🧭 LangGraph Flashcards
🔍 What is LangGraph?
LangGraph is a Python framework for building stateful, multi-agent applications using LLMs and graph-based flows.
🧠 What does LangGraph enable?
It allows developers to model agents, tools, memory, and control flow using directed graphs that support branching and looping.
📌 How is LangGraph different from LangChain?
LangChain focuses on tool orchestration; LangGraph adds memory and control flow between nodes and agents via graphs.
🔁 What is the role of a node in LangGraph?
Each node can be a function, an LLM call, or an agent step. Nodes are connected to represent complex logic flows.
⚙️ What’s an edge in LangGraph?
Edges define the transitions between nodes. They can be conditional based on the result of an LLM or agent response.
🧪 Can LangGraph handle loops?
Yes. Unlike basic chains, LangGraph supports cyclic paths, enabling agents to revisit nodes, retry, or iterate steps.
🛠️ Does LangGraph support tool calling?
Yes. Each node or agent can access tools just like in LangChain, allowing modular and complex applications.
📦 How do you install LangGraph?
You can install it via pip:
pip install langgraph🌐 What are use cases for LangGraph?
LangGraph is ideal for multi-agent collaboration, planning, decision-making, and agent-based simulations.
💡 What’s a real-world example?
A customer service assistant where multiple agents (FAQ, escalation, feedback) interact dynamically using LangGraph.