init

entrypoints/logger.py

@@ -0,0 +1,50 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from typing import Optional, Union
+
+import torch
+
+from vllm.logger import init_logger
+from vllm.lora.request import LoRARequest
+from vllm.pooling_params import PoolingParams
+from vllm.prompt_adapter.request import PromptAdapterRequest
+from vllm.sampling_params import BeamSearchParams, SamplingParams
+
+logger = init_logger(__name__)
+
+
+class RequestLogger:
+
+    def __init__(self, *, max_log_len: Optional[int]) -> None:
+        super().__init__()
+
+        self.max_log_len = max_log_len
+
+    def log_inputs(
+        self,
+        request_id: str,
+        prompt: Optional[str],
+        prompt_token_ids: Optional[list[int]],
+        prompt_embeds: Optional[torch.Tensor],
+        params: Optional[Union[SamplingParams, PoolingParams,
+                               BeamSearchParams]],
+        lora_request: Optional[LoRARequest],
+        prompt_adapter_request: Optional[PromptAdapterRequest],
+    ) -> None:
+        max_log_len = self.max_log_len
+        if max_log_len is not None:
+            if prompt is not None:
+                prompt = prompt[:max_log_len]
+
+            if prompt_token_ids is not None:
+                prompt_token_ids = prompt_token_ids[:max_log_len]
+
+        logger.info(
+            "Received request %s: prompt: %r, "
+            "params: %s, prompt_token_ids: %s, "
+            "prompt_embeds shape: %s, "
+            "lora_request: %s, prompt_adapter_request: %s.", request_id,
+            prompt, params, prompt_token_ids,
+            prompt_embeds.shape if prompt_embeds is not None else None,
+            lora_request, prompt_adapter_request)