Comparing prompt versions in LangChain - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What output does this LangChain prompt version comparison produce?

Given two prompt versions in LangChain, what will be the printed output when comparing their templates?

LangChain

from langchain.prompts import PromptTemplate

prompt_v1 = PromptTemplate(template="Hello, {name}!")
prompt_v2 = PromptTemplate(template="Hello, {name}! How are you?")

print(prompt_v1.template == prompt_v2.template)
print(prompt_v1.format(name="Alice"))
print(prompt_v2.format(name="Alice"))

A False\nHello, Alice!\nHello, Alice! How are you?

B True\nHello, Alice!\nHello, Alice!

C False\nHello, {name}!\nHello, {name}! How are you?

D True\nHello, Alice! How are you?\nHello, Alice! How are you?

💡 Hint

Check if the template strings are exactly the same and how format replaces placeholders.

The two prompt templates have different template strings, so comparing them returns False. Formatting replaces {name} with 'Alice' in each template, producing different outputs.

📝 Syntax

intermediate

Which prompt version code snippet will raise a KeyError?

Identify which LangChain prompt version code will cause a KeyError when formatting.

A PromptTemplate(template="Welcome, {user}!").format(user="Bob", extra="data")

B PromptTemplate(template="Welcome, {user}!").format(user="Bob")

C PromptTemplate(template="Welcome, {user}!").format(username="Bob")

D PromptTemplate(template="Welcome, {username}!").format(user="Bob")

💡 Hint

Check if the placeholder name matches the format argument name.

Option D uses a template with {username} but calls format with user="Bob", causing a KeyError because 'username' is missing.

❓ state_output

advanced

What is the output of comparing two PromptTemplate objects with identical templates but different input variables?

Consider these two prompt versions. What will be the result of comparing their templates and input variables?

LangChain

from langchain.prompts import PromptTemplate

prompt1 = PromptTemplate(template="Hi {name}, your age is {age}.", input_variables=["name", "age"])
prompt2 = PromptTemplate(template="Hi {name}, your age is {age}.", input_variables=["name"])

print(prompt1.template == prompt2.template)
print(prompt1.input_variables == prompt2.input_variables)

A False\nFalse

B True\nFalse

C False\nTrue

D True\nTrue

💡 Hint

Templates are strings; input_variables are lists. Compare both separately.

The template strings are identical, so the first comparison is True. The input_variables lists differ, so the second comparison is False.

🔧 Debug

advanced

Why does this prompt version comparison raise a TypeError?

Examine the code and identify why comparing prompt_v1 and prompt_v2 raises a TypeError.

LangChain

from langchain.prompts import PromptTemplate

prompt_v1 = PromptTemplate(template="Hello {name}")
prompt_v2 = "Hello {name}"

print(prompt_v1 == prompt_v2)

A Because PromptTemplate objects cannot be compared with strings using ==

B Because prompt_v1.template is None

C Because the template strings differ in whitespace

D Because prompt_v2 is a string, not a PromptTemplate object, so comparison fails

💡 Hint

Check the types of the objects being compared and how LangChain defines equality.

LangChain's PromptTemplate does not support equality comparison with strings, so comparing prompt_v1 (PromptTemplate) with prompt_v2 (string) raises a TypeError.

🧠 Conceptual

expert

Which statement best describes the difference between prompt versions in LangChain?

Select the most accurate description of how prompt versions differ and how LangChain manages them.

A Prompt versions differ only in template strings; LangChain tracks versions by template hash internally.

B LangChain automatically merges prompt versions and resolves conflicts based on input variables.

C Prompt versions can differ in template, input variables, and partial variables; LangChain treats each PromptTemplate instance independently without built-in version control.

D Prompt versions are managed by LangChain using a built-in version number property that increments on each change.

💡 Hint

Consider what aspects define a prompt version and how LangChain handles PromptTemplate objects.

LangChain's PromptTemplate instances differ by template, input variables, and partial variables. LangChain does not provide built-in version control or automatic merging; each instance is independent.

Practice

1. What is the main purpose of comparing different prompt versions in Langchain?

easy

A. To find the best wording that improves AI task results

B. To increase the number of API calls

C. To reduce the size of the prompt template

D. To change the programming language used

Solution

1. Step 1: Understand the goal of prompt comparison

   Comparing prompt versions helps identify which wording or structure yields better AI responses.

2. Step 2: Eliminate unrelated options

   Increasing API calls, reducing prompt size, or changing language do not relate to improving prompt effectiveness.

