[Misc] IO Processor plugins for pooling models (#22820)

Signed-off-by: Christian Pinto <christian.pinto@ibm.com>
Signed-off-by: Max de Bayser <mbayser@br.ibm.com>
Co-authored-by: Max de Bayser <mbayser@br.ibm.com>

vllm/entrypoints/openai/protocol.py

@@ -6,7 +6,8 @@
 import json
 import time
 from http import HTTPStatus
-from typing import Annotated, Any, ClassVar, Literal, Optional, Union
+from typing import (Annotated, Any, ClassVar, Generic, Literal, Optional,
+                    TypeVar, Union)
 
 import regex as re
 import torch
@@ -1405,7 +1406,46 @@ EmbeddingRequest = Union[EmbeddingCompletionRequest, EmbeddingChatRequest]
 
 PoolingCompletionRequest = EmbeddingCompletionRequest
 PoolingChatRequest = EmbeddingChatRequest
-PoolingRequest = Union[PoolingCompletionRequest, PoolingChatRequest]
+
+T = TypeVar("T")
+
+
+class IOProcessorRequest(OpenAIBaseModel, Generic[T]):
+    model: Optional[str] = None
+
+    priority: int = Field(default=0)
+    """
+    The priority of the request (lower means earlier handling;
+    default: 0). Any priority other than 0 will raise an error
+    if the served model does not use priority scheduling.
+    """
+    data: T
+    """
+    When using plugins IOProcessor plugins, the actual input is processed
+    by the plugin itself. Hence, we use a generic type for the request data
+    """
+
+    def to_pooling_params(self):
+        return PoolingParams(task="encode")
+
+
+class IOProcessorResponse(OpenAIBaseModel, Generic[T]):
+
+    request_id: Optional[str] = None
+    """
+    The request_id associated with this response
+    """
+    created_at: int = Field(default_factory=lambda: int(time.time()))
+
+    data: T
+    """
+    When using plugins IOProcessor plugins, the actual output is generated
+    by the plugin itself. Hence, we use a generic type for the response data
+    """
+
+
+PoolingRequest = Union[PoolingCompletionRequest, PoolingChatRequest,
+                       IOProcessorRequest]
 
 
 class ScoreRequest(OpenAIBaseModel):