LangChain + Chroma: Multi-turn RAG Memory and Automated Testing That Turned 2-Hour Bugs Into 5-Minute Fixes

A developer built a persistent memory system for multi-turn RAG chatbots using ChromaDB, solving the problem of conversation history loss after service restarts. The solution stores conversation turns as vector embeddings with metadata, enabling semantic retrieval of relevant historical context alongside a short-term raw message window. Automated pytest suites now catch memory-related regressions in minutes instead of the hours previously spent debugging user-reported failures.