Comments (2)
From https://langchain.readthedocs.io/en/latest/ecosystem/pinecone.html:
- Add client as dependency:
pip install pinecone-client
(add to README and Dockerfile) - Add import to
microllama.py
:from langchain.vectorstores import Pinecone
From Pinecone notebook example:
import pinecone
# initialize pinecone
pinecone.init(
api_key="YOUR_API_KEY", # find at app.pinecone.io
environment="YOUR_ENV" # next to api key in console
)
pinecone_index_name = "langchain-demo"
Then something like
def build_pinecone_index():
return Pinecone.from_documents(
get_text_chunks(), OpenAIEmbeddings(), index_name=PINECONE_INDEX_NAME
)
def get_pinecone_index(index_name=PINECONE_INDEX_NAME):
return Pinecone.from_existing_index(index_name, OpenAIEmbeddings())
from microllama.
Initial impressions are the Pinecone is noticeably slower than FAISS. I'd need to refactor get_index
to support multiple index types. The check for an existing index (pinecone.describe_index("index-name")
) is ~0.7s.
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Related Issues (4)
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