A/B testing prompt variations in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the correct class for prompt templates in LangChain.

LangChain

from langchain.prompts import [1]

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

APromptManager

BPromptTemplate

CPromptBuilder

DPromptFactory

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent class like PromptManager.

Confusing with other prompt-related classes.

The PromptTemplate class is used to create prompt templates in LangChain.

2fill in blank

medium

Complete the code to create two prompt templates for A/B testing with different greetings.

LangChain

prompt_a = PromptTemplate(template="Hello, {" + [1] + "}! How can I help you?")
prompt_b = PromptTemplate(template="Hi, {" + [1] + "}! What can I do for you?")

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

Acustomer

Buser

Cname

Dclient

Attempts:

3 left

💡 Hint

Common Mistakes

Using generic terms like 'user' or 'client' instead of a variable name.

Leaving the placeholder empty.

The variable name is commonly used to personalize prompts by inserting the user's name.

3fill in blank

hard

Fix the error in the code to select a prompt template randomly for A/B testing.

LangChain

import random
prompts = [prompt_a, prompt_b]
selected_prompt = prompts[[1](0, 1)]

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

Arandint

Bchoice

Crandom

Drandrange

Attempts:

3 left

💡 Hint

Common Mistakes

Using random.choice which returns an element, not an index.

Using random.random which returns a float.

random.randint(0, 1) returns a random integer 0 or 1, which is used as an index to select a prompt.

4fill in blank

hard

Fill both blanks to create a dictionary that maps prompt names to their templates for easy access.

LangChain

prompt_variations = { [1]: prompt_a, [2]: prompt_b }

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

A"A"

B"B"

C"prompt_a"

D"prompt_b"

Attempts:

3 left

💡 Hint

Common Mistakes

Using variable names as keys instead of strings.

Omitting quotes around keys.

Using simple keys like "A" and "B" helps identify prompt variations clearly.

5fill in blank

hard

Fill all three blanks to complete the function that runs A/B testing by selecting a prompt and formatting it with a user name.

LangChain

def run_ab_test(user_name):
    selected = prompt_variations[[1]]
    formatted_prompt = selected.[2]([3]=user_name)
    return formatted_prompt

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

A"A"

Bformat

Cname

D"B"

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect keys that don't exist in the dictionary.

Calling a non-existent method instead of format.

Passing the wrong argument name.

The function selects prompt "B", calls format with the keyword argument name to personalize the prompt.

Practice

1. What is the main purpose of using A/B testing with prompt variations in Langchain?

easy

A. To compare different prompt versions and find the best one

B. To speed up the execution of a single prompt

C. To combine multiple prompts into one

D. To automatically fix errors in prompts

Solution

1. Step 1: Understand A/B testing concept

   A/B testing means comparing two or more versions to see which works better.

2. Step 2: Apply to prompt variations

   In Langchain, this means running different prompt templates and comparing their outputs.

3. Final Answer:

   To compare different prompt versions and find the best one -> Option A

4. Quick Check:

   A/B testing = Compare versions [OK]

Hint: A/B testing means comparing versions to pick the best [OK]

Common Mistakes:

• Thinking A/B testing speeds up prompts
• Believing it merges prompts automatically
• Assuming it fixes prompt errors

2. Which of the following is the correct way to create two prompt variations for A/B testing in Langchain using the 'template=' keyword argument for both PromptTemplates?

easy

A. prompt1 = PromptTemplate('Hello {name}'); prompt2 = PromptTemplate(template='Hi {name}')

B. prompt1 = PromptTemplate('Hello {name}'); prompt2 = PromptTemplate('Hi {name}')

C. prompt1 = PromptTemplate(template='Hello {name}'); prompt2 = PromptTemplate(template='Hi {name}')

D. prompt1 = PromptTemplate(template='Hello {name}'); prompt2 = PromptTemplate('Hi {name}')

Solution

1. Step 1: Check PromptTemplate syntax

   PromptTemplate uses the named argument 'template' to define the prompt string.

