I Built a Stock Monitoring Agent with OpenClaw, Exa, and Milvus for $20/Month

This post details the integration of Milvus Lite for storing personal trading history and preferences to build a stock monitoring agent. It describes creating three distinct collections ('decisions', 'preferences', 'patterns') with a 1536-dimensional embedding space to store different types of personal data. The post also outlines a memory extraction mechanism that uses an LLM to identify and deduplicate insights from conversations before storing them in Milvus, preventing redundant entries by checking for >92% similarity.