[LLM] support send batch data and aggregate data (#2860)

* [LLM] support send batch data and aggregate data

* [LLM] fix ci bugs

* [LLM] fix ci bugs

* [LLM] fix ci bugs

* [LLM] fix ci bugs

* [LLM] update

fastdeploy/engine/request.py

@@ -20,7 +20,7 @@ import time
 from dataclasses import asdict, dataclass, fields
 from typing import Any, Dict, Optional, Union
 
-import numpy
+import numpy as np
 
 from fastdeploy.engine.sampling_params import SamplingParams
 from fastdeploy.utils import data_processor_logger
@@ -181,7 +181,7 @@ class Request:
                 f"sampling_params={self.sampling_params})")
 
 
-@dataclass
+@dataclass(slots=True)
 class CompletionOutput:
     """The output data of one completion output of a request.
 
@@ -235,7 +235,7 @@ class CompletionOutput:
                 f"reasoning_content={self.reasoning_content!r}")
 
 
-@dataclass
+@dataclass(slots=True)
 class RequestMetrics:
     """Metrics associated with a request.
 
@@ -310,6 +310,10 @@ class RequestOutput:
                                   None if decoder-only.
         num_cached_tokens: The number of tokens with prefix cache hit.
     """
+    __slots__ = (
+        'request_id', 'prompt', 'prompt_token_ids', 'outputs', 
+        'finished', 'metrics', 'num_cached_tokens', 'error_code', 'error_msg'
+    )
 
     def __init__(
         self,
@@ -333,6 +337,12 @@ class RequestOutput:
         self.error_code = error_code
         self.error_msg = error_msg
 
+
+        if prompt_token_ids is None:
+            self.prompt_token_ids = []
+        elif isinstance(self.prompt_token_ids, np.ndarray):
+            self.prompt_token_ids = self.prompt_token_ids.tolist()
+
     def add(self, next_output: "RequestOutput") -> None:
         """Merge RequestOutput into this one"""
 
@@ -365,11 +375,6 @@ class RequestOutput:
 
     def to_dict(self):
         """convert RequestOutput into a serializable dict """
-        if self.prompt_token_ids is None:
-            self.prompt_token_ids = []
-
-        if type(self.prompt_token_ids) is numpy.ndarray:
-            self.prompt_token_ids = self.prompt_token_ids.tolist()
 
         return {
             "request_id": self.request_id,