Creating tools for agents in LangChain - Try It Yourself

Creating Tools for Agents with LangChain

📖 Scenario: You are building a simple assistant that can perform specific tasks using tools. These tools help the assistant answer questions or perform actions by connecting to external functions.

🎯 Goal: Create a LangChain agent that uses a custom tool to answer questions about the current date and time.

📋 What You'll Learn

Create a tool function that returns the current date and time as a string.

Create a LangChain Tool object using the tool function.

Create an agent that uses the tool to answer questions.

Run the agent with a sample question about the current date and time.

💡 Why This Matters

🌍 Real World

Agents with tools help automate tasks by connecting language models to real functions, making assistants smarter and more useful.

💼 Career

Understanding how to create and use tools in LangChain is valuable for building AI assistants, chatbots, and automation systems in software development roles.

1

Create a tool function to get current date and time

Write a Python function called get_current_datetime that returns the current date and time as a string using datetime.now() and strftime with format "%Y-%m-%d %H:%M:%S".

LangChain

# Your code here
def get_current_datetime():
    pass

Hint

Use from datetime import datetime and return datetime.now().strftime("%Y-%m-%d %H:%M:%S").

2

Create a LangChain Tool using the function

Import Tool from langchain.agents and create a variable called datetime_tool that is a Tool object. Set its name to "CurrentDateTime", func to get_current_datetime, and description to "Returns the current date and time as a string.".

LangChain

from datetime import datetime

def get_current_datetime():
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")

# Your code here

Hint

Use Tool(name=..., func=..., description=...) to create the tool.

3

Create an agent using the tool

Import initialize_agent and AgentType from langchain.agents. Create a variable called agent by calling initialize_agent with a list containing datetime_tool, an llm set to None (placeholder), and agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION. This sets up the agent to use the tool.

LangChain

from datetime import datetime
from langchain.agents import Tool, initialize_agent, AgentType

def get_current_datetime():
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")

datetime_tool = Tool(
    name="CurrentDateTime",
    func=get_current_datetime,
    description="Returns the current date and time as a string."
)

# Your code here

Hint

Use initialize_agent(tools=[datetime_tool], llm=None, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION).

4

Run the agent with a sample question

Call agent.run with the string "What is the current date and time?" to get the answer using the tool.

LangChain

from datetime import datetime
from langchain.agents import Tool, initialize_agent, AgentType

def get_current_datetime():
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")

datetime_tool = Tool(
    name="CurrentDateTime",
    func=get_current_datetime,
    description="Returns the current date and time as a string."
)

agent = initialize_agent(
    tools=[datetime_tool],
    llm=None,
    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION
)

# Your code here

Hint

Use agent.run("What is the current date and time?") to ask the agent.

Practice

1. What is the main purpose of creating tools for agents in Langchain?

easy

A. To let agents perform specific tasks easily

B. To make the code run faster

C. To store data permanently

D. To create user interfaces

Solution

1. Step 1: Understand the role of tools in Langchain

   Tools are designed to help agents do tasks by providing specific functions.

2. Step 2: Identify the main benefit

   By using tools, agents can perform tasks more easily and effectively.

3. Final Answer:

   To let agents perform specific tasks easily -> Option A

4. Quick Check:

   Tools help agents do tasks = B [OK]

Hint: Tools help agents do tasks simply and clearly [OK]

Common Mistakes:

• Thinking tools speed up code execution
• Confusing tools with data storage
• Assuming tools create user interfaces

2. Which of the following is the correct way to create a tool in Langchain?

easy

A. tool = Tool(func=search_function)

B. tool = Tool('search', description='Searches data')

C. tool = Tool(name='search', description='Searches data')

D. tool = Tool(name='search', func=search_function, description='Searches data')

Solution

1. Step 1: Check required parameters for Tool

   The Tool constructor needs a name, a function (func), and a description.

2. Step 2: Match parameters with options

   Only tool = Tool(name='search', func=search_function, description='Searches data') provides all three: name, func, and description correctly.

