Metal Vector Store¶

Creating a Metal Vector Store¶

1. Register an account for Metal
2. Generate an API key in Metal's Settings. Save the api_key + client_id
3. Generate an Index in Metal's Dashboard. Save the index_id

Load data into your Index¶

In [ ]:

%pip install llama-index-vector-stores-metal

%pip install llama-index-vector-stores-metal

In [ ]:

import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

import logging import sys logging.basicConfig(stream=sys.stdout, level=logging.INFO) logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

In [ ]:

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.vector_stores.metal import MetalVectorStore
from IPython.display import Markdown, display

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader from llama_index.vector_stores.metal import MetalVectorStore from IPython.display import Markdown, display

Download Data

In [ ]:

!mkdir -p 'data/paul_graham/'
!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'

!mkdir -p 'data/paul_graham/' !wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'

In [ ]:

# load documents
documents = SimpleDirectoryReader("./data/paul_graham/").load_data()

# load documents documents = SimpleDirectoryReader("./data/paul_graham/").load_data()

In [ ]:

# 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
)

# 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¶

In [ ]:

# 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?")

# 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?")

In [ ]:

display(Markdown(f"<b>{response}</b>"))

display(Markdown(f"{response}"))