[template] update glm4.5 agent template

swift/llm/template/base.py

@@ -1110,9 +1110,14 @@ def _swift_encode(self, inputs: StdTemplateInputs):
             elif response is not None:
                 # It is the final round, and the response exists (during training).
                 context_list.append('{{RESPONSE}}')
+                # The GLM-4.5 assistant part (tool call) may end with <|observation|>,
+                # and here we avoid adding <|user|>.
+                endswith_stop_words = any(
+                    response.endswith(stop_word) for stop_word in template_meta.stop_words
+                    if isinstance(stop_word, str))
                 # self.is_training needed because we may want to continue generation from
                 # the current response
-                if self.is_training and not sep_token or self.task_type == 'embedding':
+                if self.is_training and not sep_token or self.task_type == 'embedding' and not endswith_stop_words:
                     extra_context_list = template_meta.suffix
                     extra_context_type = ContextType.SUFFIX
             elif template_meta.response_prefix:
@@ -1201,6 +1206,7 @@ def _encode_truncated(self, inputs: StdTemplateInputs):
         return encoded
 
     def _encode(self, inputs: StdTemplateInputs) -> Dict[str, Any]:
+        inputs.messages = deepcopy(inputs.messages)
         template_backend = self.template_backend
         if (self.template_meta.template_type == 'dummy' and self.use_chat_template and not self.is_training
                 and self.task_type != 'seq_cls'):

swift/llm/template/template/glm.py

@@ -239,15 +239,12 @@ class GLM4_5Template(ThinkingTemplate):
     no_think_prefix = '<think></think>\n'
     history_think_prefix = '<think></think>\n'
 
-    def _swift_encode(self, inputs: StdTemplateInputs):
-        res_context_list, loss_scale_list, answer_len = super()._swift_encode(inputs)
-        # When it's a tool_call, avoid generating <|observation|><|user|>
-        penultimate_content = res_context_list[-2] if len(res_context_list) >= 2 else None
-        if isinstance(penultimate_content,
-                      str) and penultimate_content.endswith('<|observation|>') and res_context_list[-1] == '<|user|>':
-            res_context_list = res_context_list[:-1]
-            answer_len -= 1
-        return res_context_list, loss_scale_list, answer_len
+    def _jinja_encode(self, inputs: StdTemplateInputs):
+        for message in inputs.messages:
+            if message['role'] == 'assistant' and isinstance(message['content'],
+                                                             str) and message['content'].endswith('<|observation|>'):
+                message['content'] = message['content'][:-len('<|observation|>')]
+        return super()._jinja_encode(inputs)
 
 
 register_template(GLM4_5TemplateMeta(LLMTemplateType.glm4_5, template_cls=GLM4_5Template))

swift/plugin/agent_template/glm4.py

@@ -132,7 +132,7 @@ def _format_tool_responses(
         if with_action:
             return super()._format_tool_responses(assistant_content, tool_messages)
         res = []
-        for _, tool_message in enumerate(tool_messages):
+        for tool_message in tool_messages:
             tool_content = tool_message['content']
             res.append(f'\n<tool_response>\n{tool_content}\n</tool_response>')
         res.append('<|assistant|>\n')

tests/test_align/test_template/test_agent.py

@@ -1,6 +1,7 @@
 import os
 
 os.environ['SWIFT_DEBUG'] = '1'
+os.environ['CUDA_VISIBLE_DEVICES'] = '0,1,2,3'
 
 system = 'You are a helpful assistant.'
 
@@ -327,7 +328,29 @@ def test_hunyuan():
     encoded2 = template.encode(data)
     print(f'input_ids: {template.safe_decode(encoded2["input_ids"])}')
     print(f'labels: {template.safe_decode(encoded2["labels"])}')
-    assert encoded['input_ids'] == encoded2['input_ids']
+    assert encoded['input_ids'][:-1] == encoded2['input_ids']
+
+
+def test_glm4_5():
+    engine = PtEngine('ZhipuAI/GLM-4.5-Air')
+    template = engine.default_template
+    template.template_backend = 'jinja'
+    _infer(engine, num_tools=2)
+
+    dataset = load_dataset('AI-ModelScope/function-calling-chatml')[0]
+    data = dataset[6]
+    data['messages'].insert(1, data['messages'][1])
+    data['messages'].insert(3, data['messages'][3])
+    template.template_backend = 'swift'
+    template.set_mode('train')
+    encoded = template.encode(data)
+    print(f'input_ids: {template.safe_decode(encoded["input_ids"])}')
+    print(f'labels: {template.safe_decode(encoded["labels"])}')
+    template.template_backend = 'jinja'
+    encoded2 = template.encode(data)
+    print(f'input_ids: {template.safe_decode(encoded2["input_ids"])}')
+    print(f'labels: {template.safe_decode(encoded2["labels"])}')
+    assert encoded['input_ids'][:-1] == encoded2['input_ids']
 
 
 if __name__ == '__main__':
@@ -345,4 +368,5 @@ def test_hunyuan():
     # test_glm4_0414()
     # test_llama3()
     # test_llama4()
-    test_hunyuan()
+    # test_hunyuan()
+    test_glm4_5()