LangGraph Quiz (2026) — Test Your Knowledge

🧠 LangGraph Knowledge Quiz (2026)

Test what you learned from the interview guide — 10 questions, multiple choice.

📅 June 13, 2026 ⏱️ ~5 min 🎯 Beginner to Senior

1What is the key architectural difference between LangChain and LangGraph?

• LangGraph only works with OpenAI models
• LangGraph supports cyclic graphs; LangChain chains are acyclic
• LangChain is newer and replaces LangGraph
• LangGraph cannot use tools or retrievers

Correct! LangGraph's defining feature is support for cyclic graphs — nodes can loop back, enabling agents that retry, branch, and revisit steps. LangChain chains are strictly acyclic (one-pass).

2Which of the following is NOT one of LangGraph's three core primitives?

• State
• Edges
• Nodes
• Chains

Correct! The three core primitives are State, Nodes, and Edges. "Chains" is a LangChain concept, not a LangGraph primitive.

3What does the .compile() method return in LangGraph?

• A JSON schema of the graph
• A Python list of nodes
• A runnable CompiledGraph with .invoke() and .stream() methods
• A LangSmith trace object

Correct! .compile() validates the graph and returns a CompiledGraph that exposes .invoke(), .stream(), and their async variants.

4Which checkpointer backend is recommended for production LangGraph deployments?

• MemorySaver
• FileSaver
• PostgresSaver
• JSONSaver

Correct! PostgresSaver (or RedisSaver) is recommended for production — it's durable and multi-replica safe. MemorySaver is in-process only and loses state on restart.

5How do you implement a human-in-the-loop approval gate in LangGraph?

• By adding a sleep() call inside a node
• By using interrupt_before=["node_name"] in .compile()
• By setting human=True on the StateGraph constructor
• By calling graph.pause() from a node

Correct! Passing interrupt_before=["node_name"] to .compile() makes the graph pause before that node, save state, and wait for an external signal to resume.

6In the ReAct agent pattern, what does the conditional edge after the call_llm node check?

• Whether the response is longer than 100 tokens
• Whether the user has approved the action
• Whether the last LLM output contains tool calls
• Whether the state has more than 10 messages

Correct! The conditional edge in a ReAct loop checks whether the LLM output contains tool calls. If yes, route to run_tools; if no, route to END with the final answer.

7What are the three capabilities that checkpointing enables in LangGraph?

• Caching, compression, and encryption
• Pause & resume, time travel, and fault tolerance
• Logging, monitoring, and alerting
• Versioning, branching, and merging of LLM models

Correct! Checkpointing enables: pause & resume (human-in-the-loop), time travel (replay from any checkpoint for debugging), and fault tolerance (retry from last successful node).

8In the Supervisor multi-agent pattern, what determines which sub-agent is called next?

• A random selection from available agents
• The order in which agents were added to the graph
• A supervisor node (usually an LLM) whose output drives a conditional edge
• A static configuration file

Correct! The supervisor is a node — typically an LLM call — that returns a routing decision. That decision is read by a conditional edge to dispatch to the appropriate specialist sub-agent.

9Which method should you use for real-time token streaming to end users in a LangGraph production application?

• .invoke()
• .run()
• .astream_events()
• .batch()

Correct! .astream_events() streams individual token events as they are generated, enabling real-time display to users and significantly improving perceived latency.

10LangGraph surpassed which framework in GitHub stars during early 2026, signalling its rise as the enterprise standard?

• AutoGen
• CrewAI
• LlamaIndex
• Haystack

Correct! LangGraph surpassed CrewAI in GitHub stars in early 2026, driven by enterprise adoption of its graph-based, stateful architecture that maps cleanly to production requirements.

Quiz Complete! 🎉

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