from rotastellar_distributed import FederatedClient, CompressionConfig

# Configure compression
compression = CompressionConfig(
    method="topk_quantized",
    k_ratio=0.01,
    quantization_bits=8
)

# Initialize federated client
client = FederatedClient(
    api_key="rs_...",
    node_id="orbital-3",
    node_type="orbital",
    compression=compression
)

# Train locally
gradients = client.train_step(model, batch)

# Sync during ground pass
client.sync(gradients, priority="high")

import { FederatedClient, CompressionConfig } from '@rotastellar/distributed';

const compression = new CompressionConfig({
  method: 'topk_quantized',
  kRatio: 0.01,
  quantizationBits: 8
});

const client = new FederatedClient({
  apiKey: 'rs_...',
  nodeId: 'orbital-3',
  nodeType: 'orbital',
  compression
});

const gradients = client.trainStep(model, batch);
client.sync(gradients, { priority: 'high' });

use rotastellar_distributed::{FederatedClient, CompressionConfig, CompressionMethod};

let compression = CompressionConfig::new()
    .method(CompressionMethod::TopKQuantized)
    .k_ratio(0.01)
    .quantization_bits(8);

let client = FederatedClient::new("orbital-3", compression);

let gradients = client.train_step(&model, &batch);
client.sync(gradients, Priority::High);