updated search_commands to use the new heuristic

NLP_and_backend/search_commands.py

@@ -12,12 +12,28 @@ def semantic_search_sbert(query:str, command_embeddings, model:str):
     query_embedding = embedder.encode(query, 
                                       convert_to_numpy=True, 
                                       normalize_embeddings=True)
+
+    embedding_command_ids = command_embeddings[:, 0, :]
+    embedding_titles = command_embeddings[:, 1, :]
+
+    scores_ids = sentence_transformers.util.semantic_search(query_embedding,
+                                                      embedding_command_ids,
+                                                      top_k=20000, # this k needs to be very big 
+                                                      score_function=sentence_transformers.util.dot_score
+                                                      )[0] # index 0 because we have only one query
 
-    return sentence_transformers.util.semantic_search(query_embedding,
-                                                      command_embeddings,
+    scores_titles = sentence_transformers.util.semantic_search(query_embedding,
+                                                      embedding_titles,
                                                       top_k=20000, # this k needs to be very big 
                                                       score_function=sentence_transformers.util.dot_score
                                                       )[0] # index 0 because we have only one query 
+
+    combined_scores = []
+    for i in range(len(scores_ids)):
+        combined_scores.append({'corpus_id': scores_ids[i]['corpus_id'], 
+                                'score': max(scores_ids[i]['score'], scores_titles[i]['score'])})
+
+    return combined_scores
 
     # cosine_scores = sentence_transformers.util.dot_score(
     #                        query_embedding, command_embeddings)
@@ -36,8 +52,7 @@ def semantic_search(query:str, command_embeddings, method:str, model:str):
 
     command_dict_list: a list of commands, 
                     each a dict: 
-                {"key":str, "command":str, "when":str, "to-ebd": str}
-                to-ebd is the string to embed the command itself or its label
+                {"command_id":str, "command_title":str, "command_id_normalized":str}
 
     """
 
@@ -72,8 +87,8 @@ def combine_results(scores:dict[list], command_dict_list, k, p):
     cutoff_index = filter_results([s['score'] for s in scores], k, p)
 
     for score in scores[:cutoff_index]:
-        command_id = score['corpus_id']
-        command = command_dict_list[command_id]['command']
+        command_idx = score['corpus_id']
+        command = command_dict_list[command_idx]['command_id']
         results.append((command, score['score']))
     return results