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Connection and Setup

pc init
Initialize Pinecone client with API key and environment

from pinecone import Pinecone
Import Pinecone in Python

pc = Pinecone(api_key='YOUR_API_KEY')
Create a Pinecone client instance

Index Management

pc.create_index(name='index-name', dimension=1536, metric='cosine')
Create a new vector index

pc.list_indexes()
List all indexes

pc.describe_index(name='index-name')
Get details about an index

pc.delete_index(name='index-name')
Delete an index

Vector Operations

index = pc.Index('index-name')
Connect to a specific index

index.upsert(vectors=[{'id': 'vec1', 'values': [0.1, 0.2, ...], 'metadata': {...}}])
Insert or update vectors

index.query(vector=[0.1, 0.2, ...], top_k=10, include_metadata=True)
Query for similar vectors

index.fetch(ids=['vec1', 'vec2'])
Retrieve specific vectors by ID

index.delete(ids=['vec1', 'vec2'])
Delete vectors by ID

index.delete(filter={'metadata_field': 'value'})
Delete vectors using metadata filter

Namespace Operations

index.describe_index_stats()
Get statistics about the index

index.upsert(vectors=[...], namespace='custom-namespace')
Upsert vectors to a specific namespace

index.query(vector=[...], namespace='custom-namespace')
Query vectors in a specific namespace

index.delete(delete_all=True, namespace='custom-namespace')
Delete all vectors in a namespace

Metadata Filtering

index.query(vector=[...], filter={'category': 'electronics'})
Query with metadata filter

index.delete(filter={'category': 'electronics'})
Delete vectors matching a metadata filter