Why LangChain simplifies LLM applications in Prompt Engineering / GenAI - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the main LangChain class for building LLM apps.

Prompt Engineering / GenAI

from langchain.chains import [1]

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AChain

BLLMChain

CModel

DLangChain

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a class that does not exist in LangChain.

Confusing LangChain with the model class.

The LLMChain class is the core building block in LangChain for chaining language model calls.

2fill in blank

medium

Complete the code to create a prompt template in LangChain.

Prompt Engineering / GenAI

from langchain.prompts import [1]
prompt = [1](template="Hello, {name}!")

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APromptBuilder

BPrompt

CTemplatePrompt

DPromptTemplate

Attempts:

3 left

💡 Hint

Common Mistakes

Using a class that does not exist in LangChain prompts module.

Confusing with generic 'Prompt'.

PromptTemplate is the class used to create prompt templates with variables.

3fill in blank

hard

Fix the error in this LangChain code to run the chain with input variables.

Prompt Engineering / GenAI

result = chain.run([1])

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A{'name': 'Alice'}

B"name='Alice'"

Cname='Alice'

D['name', 'Alice']

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a string instead of a dictionary.

Passing a tuple or list instead of dict.

The run method expects a dictionary of input variables, so use {'name': 'Alice'}.

4fill in blank

hard

Fill both blanks to create an LLMChain with OpenAI model and prompt template.

Prompt Engineering / GenAI

from langchain.llms import [1]
from langchain.prompts import [2]
from langchain.chains import LLMChain
chain = LLMChain(llm=[1](), prompt=[2](template="Hello, {name}!"))

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AOpenAI

BChatOpenAI

CPromptTemplate

DPrompt

Attempts:

3 left

💡 Hint

Common Mistakes

Using ChatOpenAI instead of OpenAI for this example.

Using a wrong prompt class.

OpenAI is the LLM class and PromptTemplate is used for the prompt in LLMChain.

5fill in blank

hard

Fill all three blanks to build and run a LangChain app that greets a user.

Prompt Engineering / GenAI

from langchain.llms import [1]
from langchain.prompts import [2]
from langchain.chains import LLMChain
chain = LLMChain(llm=[1](), prompt=[2](template="Hello, {name}!"))
output = chain.run([3])
print(output)

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AOpenAI

BPromptTemplate

C{'name': 'Bob'}

DChatOpenAI

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up LLM classes.

Passing inputs as string instead of dict.

Using wrong prompt class.

Use OpenAI as the LLM, PromptTemplate for the prompt, and pass inputs as a dictionary {'name': 'Bob'} to run.