diff --git a/fastdeploy/entrypoints/engine_client.py b/fastdeploy/entrypoints/engine_client.py index 106ebc7bb..8cff539f3 100644 --- a/fastdeploy/entrypoints/engine_client.py +++ b/fastdeploy/entrypoints/engine_client.py @@ -206,7 +206,15 @@ class EngineClient: task["prompt_token_ids_len"] = len(task["prompt_token_ids"]) input_ids_len = task["prompt_token_ids_len"] - task["max_tokens"] = min(self.max_model_len - input_ids_len, task.get("max_tokens")) + + completion_token_len = len(task["completion_token_ids"]) if task.get("completion_token_ids") else 0 + task["max_tokens"] = min( + self.max_model_len - input_ids_len, max(0, task.get("max_tokens") - completion_token_len) + ) + + if task.get("min_tokens") is not None: + task["min_tokens"] = max(1, task["min_tokens"] - completion_token_len) + min_tokens = task.get("min_tokens", 1) if "messages" in task: del task["messages"] diff --git a/fastdeploy/input/ernie4_5_vl_processor/ernie4_5_vl_processor.py b/fastdeploy/input/ernie4_5_vl_processor/ernie4_5_vl_processor.py index d86eb86c5..00c2df81a 100644 --- a/fastdeploy/input/ernie4_5_vl_processor/ernie4_5_vl_processor.py +++ b/fastdeploy/input/ernie4_5_vl_processor/ernie4_5_vl_processor.py @@ -252,8 +252,11 @@ class Ernie4_5_VLProcessor(Ernie4_5Processor): else: raise ValueError(f"Request must contain 'prompt', or 'messages': {request}") + completion_token_len = 0 if request.get("completion_token_ids"): + completion_token_len = len(request.get("completion_token_ids")) self.append_completion_tokens(outputs, request["completion_token_ids"]) + outputs = self.pack_outputs(outputs) request["prompt_token_ids"] = outputs["input_ids"].tolist() request["prompt_token_ids_len"] = len(request["prompt_token_ids"]) @@ -262,12 +265,17 @@ class Ernie4_5_VLProcessor(Ernie4_5Processor): # 截断超过长度限制的prompt if max_model_len is not None and len(request["prompt_token_ids"]) > max_model_len: request["prompt_token_ids"] = request["prompt_token_ids"][: max_model_len - 1] + + tmp_max_tokens = 0 if request.get("max_tokens") is None: request["max_tokens"] = max(1, max_model_len - len(request["prompt_token_ids"])) + tmp_max_tokens = request["max_tokens"] else: - request["max_tokens"] = min(max_model_len - len(request["prompt_token_ids"]), request["max_tokens"]) + tmp_max_tokens = min( + max_model_len - len(request["prompt_token_ids"]), max(0, request["max_tokens"] - completion_token_len) + ) if request.get("reasoning_max_tokens") is None: - request["reasoning_max_tokens"] = max(int(request["max_tokens"] * 0.8), 1) + request["reasoning_max_tokens"] = max(int(tmp_max_tokens * 0.8), 1) data_processor_logger.info(f"Processed request {request}") if request.get("top_p") is not None and request.get("top_p") < _SAMPLING_EPS: diff --git a/tests/entrypoints/openai/test_max_and_min_tokens.py b/tests/entrypoints/openai/test_max_and_min_tokens.py new file mode 100644 index 000000000..b8088598b --- /dev/null +++ b/tests/entrypoints/openai/test_max_and_min_tokens.py @@ -0,0 +1,139 @@ +import unittest +from unittest.mock import MagicMock, patch + +from fastdeploy.entrypoints.engine_client import EngineClient, EngineError +from fastdeploy.input.ernie4_5_vl_processor.ernie4_5_vl_processor import ( + Ernie4_5_VLProcessor, +) + + +class TestChatContinuationPreprocess(unittest.IsolatedAsyncioTestCase): + + async def asyncSetUp(self): + with patch( + "fastdeploy.input.ernie4_5_vl_processor.ernie4_5_vl_processor.DataProcessor" + ) as mock_data_processor: + mock_ernie4_5_processor = MagicMock() + mock_data_processor.return_value = mock_ernie4_5_processor + + mock_tokenizer = MagicMock() + mock_tokenizer.eos_token_id = 102 + mock_tokenizer.pad_token_id = 0 + mock_ernie4_5_processor.tokenizer = mock_tokenizer + mock_ernie4_5_processor.eval = MagicMock() + mock_ernie4_5_processor.image_patch_id = MagicMock() + mock_ernie4_5_processor.spatial_conv_size = MagicMock() + + self.ernie_processor = Ernie4_5_VLProcessor(model_name_or_path="mock_model_path") + self.ernie_processor.ernie4_5_processor = mock_ernie4_5_processor + + def _create_mock_tensor(initial_ids): + mock_tensor = MagicMock() + mock_tensor._data = initial_ids + mock_tensor.extend = lambda x: mock_tensor._data.extend(x) + mock_tensor.tolist = lambda: mock_tensor._data + return mock_tensor + + self.ernie_processor.ernie4_5_processor.request2ids.return_value = { + "input_ids": _create_mock_tensor([101] * 200) + } + self.ernie_processor.pack_outputs = lambda x: x + + def mock_append_completion_tokens(multimodal_inputs, completion_token_ids): + multimodal_inputs["input_ids"].extend(completion_token_ids) + + self.ernie_processor.append_completion_tokens = MagicMock(side_effect=mock_append_completion_tokens) + self.ernie_processor.eos_token_ids = [102] + self.ernie_processor._parse_limits = MagicMock(return_value=None) + + with patch.object(EngineClient, "__init__", return_value=None): + self.engine_client = EngineClient("mock_model_path") + self.engine_client.data_processor = self.ernie_processor + self.engine_client.max_model_len = 300 + self.engine_client.enable_mm = False + self.engine_client.enable_prefix_caching = False + self.engine_client.zmq_client = MagicMock() + self.engine_client.valid_parameters = MagicMock() + + self.mock_api_logger = patch("fastdeploy.entrypoints.engine_client.api_server_logger").start() + self.mock_data_logger = patch( + "fastdeploy.input.ernie4_5_vl_processor.ernie4_5_vl_processor.data_processor_logger" + ).start() + + async def asyncTearDown(self): + patch.stopall() + + def _update_processor_token_ids(self, prompt_token_ids_len: int): + def _create_mock_tensor(initial_ids): + mock_tensor = MagicMock() + mock_tensor._data = initial_ids + mock_tensor.extend = lambda x: mock_tensor._data.extend(x) + mock_tensor.tolist = lambda: mock_tensor._data + return mock_tensor + + self.ernie_processor.ernie4_5_processor.request2ids.return_value = { + "input_ids": _create_mock_tensor([101] * prompt_token_ids_len) + } + + @patch("uuid.uuid4", return_value="test-request-id") + async def test_continuation_first_request(self, mock_uuid): + request = {"messages": [{"role": "user", "content": "描述这张图片"}], "max_tokens": 50, "min_tokens": 10} + + await self.engine_client.format_and_add_data(request) + + self.assertEqual(request["max_tokens"], 50) + self.assertEqual(request["min_tokens"], 10) + self.assertEqual(len(request["prompt_token_ids"]), 200) + + @patch("uuid.uuid4", return_value="test-request-id-2") + async def test_continuation_second_request(self, mock_uuid): + self._update_processor_token_ids(prompt_token_ids_len=50) + + request = { + "messages": [{"role": "user", "content": "描述这张图片"}], + "completion_token_ids": [103] * 30, + "max_tokens": 200, + "min_tokens": 100, + } + + await self.engine_client.format_and_add_data(request) + + self.assertEqual(request["max_tokens"], 170) + self.assertEqual(request["min_tokens"], 70) + self.assertEqual(len(request["prompt_token_ids"]), 80) + + @patch("uuid.uuid4", return_value="test-request-id-3") + async def test_continuation_boundary_max_tokens_exhausted(self, mock_uuid): + self._update_processor_token_ids(prompt_token_ids_len=100) + + request = { + "messages": [{"role": "user", "content": "描述这张图片"}], + "completion_token_ids": [103] * 190, + "max_tokens": 200, + "min_tokens": 5, + } + + await self.engine_client.format_and_add_data(request) + + self.assertEqual(request["max_tokens"], 10) + self.assertEqual(request["min_tokens"], 1) + + @patch("uuid.uuid4", return_value="test-request-id-4") + async def test_continuation_boundary_no_capacity(self, mock_uuid): + self._update_processor_token_ids(prompt_token_ids_len=260) + + request = { + "messages": [{"role": "user", "content": "描述这张图片"}], + "completion_token_ids": [103] * 50, + "max_tokens": 200, + "min_tokens": 5, + } + + with self.assertRaises(EngineError) as ctx: + await self.engine_client.format_and_add_data(request) + + self.assertIn("Input text is too long", str(ctx.exception)) + + +if __name__ == "__main__": + unittest.main()