Expand description
FAISS Integration for Advanced Vector Search
This module provides integration with Facebook’s FAISS (Facebook AI Similarity Search) library for high-performance vector similarity search and clustering. FAISS is particularly well-suited for large-scale vector databases with billions of vectors.
Structs§
- Faiss
Backup Config - Backup configuration for FAISS indices
- Faiss
Config - Configuration for FAISS integration
- Faiss
Factory - FAISS integration factory
- Faiss
Index - FAISS vector index implementation
- Faiss
Index Handle - Simulated FAISS index handle (would be actual FAISS bindings in real implementation)
- Faiss
Monitoring Config - Monitoring configuration for FAISS operations
- Faiss
Optimization Config - Optimization configuration for FAISS
- Faiss
Persistence Config - Persistence configuration for FAISS indices
- Faiss
Search Params - FAISS search parameters
- Faiss
Statistics - Performance statistics for FAISS operations
- Performance
Snapshot - Performance snapshot for monitoring
- Training
State - Training state for FAISS indices
- Vector
Metadata - Vector metadata for FAISS integration
Enums§
- Faiss
Index Type - FAISS index types supported