langchain-aneforge
LangChain embeddings that run on the Apple Neural Engine, via ANEForge. The encoder runs on the ANE with no CoreML, matching the fp32 reference to cosine ~1.0 at a fraction of the GPU's energy.
pip install langchain-aneforge
Apple Silicon macOS only (ANEForge reaches the engine through a built dispatch shim; see the ANEForge install notes).
Use
from langchain_aneforge import ANEEmbeddings
emb = ANEEmbeddings(model="sentence-transformers/all-MiniLM-L6-v2")
vec = emb.embed_query("the Apple Neural Engine runs networks at low power")
docs = emb.embed_documents(["one passage", "another passage"])
ANEEmbeddings is a standard langchain_core.embeddings.Embeddings, so it drops
into any LangChain retriever or vector store:
from langchain_community.vectorstores import FAISS
store = FAISS.from_texts(["...", "..."], ANEEmbeddings())
hits = store.similarity_search("query", k=3)
model is any BERT-family sentence encoder on the Hugging Face hub. Its pooling
mode and normalize flag are read from the model's own sentence-transformers config,
so mean-pooled (MiniLM, E5) and cls-pooled (BGE, GTE) models both produce correct
vectors. Pass int8=True to stream int8 weights (half the size, cosine ~0.9999).
License
MIT. Not affiliated with or endorsed by Apple or LangChain.
1 maintainer
Metadata
1 maintainer
Release files for langchain-aneforge 0.1.0
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