[assets] update wechat (#9129)

src/llamafactory/data/converter.py

@@ -257,8 +257,8 @@ class OpenAIDatasetConverter(DatasetConverter):
             content = message[self.dataset_attr.content_tag]
 
             if role in [self.dataset_attr.assistant_tag, self.dataset_attr.function_tag]:
-                if "tool_calls" in message and len(message['tool_calls']) > 0:
-                    tool_calls_list = [tool['function'] for tool in message['tool_calls']]
+                if "tool_calls" in message and len(message["tool_calls"]) > 0:
+                    tool_calls_list = [tool["function"] for tool in message["tool_calls"]]
                     content = json.dumps(tool_calls_list, ensure_ascii=False)
                     role = self.dataset_attr.function_tag
 
@@ -340,7 +340,7 @@ class OpenAIDatasetConverter(DatasetConverter):
         if isinstance(tools, dict) or isinstance(tools, list):
             tools = json.dumps(tools, ensure_ascii=False)
 
-        short_system_prompt = 'detailed thinking off'
+        short_system_prompt = "detailed thinking off"
         if not system:
             if not tools:
                 system = short_system_prompt
@@ -348,13 +348,12 @@ class OpenAIDatasetConverter(DatasetConverter):
                 pass
         else:
             if not tools:
-                if 'detailed thinking on' in system or 'detailed thinking off' in system:
+                if "detailed thinking on" in system or "detailed thinking off" in system:
                     pass
                 else:
-                    system += '\n' + short_system_prompt
+                    system += "\n" + short_system_prompt
             else:
-                system += '\n'
-
+                system += "\n"
 
         output = {
             "_prompt": prompt,

src/llamafactory/data/template.py

@@ -685,7 +685,9 @@ register_template(
     format_system=StringFormatter(slots=["<role>SYSTEM</role>{{content}}<|role_end|>"]),
     format_assistant=StringFormatter(slots=["{{content}}<|role_end|>"]),
     format_observation=StringFormatter(
-        slots=["<role>OBSERVATION</role>\n<tool_response>\n{{content}}\n</tool_response><|role_end|><role>ASSISTANT</role>"]
+        slots=[
+            "<role>OBSERVATION</role>\n<tool_response>\n{{content}}\n</tool_response><|role_end|><role>ASSISTANT</role>"
+        ]
     ),
     format_function=FunctionFormatter(slots=["{{content}}<|role_end|>"], tool_format="ling"),
     format_tools=ToolFormatter(tool_format="ling"),

src/llamafactory/model/patcher.py

@@ -219,7 +219,7 @@ def patch_valuehead_model(model: "AutoModelForCausalLMWithValueHead") -> None:
 
         if base_model and hasattr(base_model, "get_rope_index"):
             return base_model.get_rope_index
-        elif (base_model and hasattr(base_model, "model") and hasattr(base_model.model, "get_rope_index")):
+        elif base_model and hasattr(base_model, "model") and hasattr(base_model.model, "get_rope_index"):
             return base_model.model.get_rope_index
         else:
             return None