OpenAI functions agent in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the OpenAI functions agent from LangChain.

LangChain

from langchain_community.agents import [1]

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

AAgentExecutor

BOpenAIChatAgent

COpenAIFunctionsAgent

DTool

Attempts:

3 left

💡 Hint

Common Mistakes

Importing OpenAIChatAgent instead of OpenAIFunctionsAgent

Using AgentExecutor which is a different class

Importing Tool which is unrelated here

The OpenAIFunctionsAgent is the correct import to create an agent that uses OpenAI functions in LangChain.

2fill in blank

medium

Complete the code to create an OpenAI chat model with temperature 0.

LangChain

from langchain_openai import ChatOpenAI
chat = ChatOpenAI(temperature=[1])

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

A0

B1.0

C0.5

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using temperature 1.0 which is very random

Using negative temperature which is invalid

Using 0.5 which is moderate randomness

Setting temperature=0 makes the model deterministic, which is common for function calling agents.

3fill in blank

hard

Fix the error in the code to create an OpenAI functions agent with the chat model and tools.

LangChain

agent = OpenAIFunctionsAgent.from_llm_and_tools([1], tools)

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

Allm

Bmodel

Copenai

Dchat

Attempts:

3 left

💡 Hint

Common Mistakes

Passing 'llm' which is undefined here

Passing 'model' or 'openai' which are not defined variables

The variable 'chat' is the ChatOpenAI instance passed to the agent constructor.

4fill in blank

hard

Fill both blanks to create a list of tools and initialize the agent executor.

LangChain

tools = [[1]]
agent_executor = AgentExecutor(agent=agent, tools=[2])

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

Atool

Btools

Cagent

Dexecutor

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'tools' inside the list instead of 'tool'

Passing 'agent' instead of 'tools' to AgentExecutor

The tools list contains 'tool' and the AgentExecutor uses the 'tools' list as argument.

5fill in blank

hard

Fill all three blanks to run the agent executor with input and print the output.

LangChain

input_text = [1]
output = agent_executor.run([2])
print([3])

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

A"What is the weather today?"

Binput_text

Coutput

D"Hello world"

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a variable name instead of a string literal for input_text

Printing input_text instead of output

Passing output instead of input_text to run()

We assign a string to input_text, run the agent with input_text, and print the output variable.

Practice

1. What is the main purpose of an OpenAI functions agent in Langchain?

easy

A. To store large datasets for AI processing

B. To train new AI models from scratch

C. To create user interfaces for AI applications

D. To connect AI chat with your own custom functions for smarter responses

Solution

1. Step 1: Understand the role of an OpenAI functions agent

   An OpenAI functions agent links AI chat capabilities with user-defined functions to perform tasks.

2. Step 2: Compare options to the definition

   Only To connect AI chat with your own custom functions for smarter responses describes connecting AI chat with custom functions, which matches the agent's purpose.

3. Final Answer:

   To connect AI chat with your own custom functions for smarter responses -> Option D

4. Quick Check:

   Agent purpose = connect AI chat + functions [OK]

Hint: Remember: functions agent links AI chat to your code [OK]

Common Mistakes:

• Confusing agent with AI model training
• Thinking it stores data instead of connecting functions
• Assuming it builds user interfaces

2. Which of the following is the correct way to create an OpenAI functions agent in Langchain?

easy

A. agent = OpenAIFunctionsAgent(functions, model)

B. agent = OpenAIChatAgent(model, funcs)

C. agent = OpenAIFunctionsAgent(llm=model, tools=funcs)

D. agent = FunctionsAgent(llm=model, funcs=functions)

Solution

1. Step 1: Recall the correct constructor syntax

   The OpenAI functions agent requires named parameters: llm for the model and tools for the list of tools.

2. Step 2: Check each option for correct names and syntax

   agent = OpenAIFunctionsAgent(llm=model, tools=funcs) uses correct class name and named parameters. Others either use wrong class names or positional arguments incorrectly.

3. Final Answer:

   agent = OpenAIFunctionsAgent(llm=model, tools=funcs) -> Option C

4. Quick Check:

   Correct constructor = agent = OpenAIFunctionsAgent(llm=model, tools=funcs) [OK]

Hint: Look for named parameters llm and tools in constructor [OK]

Common Mistakes:

• Using positional arguments instead of named
• Wrong class names like OpenAIChatAgent
• Mixing parameter names like funcs vs tools

3. Given the code snippet:

from langchain.agents import OpenAIFunctionsAgent

model = OpenAI()
functions = [get_weather, get_news]
agent = OpenAIFunctionsAgent(llm=model, tools=functions)
response = agent.invoke({'input': 'What is the weather today?'})
print(response)

What will print(response) most likely output?

medium

A. A string response from the AI calling get_weather function

B. A syntax error due to missing parameters

C. An empty dictionary because no functions are called

D. A runtime error because invoke method does not exist

Solution

1. Step 1: Understand agent.invoke behavior

   The agent uses the AI model and tools list to process input and call the right function, here likely get_weather.

2. Step 2: Analyze the code flow

   Input asks about weather, so the agent calls get_weather and returns its result as a string response.

3. Final Answer:

   A string response from the AI calling get_weather function -> Option A

4. Quick Check:

   invoke calls function and returns response [OK]

Hint: Input about weather triggers get_weather function call [OK]

Common Mistakes:

• Assuming invoke method does not exist
• Expecting empty output without function calls
• Confusing syntax errors with runtime behavior

4. What is wrong with this code snippet for creating an OpenAI functions agent?

model = OpenAI()
functions = [get_time]
agent = OpenAIFunctionsAgent(functions, model)
response = agent.invoke({'input': 'What time is it?'})

medium

A. The agent constructor is missing named parameters for llm and tools

B. The tools list should be a dictionary, not a list

C. The invoke method requires a string, not a dictionary

D. The OpenAI model must be passed as a string, not an object

Solution

1. Step 1: Check constructor parameter usage

   The OpenAIFunctionsAgent requires named parameters: llm= and tools=, not positional arguments.

2. Step 2: Verify other parts of the code

   Tools as list is correct, invoke accepts a dictionary input, and model is an object as expected.

3. Final Answer:

   The agent constructor is missing named parameters for llm and tools -> Option A

4. Quick Check:

   Constructor needs named params llm= and tools= [OK]

Hint: Always use named parameters llm= and tools= in constructor [OK]

Common Mistakes:

• Passing positional arguments instead of named
• Thinking tools must be a dictionary
• Misunderstanding invoke input type

5. You want to build a Langchain app that answers user questions by calling either get_weather or get_news functions based on input. Which approach correctly sets up the OpenAI functions agent to handle this?

hard

A. Create two separate agents, one for weather and one for news, and switch manually

B. Pass both functions in a list to OpenAIFunctionsAgent and let it decide which to call

C. Use only get_weather function and ignore get_news for simplicity

D. Call functions directly without using an agent

Solution

1. Step 1: Understand agent's function selection

   The OpenAI functions agent can receive multiple functions and uses AI to pick the right one based on input.

2. Step 2: Evaluate options for best design

   Passing both functions in a list lets the agent decide automatically, which is the intended use.

3. Final Answer:

   Pass both functions in a list to OpenAIFunctionsAgent and let it decide which to call -> Option B

4. Quick Check:

   Agent selects function from list automatically [OK]

Hint: Give all functions to agent; it picks based on input [OK]

Common Mistakes:

• Manually switching between agents instead of one agent
• Ignoring needed functions for simplicity
• Bypassing agent and losing AI routing benefits