DeterministicFakeEmbedding()Deterministic fake embedding model for unit testing purposes.
This embedding model creates embeddings by sampling from a normal distribution with a seed based on the hash of the text.
Do not use this outside of testing, as it is not a real embedding model.
Instantiate:
from langchain_core.embeddings import DeterministicFakeEmbedding
embed = DeterministicFakeEmbedding(size=100)Embed single text:
input_text = "The meaning of life is 42"
vector = embed.embed_query(input_text)
print(vector[:3])[-0.700234640213188, -0.581266257710429, -1.1328482266445354]Embed multiple texts:
input_texts = ["Document 1...", "Document 2..."]
vectors = embed.embed_documents(input_texts)
print(len(vectors))
# The first 3 coordinates for the first vector
print(vectors[0][:3])2
[-0.5670477847544458, -0.31403828652395727, -0.5840547508955257]