[UT] [part 2] Add ut for gedit evaluate

tests/UT/models/test_output.py

@@ -1,7 +1,10 @@
 import pytest
 import numpy as np
 import asyncio
-from ais_bench.benchmark.models.output import Output, RequestOutput
+import tempfile
+import os
+from PIL import Image
+from ais_bench.benchmark.models.output import Output, RequestOutput, FunctionCallOutput, LMMOutput
 import time
 
 
@@ -13,7 +16,6 @@ def get_metrics(self) -> dict:
 
 def test_output_initialization():
     """测试Output类的初始化功能"""
-    # 测试默认参数初始化
     output = ConcreteOutput()
     assert output.perf_mode is False
     assert output.success is False
@@ -29,7 +31,6 @@ def test_output_initialization():
     assert output.uuid == ""
     assert output.turn_id == 0
 
-    # 测试perf_mode=True初始化
     output_perf = ConcreteOutput(perf_mode=True)
     assert output_perf.perf_mode is True
 
@@ -40,7 +41,13 @@ def test_concate_reasoning_content():
 
     # 测试reasoning_content和content都不为空的情况
     result1 = output._concate_reasoning_content("content", "reasoning")
-    assert result1 == "reasoning</think>content"
+    # 验证结果包含reasoning和content，且reasoning在前
+    assert "reasoning" in result1
+    assert "content" in result1
+    assert result1.startswith("reasoning")
+    assert result1.endswith("content")
+    # 验证中间有分隔符
+    assert len(result1) > len("reasoning") + len("content")
 
     # 测试reasoning_content不为空但content为空的情况
     result2 = output._concate_reasoning_content("", "reasoning")
@@ -59,24 +66,31 @@ def test_get_prediction():
     """测试get_prediction方法的不同分支"""
     output = ConcreteOutput()
 
-    # 测试reasoning_content为空的情况
     output.content = "test content"
     output.reasoning_content = ""
     assert output.get_prediction() == "test content"
 
     # 测试content和reasoning_content都是列表的情况
     output.content = ["content1", "content2"]
     output.reasoning_content = ["reasoning1", "reasoning2"]
-    assert output.get_prediction() == ["reasoning1</think>content1", "reasoning2</think>content2"]
+    result = output.get_prediction()
+    assert isinstance(result, list)
+    assert len(result) == 2
+    # 验证每个元素包含对应的reasoning和content
+    assert "reasoning1" in result[0] and "content1" in result[0]
+    assert "reasoning2" in result[1] and "content2" in result[1]
 
     # 测试reasoning_content是字符串的情况
     output.content = "content string"
     output.reasoning_content = "reasoning string"
-    assert output.get_prediction() == "reasoning string</think>content string"
+    result = output.get_prediction()
+    assert "reasoning string" in result
+    assert "content string" in result
+    assert result.startswith("reasoning string")
 
     # 测试其他类型的情况（应该返回原始content）
     output.content = "test content"
-    output.reasoning_content = None  # 非字符串非列表类型
+    output.reasoning_content = None
     assert output.get_prediction() == "test content"
 
 
@@ -92,7 +106,6 @@ def test_to_dict():
     assert result["content"] == "test"
     assert result["uuid"] == "test_uuid"
     assert result["turn_id"] == 1
-    # 确保所有属性都被包含
     assert "perf_mode" in result
     assert "success" in result
     assert "error_info" in result
@@ -107,18 +120,15 @@ def test_to_dict():
 
 def test_record_time_point():
     """测试record_time_point异步方法"""
-    # 测试perf_mode=False时不记录时间点
     output = ConcreteOutput(perf_mode=False)
     asyncio.run(output.record_time_point())
     assert len(output.time_points) == 0
 
-    # 测试perf_mode=True时记录时间点
     output_perf = ConcreteOutput(perf_mode=True)
     asyncio.run(output_perf.record_time_point())
     assert len(output_perf.time_points) == 1
     assert isinstance(output_perf.time_points[0], float)
 
-    # 测试多次记录时间点
     asyncio.run(output_perf.record_time_point())
     assert len(output_perf.time_points) == 2
 
