pinecone-integration

# Pinecone Integration Skill ## Capabilities - Set up Pinecone index and environment - Configure index parameters and pods - Implement upsert and query operations - Design namespace strategies for multi-tenancy - Configure metadata filtering - Implement batch operations and optimization ## Target Processes - vector-database-setup - rag-pipeline-implementation ## Implementation Details ### Core Operations 1. **Index Management**: Create, configure, delete indices 2. **Upsert**: Single and batch vector uploads 3. **Query**: Similarity search with metadata filters 4. **Fetch/Delete**: Direct vector operations 5. **Index Stats**: Monitor index usage ### Configuration Options - Index dimension and metric - Pod type and replicas - Serverless vs pod-based deployment - Namespace configuration - Metadata schema design ### Best Practices - Use appropriate metric for embeddings - Design namespaces for isolation - Batch upserts for efficiency - Implement proper error handling - Monitor index performance ### Dependencies - pinecone-client - langchain-pinecone