[BugFix] Fix issues related to data retrieval logic, parameter validation, and result serialization in both online and offline interfaces.

fastdeploy/entrypoints/engine_client.py

@@ -418,13 +418,16 @@ def valid_parameters(self, data):
         # logprobs
         logprobs = data.get("logprobs")
         top_logprobs = None
+        is_chat = False
 
-        if isinstance(logprobs, bool) and logprobs:
-            if not self.enable_logprob:
-                err_msg = "Logprobs is disabled, please enable it in startup config."
-                api_server_logger.error(err_msg)
-                raise ParameterError("logprobs", err_msg)
-            top_logprobs = data.get("top_logprobs")
+        if isinstance(logprobs, bool):
+            if logprobs:
+                is_chat = True
+                if not self.enable_logprob:
+                    err_msg = "Logprobs is disabled, please enable it in startup config."
+                    api_server_logger.error(err_msg)
+                    raise ParameterError("logprobs", err_msg)
+                top_logprobs = data.get("top_logprobs")
         elif isinstance(logprobs, int):
             top_logprobs = logprobs
         elif logprobs:
@@ -478,38 +481,40 @@ def valid_parameters(self, data):
                 raise ValueError("prompt_logprobs", err_msg)
 
         # enable_logprob
-        if top_logprobs:
+        if top_logprobs is not None:
             if not self.enable_logprob:
                 err_msg = "Logprobs is disabled, please enable it in startup config."
                 api_server_logger.error(err_msg)
-                raise ParameterError("logprobs", err_msg)
+                raise ParameterError("top_logprobs" if is_chat else "logprobs", err_msg)
 
             if not isinstance(top_logprobs, int):
                 err_type = type(top_logprobs).__name__
-                err_msg = f"Invalid type for 'top_logprobs': expected int but got {err_type}."
+                err_msg = (
+                    f"Invalid type for {'top_logprobs' if is_chat else 'logprobs'}: expected int but got {err_type}."
+                )
+                api_server_logger.error(err_msg)
+                raise ParameterError("top_logprobs" if is_chat else "logprobs", err_msg)
+
+            if top_logprobs > max_logprobs:
+                err_msg = f"Number of {'top_logprobs' if is_chat else 'logprobs'} requested ({top_logprobs}) exceeds maximum allowed value ({max_logprobs})."
                 api_server_logger.error(err_msg)
-                raise ParameterError("top_logprobs", err_msg)
+                raise ValueError("top_logprobs" if is_chat else "logprobs", err_msg)
 
             if not envs.FD_USE_GET_SAVE_OUTPUT_V1:
-                if top_logprobs < 0 or top_logprobs > 20:
-                    err_msg = f"top_logprobs must be between 0 and 20; the current value is {top_logprobs}."
+                if top_logprobs < 0 or top_logprobs > max_logprobs:
+                    err_msg = f"{'top_logprobs' if is_chat else 'logprobs'} must be between 0 and {max_logprobs}; the current value is {top_logprobs}."
                     api_server_logger.error(err_msg)
-                    raise ValueError("top_logprobs", err_msg)
+                    raise ValueError("top_logprobs" if is_chat else "logprobs", err_msg)
             else:
                 if top_logprobs == -1 and self.ori_vocab_size > max_logprobs:
-                    err_msg = f"The requested value of ({self.ori_vocab_size}) for top_logprobs (-1) exceeds the maximum allowed value of ({max_logprobs})"
+                    err_msg = f"The requested value of ({self.ori_vocab_size}) for {'top_logprobs' if is_chat else 'logprobs'} (-1) exceeds the maximum allowed value of ({max_logprobs})"
                     api_server_logger.error(err_msg)
-                    raise ValueError("top_logprobs", err_msg)
+                    raise ValueError("top_logprobs" if is_chat else "logprobs", err_msg)
 
                 if top_logprobs < -1:
-                    err_msg = f"top_logprobs must be a non-negative value or -1; the current value is {top_logprobs}."
-                    api_server_logger.error(err_msg)
-                    raise ValueError("top_logprobs", err_msg)
-
-                if top_logprobs > max_logprobs:
-                    err_msg = f"Number of logprobs requested ({top_logprobs}) exceeds maximum allowed value ({max_logprobs})."
+                    err_msg = f"{'top_logprobs' if is_chat else 'logprobs'} must be a non-negative value or -1; the current value is {top_logprobs}."
                     api_server_logger.error(err_msg)
-                    raise ValueError("top_logprobs", err_msg)
+                    raise ValueError("top_logprobs" if is_chat else "logprobs", err_msg)
 
     def check_health(self, time_interval_threashold=30):
         """

