docs/examples/embeddings/Langchain.ipynb
This guide shows you how to use embedding models from LangChain.
<a href="https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/embeddings/Langchain.ipynb" target="_parent"></a>
If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.
%pip install llama-index-embeddings-langchain
!pip install llama-index
from langchain.embeddings import HuggingFaceEmbeddings
from llama_index.embeddings.langchain import LangchainEmbedding
lc_embed_model = HuggingFaceEmbeddings(
model_name="sentence-transformers/all-mpnet-base-v2"
)
embed_model = LangchainEmbedding(lc_embed_model)
# Basic embedding example
embeddings = embed_model.get_text_embedding(
"It is raining cats and dogs here!"
)
print(len(embeddings), embeddings[:10])