initial commit

Signed-off-by: Sienna Meridian Satterwhite <sienna@r3t.io>

src/semantic/index.rs

@@ -0,0 +1,51 @@
+// Semantic Index — cosine similarity search over in-memory vectors.
+// Uses a HashMap so deletion is O(1) and the index stays consistent
+// with the database after deletes.
+
+use std::collections::HashMap;
+
+pub struct SemanticIndex {
+    vectors: HashMap<String, Vec<f32>>,
+}
+
+impl SemanticIndex {
+    pub fn new(_dimension: usize) -> Self {
+        Self {
+            vectors: HashMap::new(),
+        }
+    }
+
+    pub fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
+        let dot: f32 = a.iter().zip(b.iter()).map(|(&x, &y)| x * y).sum();
+        let norm_a: f32 = a.iter().map(|x| x * x).sum::<f32>().sqrt();
+        let norm_b: f32 = b.iter().map(|x| x * x).sum::<f32>().sqrt();
+        if norm_a == 0.0 || norm_b == 0.0 {
+            0.0
+        } else {
+            dot / (norm_a * norm_b)
+        }
+    }
+
+    pub fn add_vector(&mut self, vector: &[f32], id: &str) -> bool {
+        self.vectors.insert(id.to_string(), vector.to_vec());
+        true
+    }
+
+    /// Remove a vector by id. Returns true if it existed.
+    pub fn remove_vector(&mut self, id: &str) -> bool {
+        self.vectors.remove(id).is_some()
+    }
+
+    /// Return the top-k most similar ids with their scores, highest first.
+    pub fn search(&self, query: &[f32], k: usize) -> Vec<(String, f32)> {
+        let mut results: Vec<(String, f32)> = self
+            .vectors
+            .iter()
+            .map(|(id, vec)| (id.clone(), Self::cosine_similarity(query, vec)))
+            .collect();
+
+        results.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
+        results.truncate(k);
+        results
+    }
+}