RAG

val session = RunAnywhere.rag.open(
    embeddingModel = ModelRef("all-minilm-l6-v2"),
    llmModel = ModelRef("qwen3-0.6b")
)

session.ingest(RagDocument.file(path))

val answer = session.query("What is the refund window?")
println(answer.text)

session.close()

suspend fun open(
    embeddingModel: ModelRef,
    llmModel: ModelRef? = null,
    config: RagConfig? = null
): RagSession

suspend fun ingest(document: RagDocument)
suspend fun ingest(documents: List<RagDocument>)
suspend fun search(query: String, topK: Int? = null): List<Match>
suspend fun query(question: String, options: RagQueryOptions? = null): RagResult
fun queryStream(question: String, options: RagQueryOptions? = null): Flow<RagEvent>
suspend fun stats(): RagStats
suspend fun clear()
suspend fun close()

session.ingest(RagDocument.file(path))
session.ingest(listOf(doc1, doc2, doc3))

val matches = session.search("refund policy", topK = 5)

session.queryStream("What is the refund window?").collect { event ->
    when (event) {
        is RagEvent.Token -> answer += event.text
        is RagEvent.Sources -> sources = event.matches
        else -> {}
    }
}

val session = RunAnywhere.rag.open(
    embeddingModel = ModelRef("all-minilm-l6-v2"),
    llmModel = ModelRef("qwen3-0.6b"),
    config = RagConfig(
        retrievalTopK = 5,
        chunkSize = 512,
        chunkOverlap = 64
    )
)

session.close()

val stats = session.stats()
session.clear()