mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00
a47976e82d
* wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. * wenxin-tools-700 When the prompt type is list[int] or list[list[int]], it needs to support echoing after decoding. --------- Co-authored-by: luukunn <83932082+luukunn@users.noreply.github.com>
205 lines
7.9 KiB
Python
205 lines
7.9 KiB
Python
"""
|
|
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License"
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""
|
|
|
|
import unittest
|
|
from unittest.mock import MagicMock
|
|
|
|
from fastdeploy.entrypoints.openai.serving_completion import (
|
|
CompletionRequest,
|
|
OpenAIServingCompletion,
|
|
)
|
|
|
|
|
|
class TestCompletionEcho(unittest.IsolatedAsyncioTestCase):
|
|
def setUp(self):
|
|
self.mock_engine = MagicMock()
|
|
self.completion_handler = None
|
|
self.mock_engine.data_processor.tokenizer.decode = lambda x: f"decoded_{x}"
|
|
|
|
"""Testing echo prompt in non-streaming of a single str prompt"""
|
|
|
|
def test_single_str_prompt_non_streaming(self):
|
|
self.completion_handler = OpenAIServingCompletion(
|
|
self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
|
|
)
|
|
|
|
request = CompletionRequest(prompt="test prompt", max_tokens=10, echo=True, logprobs=1)
|
|
|
|
mock_output = {
|
|
"outputs": {
|
|
"text": " generated text",
|
|
"token_ids": [1, 2, 3],
|
|
"top_logprobs": {"token1": -0.1, "token2": -0.2},
|
|
"finished": True,
|
|
},
|
|
"output_token_ids": 3,
|
|
}
|
|
self.mock_engine.generate.return_value = [mock_output]
|
|
|
|
response = self.completion_handler.request_output_to_completion_response(
|
|
final_res_batch=[mock_output],
|
|
request=request,
|
|
request_id="test_id",
|
|
created_time=12345,
|
|
model_name="test_model",
|
|
prompt_batched_token_ids=[[1, 2]],
|
|
completion_batched_token_ids=[[3, 4, 5]],
|
|
text_after_process_list=["test prompt"],
|
|
)
|
|
|
|
self.assertEqual(response.choices[0].text, "test prompt generated text")
|
|
|
|
"""Testing echo prompt in non-streaming of a single int prompt"""
|
|
|
|
def test_single_int_prompt_non_streaming(self):
|
|
self.completion_handler = OpenAIServingCompletion(
|
|
self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
|
|
)
|
|
|
|
request = CompletionRequest(prompt=[1, 2, 3], max_tokens=10, echo=True, logprobs=1)
|
|
|
|
mock_output = {
|
|
"outputs": {
|
|
"text": " generated text",
|
|
"token_ids": [1, 2, 3],
|
|
"top_logprobs": {"token1": -0.1, "token2": -0.2},
|
|
"finished": True,
|
|
},
|
|
"output_token_ids": 3,
|
|
}
|
|
self.mock_engine.generate.return_value = [mock_output]
|
|
|
|
response = self.completion_handler.request_output_to_completion_response(
|
|
final_res_batch=[mock_output],
|
|
request=request,
|
|
request_id="test_id",
|
|
created_time=12345,
|
|
model_name="test_model",
|
|
prompt_batched_token_ids=[[1, 2]],
|
|
completion_batched_token_ids=[[3, 4, 5]],
|
|
text_after_process_list=["test prompt"],
|
|
)
|
|
self.assertEqual(response.choices[0].text, "decoded_[1, 2, 3] generated text")
|
|
|
|
"""Testing echo prompts in non-streaming of multiple str prompts"""
|
|
|
|
def test_multi_str_prompt_non_streaming(self):
|
|
self.completion_handler = OpenAIServingCompletion(
|
|
self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
|
|
)
|
|
|
|
request = CompletionRequest(prompt=["prompt1", "prompt2"], max_tokens=10, echo=True)
|
|
|
|
mock_outputs = [
|
|
{
|
|
"outputs": {"text": " response1", "token_ids": [1, 2], "top_logprobs": None, "finished": True},
|
|
"output_token_ids": 2,
|
|
},
|
|
{
|
|
