llama-index-embeddings-nebius 0.2.0

llama-index embeddings Nebius AI Studio integration

LlamaIndex Embeddings Integration: Nebius AI Studio

Overview

Integrate with Nebius AI Studio API, which provides access to open-source state-of-the-art text embeddings models.

Installation

pip install llama-index-embeddings-nebius

Usage

Initialization

With environmental variables.

NEBIUS_API_KEY=your_api_key

from llama_index.embeddings.nebius import NebiusEmbedding

embed_model = NebiusEmbedding(model_name="BAAI/bge-en-icl")

Without environmental variables

from llama_index.embeddings.nebius import NebiusEmbedding

embed_model = NebiusEmbedding(
    api_key="your_api_key", model_name="BAAI/bge-en-icl"
)

Launching

Basic usage

text = "Everyone loves justice at another person's expense"
embeddings = embed_model.get_text_embedding(text)
print(embeddings[:5])

Asynchronous usage

text = "Everyone loves justice at another person's expense"
embeddings = await embed_model.aget_text_embedding(text)
print(embeddings[:5])

Batched usage

texts = [
    "As the hours pass",
    "I will let you know",
    "That I need to ask",
    "Before I'm alone",
]

embeddings = embed_model.get_text_embedding_batch(texts)
print(*[x[:3] for x in embeddings], sep="\n")

Batched asynchronous usage

texts = [
    "As the hours pass",
    "I will let you know",
    "That I need to ask",
    "Before I'm alone",
]

embeddings = await embed_model.aget_text_embedding_batch(texts)
print(*[x[:3] for x in embeddings], sep="\n")