Gemini Embedder

from math import sqrt

from agno.knowledge.embedder.google import GeminiEmbedder


def normalize(vector: list[float]) -> list[float]:
    magnitude = sqrt(sum(value * value for value in vector))
    return [value / magnitude for value in vector] if magnitude else vector


document_embedder = GeminiEmbedder(
    id="gemini-embedding-001",
    dimensions=1536,
    task_type="RETRIEVAL_DOCUMENT",
)
query_embedder = GeminiEmbedder(
    id="gemini-embedding-001",
    dimensions=1536,
    task_type="RETRIEVAL_QUERY",
)

document_vector = normalize(
    document_embedder.get_embedding(
        "The quick brown fox jumps over the lazy dog."
    )
)
query_vector = normalize(query_embedder.get_embedding("Which animal jumps?"))

print(f"Document dimensions: {len(document_vector)}")
print(f"Query dimensions: {len(query_vector)}")