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Hamza Kyamanywa 064a1db2b2 [Documentation] Show how to initiate pinecone from an existing index (#3070 )

## What is this PR for:
* This PR adds a commented line of code in the documentation that shows
how someone can use the Pinecone client with an already existing
Pinecone index
* The documentation currently only shows how to create a pinecone index
from langchain documents but not how to load one that already exists

2023-04-18 07:27:46 -07:00

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Pinecone

This notebook shows how to use functionality related to the Pinecone vector database.

In [1]:

from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import Pinecone
from langchain.document_loaders import TextLoader

In [2]:

from langchain.document_loaders import TextLoader
loader = TextLoader('../../../state_of_the_union.txt')
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

embeddings = OpenAIEmbeddings()

In [ ]:

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
)

index_name = "langchain-demo"

docsearch = Pinecone.from_documents(docs, embeddings, index_name=index_name)

# if you already have an index, you can load it like this
# docsearch = Pinecone.from_existing_index(index_name, embeddings)

query = "What did the president say about Ketanji Brown Jackson"
docs = docsearch.similarity_search(query)

In [ ]:

print(docs[0].page_content)

In [ ]:

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Pinecone

2.6 KiB

Raw Blame History