Memory and Conversational Context in LangChain
Learn how LangChain memory keeps track of conversation history so chains and chatbots can hold coherent multi-turn conversations.
LLMs Are Stateless
A language model has no memory between calls. Each request is independent — it only knows what you put in the current prompt. To build a chatbot that remembers, you must feed prior turns back in yourself.
What LangChain Memory Does
LangChain memory automates this: it stores the conversation and injects relevant history into the prompt on each new turn. Your chain stays simple while the model appears to remember.
All lessons in this course
- Setting Up Your LangChain Environment
- Prompts, LLMs, and Basic Chains
- Output Parsers and Callbacks
- Memory and Conversational Context in LangChain