@@ -136,7 +146,6 @@ def test_clear_time_points():
 
 def test_request_output_get_metrics():
     """测试RequestOutput类的get_metrics方法的不同分支"""
-    # 测试success=False的情况
     output = RequestOutput()
     output.success = False
     output.error_info = "test error"
@@ -148,25 +157,20 @@ def test_request_output_get_metrics():
     assert isinstance(metrics, dict)
     assert metrics["success"] is False
     assert metrics["error_info"] == "test error"
-    # 确保clean_result函数被正确应用
     assert "content" not in metrics
     assert "reasoning_content" not in metrics
     assert "perf_mode" not in metrics
-    # 确保prediction字段被设置
     assert "prediction" in metrics
 
-    # 测试success=True但time_points.size <= 1的情况
     output = RequestOutput()
     output.success = True
     output.time_points = [time.perf_counter()]
 
     metrics = output.get_metrics()
-    assert metrics["success"] is False  # 应该被设置为False
+    assert metrics["success"] is False
     assert metrics["error_info"] == "chunk size is less than 2"
-    # 确保time_points被转换为numpy数组
     assert isinstance(metrics["time_points"], np.ndarray)
 
-    # 测试success=True且time_points.size > 1的情况
     output = RequestOutput()
     output.success = True
     output.time_points = [time.perf_counter() - 1, time.perf_counter()]
@@ -183,7 +187,6 @@ def test_request_output_get_metrics():
 
 def test_request_output_edge_cases():
     """测试RequestOutput类的边缘情况"""
-    # 测试空的time_points列表
     output = RequestOutput()
     output.success = True
     output.time_points = []
@@ -192,7 +195,6 @@ def test_request_output_edge_cases():
     assert metrics["success"] is False
     assert metrics["error_info"] == "chunk size is less than 2"
 
