Update app/policy_vector_db.py

app/policy_vector_db.py

@@ -120,13 +120,13 @@ class PolicyVectorDB:
 
         search_results = []
         if results and results.get('documents') and results['documents']:
-            for i, doc in enumerate(results['documents'][0]):  # ← Fixed indexing
+            for i, doc in enumerate(results['documents'][0]):  # Access first sublist
                 # The distance for normalized embeddings is often interpreted as 1 - cosine_similarity
-                relevance_score = 1 - results['distances'][i]  # ← Fixed indexing
+                relevance_score = 1 - results['distances'][0][i]  # ✅ Fixed: Access distances correctly
                 if relevance_score >= self.relevance_threshold:
                     search_results.append({
                         'text': doc,
-                        'metadata': results['metadatas'][i],  # ← Fixed indexing
+                        'metadata': results['metadatas'][0][i],  # ✅ Fixed: Access metadatas correctly
                         'relevance_score': relevance_score
                     })
 
@@ -168,12 +168,12 @@ class PolicyVectorDB:
         
         search_results = []
         if results and results.get('documents') and results['documents']:
-            for i, doc in enumerate(results['documents'][0]):  # ← Fixed indexing
-                relevance_score = 1 - results['distances'][i]  # ← Fixed indexing
+            for i, doc in enumerate(results['documents'][0]):  # Access first sublist
+                relevance_score = 1 - results['distances'][0][i]  # ✅ Fixed: Access distances correctly
                 if relevance_score >= self.relevance_threshold:
                     search_results.append({
                         'text': doc,
-                        'metadata': results['metadatas'][i],  # ← Fixed indexing
+                        'metadata': results['metadatas'][0][i],  # ✅ Fixed: Access metadatas correctly
                         'relevance_score': relevance_score
                     })
         
@@ -213,4 +213,4 @@ def ensure_db_populated(db_instance: PolicyVectorDB, chunks_file_path: str) -> b
 
     except Exception as e:
         logger.error(f"An error occurred during DB population check: {e}", exc_info=True)
-        return False
+        return False