Nomad changes

docs/snippets/kotlin/metadata/vector_database_integration.md

@@ -0,0 +1,57 @@
+```kotlin title="Kotlin"
+import dev.kreuzberg.*
+import java.nio.file.Paths
+import java.util.Optional
+
+data class VectorRecord(
+    val id: String,
+    val content: String,
+    val embedding: List<Float>,
+    val metadata: Map<String, String>,
+)
+
+fun extractAndVectorize(documentPath: String, documentId: String): List<VectorRecord> {
+    val embedding = EmbeddingConfig.builder()
+        .withModel(EmbeddingModelType.Preset("balanced"))
+        .withNormalize(true)
+        .withBatchSize(32L)
+        .build()
+
+    val chunking = ChunkingConfig.builder()
+        .withMaxCharacters(512L)
+        .withOverlap(50L)
+        .withEmbedding(Optional.of(embedding))
+        .build()
+
+    val config = ExtractionConfig.builder()
+        .withChunking(Optional.of(chunking))
+        .build()
+
+    val result = Kreuzberg.extractFileSync(Paths.get(documentPath), null, config)
+
+    val records = mutableListOf<VectorRecord>()
+    val chunks = result.chunks() ?: return records
+    for ((index, chunk) in chunks.withIndex()) {
+        val vector = chunk.embedding() ?: continue
+        val metadata = mapOf(
+            "document_id" to documentId,
+            "chunk_index" to index.toString(),
+            "content_length" to chunk.content().length.toString(),
+        )
+        records.add(
+            VectorRecord(
+                id = "${documentId}_chunk_$index",
+                content = chunk.content(),
+                embedding = vector,
+                metadata = metadata,
+            )
+        )
+    }
+    return records
+}
+
+fun main() {
+    val records = extractAndVectorize("document.pdf", "doc-001")
+    println("Generated ${records.size} vector records")
+}
+```