ChatPromptTemplate for conversations in LangChain - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What is the output of this ChatPromptTemplate usage?

Given this LangChain ChatPromptTemplate code, what will be the final prompt text after formatting?

from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate

system_template = SystemMessagePromptTemplate.from_template("You are a helpful assistant.")
human_template = HumanMessagePromptTemplate.from_template("Translate this: {text}")

chat_prompt = ChatPromptTemplate.from_messages([system_template, human_template])

final_prompt = chat_prompt.format_prompt(text="Hello world")
print(final_prompt.to_string())

LangChain

from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate

system_template = SystemMessagePromptTemplate.from_template("You are a helpful assistant.")
human_template = HumanMessagePromptTemplate.from_template("Translate this: {text}")

chat_prompt = ChatPromptTemplate.from_messages([system_template, human_template])

final_prompt = chat_prompt.format_prompt(text="Hello world")
print(final_prompt.to_string())

A You are a helpful assistant.\nTranslate this: Hello world

B System: You are a helpful assistant.\nHuman: Translate this: {text}

C System: You are a helpful assistant.\nHuman: Translate this: Hello world

D System: You are a helpful assistant.\nHuman: Hello world

💡 Hint

Remember that format_prompt replaces placeholders in all message templates.

The ChatPromptTemplate combines system and human messages. The human message has a placeholder {text} replaced by 'Hello world'. The to_string() method shows role and content lines.

📝 Syntax

intermediate

Which option causes a syntax error in ChatPromptTemplate usage?

Identify which code snippet will raise a syntax error when creating a ChatPromptTemplate with message templates.

A ChatPromptTemplate.from_messages([SystemMessagePromptTemplate.from_template("Hello"), HumanMessagePromptTemplate.from_template("Say {word")])

B ChatPromptTemplate.from_messages([SystemMessagePromptTemplate.from_template("Hello"), HumanMessagePromptTemplate.from_template("Say {word}")])

C ChatPromptTemplate.from_messages([SystemMessagePromptTemplate.from_template("Hello"), HumanMessagePromptTemplate.from_template("Say {word}!")])

D ChatPromptTemplate.from_messages([SystemMessagePromptTemplate.from_template("Hello"), HumanMessagePromptTemplate.from_template("Say {word}.")])

💡 Hint

Check if all curly braces are properly closed in the template strings.

Option A has an unclosed placeholder {word which causes a syntax error during template parsing.

❓ state_output

advanced

What is the value of 'final_prompt.messages[1].content' after formatting?

Consider this code snippet:

from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate

chat_prompt = ChatPromptTemplate.from_messages([
    SystemMessagePromptTemplate.from_template("System: {system_msg}"),
    HumanMessagePromptTemplate.from_template("User says: {user_msg}")
])

final_prompt = chat_prompt.format_prompt(system_msg="Ready", user_msg="Hello")

result = final_prompt.messages[1].content
print(result)

What will be printed?

LangChain

from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate

chat_prompt = ChatPromptTemplate.from_messages([
    SystemMessagePromptTemplate.from_template("System: {system_msg}"),
    HumanMessagePromptTemplate.from_template("User says: {user_msg}")
])

final_prompt = chat_prompt.format_prompt(system_msg="Ready", user_msg="Hello")

result = final_prompt.messages[1].content
print(result)

A System: Ready

B User says: Hello

C User says: {user_msg}

D System: {system_msg}

💡 Hint

final_prompt.messages is a list of message objects in order of templates.

The second message (index 1) is the human message with placeholder replaced by 'Hello'.

🔧 Debug

advanced

Why does this ChatPromptTemplate.format_prompt call raise a KeyError?

Examine this code:

from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate

chat_prompt = ChatPromptTemplate.from_messages([
    SystemMessagePromptTemplate.from_template("System: {system_msg}"),
    HumanMessagePromptTemplate.from_template("User says: {user_msg}")
])

final_prompt = chat_prompt.format_prompt(system_msg="Ready")

Why does the last line raise a KeyError?

LangChain

from langchain.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, HumanMessagePromptTemplate

chat_prompt = ChatPromptTemplate.from_messages([
    SystemMessagePromptTemplate.from_template("System: {system_msg}"),
    HumanMessagePromptTemplate.from_template("User says: {user_msg}")
])

final_prompt = chat_prompt.format_prompt(system_msg="Ready")

A Because the placeholder {system_msg} is missing in the template

B Because the HumanMessagePromptTemplate is not properly imported

C Because format_prompt requires no arguments for this template

D Because the placeholder {user_msg} is not provided in format_prompt arguments

💡 Hint

Check if all placeholders in all message templates have matching arguments.

The human message template has {user_msg} placeholder but format_prompt was called without user_msg argument, causing KeyError.

🧠 Conceptual

expert

Which option best describes the role of ChatPromptTemplate in LangChain?

Select the most accurate description of what ChatPromptTemplate does in LangChain.

A It combines multiple message templates into a single prompt that can be formatted with variables for chat models.

B It executes chat models and returns their responses directly without formatting.

C It stores raw text prompts without any variable placeholders or message roles.

D It is used to train chat models by providing labeled conversation data.

💡 Hint

Think about how ChatPromptTemplate helps prepare prompts for chat models.

ChatPromptTemplate organizes system and human message templates with placeholders, then formats them into a full prompt for chat models.