Records plugin for Pinecone SDK
Project description
Records API plugin for Pinecone python SDK
Installation
The plugin is distributed separately from the core python SDK.
# Install the base python SDK, version 5.4.0 or higher
pip install pinecone
# And also the plugin functionality
pip install pinecone-plugin-records
Usage
This plugin extends the functionality of the pinecone
SDK to allow creating indexes for specific embedding models, and upserting and searching records in these indexes. These operations are added to the existing Pinecone
and Index
classes.
Models currently supported:
Create an index for an embedding model, upsert records, and search
The following example highlights how to use the Pinecone
class to create a new index for an embedding model, and then uses Index
to upsert and query some records.
from pinecone import Pinecone
pc = Pinecone(api_key="<<PINECONE_API_KEY>>")
# Create an index for your embedding model
index_model = pc.create_index_for_model(
model="multilingual-e5-large",
field_map={"text": "my_text_field"},
name="my-model-index",
cloud="aws",
region="us-east-1",
)
# establish an index connection
index = pc.Index(host=index_model.host)
# upsert records
index.upsert_records(
"my-namespace",
[
{
"_id": "test1",
"my_text_field": "Apple is a popular fruit known for its sweetness and crisp texture.",
},
{
"_id": "test2",
"my_text_field": "The tech company Apple is known for its innovative products like the iPhone.",
},
{
"_id": "test3",
"my_text_field": "Many people enjoy eating apples as a healthy snack.",
},
{
"_id": "test4",
"my_text_field": "Apple Inc. has revolutionized the tech industry with its sleek designs and user-friendly interfaces.",
},
{
"_id": "test5",
"my_text_field": "An apple a day keeps the doctor away, as the saying goes.",
},
{
"_id": "test6",
"my_text_field": "Apple Computer Company was founded on April 1, 1976, by Steve Jobs, Steve Wozniak, and Ronald Wayne as a partnership.",
},
],
)
# search for similar records
response = index.search_records(
namespace="test-namespace",
query={
"inputs":{
"text": "Apple corporation"
},
"top_k":3
}
)
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