"outputs": {"text": " response2", "token_ids": [3, 4], "top_logprobs": None, "finished": True},
|
|
"output_token_ids": 2,
|
|
},
|
|
]
|
|
self.mock_engine.generate.return_value = mock_outputs
|
|
|
|
response = self.completion_handler.request_output_to_completion_response(
|
|
final_res_batch=mock_outputs,
|
|
request=request,
|
|
request_id="test_id",
|
|
created_time=12345,
|
|
model_name="test_model",
|
|
prompt_batched_token_ids=[[1], [2]],
|
|
completion_batched_token_ids=[[1, 2], [3, 4]],
|
|
text_after_process_list=["prompt1", "prompt2"],
|
|
)
|
|
|
|
self.assertEqual(len(response.choices), 2)
|
|
self.assertEqual(response.choices[0].text, "prompt1 response1")
|
|
self.assertEqual(response.choices[1].text, "prompt2 response2")
|
|
|
|
"""Testing echo prompts in non-streaming of multiple int prompts"""
|
|
|
|
def test_multi_int_prompt_non_streaming(self):
|
|
self.completion_handler = OpenAIServingCompletion(
|
|
self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30
|
|
)
|
|
|
|
request = CompletionRequest(prompt=[[1, 2, 3], [4, 5, 6]], max_tokens=10, echo=True)
|
|
|
|
mock_outputs = [
|
|
{
|
|
"outputs": {"text": " response1", "token_ids": [1, 2], "top_logprobs": None, "finished": True},
|
|
"output_token_ids": 2,
|
|
},
|
|
{
|
|
"outputs": {"text": " response2", "token_ids": [3, 4], "top_logprobs": None, "finished": True},
|
|
"output_token_ids": 2,
|
|
},
|
|
]
|
|
self.mock_engine.generate.return_value = mock_outputs
|
|
|
|
response = self.completion_handler.request_output_to_completion_response(
|
|
final_res_batch=mock_outputs,
|
|
request=request,
|
|
request_id="test_id",
|
|
created_time=12345,
|
|
model_name="test_model",
|
|
prompt_batched_token_ids=[[1], [2]],
|
|
completion_batched_token_ids=[[1, 2], [3, 4]],
|
|
text_after_process_list=["prompt1", "prompt2"],
|
|
)
|
|
|
|
self.assertEqual(len(response.choices), 2)
|
|
self.assertEqual(response.choices[0].text, "decoded_[1, 2, 3] response1")
|
|
self.assertEqual(response.choices[1].text, "decoded_[4, 5, 6] response2")
|
|
|
|
"""Testing echo prompts in streaming of a single str prompt"""
|
|
|
|
async def test_single_str_prompt_streaming(self):
|
|
request = CompletionRequest(prompt="test prompt", max_tokens=10, stream=True, echo=True)
|
|
res = {"outputs": {"send_idx": 0, "text": "!"}}
|
|
idx = 0
|
|
|
|
instance = OpenAIServingCompletion(self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30)
|
|
res = await instance._process_echo_logic(request, idx, res["outputs"])
|
|
self.assertEqual(res["text"], "test prompt!")
|
|
|
|
"""Testing echo prompts in streaming of a single int prompt"""
|
|
|
|
async def test_single_int_prompt_streaming(self):
|
|
request = CompletionRequest(prompt=[1, 2, 3], max_tokens=10, stream=True, echo=True)
|
|
res = {"outputs": {"send_idx": 0, "text": "!"}}
|
|
idx = 0
|
|
|
|
instance = OpenAIServingCompletion(self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30)
|
|
res = await instance._process_echo_logic(request, idx, res["outputs"])
|
|
self.assertEqual(res["text"], "decoded_[1, 2, 3]!")
|
|
|
|
"""Testing echo prompts in streaming of multi str prompt"""
|
|
|
|
async def test_multi_str_prompt_streaming(self):
|
|
request = CompletionRequest(prompt=["test prompt1", "test prompt2"], max_tokens=10, stream=True, echo=True)
|
|
res = {"outputs": {"send_idx": 0, "text": "!"}}
|
|
idx = 0
|
|
|
|
instance = OpenAIServingCompletion(self.mock_engine, models=None, pid=123, ips=None, max_waiting_time=30)
|
|
res = await instance._process_echo_logic(request, idx, res["outputs"])
|
|
self.assertEqual(res["text"], "test prompt1!")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|