Fix for MLX Model when stop sequence is followed by any chars (#623)

src/smolagents/models.py

@@ -525,7 +525,7 @@ class MLXModel(Model):
 
     def _to_message(self, text, tools_to_call_from):
         if tools_to_call_from:
-            # tmp solution for extracting tool JSON without assuming a specific model output format
+            # solution for extracting tool JSON without assuming a specific model output format
             maybe_json = "{" + text.split("{", 1)[-1][::-1].split("}", 1)[-1][::-1] + "}"
             parsed_text = json.loads(maybe_json)
             tool_name = parsed_text.get(self.tool_name_key, None)
@@ -579,8 +579,9 @@ class MLXModel(Model):
             self.last_output_token_count += 1
             text += _.text
             for stop_sequence in prepared_stop_sequences:
-                if text.strip().endswith(stop_sequence):
-                    text = text[: -len(stop_sequence)]
+                stop_sequence_start = text.rfind(stop_sequence)
+                if stop_sequence_start != -1:
+                    text = text[:stop_sequence_start]
                     return self._to_message(text, tools_to_call_from)
 
         return self._to_message(text, tools_to_call_from)

tests/test_models.py

@@ -69,6 +69,19 @@ class ModelTests(unittest.TestCase):
         output = model(messages, stop_sequences=["great"]).content
         assert output.startswith("Hello")
 
+    @unittest.skipUnless(sys.platform.startswith("darwin"), "requires macOS")
+    def test_get_mlx_message_tricky_stop_sequence(self):
+        # In this test HuggingFaceTB/SmolLM2-135M-Instruct generates the token ">'"
+        # which is required to test capturing stop_sequences that have extra chars at the end.
+        model = MLXModel(model_id="HuggingFaceTB/SmolLM2-135M-Instruct", max_tokens=100)
+        stop_sequence = " print '>"
+        messages = [{"role": "user", "content": [{"type": "text", "text": f"Please{stop_sequence}'"}]}]
+        # check our assumption that that ">" is followed by "'"
+        assert model.tokenizer.vocab[">'"]
+        assert model(messages, stop_sequences=[]).content == f"I'm ready to help you{stop_sequence}'"
+        # check stop_sequence capture when output has trailing chars
+        assert model(messages, stop_sequences=[stop_sequence]).content == "I'm ready to help you"
+
     def test_transformers_message_no_tool(self):
         model = TransformersModel(
             model_id="HuggingFaceTB/SmolLM2-135M-Instruct",