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Function Calling in LLMs Quiz

Total questions: 10

Worksheet time: 8mins

Name
Class
Date
1.

What is the primary limitation that function calling solves for LLMs?

a)

LLMs can't generate creative text

b)

LLMs can't perform precise calculations or access real-time data

c)

LLMs can't understand natural language

d)

LLMs can't work with multiple languages

2.

In the Google GenAI Python SDK, automatic function calling is:

a)

Disabled by default and must be explicitly enabled

b)

Only available for paid accounts

c)

Enabled by default when using client.chats.create()

d)

Not supported in the Python SDK

3.

What is required for a Python function to work with automatic function calling?

a)

The function name must start with 'tool_'

b)

Type hints and a clear docstring

c)

The function must return JSON

d)

The function must be async

4.

When a function encounters an error, what's the best practice for handling it?

a)

Raise an exception to stop execution

b)

Return None and let the SDK handle it

c)

Return an error message as a string

d)

Log the error and return an empty response

5.

What makes something an 'agent' rather than just an LLM with function calling?

a)

It costs more to run

b)

It autonomously decides which tools to use to accomplish goals

c)

It requires a special SDK version

d)

It can only use one function at a time

6.

In the SimpleAgent class, what three components define an agent?

a)

Model, temperature, and max_tokens

b)

Tools, system_instruction, and ChatSession

c)

Functions, database, and API keys

d)

Prompt, response, and history

7.

Why should you include a system_instruction when using automatic function calling?

a)

It's required by the SDK or the code will crash

b)

It makes function calls execute faster

c)

It tries to ensure the model generates a final text response after using tools

d)

It's only needed for paid API plans

8.

What does an orchestrator agent do?

a)

Executes all functions in parallel

b)

Routes requests to specialized agents based on the task

c)

Prevents the LLM from calling functions

d)

Stores conversation history in a database

9.

In a multi-turn conversation, how does the agent remember previous interactions?

a)

You must manually save and reload conversation history

b)

The ChatSession automatically maintains conversation history

c)

Each message is completely independent

d)

History is only stored if you enable a special flag

10.

When combining Week 4 (document processing) and Week 5 (function calling), what can you build?

a)

An agent that only reads documents

b)

An agent that extracts data from documents and takes actions based on that data

c)

A chatbot that can't access external data

d)

A system that requires manual function execution