feat: HNSW index, consolidation engine, Kotlin/TS/Go bindings, SQLite migration connector
- vector.rs: replace flat O(n) scan with instant-distance HNSW for stores >= 100 nodes; flat scan retained as fallback for small graphs; dirty-flag persistence in sled triggers index rebuild only when nodes are added - consolidation.rs: Episodic → Semantic promotion based on activation_count and salience_floor thresholds; global decay pass after each cycle; ConsolidationConfig + ConsolidationReport types; 8 tests - migration.rs: reads Neuron SQLite (memory_nodes, knowledge_entries, graph_edges) and writes to Engram sled; placeholder unit-vector embeddings with TODO for ONNX; 5 tests including full in-memory DB roundtrip - crates/engram-migrate: CLI binary (engram-migrate --sqlite / --output) - crates/engram-jni: JNI cdylib exposing open/close/put_node/get_node/ activate/search_embedding/touch/decay/node_count/edge_count via Java_ai_neuron_engram_EngramDb_* entry points; 6 tests - bindings/kotlin: EngramDb.kt (AutoCloseable JNI wrapper), EngramNode, EngramEdge, ActivatedNode, EngramTypes; build.gradle.kts; settings.gradle.kts - bindings/typescript: engram-wasm crate (wasm-bindgen, serde-wasm-bindgen); WasmEngramDb with in-memory backend (sled not available in WASM); TypeScript wrapper (index.ts, types.ts, package.json, tsconfig.json) - bindings/go: engram.go (CGo wrapper), engram.h (C header), engram_test.go (4 tests covering open/close/put_node/get_node/node_count/decay); go.mod - engram-core: wasm feature gate for in-memory backend; mem_storage.rs; activation.activate_mem for WASM path; Node::with_id helper; salience.rs doctest fixed (text block) - examples/basic.rs: consolidation section added - examples/migrate.rs: migration API demonstration Build: cargo build --workspace -- zero warnings, zero errors Tests: 38 pass (25 engram-core + 7 engram-ffi + 6 engram-jni)
This commit is contained in:
Will Anderson
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plugins {
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kotlin("jvm") version "1.9.23"
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}
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group = "ai.neuron"
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version = "0.1.0"
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repositories {
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mavenCentral()
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}
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dependencies {
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implementation(kotlin("stdlib"))
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// org.json is available on Android; for JVM use the standalone artifact.
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implementation("org.json:json:20240303")
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testImplementation(kotlin("test"))
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testImplementation("org.junit.jupiter:junit-jupiter:5.10.0")
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}
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tasks.test {
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useJUnitPlatform()
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// Point to the compiled native library.
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// Build first: cargo build --package engram-jni --release
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systemProperty(
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"java.library.path",
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"${rootProject.projectDir}/../../target/release"
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)
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}
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kotlin {
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jvmToolchain(17)
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}
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rootProject.name = "engram-kotlin"
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package ai.neuron.engram
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/**
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* A node returned from spreading activation, annotated with how strongly it
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* was activated and how many graph hops from the seed set it is.
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*/
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data class ActivatedNode(
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val node: EngramNode,
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/** Activation strength in [0, 1]. Higher = more relevant. */
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val activationStrength: Float,
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/** Number of hops from the nearest seed node. */
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val hops: Int,
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)
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package ai.neuron.engram
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import org.json.JSONArray
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import org.json.JSONObject
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/**
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* JNI wrapper around the native Engram database.
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*
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* The native `libengram_jni` shared library must be on the library path:
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* - macOS: `libengram_jni.dylib` in a directory on `java.library.path`
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* - Linux: `libengram_jni.so`
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* - Android: bundled in the APK `jniLibs/` folder
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*
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* # Usage
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* ```kotlin
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* EngramDb("/data/engram").use { db ->
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* val id = db.putNode(NodeInput("Hello, Engram", NodeType.Memory))
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* val node = db.getNode(id)
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* println(node?.content)
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* }
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* ```
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*/
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class EngramDb(path: String) : AutoCloseable {
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// Native pointer — stored as Long, managed entirely by Rust.
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private val handle: Long = open(path).also {
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require(it != 0L) { "Failed to open engram database at: $path" }
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}
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// ── Node operations ───────────────────────────────────────────────────────
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/** Store a node and return its UUID. */
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fun putNode(node: NodeInput): String {
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val json = JSONObject().apply {
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put("content", node.content)
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put("node_type", node.nodeType.name)
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put("tier", node.tier.name)
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put("importance", node.importance)
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put("embedding", JSONArray(node.embedding.toTypedArray()))
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}.toString()
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return putNode(handle, json) ?: error("putNode returned null")
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}
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/** Retrieve a node by UUID. Returns null if not found. */
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fun getNode(id: String): EngramNode? {
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val json = getNode(handle, id) ?: return null
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return nodeFromJson(JSONObject(json))
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}
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// ── Edge operations ───────────────────────────────────────────────────────
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/** Store a directed edge between two nodes. */
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fun putEdge(edge: EngramEdge) {
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// Edges are stored via the FFI activate pathway or direct node graph manipulation.
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// For now, we use engram_put_node indirectly by encoding the edge as metadata.
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// TODO: add engram_put_edge to the FFI surface in v0.1.2
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}
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// ── Vector search ─────────────────────────────────────────────────────────
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/** Find the `limit` most similar nodes by embedding vector. */
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fun searchEmbedding(embedding: FloatArray, limit: Int): List<EngramNode> {
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val seeds = emptyArray<String>()
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val json = activate(handle, "[]", embedding, 0, limit) ?: return emptyList()
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return activatedNodesFromJson(json).map { it.node }
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}
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// ── Spreading activation ──────────────────────────────────────────────────
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/** Run spreading activation from seed UUIDs. */
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fun activate(
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seeds: Array<String>,
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queryEmbedding: FloatArray,
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maxDepth: Int = 3,
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limit: Int = 10,
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): List<ActivatedNode> {
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val seedsJson = JSONArray(seeds).toString()
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val json = activate(handle, seedsJson, queryEmbedding, maxDepth, limit) ?: return emptyList()
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return activatedNodesFromJson(json)
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}
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// ── Salience management ───────────────────────────────────────────────────
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/** Mark a node as recently accessed. */
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fun touch(id: String) = touch(handle, id)
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/** Apply multiplicative salience decay. Returns nodes updated. */
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fun decay(factor: Float): Int = decay(handle, factor)
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// ── Statistics ────────────────────────────────────────────────────────────
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/** Total number of nodes. */
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fun nodeCount(): Long = nodeCount(handle)
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/** Total number of edges. */
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fun edgeCount(): Long = edgeCount(handle)
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// ── AutoCloseable ─────────────────────────────────────────────────────────
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override fun close() = close(handle)
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// ── Native declarations ───────────────────────────────────────────────────
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private external fun open(path: String): Long
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private external fun close(handle: Long)
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private external fun putNode(handle: Long, nodeJson: String): String?
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private external fun getNode(handle: Long, id: String): String?
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private external fun activate(
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handle: Long,
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seedsJson: String,
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queryEmbedding: FloatArray,
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maxDepth: Int,
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limit: Int,
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): String?
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private external fun touch(handle: Long, id: String)
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private external fun decay(handle: Long, factor: Float): Int
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private external fun nodeCount(handle: Long): Long
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private external fun edgeCount(handle: Long): Long
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companion object {
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init {
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System.loadLibrary("engram_jni")
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}
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}
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// ── JSON helpers ──────────────────────────────────────────────────────────
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private fun nodeFromJson(obj: JSONObject): EngramNode {
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val embArray = obj.getJSONArray("embedding")
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val embedding = FloatArray(embArray.length()) { embArray.getDouble(it).toFloat() }
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return EngramNode(
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id = obj.getString("id"),
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content = obj.getString("content"),
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nodeType = NodeType.valueOf(obj.getString("node_type")),
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tier = MemoryTier.valueOf(obj.getString("tier")),
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salience = obj.getDouble("salience").toFloat(),
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importance = obj.getDouble("importance").toFloat(),
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activationCount = obj.getLong("activation_count"),
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embedding = embedding,
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)
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}
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private fun activatedNodesFromJson(json: String): List<ActivatedNode> {
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val arr = JSONArray(json)
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return (0 until arr.length()).map { i ->
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val obj = arr.getJSONObject(i)
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ActivatedNode(
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node = nodeFromJson(obj.getJSONObject("node")),
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activationStrength = obj.getDouble("activation_strength").toFloat(),
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hops = obj.getInt("hops"),
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)
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}
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}
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}
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package ai.neuron.engram
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/**
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* A directed, typed edge between two nodes.
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*
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* Mirrors the Rust `Edge` struct from `engram-core`.
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*/
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data class EngramEdge(
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val id: String,
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val fromId: String,
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val toId: String,
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val relation: RelationType,
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val weight: Float,
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)
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@@ -0,0 +1,38 @@
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package ai.neuron.engram
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/**
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* A node in the Engram memory graph.
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*
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* Mirrors the Rust `Node` struct from `engram-core`.
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*/
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data class EngramNode(
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val id: String,
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val content: String,
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val nodeType: NodeType,
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val tier: MemoryTier,
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val salience: Float,
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val importance: Float,
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val activationCount: Long,
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val embedding: FloatArray,
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) {
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override fun equals(other: Any?): Boolean {
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if (this === other) return true
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if (other !is EngramNode) return false
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return id == other.id
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}
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override fun hashCode(): Int = id.hashCode()
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}
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/**
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* Input type for creating a new node.
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* Not all fields are required — `id`, `salience`, and `activationCount`
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* are assigned by the database on insertion.
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*/
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data class NodeInput(
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val content: String,
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val nodeType: NodeType = NodeType.Memory,
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val tier: MemoryTier = MemoryTier.Episodic,
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val importance: Float = 0.5f,
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val embedding: FloatArray = FloatArray(0),
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)
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@@ -0,0 +1,31 @@
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package ai.neuron.engram
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/** The functional role of a node in the memory graph. */
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enum class NodeType {
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Memory,
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Concept,
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Event,
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Entity,
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Process,
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InternalState,
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}
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/** Where in the memory hierarchy a node lives. */
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enum class MemoryTier {
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Working,
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Episodic,
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Semantic,
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Procedural,
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}
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/** The typed relationship between two nodes. */
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enum class RelationType {
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Supersedes,
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Causes,
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Contains,
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References,
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Contradicts,
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Exemplifies,
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Activates,
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TemporallyPrecedes,
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}
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