Atlas

Atlas is a platform by Nomic made for interacting with both small and internet scale unstructured datasets. It enables anyone to visualize, search, and share massive datasets in their browser.

This notebook shows you how to use functionality related to the AtlasDB vectorstore.

pip install spacy

python3 -m spacy download en_core_web_sm

pip install nomic

Load Packages

import time
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import SpacyTextSplitter
from langchain.vectorstores import AtlasDB
from langchain.document_loaders import TextLoader

API Reference:

• OpenAIEmbeddings
• SpacyTextSplitter
• AtlasDB
• TextLoader

ATLAS_TEST_API_KEY = "7xDPkYXSYDc1_ErdTPIcoAR9RNd8YDlkS3nVNXcVoIMZ6"

Prepare the Data

loader = TextLoader("../../../state_of_the_union.txt")
documents = loader.load()
text_splitter = SpacyTextSplitter(separator="|")
texts = []
for doc in text_splitter.split_documents(documents):
    texts.extend(doc.page_content.split("|"))

texts = [e.strip() for e in texts]

Map the Data using Nomic's Atlas

db = AtlasDB.from_texts(
    texts=texts,
    name="test_index_" + str(time.time()),  # unique name for your vector store
    description="test_index",  # a description for your vector store
    api_key=ATLAS_TEST_API_KEY,
    index_kwargs={"build_topic_model": True},
)

db.project.wait_for_project_lock()

db.project

Here is a map with the result of this code. This map displays the texts of the State of the Union. https://atlas.nomic.ai/map/3e4de075-89ff-486a-845c-36c23f30bb67/d8ce2284-8edb-4050-8b9b-9bb543d7f647