llama-index-integrations/readers/llama-index-readers-astra-db/README.md
pip install llama-index-readers-astra-db
The Astra DB Loader returns a set of documents retrieved from Astra DB. The user initializes the loader with an Astra DB index. They then pass in a vector.
Here's an example usage of the AstraDBReader.
from openai import OpenAI
# Get the credentials for Astra DB
api_endpoint = "https://324<...>f1c.astra.datastax.com"
token = "AstraCS:<...>"
# EXAMPLE: OpenAI embeddings
client = OpenAI(api_key="sk-<...>")
# Call OpenAI (or generate embeddings another way)
response = client.embeddings.create(
input="Your text string goes here", model="text-embedding-ada-002"
)
# Get the embedding
query_vector = response.data[0].embedding
# Initialize the Reader object
from llama_index.readers.astra_db import AstraDBReader
# Your Astra DB Account will provide you with the endpoint URL and Token
reader = AstraDBReader(
collection_name="astra_v_table",
token=token,
api_endpoint=api_endpoint,
embedding_dimension=len(query_vector),
)
# Fetch data from the reader
documents = reader.load_data(vector=query_vector, limit=5)
This loader is designed to be used as a way to load data into LlamaIndex.
Note: Please see the AstraDB documentation here.