Why LangChain simplifies LLM application development - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a LangChain LLM instance.

LangChain

from langchain.llms import OpenAI
llm = OpenAI(model_name=[1])

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

A"text-davinci-003"

B"gpt-3.5-turbo"

C"bert-base"

D"gpt-2"

Attempts:

3 left

💡 Hint

Common Mistakes

Using unsupported model names like 'bert-base' which is not an OpenAI model.

The OpenAI class in LangChain uses model names like text-davinci-003 to specify which LLM to use.

2fill in blank

medium

Complete the code to generate a response from the LLM.

LangChain

response = llm.[1]("Hello, how are you?")

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

Acall

Bgenerate_text

Crun

Dpredict

Attempts:

3 left

💡 Hint

Common Mistakes

Using methods like 'generate_text' which do not exist in LangChain's LLM interface.

In LangChain, the predict method is used to get the LLM's response to a prompt.

3fill in blank

hard

Fix the error in the code to create a prompt template.

LangChain

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

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

Aname

B"name"

C["name"]

D'name'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a single string without list brackets, causing type errors.

The input_variables parameter expects a list of strings, so it must be ["name"].

4fill in blank

hard

Fill both blanks to create and use a chain that combines prompt and LLM.

LangChain

from langchain.chains import LLMChain
chain = LLMChain(llm=[1], prompt=[2])
result = chain.run("LangChain")

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

Allm

Bprompt

Cllm_chain

Dchain

Attempts:

3 left

💡 Hint

Common Mistakes

Using variable names that are not defined or incorrect parameter names.

The LLMChain constructor requires the llm and prompt arguments to connect the model and prompt template.

5fill in blank

hard

Fill all three blanks to create a simple LangChain app that uses an LLM, prompt, and chain.

LangChain

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

llm = OpenAI(model_name=[1])
prompt = PromptTemplate(input_variables=[2], template="Say hello to {{name}}.")
chain = LLMChain(llm=[3], prompt=prompt)
print(chain.run("Alice"))

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

A"text-davinci-003"

B["name"]

Cllm

D"gpt-4"

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect model names, wrong input_variables format, or wrong variable names in the chain.

This code sets up an OpenAI LLM with model text-davinci-003, defines a prompt template with input variable name, and creates a chain connecting the LLM and prompt. Then it runs the chain with input Alice.