langchain/docs/modules/indexes/vectorstores/examples/pinecone.ipynb

169 lines
4.0 KiB
Plaintext
Raw Normal View History

2023-02-20 07:14:50 +00:00
{
"cells": [
{
"cell_type": "markdown",
"id": "683953b3",
"metadata": {},
"source": [
"# Pinecone\n",
"\n",
"[Pinecone](https://docs.pinecone.io/docs/overview) is a vector database with broad functionality.\n",
"\n",
"This notebook shows how to use functionality related to the `Pinecone` vector database.\n",
"\n",
"To use Pinecone, you must have an API key. \n",
"Here are the [installation instructions](https://docs.pinecone.io/docs/quickstart)."
2023-02-20 07:14:50 +00:00
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b4c41cad-08ef-4f72-a545-2151e4598efe",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"!pip install pinecone-client"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c1e38361-c1fe-4ac6-86e9-c90ebaf7ae87",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import getpass\n",
"\n",
"PINECONE_API_KEY = getpass.getpass('Pinecone API Key:')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "02a536e0-d603-4d79-b18b-1ed562977b40",
"metadata": {},
"outputs": [],
"source": [
"PINECONE_ENV = getpass.getpass('Pinecone Environment:')"
]
},
{
"cell_type": "markdown",
"id": "320af802-9271-46ee-948f-d2453933d44b",
"metadata": {},
"source": [
"We want to use `OpenAIEmbeddings` so we have to get the OpenAI API Key."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ffea66e4-bc23-46a9-9580-b348dfe7b7a7",
2023-02-20 07:14:50 +00:00
"metadata": {},
"outputs": [],
"source": [
"os.environ['OPENAI_API_KEY'] = getpass.getpass('OpenAI API Key:')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "aac9563e",
"metadata": {
"tags": []
},
"outputs": [],
2023-02-20 07:14:50 +00:00
"source": [
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain.vectorstores import Pinecone\n",
"from langchain.document_loaders import TextLoader"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a3c3999a",
"metadata": {},
"outputs": [],
"source": [
"from langchain.document_loaders import TextLoader\n",
"loader = TextLoader('../../../state_of_the_union.txt')\n",
2023-02-20 07:14:50 +00:00
"documents = loader.load()\n",
"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
"docs = text_splitter.split_documents(documents)\n",
"\n",
"embeddings = OpenAIEmbeddings()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6e104aee",
"metadata": {},
"outputs": [],
"source": [
"import pinecone \n",
"\n",
"# initialize pinecone\n",
"pinecone.init(\n",
" api_key=PINECONE_API_KEY, # find at app.pinecone.io\n",
" environment=PINECONE_ENV # next to api key in console\n",
2023-02-20 07:14:50 +00:00
")\n",
"\n",
"index_name = \"langchain-demo\"\n",
"\n",
"docsearch = Pinecone.from_documents(docs, embeddings, index_name=index_name)\n",
"\n",
"# if you already have an index, you can load it like this\n",
"# docsearch = Pinecone.from_existing_index(index_name, embeddings)\n",
"\n",
2023-02-20 07:14:50 +00:00
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"docs = docsearch.similarity_search(query)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9c608226",
"metadata": {},
"outputs": [],
"source": [
"print(docs[0].page_content)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a359ed74",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
2023-02-20 07:14:50 +00:00
}
},
"nbformat": 4,
"nbformat_minor": 5
}