[Feature] Online Chat API Support Return logprobs (#2777)

* online chat support logprobs

* check xpu

* check vl_gpu_model_runner and xpu_model_runner

* get_worker() check platform

fastdeploy/entrypoints/openai/protocol.py

@@ -122,6 +122,7 @@ class ChatCompletionResponseChoice(BaseModel):
     """
     index: int
     message: ChatMessage
+    logprobs: Optional[LogProbs] = None
     finish_reason: Optional[Literal["stop", "length", "tool_calls", "recover_stop"]]
 
 
@@ -136,6 +137,21 @@ class ChatCompletionResponse(BaseModel):
     choices: List[ChatCompletionResponseChoice]
     usage: UsageInfo
 
+class LogProbEntry(BaseModel):
+    """
+    Log probability entry.
+    """
+    token: str
+    logprob: float
+    bytes: Optional[List[int]] = None
+    top_logprobs: Optional[List["LogProbEntry"]] = None
+
+class LogProbs(BaseModel):
+    """
+    LogProbs.
+    """
+    content: Optional[List[LogProbEntry]] = None
+    refusal: Optional[Union[str, None]] = None
 
 class DeltaMessage(BaseModel):
     """
@@ -154,6 +170,7 @@ class ChatCompletionResponseStreamChoice(BaseModel):
     """
     index: int
     delta: DeltaMessage
+    logprobs: Optional[LogProbs] = None
     finish_reason: Optional[Literal["stop", "length", "tool_calls"]] = None
     arrival_time: Optional[float] = None
 
@@ -392,6 +409,8 @@ class ChatCompletionRequest(BaseModel):
     tools: Optional[List[ChatCompletionToolsParam]] = None
     model: Optional[str] = "default"
     frequency_penalty: Optional[float] = None
+    logprobs: Optional[bool] = False
+    top_logprobs: Optional[int] = 0
     # remove max_tokens when field is removed from OpenAI API
     max_tokens: Optional[int] = Field(
         default=None,
@@ -434,6 +453,9 @@ class ChatCompletionRequest(BaseModel):
         if request_id is not None:
             req_dict['request_id'] = request_id
 
+        req_dict["max_tokens"] = self.max_completion_tokens or self.max_tokens
+        req_dict["logprobs"] = self.top_logprobs if self.logprobs else None
+
         if self.metadata is not None:
             for key, value in self.metadata.items():
                 req_dict[key] = value
@@ -505,3 +527,18 @@ class ChatCompletionRequest(BaseModel):
             )
 
         return data
+
+    @model_validator(mode="before")
+    @classmethod
+    def check_logprobs(cls, data):
+
+        if (top_logprobs := data.get("top_logprobs")) is not None:
+            if top_logprobs < 0:
+                raise ValueError("`top_logprobs` must be a positive value.")
+
+            if top_logprobs > 0 and not data.get("logprobs"):
+                raise ValueError(
+                    "when using `top_logprobs`, `logprobs` must be set to true."
+                )
+
+        return data