feat: Implement semantic search and smart note linking with embedding generation, vector storage, and link persistence.

notes-infra/src/embeddings/fastembed.rs

@@ -0,0 +1,48 @@
+use async_trait::async_trait;
+use fastembed::{EmbeddingModel, InitOptions, TextEmbedding};
+use notes_domain::errors::{DomainError, DomainResult};
+use notes_domain::ports::EmbeddingGenerator;
+use std::sync::{Arc, Mutex};
+
+pub struct FastEmbedAdapter {
+    model: Arc<Mutex<TextEmbedding>>,
+}
+
+impl FastEmbedAdapter {
+    pub fn new() -> DomainResult<Self> {
+        let mut options = InitOptions::default();
+        options.model_name = EmbeddingModel::AllMiniLML6V2;
+        options.show_download_progress = false;
+
+        let model = TextEmbedding::try_new(options).map_err(|e| {
+            DomainError::InfrastructureError(format!("Failed to init fastembed: {}", e))
+        })?;
+
+        Ok(Self {
+            model: Arc::new(Mutex::new(model)),
+        })
+    }
+}
+
+#[async_trait]
+impl EmbeddingGenerator for FastEmbedAdapter {
+    async fn generate_embedding(&self, text: &str) -> DomainResult<Vec<f32>> {
+        let model = self.model.clone();
+        let text = text.to_string();
+
+        let embeddings = tokio::task::spawn_blocking(move || {
+            let mut model = model.lock().map_err(|e| format!("Lock error: {}", e))?;
+            model
+                .embed(vec![text], None)
+                .map_err(|e| format!("Embed error: {}", e))
+        })
+        .await
+        .map_err(|e| DomainError::InfrastructureError(format!("Join error: {}", e)))?
+        .map_err(|e| DomainError::InfrastructureError(e))?;
+
+        embeddings
+            .into_iter()
+            .next()
+            .ok_or_else(|| DomainError::InfrastructureError("No embedding generated".to_string()))
+    }
+}