Sentence Transformer Embedder

Generate local embeddings with the sentence-transformers library.

SentenceTransformerEmbedder defaults to sentence-transformers/all-MiniLM-L6-v2 with 384 dimensions. Models download from Hugging Face on first use and run locally.

from agno.knowledge.embedder.sentence_transformer import SentenceTransformerEmbedder

embedder = SentenceTransformerEmbedder()
embedding = embedder.get_embedding("The quick brown fox jumps over the lazy dog.")

print(embedding[:5])
print(len(embedding))

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Install dependencies

uv pip install -U agno sentence-transformers

Run the example

python sentence_transformer_embedder.py

Developer Resources