3. Final Answer:

   To find the best wording that improves AI task results -> Option A

4. Quick Check:

   Comparing prompts = find best wording [OK]

Hint: Focus on improving AI output quality, not technical details [OK]

Common Mistakes:

• Thinking prompt comparison reduces API calls
• Confusing prompt size with prompt quality
• Assuming language change is the goal

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

easy

A. PromptTemplate(prompt="Hello {name}", args=["name"])

B. PromptTemplate(name="Hello {name}", variables=["name"])

C. PromptTemplate(text="Hello {name}", inputs=["name"])

D. PromptTemplate(template="Hello {name}", input_variables=["name"])

Solution

1. Step 1: Recall PromptTemplate syntax

   The correct constructor uses 'template' for the prompt text and 'input_variables' for placeholders.

2. Step 2: Check each option

   Only PromptTemplate(template="Hello {name}", input_variables=["name"]) uses 'template' and 'input_variables' correctly; others use wrong parameter names.

3. Final Answer:

   PromptTemplate(template="Hello {name}", input_variables=["name"]) -> Option D

4. Quick Check:

   Correct parameters = template + input_variables [OK]

Hint: Remember: 'template' and 'input_variables' are required keys [OK]

Common Mistakes:

• Using 'name' instead of 'template' for prompt text
• Using 'variables' instead of 'input_variables'
• Confusing parameter names

3. Given the code below, what will be printed?

from langchain import PromptTemplate

prompt_v1 = PromptTemplate(template="Hello, {name}!", input_variables=["name"])
prompt_v2 = PromptTemplate(template="Hi {name}, how are you?", input_variables=["name"])

print(prompt_v1.format(name="Alice"))
print(prompt_v2.format(name="Alice"))

medium

A. Hello Alice!
Hi Alice, how are you?

B. Hello, Alice!
Hi Alice, how are you?

C. Hello, {name}!
Hi {name}, how are you?

D. Error: Missing input variable

Solution

1. Step 1: Understand PromptTemplate.format()

   The format method replaces placeholders with provided values, here 'name' is 'Alice'.

2. Step 2: Apply formatting to each prompt

   prompt_v1 becomes "Hello, Alice!" and prompt_v2 becomes "Hi Alice, how are you?".

3. Final Answer:

   Hello, Alice! Hi Alice, how are you? -> Option B

4. Quick Check:

   Formatted prompts show replaced names [OK]

Hint: Format replaces {name} with 'Alice' exactly [OK]

Common Mistakes:

• Ignoring commas or punctuation in output
• Printing raw template without formatting
• Assuming error without missing inputs

4. What is the error in the following code snippet?

from langchain import PromptTemplate

prompt = PromptTemplate(template="Hello, {user}!")
print(prompt.format(name="Bob"))

medium

A. Missing input_variables parameter in PromptTemplate

B. PromptTemplate cannot be imported from langchain

C. Using 'name' instead of 'user' in format call

D. No error, code runs fine

Solution

1. Step 1: Check PromptTemplate parameters

   While 'input_variables' is recommended, it is optional if placeholders are in template.

2. Step 2: Check format call variables

   The template expects 'user' but format is called with 'name', causing a KeyError.

3. Final Answer:

   Using 'name' instead of 'user' in format call -> Option C

4. Quick Check:

   Format keys must match template placeholders [OK]

Hint: Match format keys exactly to template placeholders [OK]

Common Mistakes:

• Assuming missing input_variables causes error
• Thinking import is wrong
• Ignoring variable name mismatch

5. You want to compare two prompt versions to see which generates a more polite greeting. You have these prompts:

prompt_v1 = PromptTemplate(template="Hey {name}, what's up?", input_variables=["name"])
prompt_v2 = PromptTemplate(template="Good day, {name}. How do you do?", input_variables=["name"])

Which approach best helps you compare their effectiveness?

hard

A. Format both prompts with the same name and print outputs side-by-side for review

B. Use only prompt_v1 since it is shorter and simpler

C. Change the input variable names to different ones for each prompt

D. Run prompt_v2 without formatting to see the raw template

Solution

1. Step 1: Understand comparison goal

   You want to see which prompt wording sounds more polite for the same input.

2. Step 2: Use consistent input and print both outputs

   Formatting both prompts with the same name and printing outputs side-by-side lets you compare wording clearly.

3. Final Answer:

   Format both prompts with the same name and print outputs side-by-side for review -> Option A

4. Quick Check:

   Compare outputs side-by-side for best prompt [OK]

Hint: Print both formatted prompts together to compare easily [OK]

Common Mistakes:

• Choosing only one prompt without comparison
• Changing input variable names inconsistently
• Not formatting prompts before comparing