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Agentic AIml~10 mins

LangGraph for stateful agents in Agentic AI - Interactive Code Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to initialize a LangGraph agent with a state.

Agentic AI
agent = LangGraphAgent(state=[1])
Drag options to blanks, or click blank then click option'
A{}
B0
CNone
D[]
Attempts:
3 left
💡 Hint
Common Mistakes
Using None instead of an empty dictionary causes errors when updating state.
Using a list [] does not allow key-based state storage.
2fill in blank
medium

Complete the code to update the agent's state with a new key-value pair.

Agentic AI
agent.state[[1]] = 'active'
Drag options to blanks, or click blank then click option'
Astatus
B'status'
C'state'
D'mode'
Attempts:
3 left
💡 Hint
Common Mistakes
Forgetting quotes around the key causes a NameError.
Using an incorrect key name that doesn't match the intended state.
3fill in blank
hard

Fix the error in the code to retrieve the agent's current mode safely.

Agentic AI
current_mode = agent.state.get([1], 'idle')
Drag options to blanks, or click blank then click option'
Amode
Bstatus
C'state'
D'mode'
Attempts:
3 left
💡 Hint
Common Mistakes
Using unquoted keys causes NameError.
Using wrong key names returns unexpected results.
4fill in blank
hard

Fill both blanks to create a LangGraph agent that updates state and then retrieves a value.

Agentic AI
agent.state[[1]] = 'running'
mode = agent.state.get([2], 'stopped')
Drag options to blanks, or click blank then click option'
A'mode'
B'status'
D'state'
Attempts:
3 left
💡 Hint
Common Mistakes
Mixing up keys causes wrong state updates or retrievals.
Forgetting quotes around keys causes errors.
5fill in blank
hard

Fill all three blanks to define a function that updates the agent's state and returns the updated value.

Agentic AI
def update_agent_state(agent, key, value):
    agent.state[[1]] = [2]
    return agent.state.get([3])
Drag options to blanks, or click blank then click option'
Akey
Bvalue
D'value'
Attempts:
3 left
💡 Hint
Common Mistakes
Using string literals instead of variables.
Forgetting to return the updated value.

Practice

(1/5)
1. What is the main purpose of LangGraph in stateful agents?
easy
A. To store states as nodes and actions as edges for memory
B. To train deep learning models faster
C. To generate random actions without memory
D. To visualize data without storing states

Solution

  1. Step 1: Understand LangGraph structure

    LangGraph uses nodes to represent states and edges to represent actions connecting those states.
  2. Step 2: Identify the purpose of this structure

    This structure helps agents remember past states and decide next actions based on memory.
  3. Final Answer:

    To store states as nodes and actions as edges for memory -> Option A
  4. Quick Check:

    LangGraph = state nodes + action edges [OK]
Hint: Remember: LangGraph = states (nodes) + actions (edges) [OK]
Common Mistakes:
  • Confusing LangGraph with model training
  • Thinking LangGraph generates random actions
  • Assuming LangGraph only visualizes data
2. Which of the following is the correct way to add a new state node in a LangGraph agent?
easy
A. langgraph.add_edge(state1, state2, action)
B. langgraph.remove_node(state)
C. langgraph.add_node(new_state)
D. langgraph.update_action(state, new_action)

Solution

  1. Step 1: Identify method to add nodes

    Adding a new state means adding a node, so the method should be add_node.
  2. Step 2: Check options for adding nodes

    Only langgraph.add_node(new_state) uses add_node(new_state), which correctly adds a state node.
  3. Final Answer:

    langgraph.add_node(new_state) -> Option C
  4. Quick Check:

    Add state = add_node() method [OK]
Hint: Add states with add_node(), not add_edge() [OK]
Common Mistakes:
  • Using add_edge() to add states
  • Confusing remove_node() with adding
  • Trying to update actions to add states
3. Given the code snippet:
langgraph.add_node('S1')
langgraph.add_node('S2')
langgraph.add_edge('S1', 'S2', 'move')
print(langgraph.get_next_action('S1'))

What will be the output?
medium
A. 'S2'
B. 'move'
C. None
D. Error: method not found

Solution

  1. Step 1: Understand the graph setup

    Two states 'S1' and 'S2' are added, then an edge from 'S1' to 'S2' with action 'move'.
  2. Step 2: Check get_next_action('S1')

    This method returns the action on the edge from 'S1' to its next state, which is 'move'.
  3. Final Answer:

    'move' -> Option B
  4. Quick Check:

    Edge action from S1 = 'move' [OK]
Hint: Edges store actions; get_next_action returns that action [OK]
Common Mistakes:
  • Confusing action with next state
  • Expecting None if not familiar with method
  • Assuming method does not exist
4. What is wrong with this code snippet for updating an action in LangGraph?
langgraph.add_node('S1')
langgraph.add_node('S2')
langgraph.add_edge('S1', 'S2', 'jump')
langgraph.update_edge('S1', 'S2', 'run')
medium
A. Edges cannot be updated once added
B. add_node should be called after update_edge
C. The action 'run' is invalid
D. update_edge method does not exist; should remove and add edge

Solution

  1. Step 1: Check if update_edge method exists

    LangGraph typically does not have update_edge; edges are removed and re-added to update.
  2. Step 2: Identify correct update approach

    To change an action, remove the old edge and add a new edge with the new action.
  3. Final Answer:

    update_edge method does not exist; should remove and add edge -> Option D
  4. Quick Check:

    No update_edge method in LangGraph [OK]
Hint: Update edges by remove + add, no update_edge method [OK]
Common Mistakes:
  • Assuming update_edge exists
  • Trying to update nodes instead of edges
  • Thinking action strings are invalid
5. You want your LangGraph agent to remember a sequence of states and actions to avoid loops. Which approach best helps achieve this?
hard
A. Store visited states as nodes and add edges only for new actions
B. Clear the graph after each action to reset memory
C. Add duplicate nodes for repeated states to track loops
D. Use a separate list outside LangGraph to track visited states

Solution

  1. Step 1: Understand loop avoidance in LangGraph

    Storing visited states as nodes and adding edges only for new actions helps the agent remember paths and avoid loops.
  2. Step 2: Evaluate other options

    Clearing the graph loses memory, duplicates confuse state identity, and external lists separate memory from LangGraph.
  3. Final Answer:

    Store visited states as nodes and add edges only for new actions -> Option A
  4. Quick Check:

    Memory in LangGraph = nodes + edges tracking [OK]
Hint: Keep states as nodes and edges for memory, avoid duplicates [OK]
Common Mistakes:
  • Resetting graph loses memory
  • Duplicating nodes breaks state tracking
  • Using external lists splits memory logic