LangChain

Pinecone #

松果（Pinecone） (opens in a new tab)是一个功能广泛的向量数据库。

本教程展示了如何使用与松果（Pinecone）向量数据库相关的功能。

要使用松果（Pinecone），您必须拥有API密钥。以下是安装说明 (opens in a new tab)。

!pip install pinecone-client

import os
import getpass
 
PINECONE_API_KEY = getpass.getpass('Pinecone API Key:')

PINECONE_ENV = getpass.getpass('Pinecone Environment:')

我们想使用OpenAI Embeddings，因此我们必须获取OpenAI API密钥。

os.environ['OPENAI_API_KEY'] = getpass.getpass('OpenAI API Key:')

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

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()

import pinecone 
 
# initialize pinecone
pinecone.init(
    api_key=PINECONE_API_KEY,  # find at app.pinecone.io
    environment=PINECONE_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)

print(docs[0].page_content)

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