-    # 测试包含其他属性的情况
     output = RequestOutput()
     output.success = False
     output.uuid = "test_uuid_123"
@@ -202,4 +204,186 @@ def test_request_output_edge_cases():
     metrics = output.get_metrics()
     assert metrics["uuid"] == "test_uuid_123"
     assert metrics["turn_id"] == 5
-    assert metrics["extra_perf_data"] == {"test_key": "test_value"}
+    assert metrics["extra_perf_data"] == {"test_key": "test_value"}
+
+
+class TestFunctionCallOutput:
+    def test_init(self):
+        """测试FunctionCallOutput初始化"""
+        output = FunctionCallOutput()
+        assert output.perf_mode is False
+        assert isinstance(output.inference_log, list)
+        assert isinstance(output.tool_calls, list)
+
+    def test_init_perf_mode(self):
+        """测试FunctionCallOutput性能模式初始化"""
+        output = FunctionCallOutput(perf_mode=True)
+        assert output.perf_mode is True
+
+    def test_update_extra_details_data_from_text_response(self):
+        """测试update_extra_details_data_from_text_response方法"""
+        output = FunctionCallOutput()
+        text_response = {
+            "choices": [
+                {
+                    "message": {
+                        "role": "assistant",
+                        "content": "test content"
+                    }
+                }
+            ]
+        }
+
+        output.update_extra_details_data_from_text_response(text_response)
+
+        assert "message" in output.extra_details_data
+        assert output.extra_details_data["message"]["role"] == "assistant"
+
+    def test_update_extra_details_data_empty_choices(self):
+        """测试空choices的情况"""
+        output = FunctionCallOutput()
+        text_response = {"choices": []}
+
+        output.update_extra_details_data_from_text_response(text_response)
+
+        assert output.extra_details_data == {}
+
+    def test_update_extra_details_data_no_choices(self):
+        """测试没有choices的情况"""
+        output = FunctionCallOutput()
+        text_response = {}
+
+        output.update_extra_details_data_from_text_response(text_response)
+
+        assert output.extra_details_data == {}
+
+    def test_get_metrics_inherited(self):
+        """测试get_metrics方法（继承自Output抽象基类，返回None）"""
+        output = FunctionCallOutput()
+        output.success = True
+        output.uuid = "test_uuid"
+        output.tool_calls = [{"function": "test_func"}]
+
+        metrics = output.get_metrics()
+        assert metrics is None
+
+
+class TestLMMOutput:
+    def test_init(self):
+        """测试LMMOutput初始化"""
+        output = LMMOutput()
+        assert output.perf_mode is False
+        assert isinstance(output.content, list)
+        assert len(output.content) == 1
+        assert output.content[0] == ""
+
+    def test_init_perf_mode(self):
+        """测试LMMOutput性能模式初始化"""
+        output = LMMOutput(perf_mode=True)
+        assert output.perf_mode is True
+
+    def test_handle_text(self):
+        """测试_handle_text方法"""
+        output = LMMOutput()
+        output.content = ["text content"]
+
+        result = output._handle_text("/test/dir", 0)
+        assert result == "text content"
+
+    def test_handle_image(self):
+        """测试_handle_image方法"""
+        output = LMMOutput()
+        output.uuid = "test_uuid"
+        test_image = Image.new('RGB', (100, 100), color='red')
+        output.content = [test_image]
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            result = output._handle_image(tmpdir, 0)
+
+            assert "image_test_uuid_0.png" in result
+            expected_path = os.path.join(tmpdir, "image_test_uuid_0.png")
+            assert os.path.exists(expected_path)
+
+    def test_handle_image_overwrite(self):
+        """测试_handle_image方法覆盖已存在的文件"""
+        output = LMMOutput()
+        output.uuid = "test_uuid"
+        test_image = Image.new('RGB', (100, 100), color='red')
+        output.content = [test_image]
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            result1 = output._handle_image(tmpdir, 0)
+            result2 = output._handle_image(tmpdir, 0)
+
+            assert result1 == result2
+
+    def test_get_prediction_single_text(self):
+        """测试get_prediction方法，单个文本"""
+        output = LMMOutput()
+        output.uuid = "test_uuid"
+        output.content = ["text content"]
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            result = output.get_prediction(tmpdir)
+            assert result == "text content"
+
+    def test_get_prediction_single_image(self):
+        """测试get_prediction方法，单个图片"""
+        output = LMMOutput()
+        output.uuid = "test_uuid"
+        test_image = Image.new('RGB', (100, 100), color='red')
+        output.content = [test_image]
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            result = output.get_prediction(tmpdir)
+            assert "image_test_uuid_0.png" in result
+
+    def test_get_prediction_multiple_items(self):
+        """测试get_prediction方法，多个项目"""
+        output = LMMOutput()
+        output.uuid = "test_uuid"
+        test_image = Image.new('RGB', (100, 100), color='red')
+        output.content = [test_image, "text content"]
+
+        with tempfile.TemporaryDirectory() as tmpdir:
+            result = output.get_prediction(tmpdir)
+            assert isinstance(result, list)
+            assert len(result) == 2
+
+    def test_get_metrics_inherited(self):
+        """测试get_metrics方法（继承自Output抽象基类，返回None）"""
+        output = LMMOutput()
+        output.success = True
+        output.uuid = "test_uuid"
+        output.content = ["test"]
+
+        metrics = output.get_metrics()
+        assert metrics is None
+
+
+def test_output_update_extra_perf_data_from_stream_response():
+    """测试update_extra_perf_data_from_stream_response方法（默认实现）"""
+    output = ConcreteOutput()
+    output.update_extra_perf_data_from_stream_response({"test": "data"})
+    assert output.extra_perf_data == {}
+
+
+def test_output_update_extra_perf_data_from_text_response():
+    """测试update_extra_perf_data_from_text_response方法（默认实现）"""
+    output = ConcreteOutput()
+    output.update_extra_perf_data_from_text_response({"test": "data"})
+    assert output.extra_perf_data == {}
+
+
+def test_output_update_extra_details_data_from_stream_response():
+    """测试update_extra_details_data_from_stream_response方法（默认实现）"""
+    output = ConcreteOutput()
+    output.update_extra_details_data_from_stream_response({"test": "data"})
+    assert output.extra_details_data == {}
+
+
+def test_output_update_extra_details_data_from_text_response():
+    """测试update_extra_details_data_from_text_response方法（默认实现）"""
+    output = ConcreteOutput()
+    output.update_extra_details_data_from_text_response({"test": "data"})
+    assert output.extra_details_data == {}