feat(memory): migrate EmbeddingProvider to KMP-compatible TextEmbeddingExecutor, add :memory-md-vector, and hybrid backend support

- Replaced `EmbeddingProvider` with cross-platform `TextEmbeddingExecutor` for native target compatibility.
- Introduced `:memory-md-vector` module combining vector-cache and `.md` file-based memory systems (`hybrid` backend).
- Updated `SiglipEmbeddingProvider` to use KMP `TextEmbeddingExtractor` and streamlined compatibility via `asExecutor`.
- Added hybrid memory backend to `standalone`, supporting `.md` reconciliation with vector-cache for semantic

memory-vector/build.gradle.kts

@@ -25,6 +25,10 @@ kotlin {
             api(project(":memory-api"))
             implementation(libs.kotlinx.coroutines.core)
             implementation(libs.kotlinx.serialization.json)
+            // `pw.binom.ai.embeddingtext:api` (TextEmbeddingExtractor + TextEmbedding)
+            // теперь KMP с нативом (linuxX64/mingwX64/macOS/ios); тянем в commonMain.
+            // Реализации (`siglip`, `http`) — JVM+Android only, см. jvmMain ниже.
+            api(libs.text.embedding.api)
         }
         commonTest.dependencies {
             implementation(kotlin("test"))
@@ -34,14 +38,11 @@ kotlin {
         jvmMain.dependencies {
             implementation(libs.jvector)
             implementation(libs.sqldelight.sqlite.driver)
+            // Конкретная реализация TextEmbeddingExtractor поверх ONNX.
+            implementation(libs.text.embedding.siglip)
         }
         jvmTest.dependencies {
             implementation(kotlin("test"))
         }
     }
 }
-
-dependencies {
-    add("jvmMainApi", libs.text.embedding.api)
-    add("jvmMainImplementation", libs.text.embedding.siglip)
-}