Test cases for tool-using agents in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the agent with the correct tool.

Agentic AI

agent = Agent(tools=[[1]])

Drag options to blanks, or click blank then click option'

Asearch_tool

Btrain_model

Cdata_loader

Doptimizer

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'train_model' instead of a tool for searching.

Confusing data loader with a tool for the agent.

The agent needs a search tool to perform queries, so 'search_tool' is the correct initialization.

2fill in blank

medium

Complete the code to run the agent with the input query.

Agentic AI

response = agent.[1](input_query)

Drag options to blanks, or click blank then click option'

Atrain

Bsave

Cload

Drun

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'train' which is for model training, not running the agent.

Using 'load' which is for loading data or models.

The method to execute the agent on an input is 'run', so 'agent.run(input_query)' is correct.

3fill in blank

hard

Fix the error in the agent's tool usage by completing the code.

Agentic AI

result = agent.tools[0].[1](query)

Drag options to blanks, or click blank then click option'

Aexecute

Btrain

Csearch

Dcompile

Attempts:

3 left

💡 Hint

Common Mistakes

Calling 'execute' which is not defined for the tool.

Using 'train' which is for model training.

The tool is a search tool, so the correct method to call is 'search' to get results.

4fill in blank

hard

Fill both blanks to correctly define the agent's tool and method call.

Agentic AI

agent = Agent(tools=[[1]])
output = agent.tools[0].[2](input_text)

Drag options to blanks, or click blank then click option'

Asearch_tool

Btrain_model

Csearch

Dcompile

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'train_model' as a tool when the agent needs a search tool.

Calling 'compile' which is not a valid method for the tool.

The agent uses 'search_tool' and calls its 'search' method to process input_text.

5fill in blank

hard

Fill all three blanks to correctly initialize the agent, run it, and get the result.

Agentic AI

agent = Agent(tools=[[1]])
response = agent.[2](query)
result = response.[3]

Drag options to blanks, or click blank then click option'

Asearch_tool

Brun

Coutput

Dtrain_model

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'train_model' instead of 'search_tool'.

Calling 'train' instead of 'run' to execute the agent.

Accessing a wrong attribute instead of 'output'.

The agent is initialized with 'search_tool', run with 'run', and the result is accessed via 'output'.

Practice

1. What is the main purpose of writing test cases for tool-using agents?

easy

A. To add more tools to the agent

B. To make agents run faster

C. To check if agents use tools correctly and handle errors

D. To reduce the size of the agent's code

Solution

1. Step 1: Understand the role of test cases

   Test cases are designed to verify that the agent behaves as expected, especially when using tools.

2. Step 2: Identify the main goal for tool-using agents

   For agents that use tools, tests ensure they use these tools correctly and handle any errors gracefully.

3. Final Answer:

   To check if agents use tools correctly and handle errors -> Option C

4. Quick Check:

   Test cases purpose = check tool use and errors [OK]

Hint: Test cases verify correct tool use and error handling [OK]

Common Mistakes:

• Thinking test cases speed up agents
• Believing test cases reduce code size
• Assuming test cases add tools

2. Which of the following is the correct way to write a test case for a tool-using agent in Python?

easy

A. test agent tool: assert agent.use_tool('calculator', '2+2') == 4

B. def test_agent_tool(): assert agent.use_tool('calculator', '2+2') == 4

C. def test_agent_tool: assert agent.use_tool('calculator', '2+2') == 4

D. def test_agent_tool() assert agent.use_tool('calculator', '2+2') == 4

Solution

1. Step 1: Check Python function syntax

   Python test functions start with 'def', have parentheses, and a colon at the end.

2. Step 2: Verify assertion syntax

   The assert statement must be inside the function and correctly compare expected output.

3. Final Answer:

   def test_agent_tool(): assert agent.use_tool('calculator', '2+2') == 4 -> Option B

4. Quick Check:

   Correct Python test function syntax = def test_agent_tool(): assert agent.use_tool('calculator', '2+2') == 4 [OK]

Hint: Remember Python functions need parentheses and colon [OK]

Common Mistakes:

• Omitting parentheses in function definition
• Missing colon after function header
• Incorrect assert statement placement

3. Given this test case code snippet, what will be the output if the agent returns 5 instead of 4?

def test_agent_tool():
    result = agent.use_tool('calculator', '2+2')
    assert result == 4
    print('Test passed')

medium

A. Test passed

B. SyntaxError

C. No output

D. AssertionError

Solution

1. Step 1: Understand assert behavior

   If the assert condition is false, Python raises an AssertionError and stops execution.

2. Step 2: Check the test condition

   The test expects result == 4, but agent returns 5, so assert fails.

3. Final Answer:

   AssertionError -> Option D

4. Quick Check:

   Assert fails if values differ = AssertionError [OK]

Hint: Assert fails if expected and actual differ [OK]

Common Mistakes:

• Thinking print runs after failed assert
• Confusing AssertionError with SyntaxError
• Assuming no output on failure

4. Identify the error in this test case for a tool-using agent:

def test_agent_tool():
    result = agent.use_tool('search', 'weather today')
    assert result = 'sunny'
    print('Test passed')

medium

A. Using '=' instead of '==' in assert

B. Missing parentheses in print

C. Wrong function name

D. Agent tool name is invalid

Solution

1. Step 1: Check assert statement syntax

   In Python, '=' is for assignment, '==' is for comparison. Assert needs '==' to compare values.

2. Step 2: Verify other parts

   Print has parentheses, function name is valid, and tool name is plausible.

3. Final Answer:

   Using '=' instead of '==' in assert -> Option A

4. Quick Check:

   Assert needs '==' for comparison [OK]

Hint: Assert compares with '==', not '=' [OK]

Common Mistakes:

• Confusing assignment '=' with comparison '=='
• Ignoring syntax errors in assert
• Assuming print needs no parentheses

5. You want to test an agent that uses a calculator tool to handle multiple expressions. Which test case best checks if the agent correctly handles both valid and invalid inputs?

hard

A. def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', 'abc') == 'error'

B. def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', '3/0') == 0

C. def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', '') == ''

D. def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', null) == null"

Solution

1. Step 1: Check valid input test

   All options test '3*3' == 9 correctly, which is good for valid input.

2. Step 2: Check invalid input handling

   def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', 'abc') == 'error' expects 'abc' input to return 'error', which correctly tests error handling. Others expect incorrect or unclear outputs.

3. Final Answer:

   def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', 'abc') == 'error' -> Option A

4. Quick Check:

   Test valid and invalid inputs properly = def test_calc(): assert agent.use_tool('calculator', '3*3') == 9; assert agent.use_tool('calculator', 'abc') == 'error' [OK]

Hint: Test both valid and invalid inputs explicitly [OK]

Common Mistakes:

• Expecting wrong output for invalid input
• Not testing error cases
• Assuming empty or null inputs return themselves