chore: import upstream snapshot with attribution

python/ray/llm/_internal/common/observability/logging_utils.py

@@ -0,0 +1,48 @@
+"""Utilities for logging."""
+
+import logging
+
+import ray
+
+
+def disable_vllm_custom_ops_logger_on_cpu_nodes():
+    """This disables a log line in the "vllm._custom_ops" logger on CPU nodes.
+
+    vllm._custom_ops is automatically imported when vllm is imported. It checks
+    for CUDA binaries that don't exist in CPU-only nodes. This makes rayllm
+    raise a scary-looking (but harmless) warning when imported on CPU nodes,
+    such as when running the generate_config.py script or running the
+    build-app task.
+    """
+
+    class SkipVLLMWarningFilter(logging.Filter):
+        def filter(self, record: logging.LogRecord):
+            """Only allow CRITICAL logs from the datasets/config.py file."""
+
+            log_fragment = "Failed to import from vllm._C with"
+
+            return log_fragment not in record.getMessage()
+
+    if not ray.is_initialized() or len(ray.get_gpu_ids()) == 0:
+        logging.getLogger("vllm._custom_ops").addFilter(SkipVLLMWarningFilter())
+
+
+def disable_datasets_logger():
+    """This disables "datasets" logs from its "config.py" file.
+
+    Upon import, rayllm imports vllm which calls datasets. The datasets package
+    emits a log from its config.py file.
+
+    The file that emits this log uses the root "datasets" logger, so we use a
+    filter to prevent logs from only the config.py file.
+    """
+
+    class SkipDatasetsConfigLogFilter(logging.Filter):
+        def filter(self, record: logging.LogRecord):
+            """Only allow CRITICAL logs from the datasets/config.py file."""
+            return (
+                record.levelno >= logging.CRITICAL
+                or "datasets/config.py" not in record.pathname
+            )
+
+    logging.getLogger("datasets").addFilter(SkipDatasetsConfigLogFilter())