fastdeploy/entrypoints/llm.py

@@ -351,6 +351,10 @@ def _add_request(
 
             if current_sampling_params.logprobs is not None:
                 num_logprobs = current_sampling_params.logprobs
+                if not self.llm_engine.cfg.model_config.enable_logprob:
+                    raise ValueError(
+                        "logprobs is only supported if `enable_logprob` is set to true in startup config."
+                    )
                 if num_logprobs == -1 and ori_vocab_size > max_logprobs:
                     raise ValueError(
                         f"Number of logprobs(-1) requested ({ori_vocab_size}) exceeds maximum allowed value ({max_logprobs})."
@@ -360,6 +364,10 @@ def _add_request(
                         f"Number of logprobs requested ({num_logprobs}) exceeds maximum allowed value ({max_logprobs})."
                     )
             if current_sampling_params.prompt_logprobs is not None:
+                if not self.llm_engine.cfg.model_config.enable_logprob:
+                    raise ValueError(
+                        "prompt_logprobs is only supported if `enable_logprob` is set to true in startup config."
+                    )
                 if self.llm_engine.cfg.cache_config.enable_prefix_caching:
                     raise ValueError("prompt_logprobs is not supported with prefix caching enabled.")
                 if kwargs.get("stream"):
@@ -403,19 +411,18 @@ def _build_sample_logprobs(self, logprobs_lists: LogprobsLists, topk_logprobs: i
                 llm_logger.warning("Empty logprob_token_ids in LogprobsLists")
                 return None
 
-            # exclude sampled token at index 0
-            available_topk = len(logprobs_lists.logprob_token_ids[0]) - 1
+            available_topk = len(logprobs_lists.logprob_token_ids[0])
             effective_topk_logprobs = min(topk_logprobs, available_topk)
 
-            if effective_topk_logprobs <= 0:
+            if effective_topk_logprobs < 0:
                 llm_logger.warning(
                     f"Invalid effective_topk_logprobs={effective_topk_logprobs}, "
                     f"available_topk={available_topk}, topk_logprobs={topk_logprobs}; returning empty result."
                 )
                 return None
 
-            # sliced 1 ~ (1 + effective_topk_logprobs)
-            sliced_logprobs_lists = logprobs_lists.slice_columns(1, 1 + effective_topk_logprobs)
+            # sliced 0 ~ effective_topk_logprobs+1
+            sliced_logprobs_lists = logprobs_lists.slice_columns(0, effective_topk_logprobs + 1)
             result = []
             for token_ids, logprobs in zip(sliced_logprobs_lists.logprob_token_ids, sliced_logprobs_lists.logprobs):
 
@@ -559,7 +566,7 @@ def _run_engine(
                     result = self.llm_engine.data_processor.process_response(result)
 
                     # filter logprobs
-                    if result.outputs.top_logprobs and topk_logprobs:
+                    if result.outputs.top_logprobs is not None and topk_logprobs is not None:
                         if topk_logprobs == -1:
                             topk_logprobs = self.llm_engine.cfg.model_config.ori_vocab_size
                         result.outputs.logprobs = self._build_sample_logprobs(

fastdeploy/entrypoints/openai/protocol.py

@@ -611,7 +611,7 @@ class ChatCompletionRequest(BaseModel):
     model: Optional[str] = "default"
     frequency_penalty: Optional[float] = Field(None, le=2, ge=-2)
     logprobs: Optional[bool] = False
-    top_logprobs: Optional[int] = 0
+    top_logprobs: Optional[int] = None
     prompt_logprobs: Optional[int] = None
     include_draft_logprobs: Optional[bool] = False
 

fastdeploy/worker/output.py

@@ -20,7 +20,8 @@
 import paddle
 
 
-class Logprob(NamedTuple):
+@dataclass
+class Logprob:
     """
     A named tuple containing information about a token's log probability.
     """

tests/entrypoints/openai/test_build_sample_logprobs.py

@@ -56,8 +56,9 @@ def test_build_sample_logprobs_basic(self):
 
         expected = [
             {
-                101: Logprob(logprob=-0.5, rank=1, decoded_token="token_101"),
-                102: Logprob(logprob=-1.0, rank=2, decoded_token="token_102"),
+                100: Logprob(logprob=-0.1, rank=1, decoded_token="token_100"),
+                101: Logprob(logprob=-0.5, rank=2, decoded_token="token_101"),
+                102: Logprob(logprob=-1.0, rank=3, decoded_token="token_102"),
             }
         ]
 
