import unittest from unittest.mock import MagicMock, patch from fastdeploy.input.ernie4_5_processor import Ernie4_5Processor class TestErnie4_5ProcessorProcessResponseDictStreaming(unittest.TestCase): def setUp(self): # 创建 Ernie4_5Processor 实例的模拟对象 with patch.object(Ernie4_5Processor, "__init__", return_value=None) as mock_init: self.processor = Ernie4_5Processor("model_path") mock_init.side_effect = lambda *args, **kwargs: print(f"__init__ called with {args}, {kwargs}") # 设置必要的属性 self.processor.tokenizer = MagicMock() self.processor.tokenizer.eos_token_id = 1 self.processor.decode_status = {} self.processor.reasoning_end_dict = {} self.processor.tool_parser_dict = {} # 模拟 ids2tokens 方法 def mock_ids2tokens(token_ids, task_id): return "delta_text", [2, 3], "previous_texts" self.processor.ids2tokens = mock_ids2tokens # 模拟推理解析器 self.mock_reasoning_parser = MagicMock() self.mock_reasoning_parser.__class__.__name__ = "ErnieX1ReasoningParser" self.mock_reasoning_parser.extract_reasoning_content_streaming.return_value = ("reasoning", "text") self.processor.reasoning_parser = self.mock_reasoning_parser # 模拟工具解析器 self.mock_tool_parser = MagicMock() self.mock_tool_parser.extract_tool_calls_streaming.return_value = None self.mock_tool_parser_obj = MagicMock() self.mock_tool_parser_obj.return_value = self.mock_tool_parser self.processor.tool_parser_obj = self.mock_tool_parser_obj def test_process_response_dict_streaming_normal_case(self): """测试正常情况下的流式响应处理""" # 准备输入 response_dict = {"finished": False, "request_id": "req1", "outputs": {"token_ids": [4, 5]}} kwargs = {"enable_thinking": True} # 调用方法 result = self.processor.process_response_dict_streaming(response_dict, **kwargs) # 验证结果 self.assertEqual(result["outputs"]["raw_prediction"], "delta_text") if __name__ == "__main__": unittest.main()