feat(memory): config embedders (LOT C2) + suggestion contextuelle (LOT C3) + contexte projet partagé

- LOT C2 (§14.5.3) : use cases de configuration des embedders déclaratifs
  (List/Save/Delete + DescribeEmbedderEngines : modèles ONNX recommandés,
  environnement local détecté, stratégies compilées). UI EmbedderSettings.
- LOT C3 (§14.5.5) : suggestion contextuelle best-effort à l'activation quand la
  mémoire dépasse le budget de recall sans embedder configuré (event
  EmbedderSuggested, anti-spam 1×/session, « ne plus demander »).
- Contexte projet partagé .ideai/CONTEXT.md (model-agnostic) injecté à tous les
  agents/profils au lancement, avant la persona. UI ProjectContextPanel.

Tests : backend workspace vert (0 échec) ; frontend 306/306.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

crates/infrastructure/tests/onnx_embedder.rs

@@ -71,7 +71,8 @@ async fn onnx_unknown_model_is_unsupported() {
     // *before* any `try_new`/download — so this is safe without a network. We point
     // the cache at a path that is never created to prove no download is attempted.
     let cache = std::path::Path::new("/idea-onnx-cache-that-never-exists");
-    let embedder = OnnxEmbedder::from_profile(&onnx_profile(Some("definitely-unknown"), 384), cache);
+    let embedder =
+        OnnxEmbedder::from_profile(&onnx_profile(Some("definitely-unknown"), 384), cache);
 
     let err = embedder
         .embed(&["x".to_string()])
@@ -113,7 +114,8 @@ async fn onnx_construction_is_cheap() {
     // and an unknown one (construction never fails for either).
     let cache = std::path::Path::new("/idea-onnx-cache-that-never-exists-3");
 
-    let known = OnnxEmbedder::from_profile(&onnx_profile(Some("multilingual-e5-small"), 384), cache);
+    let known =
+        OnnxEmbedder::from_profile(&onnx_profile(Some("multilingual-e5-small"), 384), cache);
     assert_eq!(known.id(), "test-onnx");
     assert_eq!(known.dimension(), 384);
 
@@ -139,14 +141,16 @@ async fn embedder_from_profile_localonnx_is_real_engine_not_unsupported_stub() {
     // whereas the StubEmbedder would return Unsupported even for an empty batch.
     let cache = std::path::Path::new("/idea-onnx-cache-that-never-exists-4");
     let known = onnx_profile(Some("multilingual-e5-small"), 384);
-    let embedder =
-        embedder_from_profile(&known, cache).expect("localOnnx must yield an embedder");
+    let embedder = embedder_from_profile(&known, cache).expect("localOnnx must yield an embedder");
     assert_eq!(embedder.dimension(), 384);
     let out = embedder
         .embed(&[])
         .await
         .expect("real engine short-circuits empty input to Ok(vec![])");
-    assert!(out.is_empty(), "empty batch ⇒ empty result on the real engine");
+    assert!(
+        out.is_empty(),
+        "empty batch ⇒ empty result on the real engine"
+    );
 
     // And an *unknown* model still surfaces Unsupported (deferred resolution), so the
     // mapping is the real engine in both cases (the stub would also say Unsupported,
@@ -187,11 +191,17 @@ async fn onnx_embeds_e5_small_real_model() {
     for v in &out {
         assert_eq!(v.len(), 384, "e5-small produces 384-dim vectors");
         let norm = v.iter().map(|x| x * x).sum::<f32>().sqrt();
-        assert!((norm - 1.0).abs() < 1e-2, "fastembed L2-normalises; norm ≈ 1, got {norm}");
+        assert!(
+            (norm - 1.0).abs() < 1e-2,
+            "fastembed L2-normalises; norm ≈ 1, got {norm}"
+        );
     }
 
     // Deterministic across calls (model already cached after the first call).
-    let again = embedder.embed(&texts).await.expect("second embedding must succeed");
+    let again = embedder
+        .embed(&texts)
+        .await
+        .expect("second embedding must succeed");
     assert_eq!(out, again, "embedding must be deterministic across calls");
 }