LangChain

LCEL Basics

• | pipes output to next — prompt | llm | parser
• RunnablePassthrough() forwards input unchanged — use in parallel branches
• RunnableParallel runs branches concurrently — {"a": chain1, "b": chain2}
• .invoke() for single, .batch() for multiple, .stream() for tokens
• Input must match expected keys — {"question": x} not just x if prompt expects {question}

Memory Gotchas

• Memory doesn't auto-persist between sessions — save/load explicitly
• ConversationBufferMemory grows unbounded — use ConversationSummaryMemory for long chats
• Memory key must match prompt variable — memory_key="chat_history" needs {chat_history} in prompt
• return_messages=True for chat models — False returns string for completion models

RAG Chunking

• Chunk size affects retrieval quality — too small loses context, too large dilutes relevance
• Chunk overlap prevents cutting mid-sentence — 10-20% overlap typical
• RecursiveCharacterTextSplitter preserves structure — splits on paragraphs, then sentences
• Embedding dimension must match vector store — mixing models causes silent failures