama's cold start of 95 seconds dropped to 10 seconds after warm-up, with accuracy matching the cloud.
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Quant Study 00 — pandas Basics · Trend Following vs Mean Reversion · The 4 Backtest Biases · Fake Alpha
Starting a quant learning series. pandas Series/DataFrame, loc/iloc, the warm-up period (NaN), silent data corruption from adjusted close prices, trend following (MA, golden/dead cross) vs mean reversion, the 4 backtest biases (look-ahead, overfitting, unrealistic trading costs, survivorship bias), and why you need to look at a distribution instead of a single point to filter out fake alpha (B&H beat rate / median alpha / market exposure / walk-forward).
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LangGraph Study Log #2 — Extending State + Dynamic System Prompts + Chatbot (and the Truth Behind 'AI Remembers')
I extended State beyond just messages to include user name, tool call count, and session start time, then used that State to dynamically build the system prompt. Along the way, building a chatbot led me to the real revelation of the day: what 'memory' actually is.