Databricks Certified Generative AI Engineer - Associate

Get started today

Ultimate access to all questions.

Explanation:

D is the correct answer.

Why D fixes it:

LLMChain requires both an llm (the actual model) and a prompt. The original code only passes prompt=prompt, so it fails to initialize (the import for OpenAI is there but unused).
D correctly does: LLMChain(llm=OpenAI(), prompt=prompt).
It also fixes the call to llm.generate({"adjective": "funny"}), which is the proper input format for a single example (a dict of variables). The original ["adjective": "funny"] has invalid syntax and the wrong structure.

Why the others are wrong:

A: Still missing the llm= argument and uses invalid .generate syntax.
B: Incorrectly does prompt.format("funny") (positional instead of keyword) and then passes a formatted string to LLMChain (wrong) + empty .generate().
C: Fixes only the .generate call but leaves the chain initialization broken (no LLM).

Modern/recommended note (post-LLMChain deprecation):

Newer LangChain code often uses LCEL instead:


from langchain_core.prompts import PromptTemplate

from langchain_openai import OpenAI   # or ChatOpenAI

prompt = PromptTemplate(...)

llm = OpenAI()

chain = prompt | llm

result = chain.invoke({"adjective": "funny"})


from langchain_core.prompts import PromptTemplate

from langchain_openai import OpenAI   # or ChatOpenAI

prompt = PromptTemplate(...)

llm = OpenAI()

chain = prompt | llm

result = chain.invoke({"adjective": "funny"})

Explanation:

D is the correct answer.

Why D fixes it:

LLMChain requires both an llm (the actual model) and a prompt. The original code only passes prompt=prompt, so it fails to initialize (the import for OpenAI is there but unused).
D correctly does: LLMChain(llm=OpenAI(), prompt=prompt).
It also fixes the call to llm.generate({"adjective": "funny"}), which is the proper input format for a single example (a dict of variables). The original ["adjective": "funny"] has invalid syntax and the wrong structure.

Why the others are wrong:

A: Still missing the llm= argument and uses invalid .generate syntax.
B: Incorrectly does prompt.format("funny") (positional instead of keyword) and then passes a formatted string to LLMChain (wrong) + empty .generate().
C: Fixes only the .generate call but leaves the chain initialization broken (no LLM).

Modern/recommended note (post-LLMChain deprecation):

Newer LangChain code often uses LCEL instead:


from langchain_core.prompts import PromptTemplate

from langchain_openai import OpenAI   # or ChatOpenAI

prompt = PromptTemplate(...)

llm = OpenAI()

chain = prompt | llm

result = chain.invoke({"adjective": "funny"})


from langchain_core.prompts import PromptTemplate

from langchain_openai import OpenAI   # or ChatOpenAI

prompt = PromptTemplate(...)

llm = OpenAI()

chain = prompt | llm

result = chain.invoke({"adjective": "funny"})

Comments (1)

carp もっくんJun 4, 2026 3:13 AM

ここの正解は"D"だ

LeetQuiz .Jun 7, 2026 5:41 AM

Hello carp, thank you for your comment. You're right. The correct answer is D; LLMChain must be initialized with both an llm (e.g., OpenAI()) and a prompt, and the generate method should receive a dictionary like {"adjective": "funny"}. Thank you for your feedback.

A Generative AI Engineer is testing a simple prompt template in LangChain using the code below, but it is getting an error.

from langchain.chains import LLMChain
from langchain.community.llms import OpenAI
from langchain.core.prompts import PromptTemplate

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(prompt=prompt)
llm.generate(["adjective": "funny"])

from langchain.chains import LLMChain
from langchain.community.llms import OpenAI
from langchain.core.prompts import PromptTemplate

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(prompt=prompt)
llm.generate(["adjective": "funny"])

Assuming the API key was properly defined, what change does the Generative AI Engineer need to make to fix their chain?

Exam-Like

Last updated: June 7, 2026 at 05:40

-1

prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)
llm = LLMChain(prompt=prompt)
llm.generate({"funny"})

prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)
llm = LLMChain(prompt=prompt)
llm.generate({"funny"})

16.7%

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(prompt=prompt.format("funny"))
llm.generate()

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(prompt=prompt.format("funny"))
llm.generate()

14.0%

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(prompt=prompt)
llm.generate({"adjective": "funny"})

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(prompt=prompt)
llm.generate({"adjective": "funny"})

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(llm=OpenAI(), prompt=prompt)
llm.generate({"adjective": "funny"})

prompt_template = "Tell me a {adjective} joke"

prompt = PromptTemplate(
    input_variables=["adjective"],
    template=prompt_template
)

llm = LLMChain(llm=OpenAI(), prompt=prompt)
llm.generate({"adjective": "funny"})

35.1%