Why LLM Chatbots Lose Memory and How Persistent Sessions Fix It

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Large language models process each API call in isolation, meaning they retain no memory of previous messages without developer intervention. A developer writing on DEV Community explains that the simplest fix is to store conversation history per session using an in-memory map, then pass the full message history with every API call. However, this approach has critical flaws: all data is lost on server restart, session isolation can break under concurrent users, and long histories consume excessive tokens. The article proposes moving to persistent storage — specifically serverless PostgreSQL via Neon — to properly isolate and retain user sessions across restarts. The tutorial walks through a Spring Boot implementation, progressing from a basic in-memory solution to a production-ready architecture.

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How Aqiron Security Split Its VS Code Extension from Its TypeScript Core

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Java's 'finally' Block Runs Before Exit, But Not Before Return Value Is Saved

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ProgrammingDEV Community ·

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