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docs/snippets/swift/plugins/embedding_backend.md

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+```swift title="Swift"
+import Kreuzberg
+
+// Wrap a custom embedder (e.g., CoreML, ONNX, API-based).
+// The Swift class must implement the EmbeddingBackend protocol.
+final class MyEmbedder: EmbeddingBackend {
+    private let modelUrl: URL
+
+    init(modelUrl: URL) {
+        self.modelUrl = modelUrl
+    }
+
+    // Plugin trait hooks
+    func name() -> String {
+        "my-embedder"
+    }
+
+    func version() -> String {
+        "1.0.0"
+    }
+
+    func initialize() -> String {  // Returns JSON-encoded Result
+        do {
+            // Warm-up logic here
+            return "{\"ok\": null}"
+        } catch {
+            return "{\"err\": \"Failed to initialize: \(error)\"}"
+        }
+    }
+
+    func shutdown() -> String {  // Returns JSON-encoded Result
+        "{\"ok\": null}"
+    }
+
+    // EmbeddingBackend hooks
+    func dimensions() -> UInt {
+        // Fixed dimensionality for this backend
+        768
+    }
+
+    func embed(texts: [String]) -> String {  // Returns JSON-encoded Vec<Vec<f32>>
+        do {
+            // Embed texts using your backend (e.g., CoreML inference)
+            let embeddings: [[Float]] = texts.map { _ in
+                Array(repeating: 0.5, count: 768)  // Placeholder
+            }
+            let data = try JSONEncoder().encode(embeddings)
+            let json = String(data: data, encoding: .utf8) ?? "[]"
+            return "{\"ok\": \(json)}"
+        } catch {
+            return "{\"err\": \"Embedding failed: \(error)\"}"
+        }
+    }
+}
+
+// Register once at startup
+let embedder = MyEmbedder(modelUrl: URL(fileURLWithPath: "/path/to/model"))
+try Kreuzberg.registerEmbeddingBackend(embedder)
+
+print("Embedding backend 'my-embedder' registered")
+// The registered backend can now be referenced by name in EmbeddingConfig
+// via the plugin selection mechanism once alef supports it
+```