diff --git a/ucsinfer/inference.py b/ucsinfer/inference.py
index aab3f7d..be6739e 100644
--- a/ucsinfer/inference.py
+++ b/ucsinfer/inference.py
@@ -103,7 +103,12 @@ class InferenceContext:
         else:
             print(f"Calculating embeddings for model {self.model_name}...")
 
-            for cat_defn in self.catlist:
+            # we need to calculate the embeddings for all cats, not just the 
+            # ones we're loading for this run
+            
+            full_catlist = load_ucs(full_ucs= True)
+
+            for cat_defn in full_catlist:
                 embeddings += [{
                     'CatID': cat_defn.catid,
                     'Embedding': self._encode_category(cat_defn)
@@ -113,7 +118,9 @@ class InferenceContext:
             with open(embedding_cache_path, 'wb') as g:
                 pickle.dump(embeddings, g)
 
-        return embeddings
+        whitelisted_cats = [cat.catid for cat in self.catlist]
+
+        return [e for e in embeddings if e['CatID'] in whitelisted_cats]
 
     def _encode_category(self, cat: Ucs) -> np.ndarray:
         sentence_components = [cat.explanations,
diff --git a/ucsinfer/recommend.py b/ucsinfer/recommend.py
index 5b98f33..6c92abd 100644
--- a/ucsinfer/recommend.py
+++ b/ucsinfer/recommend.py
@@ -1,7 +1,6 @@
 # recommend.py
 
 from re import match
-
 from .inference import InferenceContext
 
 def print_recommendation(path: str | None, text: str, ctx: InferenceContext, 
@@ -23,6 +22,7 @@ def print_recommendation(path: str | None, text: str, ctx: InferenceContext,
         print(f"Path: {path}")
 
     print(f"Text: {text or '<None>'}")
+    
     for i, r in enumerate(recs):
         cat, subcat, _ = ctx.lookup_category(r)
         print(f"- {i}: {r} ({cat}-{subcat})")