3. Final Answer:

   tool = Tool(name='search', func=search_function, description='Searches data') -> Option D

4. Quick Check:

   Tool needs name, func, description = C [OK]

Hint: Tool needs name, function, and description to work [OK]

Common Mistakes:

• Omitting the function parameter
• Passing parameters in wrong order
• Leaving out the description

3. Given this code snippet, what will be the output when the agent uses the tool?

def greet(name: str) -> str:
    return f"Hello, {name}!"

from langchain.agents import Tool

greet_tool = Tool(name='greet', func=greet, description='Greets a person')

result = greet_tool.func('Alice')
print(result)

medium

A. "greet Alice"

B. "Hello, Alice!"

C. Error: Missing agent call

D. "Hello!"

Solution

1. Step 1: Understand the greet function behavior

   The greet function returns a string "Hello, {name}!" with the given name.

2. Step 2: Check how the tool is used

   The tool calls greet with 'Alice', so it returns "Hello, Alice!" which is printed.

3. Final Answer:

   "Hello, Alice!" -> Option B

4. Quick Check:

   greet('Alice') = "Hello, Alice!" [OK]

Hint: Tool calls function directly with given input [OK]

Common Mistakes:

• Thinking the tool prints 'greet Alice'
• Assuming an error without agent context
• Ignoring the name parameter in output

4. Identify the error in this tool creation code:

def add_numbers(a, b):
    return a + b

from langchain.agents import Tool

add_tool = Tool(name='add', func=add_numbers, description='Adds two numbers')

result = add_tool.func(5)
print(result)

medium

A. Missing one argument when calling add_tool.func

B. Tool name must be uppercase

C. Description is too short

D. Function add_numbers should not return a value

Solution

1. Step 1: Check function parameters

   add_numbers requires two arguments: a and b.

2. Step 2: Check function call

   add_tool.func is called with only one argument (5), missing the second argument.

3. Final Answer:

   Missing one argument when calling add_tool.func -> Option A

4. Quick Check:

   Function needs 2 args, call has 1 = D [OK]

Hint: Match function parameters with call arguments count [OK]

Common Mistakes:

• Ignoring argument count mismatch
• Thinking tool name case matters
• Assuming description length causes error

5. You want to create a tool that converts temperatures from Celsius to Fahrenheit for an agent. Which code correctly creates this tool with a clear description?

hard

A. def convert_temp(f):
return (f - 32) * 5/9

from langchain.agents import Tool

tool = Tool(name='temp_convert', func=convert_temp, description='Converts Fahrenheit to Celsius')

B. def c_to_f(c):
return c + 32

from langchain.agents import Tool

temp_tool = Tool(name='temp', func=c_to_f, description='Temperature conversion')

C. def c_to_f(c):
return (c * 9/5) + 32

from langchain.agents import Tool

temp_tool = Tool(name='temp_convert', func=c_to_f, description='Converts Celsius to Fahrenheit')

D. def c_to_f(c):
return (c * 9/5) + 32

tool = Tool(func=c_to_f, description='Convert temp')

Solution

1. Step 1: Verify function correctness

   The c_to_f(c) function returns (c * 9/5) + 32, which correctly converts Celsius to Fahrenheit using the standard formula.

2. Step 2: Check tool creation parameters

   Tool(name='temp_convert', func=c_to_f, description='Converts Celsius to Fahrenheit') uses name, func, and a clear description matching the task.

3. Final Answer:

   def c_to_f(c):\n return (c * 9/5) + 32\n\nfrom langchain.agents import Tool\n\ntemp_tool = Tool(name='temp_convert', func=c_to_f, description='Converts Celsius to Fahrenheit') -> Option C

4. Quick Check:

   Correct formula and clear tool setup = A [OK]

Hint: Use correct formula and full tool parameters [OK]

Common Mistakes:

• Using wrong temperature formula
• Omitting tool name or description
• Confusing Celsius to Fahrenheit with reverse