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Python
Integrate with the FakeEmbeddings embedding model using LangChain Python.
from langchain_community.embeddings import FakeEmbeddings
embeddings = FakeEmbeddings(size=1352)
query_result = embeddings.embed_query("foo")
doc_results = embeddings.embed_documents(["foo"])
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