@@ -79,7 +80,7 @@ def test_build_sample_logprobs_invalid_topk(self):
         logprobs_lists = MagicMock(spec=LogprobsLists)
         logprobs_lists.logprob_token_ids = [[100]]
         result = self.llm._build_sample_logprobs(logprobs_lists, topk_logprobs=2)
-        self.assertIsNone(result)
+        self.assertEqual(result, [])
 
     def test_decode_token(self):
         """

tests/entrypoints/openai/test_chatcompletion_request.py

@@ -41,7 +41,7 @@ def test_default_values(self):
         req = ChatCompletionRequest(messages=[1])
         self.assertEqual(req.model, "default")
         self.assertFalse(req.logprobs)
-        self.assertEqual(req.top_logprobs, 0)
+        self.assertIsNone(req.top_logprobs)
         self.assertEqual(req.n, 1)
         self.assertEqual(req.stop, [])
 

tests/entrypoints/test_engine_client.py

@@ -489,8 +489,9 @@ def test_top_logprobs_validation_with_fd_use_get_save_output_v1_disabled(self):
             data = {"logprobs": True, "top_logprobs": 25, "request_id": "test"}
             with self.assertRaises(ValueError) as context:
                 self.engine_client.valid_parameters(data)
-            self.assertIn("top_logprobs must be between 0 and 20", str(context.exception))
-            self.assertIn("current value is 25", str(context.exception))
+            self.assertIn(
+                "Number of top_logprobs requested (25) exceeds maximum allowed value (20)", str(context.exception)
+            )
 
             # Test valid value
             data = {"logprobs": True, "top_logprobs": 10, "request_id": "test"}

tests/entrypoints/test_vllm_run_engine.py

@@ -10,9 +10,10 @@
 
 
 class DummyModelConfig:
-    def __init__(self, max_logprobs=10, ori_vocab_size=50):
+    def __init__(self, max_logprobs=10, ori_vocab_size=50, enable_logprob=True):
         self.max_logprobs = max_logprobs
         self.ori_vocab_size = ori_vocab_size
+        self.enable_logprob = enable_logprob
 
 
 class DummyCacheConfig:

tests/utils/test_clamp_prompt_logprobs.py

@@ -45,32 +45,37 @@ def test_normal_logprobs(self):
         self.assertEqual(result[0][1].logprob, -2.5)
         self.assertEqual(result[0][2].logprob, -1.0)
 
-    def test_negative_inf_logprobs_raises_error(self):
-        """Test that logprobs containing -inf raises AttributeError"""
+    def test_negative_inf_logprobs_gets_clamped(self):
+        """Test that logprobs containing -inf get clamped to -9999.0"""
         logprob_dict = {
             1: Logprob(logprob=float("-inf"), rank=1, decoded_token="hello"),
             2: Logprob(logprob=-1.0, rank=2, decoded_token="world"),
         }
         prompt_logprobs = [logprob_dict]
 
-        # Since Logprob is a NamedTuple, its fields cannot be modified, should raise AttributeError
-        with self.assertRaises(AttributeError) as context:
-            clamp_prompt_logprobs(prompt_logprobs)
+        # Since Logprob is now a dataclass, its fields can be modified
+        result = clamp_prompt_logprobs(prompt_logprobs)
 
-        self.assertIn("can't set attribute", str(context.exception))
+        # The -inf value should be clamped to -9999.0
+        self.assertEqual(result[0][1].logprob, -9999.0)
+        self.assertEqual(result[0][2].logprob, -1.0)  # unchanged
 
-    def test_multiple_negative_inf_raises_error(self):
-        """Test that multiple -inf logprobs values raise AttributeError"""
+    def test_multiple_negative_inf_gets_clamped(self):
+        """Test that multiple -inf logprobs values get clamped to -9999.0"""
         logprob_dict = {
             1: Logprob(logprob=float("-inf"), rank=1, decoded_token="hello"),
             2: Logprob(logprob=float("-inf"), rank=2, decoded_token="world"),
             3: Logprob(logprob=-0.5, rank=3, decoded_token="test"),
         }
         prompt_logprobs = [logprob_dict]
 
-        # Since Logprob is a NamedTuple, its fields cannot be modified, should raise AttributeError
-        with self.assertRaises(AttributeError):
-            clamp_prompt_logprobs(prompt_logprobs)
+        # Since Logprob is now a dataclass, its fields can be modified
+        result = clamp_prompt_logprobs(prompt_logprobs)
+
+        # All -inf values should be clamped to -9999.0
+        self.assertEqual(result[0][1].logprob, -9999.0)
+        self.assertEqual(result[0][2].logprob, -9999.0)
+        self.assertEqual(result[0][3].logprob, -0.5)  # unchanged
 
     def test_none_dict_in_list(self):
         """Test case when list contains None"""
@@ -116,15 +121,15 @@ def test_mixed_values_without_inf(self):
         self.assertEqual(result[0][4].logprob, -1.5)
 
     def test_return_same_object(self):
-        """Test that function returns the same object (in-place modification attempt)"""
+        """Test that function returns the same object (in-place modification)"""
         logprob_dict = {
             1: Logprob(logprob=-2.0, rank=1, decoded_token="hello"),
         }
         prompt_logprobs = [logprob_dict]
 
         result = clamp_prompt_logprobs(prompt_logprobs)
 
-        # Should return the same object (function attempts in-place modification)
+        # Should return the same object (function performs in-place modification)
         self.assertIs(result, prompt_logprobs)
         self.assertIs(result[0], prompt_logprobs[0])