update TestOpenAIServingCompletion for merge

Author: memoryCoderC

fastdeploy/entrypoints/openai/serving_completion.py

@@ -436,9 +436,6 @@ def request_output_to_completion_response(
                 token_ids = output["token_ids"]
                 output_text = output["text"]
 
-            num_generated_tokens += final_res["output_token_ids"]
-            num_prompt_tokens += len(prompt_token_ids)
-
             finish_reason = self.calc_finish_reason(request.max_tokens, final_res["output_token_ids"], output)
 
             choice_data = CompletionResponseChoice(
@@ -454,6 +451,10 @@ def request_output_to_completion_response(
             )
             choices.append(choice_data)
 
+            num_generated_tokens += final_res["output_token_ids"]
+
+            num_prompt_tokens += len(prompt_token_ids)
+
         usage = UsageInfo(
             prompt_tokens=num_prompt_tokens,
             completion_tokens=num_generated_tokens,

test/entrypoints/openai/test_serving_completion.py

@@ -1,7 +1,12 @@
 import unittest
+from typing import List
 from unittest.mock import Mock
 
-from fastdeploy.entrypoints.openai.serving_completion import OpenAIServingCompletion
+from fastdeploy.entrypoints.openai.serving_completion import (
+    CompletionRequest,
+    OpenAIServingCompletion,
+    RequestOutput,
+)
 
 
 class TestOpenAIServingCompletion(unittest.TestCase):
@@ -11,7 +16,7 @@ def test_calc_finish_reason_tool_calls(self):
         engine_client = Mock()
         engine_client.reasoning_parser = "ernie_x1"
         # 创建一个OpenAIServingCompletion实例
-        serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips")
+        serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips", 360)
         # 创建一个模拟的output，并设置finish_reason为"tool_calls"
         output = {"finish_reason": "tool_calls"}
         # 调用calc_finish_reason方法
@@ -24,7 +29,7 @@ def test_calc_finish_reason_stop(self):
         engine_client = Mock()
         engine_client.reasoning_parser = "ernie_x1"
         # 创建一个OpenAIServingCompletion实例
-        serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips")
+        serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips", 360)
         # 创建一个模拟的output，并设置finish_reason为其他值
         output = {"finish_reason": "other_reason"}
         # 调用calc_finish_reason方法
@@ -36,14 +41,71 @@ def test_calc_finish_reason_length(self):
         # 创建一个模拟的engine_client
         engine_client = Mock()
         # 创建一个OpenAIServingCompletion实例
-        serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips")
+        serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips", 360)
         # 创建一个模拟的output
         output = {}
         # 调用calc_finish_reason方法
         result = serving_completion.calc_finish_reason(100, 100, output)
         # 断言结果为"length"
         assert result == "length"
 
+    def test_request_output_to_completion_response(self):
+        engine_client = Mock()
+        # 创建一个OpenAIServingCompletion实例
+        openai_serving_completion = OpenAIServingCompletion(engine_client, "pid", "ips", 360)
+        final_res_batch: List[RequestOutput] = [
+            {
+                "prompt": "Hello, world!",
+                "outputs": {
+                    "token_ids": [1, 2, 3],
+                    "text": " world!",
+                    "top_logprobs": {
+                        "a": 0.1,
+                        "b": 0.2,
+                    },
+                },
+                "output_token_ids": 3,
+            },
+            {
+                "prompt": "Hello, world!",
+                "outputs": {
+                    "token_ids": [4, 5, 6],
+                    "text": " world!",
+                    "top_logprobs": {
+                        "a": 0.3,
+                        "b": 0.4,
+                    },
+                },
+                "output_token_ids": 3,
+            },
+        ]
+
+        request: CompletionRequest = Mock()
+        request_id = "test_request_id"
+        created_time = 1655136000
+        model_name = "test_model"
+        prompt_batched_token_ids = [[1, 2, 3], [4, 5, 6]]
+        completion_batched_token_ids = [[7, 8, 9], [10, 11, 12]]
+
+        completion_response = openai_serving_completion.request_output_to_completion_response(
+            final_res_batch=final_res_batch,
+            request=request,
+            request_id=request_id,
+            created_time=created_time,
+            model_name=model_name,
+            prompt_batched_token_ids=prompt_batched_token_ids,
+            completion_batched_token_ids=completion_batched_token_ids,
+        )
+
+        assert completion_response.id == request_id
+        assert completion_response.created == created_time
+        assert completion_response.model == model_name
+        assert len(completion_response.choices) == 2
+
+        # 验证 choices 的 text 属性
+        assert completion_response.choices[0].text == "Hello, world! world!"
+        assert completion_response.choices[1].text == "Hello, world! world!"
+
 
 if __name__ == "__main__":
     unittest.main()