Baseten Embeddings¶

This guide how to use performant open source embeddings and rerankers in the Baseten library. First we need to install LlamaIndex and the Baseten dependencies.

In [ ]:

%pip install llama-index llama-index-embeddings-baseten

%pip install llama-index llama-index-embeddings-baseten

Start a dedicated endpoint of your choice with the embedding you want here and paste your Baseten API key below.

In [ ]:

from llama_index.embeddings.baseten import BasetenEmbedding

from llama_index.embeddings.baseten import BasetenEmbedding

In [ ]:

# Using dedicated endpoint
embed_model = BasetenEmbedding(
    model_id="BASETEN_MODEL_ID",  # 8 character string
    api_key="BASETEN_API_KEY",
)

# Single embedding
embedding = embed_model.get_text_embedding("Hello, world!")

# Batch embeddings
embeddings = embed_model.get_text_embedding_batch(
    ["Hello, world!", "Goodbye, world!"]
)
print(embeddings)

# Using dedicated endpoint embed_model = BasetenEmbedding( model_id="BASETEN_MODEL_ID", # 8 character string api_key="BASETEN_API_KEY", ) # Single embedding embedding = embed_model.get_text_embedding("Hello, world!") # Batch embeddings embeddings = embed_model.get_text_embedding_batch( ["Hello, world!", "Goodbye, world!"] ) print(embeddings)

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