WARM

cargo add warm-rust --features security

// 1. Ingest. A store is a directory (`None` would use the current directory); it persists
// there and reopens with the same arguments.
let store_dir = tempfile::tempdir()?;
let warm = WarmCore::new(
    DIMENSIONS,
    Some(store_dir.path().display().to_string()),
    None,
)?;
let start = Instant::now();
let inputs: Vec<DocumentInput> = corpus.iter().map(to_input).collect();
warm.memorize_documents(inputs)?;
println!(
    "ingested {} documents in {:.1?}",
    corpus.len(),
    start.elapsed()
);

// Hits carry the passage and its byte range in the source text.
let hit = &warm.search_documents("asylum from persecution", &SearchOptions::default())?[0];
println!(
    "\n{} bytes {}..{} score {:.3}: {}",
    hit.document_id,
    hit.start_byte,
    hit.end_byte,
    hit.score,
    hit.text.as_deref().unwrap_or("")
);

uv pip install warm-sdk

# 1. Ingest. The server keeps one store per tenant; you send the text and a vector per document.
docs = [
    {"id": d["id"], "vector": toy_embed(d["text"]), "text": d["text"], "metadata": {"title": d["title"]}}
    for d in corpus
]
client = WarmClient(url=URL, api_key=API_KEY, tenant_id=tenant)
started = time.perf_counter()
client.add_documents(docs)
print(f"ingested {len(docs)} documents in {(time.perf_counter() - started) * 1000:.1f} ms")

# Hits carry the stored text, metadata and the exact cosine score.
top = client.query(toy_embed("asylum from persecution"), top_k=1)["matches"][0]
print(f"\n{top['id']} score {top['score']:.3f}: {top['text']}")

npm install writerslogic-warm

// 1. Ingest. A store is a directory; it persists there and reopens with the same arguments.
const memory = new DocumentMemory(new WarmMemorySystem(4096, mkdtempSync(join(tmpdir(), 'warm-quickstart-'))))
const started = performance.now()
await memory.ingest(corpus.map(toInput))
console.log(`ingested ${corpus.length} documents in ${(performance.now() - started).toFixed(1)} ms`)

// Hits carry the passage and its byte range in the source text.
const [hit] = await memory.search('asylum from persecution')
console.log(`\n${hit.documentId} bytes ${hit.startByte}..${hit.endByte} score ${hit.score.toFixed(3)}: ${hit.text}`)