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