2. Step 2: Verify both prompts use correct syntax

   Only prompt1 = PromptTemplate(template='Hello {name}'); prompt2 = PromptTemplate(template='Hi {name}') uses PromptTemplate(template='...') for both prompts correctly.

3. Final Answer:

   prompt1 = PromptTemplate(template='Hello {name}'); prompt2 = PromptTemplate(template='Hi {name}') -> Option C

4. Quick Check:

   Use template= keyword for PromptTemplate [OK]

Hint: PromptTemplate needs template='...' argument [OK]

Common Mistakes:

• Omitting the 'template=' keyword
• Mixing positional and keyword arguments
• Using incorrect string syntax

3. Given the code below, what will be the output of print(results)?

from langchain import PromptTemplate
prompt1 = PromptTemplate(template='Hello {name}')
prompt2 = PromptTemplate(template='Hi {name}')
inputs = {'name': 'Alice'}
results = [prompt1.format(**inputs), prompt2.format(**inputs)]
print(results)

medium

A. ['Hello Alice', 'Hi Alice']

B. ['Hello {name}', 'Hi {name}']

C. ['Hello', 'Hi']

D. Error: format method not found

Solution

1. Step 1: Understand PromptTemplate.format()

   The format method replaces placeholders like {name} with values from inputs.

2. Step 2: Apply inputs to both prompts

   Both prompts get 'Alice' for {name}, so outputs are 'Hello Alice' and 'Hi Alice'.

3. Final Answer:

   ['Hello Alice', 'Hi Alice'] -> Option A

4. Quick Check:

   format() replaces placeholders correctly [OK]

Hint: format() fills placeholders with input values [OK]

Common Mistakes:

• Thinking format() returns template string unchanged
• Expecting placeholders to remain in output
• Assuming format() method does not exist

4. Identify the error in this A/B testing code snippet:

from langchain import PromptTemplate
prompt1 = PromptTemplate(template='Hello {name}')
prompt2 = PromptTemplate(template='Hi {name}')
inputs = {'name': 'Bob'}
results = [prompt1.format(inputs), prompt2.format(inputs)]
print(results)

medium

A. PromptTemplate missing template argument

B. Using format() without unpacking inputs dictionary

C. inputs dictionary missing required key

D. print statement syntax error

Solution

1. Step 1: Check how format() is called

   format() expects keyword arguments, so inputs must be unpacked with **inputs.

2. Step 2: Identify the error

   Code passes inputs as a single dict argument, causing a TypeError.

3. Final Answer:

   Using format() without unpacking inputs dictionary -> Option B

4. Quick Check:

   Use **inputs to unpack dict for format() [OK]

Hint: Always unpack dict with ** when calling format() [OK]

Common Mistakes:

• Passing dict directly instead of unpacking
• Forgetting to import PromptTemplate
• Using wrong print syntax

5. You want to run A/B testing on three prompt variations and select the best output based on a scoring function. Which approach correctly implements this in Langchain?

hard

A. Use a loop to create prompts but do not run format(), just score the templates

B. Create one PromptTemplate with all variations combined, run format() once, then score the single output

C. Run format() on one prompt, then copy the output three times and score them

D. Create three PromptTemplate objects, run format() on each with inputs, then apply the scoring function to outputs and pick the highest score

Solution

1. Step 1: Understand A/B testing with multiple prompts

   You need separate prompt templates for each variation to test them individually.

2. Step 2: Run each prompt with the same inputs and score outputs

   Format each prompt with inputs, then apply scoring to compare results.

3. Step 3: Select the best output based on scores

   Pick the output with the highest score as the best prompt result.

4. Final Answer:

   Create three PromptTemplate objects, run format() on each with inputs, then apply the scoring function to outputs and pick the highest score -> Option D

5. Quick Check:

   Separate prompts + score outputs = best choice [OK]

Hint: Run all prompts, score outputs, pick highest score [OK]

Common Mistakes:

• Combining prompts into one string
• Scoring templates instead of outputs
• Not running format() before scoring