langchain-localai is a 3rd party integration package for LocalAI. It provides a simple way to use LocalAI services in LangChain.The source code is available on Github
Let’s load the LocalAI Embedding class. In order to use the LocalAI Embedding class, you need to have the LocalAI service hosted somewhere and configure the embedding models. See the documentation at localai.io/basics/getting_started/index.html and localai.io/features/embeddings/index.html. 
%pip install -U langchain-localai

from langchain_localai import LocalAIEmbeddings

embeddings = LocalAIEmbeddings(
    openai_api_base="http://localhost:8080", model="embedding-model-name"
)

text = "This is a test document."

query_result = embeddings.embed_query(text)

doc_result = embeddings.embed_documents([text])
Let’s load the LocalAI Embedding class with first generation models (e.g. text-search-ada-doc-001/text-search-ada-query-001). Note: These are not recommended models - see here 
from langchain_community.embeddings import LocalAIEmbeddings

embeddings = LocalAIEmbeddings(
    openai_api_base="http://localhost:8080", model="embedding-model-name"
)

text = "This is a test document."

query_result = embeddings.embed_query(text)

doc_result = embeddings.embed_documents([text])

import os

# if you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass through
os.environ["OPENAI_PROXY"] = "http://proxy.yourcompany.com:8080"