Distributed Vector Search, Actually Scalable

#include "client/CentroidClient.h"

int main() {
    // Connect to MLGraph server
    CentroidClient client("localhost:50051");

    // Configure index
    centroidservice::IndexConfig config;
    config.set_index_id("my_embeddings");
    config.set_dimension(1536);        // OpenAI ada-002
    config.set_nlist(1000);            // 1000 clusters
    config.set_data_dir("/data/mlgraph");

    // Initialize
    client.Initialize({config});

    // Add vectors (your embeddings here)
    std::vector<float> embedding = get_embedding("Hello world");
    client.AddVector("my_embeddings", 1, embedding, 0);

    // Search
    auto results = client.Search("my_embeddings", query, k=10);
    for (const auto& result : results) {
        std::cout << "Found: " << result.id
                  << " (distance: " << result.distance << ")\n";
    }
}