OctoAI Embeddings¶

This guide shows you how to use OctoAI's Embeddings through LlamaIndex.

First, let's install LlamaIndex and OctoAI's dependencies

In [ ]:

%pip install llama-index-embeddings-octoai

%pip install llama-index-embeddings-octoai

In [ ]:

!pip install llama-index

!pip install llama-index

Include your OctoAI API key below. You can get yours at OctoAI.

Here are some instructions in case you need more guidance.

In [ ]:

OCTOAI_API_KEY = ""

OCTOAI_API_KEY = ""

We can then query embeddings on OctoAI

In [ ]:

from llama_index.embeddings.octoai import OctoAIEmbedding

embed_model = OctoAIEmbedding(api_key=OCTOAI_API_KEY)

from llama_index.embeddings.octoai import OctoAIEmbedding embed_model = OctoAIEmbedding(api_key=OCTOAI_API_KEY)

In [ ]:

# Basic embedding example
embeddings = embed_model.get_text_embedding("How do I sail to the moon?")
print(len(embeddings), embeddings[:10])
assert len(embeddings) == 1024

# Basic embedding example embeddings = embed_model.get_text_embedding("How do I sail to the moon?") print(len(embeddings), embeddings[:10]) assert len(embeddings) == 1024

Using Batched Embeddings¶

In [ ]:

texts = [
    "How do I sail to the moon?",
    "What is the best way to cook a steak?",
    "How do I apply for a job?",
]

embeddings = embed_model.get_text_embedding_batch(texts)
print(len(embeddings))
assert len(embeddings) == 3
assert len(embeddings[0]) == 1024

texts = [ "How do I sail to the moon?", "What is the best way to cook a steak?", "How do I apply for a job?", ] embeddings = embed_model.get_text_embedding_batch(texts) print(len(embeddings)) assert len(embeddings) == 3 assert len(embeddings[0]) == 1024