mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2026-04-23 00:17:25 +08:00
kxz2002
6e416c62dd
* to_request_for_infer initial commit * refact to from_chat_completion_request * preprocess use request initial commit * bugfix * processors refact to using request * bug fix * refact Request from_generic_request * post process initial commit * bugfix * postprocess second commit * bugfix * serving_embedding initial commit * serving_reward initial commit * bugfix * replace function name * async_llm initial commit * offline initial commit and fix bug * bugfix * fix async_llm * remove add speculate_metrics into data * fix logprobs bug * fix echo bug * fix bug * fix reasoning_max_tokens * bugfix * bugfix and modify unittest * bugfix and modify unit test * bugfix * bugfix * bugfix * modify unittest * fix error when reasong_content is none for text_processor * remove some unnessary logic * revert removed logic * implement add and set method for RequestOutput and refact code * modify unit test * modify unit test * union process_request and process_request_obj * remove a unit test * union process_response and process_response_obj * support qwen3_vl_processor * modify unittest and remove comments * fix prompt_logprobs * fix codestyle * add v1 * v1 * fix unit test * fix unit test * fix pre-commit * fix * add process request * add process request * fix * fix * fix unit test * fix unit test * fix unit test * fix unit test * fix unit test * remove file * add unit test * add unit test * add unit test * fix unit test * fix unit test * fix * fix --------- Co-authored-by: Jiaxin Sui <95567040+plusNew001@users.noreply.github.com> Co-authored-by: luukunn <981429396@qq.com> Co-authored-by: luukunn <83932082+luukunn@users.noreply.github.com> Co-authored-by: Zhang Yulong <35552275+ZhangYulongg@users.noreply.github.com>
229 lines
9.0 KiB
Python
229 lines
9.0 KiB
Python
"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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import unittest
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from unittest.mock import MagicMock
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from fastdeploy.engine.request import RequestOutput
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from fastdeploy.entrypoints.openai.serving_completion import (
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CompletionRequest,
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OpenAIServingCompletion,
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)
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class TestCompletionEcho(unittest.IsolatedAsyncioTestCase):
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def setUp(self):
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self.mock_engine = MagicMock()
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self.completion_handler = None
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self.mock_engine.data_processor.tokenizer.decode = lambda x: f"decoded_{x}"
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"""Testing echo prompt in non-streaming of a single str prompt"""
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def test_single_str_prompt_non_streaming(self):
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self.completion_handler = OpenAIServingCompletion(
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self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
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)
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request = CompletionRequest(prompt="test prompt", max_tokens=10, echo=True, logprobs=1)
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mock_output = {
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"request_id": "test_id",
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"outputs": {
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"text": " generated text",
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"token_ids": [1, 2, 3],
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"top_logprobs": {"token1": -0.1, "token2": -0.2},
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"finished": True,
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},
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"metrics": {},
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}
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mock_output = RequestOutput.from_dict(mock_output)
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mock_output.output_token_ids = 3
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self.mock_engine.generate.return_value = [mock_output]
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response = self.completion_handler.request_output_to_completion_response(
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final_res_batch=[mock_output],
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request=request,
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request_id="test_id",
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created_time=12345,
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model_name="test_model",
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prompt_batched_token_ids=[[1, 2]],
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completion_batched_token_ids=[[3, 4, 5]],
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prompt_tokens_list=["test prompt"],
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max_tokens_list=[100],
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)
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self.assertEqual(response.choices[0].text, "test prompt generated text")
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"""Testing echo prompt in non-streaming of a single int prompt"""
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def test_single_int_prompt_non_streaming(self):
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self.completion_handler = OpenAIServingCompletion(
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self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
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)
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request = CompletionRequest(prompt=[1, 2, 3], max_tokens=10, echo=True, logprobs=1)
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mock_output = {
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"request_id": "test_id",
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"outputs": {
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"text": " generated text",
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"token_ids": [1, 2, 3],
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"top_logprobs": {"token1": -0.1, "token2": -0.2},
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"finished": True,
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},
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"metrics": {},
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}
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mock_output = RequestOutput.from_dict(mock_output)
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mock_output.output_token_ids = 3
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self.mock_engine.generate.return_value = [mock_output]
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response = self.completion_handler.request_output_to_completion_response(
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final_res_batch=[mock_output],
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request=request,
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request_id="test_id",
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created_time=12345,
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model_name="test_model",
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prompt_batched_token_ids=[[1, 2]],
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completion_batched_token_ids=[[3, 4, 5]],
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prompt_tokens_list=["test prompt"],
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max_tokens_list=[100],
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)
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self.assertEqual(response.choices[0].text, "decoded_[1, 2, 3] generated text")
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"""Testing echo prompts in non-streaming of multiple str prompts"""
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def test_multi_str_prompt_non_streaming(self):
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self.completion_handler = OpenAIServingCompletion(
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self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
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)
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request = CompletionRequest(prompt=["prompt1", "prompt2"], max_tokens=10, echo=True)
