Comparing prompt versions in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a prompt template using LangChain.

LangChain

from langchain.prompts import PromptTemplate

prompt = PromptTemplate(template=[1], input_variables=["name"])

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

AHello, {name}!

B"Hello name!"

C'Hello, name!'

D"Hello, {name}!"

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to put the template inside quotes.

Using single quotes without curly braces.

Not including the variable name inside curly braces.

The template must be a string with curly braces around the variable name, and it must be passed as a string literal.

2fill in blank

medium

Complete the code to compare two prompt templates by their template strings.

LangChain

prompt1 = PromptTemplate(template="Hello, {name}!", input_variables=["name"])
prompt2 = PromptTemplate(template="Hi, {name}!", input_variables=["name"])
are_equal = prompt1.[1] == prompt2.[1]

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

Atemplate

Binput_variables

Cformat

Dtext

Attempts:

3 left

💡 Hint

Common Mistakes

Comparing input_variables instead of template strings.

Using a method name instead of an attribute.

Trying to compare the whole PromptTemplate objects directly.

The template attribute holds the string template, so comparing prompt1.template and prompt2.template checks if the prompt texts are the same.

3fill in blank

hard

Fix the error in the code to correctly format a prompt with a variable.

LangChain

prompt = PromptTemplate(template="Hello, {name}!", input_variables=["name"])
message = prompt.[1](name="Alice")

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

Aformat

Bformat_prompt

Crender

Dgenerate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'render' which is not a method of PromptTemplate.

Using 'format_prompt' which returns a PromptValue, not a string.

Using 'generate' which is for chains, not templates.

The correct method to fill in variables in a PromptTemplate is 'format', which returns the formatted string.

4fill in blank

hard

Fill both blanks to create a new prompt by combining two templates and formatting it.

LangChain

prompt1 = PromptTemplate(template="Hello, {name}!", input_variables=["name"])
prompt2 = PromptTemplate(template="Welcome to {place}.", input_variables=["place"])
combined_template = f"{prompt1.[1] {prompt2.[2]"
combined_prompt = PromptTemplate(template=combined_template, input_variables=["name", "place"])

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

Atemplate

Bformat

Cinput_variables

Dtext

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'format' instead of 'template' to get the string.

Mixing up input_variables with template strings.

Trying to call methods instead of accessing attributes.

To combine templates, access the 'template' attribute of prompt1 and prompt2. The first blank is for prompt1's template string, the second blank is for prompt2's template string.

5fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps variable names to their prompt templates if the template contains a keyword.

LangChain

prompts = {
    "greet": PromptTemplate(template="Hello, {name}!", input_variables=["name"]),
    "welcome": PromptTemplate(template="Welcome to {place}.", input_variables=["place"]),
    "bye": PromptTemplate(template="Goodbye, {name}!", input_variables=["name"])
}
filtered = {k: v.template for k, v in prompts.items() if "{BLANK_2}}" in v.{{BLANK_2}}

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

A:

Bname

Ctemplate

D,

Attempts:

3 left

💡 Hint

Common Mistakes

Using ',' instead of ':' in dictionary comprehension.

Checking for the wrong keyword.

Accessing a wrong attribute instead of 'template'.

In a dictionary comprehension, the key and value are separated by ':'. We filter templates containing the keyword 'name' in their 'template' attribute.

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