LangGraph Performance Optimization (Python)

LangGraph Performance Optimization (Python)

Latest: 1.0.3 Upstream: https://github.com/langchain-ai/langgraph

Techniques

• Cache intermediate results by state keys to avoid re-computation
• Batch LLM calls when possible; stream responses
• Parallel branches with care; manage rate limits and retries

Example: Cached Node

from functools import lru_cache

@lru_cache(maxsize=1024)
def embed(text: str) -> list[float]:
    ...

def node(state: dict) -> dict:
    vec = embed(state["text"])  # reuses cache
    return {**state, "vec": vec}