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mock_outputs = [
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{
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"request_id": "test_id",
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"outputs": {"text": " response1", "token_ids": [1, 2], "top_logprobs": None, "finished": True},
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"metrics": {},
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},
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{
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"request_id": "test_id",
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"outputs": {"text": " response2", "token_ids": [3, 4], "top_logprobs": None, "finished": True},
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"metrics": {},
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},
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]
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mock_outputs = [RequestOutput.from_dict(item) for item in mock_outputs]
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for item in mock_outputs:
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item.output_token_ids = 2
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self.mock_engine.generate.return_value = mock_outputs
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response = self.completion_handler.request_output_to_completion_response(
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final_res_batch=mock_outputs,
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request=request,
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request_id="test_id",
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created_time=12345,
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model_name="test_model",
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prompt_batched_token_ids=[[1], [2]],
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completion_batched_token_ids=[[1, 2], [3, 4]],
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prompt_tokens_list=["prompt1", "prompt2"],
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max_tokens_list=[100, 100],
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)
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self.assertEqual(len(response.choices), 2)
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self.assertEqual(response.choices[0].text, "prompt1 response1")
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self.assertEqual(response.choices[1].text, "prompt2 response2")
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"""Testing echo prompts in non-streaming of multiple int prompts"""
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def test_multi_int_prompt_non_streaming(self):
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self.completion_handler = OpenAIServingCompletion(
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self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
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)
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request = CompletionRequest(prompt=[[1, 2, 3], [4, 5, 6]], max_tokens=10, echo=True)
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mock_outputs = [
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{
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"request_id": "test_id",
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"outputs": {"text": " response1", "token_ids": [1, 2], "top_logprobs": None, "finished": True},
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"metrics": {},
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},
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{
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"request_id": "test_id",
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"outputs": {"text": " response2", "token_ids": [3, 4], "top_logprobs": None, "finished": True},
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"metrics": {},
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},
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]
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mock_outputs = [RequestOutput.from_dict(item) for item in mock_outputs]
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for item in mock_outputs:
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item.output_token_ids = 2
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self.mock_engine.generate.return_value = mock_outputs
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response = self.completion_handler.request_output_to_completion_response(
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final_res_batch=mock_outputs,
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request=request,
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request_id="test_id",
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created_time=12345,
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model_name="test_model",
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prompt_batched_token_ids=[[1], [2]],
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completion_batched_token_ids=[[1, 2], [3, 4]],
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prompt_tokens_list=["prompt1", "prompt2"],
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max_tokens_list=[100, 100],
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)
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self.assertEqual(len(response.choices), 2)
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self.assertEqual(response.choices[0].text, "decoded_[1, 2, 3] response1")
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self.assertEqual(response.choices[1].text, "decoded_[4, 5, 6] response2")
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"""Testing echo prompts in streaming of a single str prompt"""
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async def test_single_str_prompt_streaming(self):
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request = CompletionRequest(prompt="test prompt", max_tokens=10, stream=True, echo=True)
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res = {"request_id": "test_id", "outputs": {"send_idx": 0, "text": "!"}}
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res = RequestOutput.from_dict(res)
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idx = 0
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instance = OpenAIServingCompletion(self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30)
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res = await instance._process_echo_logic(request, idx, res.outputs)
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self.assertEqual(res.text, "test prompt!")
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"""Testing echo prompts in streaming of a single int prompt"""
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async def test_single_int_prompt_streaming(self):
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request = CompletionRequest(prompt=[1, 2, 3], max_tokens=10, stream=True, echo=True)
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res = {"request_id": "test_id", "outputs": {"send_idx": 0, "text": "!"}}
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res = RequestOutput.from_dict(res)
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idx = 0
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instance = OpenAIServingCompletion(self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30)
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res = await instance._process_echo_logic(request, idx, res.outputs)
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self.assertEqual(res.text, "decoded_[1, 2, 3]!")
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"""Testing echo prompts in streaming of multi str prompt"""
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async def test_multi_str_prompt_streaming(self):
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request = CompletionRequest(prompt=["test prompt1", "test prompt2"], max_tokens=10, stream=True, echo=True)
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res = {"request_id": "test_id", "outputs": {"send_idx": 0, "text": "!"}}
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res = RequestOutput.from_dict(res)
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idx = 0
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instance = OpenAIServingCompletion(self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30)
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res = await instance._process_echo_logic(request, idx, res.outputs)
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self.assertEqual(res.text, "test prompt1!")
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if __name__ == "__main__":
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unittest.main()
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