fix(ci): stop re-downloading the embedding model in memory tests

.github/workflows/ci.yml

@@ -63,5 +63,14 @@ jobs:
 
       - uses: Swatinem/rust-cache@v2
 
+      # The memory tests share one embedding model cached at this path;
+      # without the cache every run downloads it from Hugging Face, which
+      # fails intermittently and turns unrelated PRs red.
+      - name: Cache embedding model
+        uses: actions/cache@v4
+        with:
+          path: /tmp/spacebot-test-embedding-cache
+          key: fastembed-onnx-v1
+
       - name: cargo test (lib)
         run: cargo test --lib

src/memory/embedding.rs

@@ -65,3 +65,18 @@ impl EmbeddingModel {
 pub async fn embed_text(model: &Arc<EmbeddingModel>, text: &str) -> Result<Vec<f32>> {
     model.embed_one(text).await
 }
+
+/// Shared embedding model for tests. Downloads once into a stable cache
+/// directory and is reused by every test in the binary, so CI can cache the
+/// model files across runs instead of fetching them from Hugging Face on
+/// each test that needs embeddings.
+#[cfg(test)]
+pub(crate) fn shared_test_model() -> std::sync::Arc<EmbeddingModel> {
+    use std::sync::{Arc, OnceLock};
+    static MODEL: OnceLock<Arc<EmbeddingModel>> = OnceLock::new();
+    Arc::clone(MODEL.get_or_init(|| {
+        let cache_dir = std::env::temp_dir().join("spacebot-test-embedding-cache");
+        std::fs::create_dir_all(&cache_dir).expect("failed to create embedding cache dir");
+        Arc::new(EmbeddingModel::new(&cache_dir).expect("failed to initialize embedding model"))
+    }))
+}

src/memory/maintenance.rs

@@ -488,20 +488,12 @@ pub struct MaintenanceReport {
 mod tests {
     use super::*;
     use crate::memory::{Association, RelationType};
-    use std::sync::{Arc, OnceLock};
+    use std::sync::Arc;
     use tempfile::tempdir;
     use tokio::time::Duration;
 
     fn shared_embedding_model() -> Arc<crate::memory::EmbeddingModel> {
-        static MODEL: OnceLock<Arc<crate::memory::EmbeddingModel>> = OnceLock::new();
-        Arc::clone(MODEL.get_or_init(|| {
-            let cache_dir = std::env::temp_dir().join("spacebot-test-embedding-cache");
-            std::fs::create_dir_all(&cache_dir).expect("failed to create embedding cache dir");
-            Arc::new(
-                crate::memory::EmbeddingModel::new(&cache_dir)
-                    .expect("failed to initialize embedding model"),
-            )
-        }))
+        crate::memory::embedding::shared_test_model()
     }
 
     async fn create_memory_with_embedding(

src/memory/search.rs

@@ -580,7 +580,7 @@ mod tests {
             .await
             .unwrap();
         let embedding_table = EmbeddingTable::open_or_create(&lance_conn).await.unwrap();
-        let embedding_model = Arc::new(EmbeddingModel::new(lance_dir.path()).unwrap());
+        let embedding_model = crate::memory::embedding::shared_test_model();
         let search = MemorySearch::new(store, embedding_table, embedding_model);
 
         let config = SearchConfig {
@@ -608,7 +608,7 @@ mod tests {
             .await
             .unwrap();
         let embedding_table = EmbeddingTable::open_or_create(&lance_conn).await.unwrap();
-        let embedding_model = Arc::new(EmbeddingModel::new(lance_dir.path()).unwrap());
+        let embedding_model = crate::memory::embedding::shared_test_model();
         let search = MemorySearch::new(store, embedding_table, embedding_model);
 
         let config = SearchConfig {
@@ -633,7 +633,7 @@ mod tests {
             .await
             .unwrap();
         let embedding_table = EmbeddingTable::open_or_create(&lance_conn).await.unwrap();
-        let embedding_model = Arc::new(EmbeddingModel::new(lance_dir.path()).unwrap());
+        let embedding_model = crate::memory::embedding::shared_test_model();
         let search = MemorySearch::new(store, embedding_table, embedding_model);
 
         let config = SearchConfig {
@@ -658,7 +658,7 @@ mod tests {
             .await
             .unwrap();
         let embedding_table = EmbeddingTable::open_or_create(&lance_conn).await.unwrap();
-        let embedding_model = Arc::new(EmbeddingModel::new(lance_dir.path()).unwrap());
+        let embedding_model = crate::memory::embedding::shared_test_model();
         let search = MemorySearch::new(store, embedding_table, embedding_model);
 
         let config = SearchConfig {