Metal Vector Store#
Creating a Metal Vector Store#
Register an account for Metal
Generate an API key in Metal’s Settings. Save the
api_key
+client_id
Generate an Index in Metal’s Dashboard. Save the
index_id
Load data into your Index#
%pip install llama-index-vector-stores-metal
import logging
import sys
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.vector_stores.metal import MetalVectorStore
from IPython.display import Markdown, display
Download Data
!mkdir -p 'data/paul_graham/'
!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'
# load documents
documents = SimpleDirectoryReader("./data/paul_graham/").load_data()
# initialize Metal Vector Store
from llama_index.core import StorageContext
api_key = "api key"
client_id = "client id"
index_id = "index id"
vector_store = MetalVectorStore(
api_key=api_key,
client_id=client_id,
index_id=index_id,
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_documents(
documents, storage_context=storage_context
)
Query Index#
# set Logging to DEBUG for more detailed outputs
query_engine = index.as_query_engine()
response = query_engine.query("What did the author do growing up?")
display(Markdown(f"<b>{response}</b>"))