FAISS is Facebook’s library for efficient similarity search.
Search billions of vectors efficiently.
Installation
pip install faiss-cpu
Example
import faiss
import numpy as np
dimension = 1536
index = faiss.IndexFlatL2(dimension)
vectors = np.random.random((1000, dimension)).astype(‘float32’)
index.add(vectors)
D, I = index.search(query_vector, k=5)
Features
✅ Extremely fast
✅ GPU support
✅ Scalable to billions
Conclusion
FAISS is the fastest option for large-scale search!