Update app/policy_vector_db.py

app/policy_vector_db.py

@@ -121,7 +121,7 @@ class PolicyVectorDB:
 
         search_results = []
         if results and results.get('documents') and results['documents'][0]:
-            for i, doc in enumerate(results['documents']):
+            for i, doc in enumerate(results['documents'][0]):
                 # The distance for normalized embeddings is often interpreted as 1 - cosine_similarity
                 relevance_score = 1 - results['distances'][0][i]
                 if relevance_score >= self.relevance_threshold: