OpenAI embeddings in LangChain - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an OpenAI embeddings object using LangChain.

LangChain

from langchain.embeddings import OpenAIEmbeddings
embeddings = OpenAIEmbeddings([1]="text-embedding-ada-002")

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

Aapi_key

Bengine

Cmodel

Dembedding_model

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'api_key' instead of 'model' causes an error.

Using 'engine' is outdated for this library.

The model parameter specifies which OpenAI embedding model to use.

2fill in blank

medium

Complete the code to get the embedding vector for a text string.

LangChain

text = "Hello world"
vector = embeddings.[1](text)

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Aencode

Bembed_query

Cget_vector

Dtransform

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'encode' causes attribute errors.

Using 'get_vector' is not a valid method here.

The method embed_query returns the embedding vector for a single text input.

3fill in blank

hard

Fix the error in the code to create embeddings with an API key.

LangChain

embeddings = OpenAIEmbeddings(model="text-embedding-ada-002", [1]="my_api_key")

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Aapi_key

Bkey

Ctoken

Dauth

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'key' or 'token' causes authentication errors.

Using 'auth' is not recognized by the constructor.

The correct parameter to pass the API key is api_key.

4fill in blank

hard

Fill both blanks to create embeddings and get vector for a list of texts.

LangChain

texts = ["apple", "banana"]
embeddings = OpenAIEmbeddings([1]="text-embedding-ada-002")
vectors = embeddings.[2](texts)

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Amodel

Bembed_documents

Capi_key

Dembed_query

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'embed_query' for multiple texts returns errors.

Using 'api_key' as the first blank is incorrect here.

Use model to specify the model and embed_documents to get embeddings for multiple texts.

5fill in blank

hard

Fill all three blanks to create embeddings with API key and get vector for a single text.

LangChain

embeddings = OpenAIEmbeddings([1]="text-embedding-ada-002", [2]="my_api_key")
text = "OpenAI is great"
vector = embeddings.[3](text)

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

Amodel

Bapi_key

Cembed_query

Dembed_documents

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'embed_documents' for a single text causes confusion.

Mixing up 'api_key' parameter name causes errors.

Use model and api_key to create the embeddings object, then embed_query to get the vector for a single text.