Add minimal vLLM 0.16.1 build repo for BI-V150

vllm/entrypoints/pooling/classify/protocol.py

@@ -0,0 +1,89 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import time
+from typing import TypeAlias
+
+from pydantic import Field
+
+from vllm import PoolingParams
+from vllm.config import ModelConfig
+from vllm.entrypoints.openai.engine.protocol import OpenAIBaseModel, UsageInfo
+from vllm.entrypoints.pooling.base.protocol import (
+    ChatRequestMixin,
+    ClassifyRequestMixin,
+    CompletionRequestMixin,
+    PoolingBasicRequestMixin,
+)
+from vllm.logger import init_logger
+from vllm.renderers import TokenizeParams
+from vllm.utils import random_uuid
+
+logger = init_logger(__name__)
+
+
+class ClassificationCompletionRequest(
+    PoolingBasicRequestMixin, CompletionRequestMixin, ClassifyRequestMixin
+):
+    def build_tok_params(self, model_config: ModelConfig) -> TokenizeParams:
+        encoder_config = model_config.encoder_config or {}
+
+        return TokenizeParams(
+            max_total_tokens=model_config.max_model_len,
+            max_output_tokens=0,
+            truncate_prompt_tokens=self.truncate_prompt_tokens,
+            do_lower_case=encoder_config.get("do_lower_case", False),
+            add_special_tokens=self.add_special_tokens,
+            max_total_tokens_param="max_model_len",
+        )
+
+    def to_pooling_params(self):
+        return PoolingParams(
+            task="classify",
+            truncate_prompt_tokens=self.truncate_prompt_tokens,
+            use_activation=self.use_activation,
+        )
+
+
+class ClassificationChatRequest(
+    PoolingBasicRequestMixin, ChatRequestMixin, ClassifyRequestMixin
+):
+    def build_tok_params(self, model_config: ModelConfig) -> TokenizeParams:
+        encoder_config = model_config.encoder_config or {}
+
+        return TokenizeParams(
+            max_total_tokens=model_config.max_model_len,
+            max_output_tokens=0,
+            truncate_prompt_tokens=self.truncate_prompt_tokens,
+            do_lower_case=encoder_config.get("do_lower_case", False),
+            add_special_tokens=self.add_special_tokens,
+            max_total_tokens_param="max_model_len",
+        )
+
+    def to_pooling_params(self):
+        return PoolingParams(
+            task="classify",
+            truncate_prompt_tokens=self.truncate_prompt_tokens,
+            use_activation=self.use_activation,
+        )
+
+
+ClassificationRequest: TypeAlias = (
+    ClassificationCompletionRequest | ClassificationChatRequest
+)
+
+
+class ClassificationData(OpenAIBaseModel):
+    index: int
+    label: str | None
+    probs: list[float]
+    num_classes: int
+
+
+class ClassificationResponse(OpenAIBaseModel):
+    id: str = Field(default_factory=lambda: f"classify-{random_uuid()}")
+    object: str = "list"
+    created: int = Field(default_factory=lambda: int(time.time()))
+    model: str
+    data: list[ClassificationData]
+    usage: UsageInfo