chore: import upstream snapshot with attribution

python/samples/02-agents/harness/console/observers/usage_display.py

@@ -0,0 +1,56 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Usage display observer for token usage statistics."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any
+
+from .base import ConsoleObserver
+
+if TYPE_CHECKING:
+    from agent_framework import Agent
+
+    from ..state_driver import IUXStateDriver
+
+
+class UsageDisplayObserver(ConsoleObserver):
+    """Displays token usage as a proportion of the context window.
+
+    Shows current token usage as reported by the API immediately when
+    usage information becomes available (via Content items or the final response).
+    The display shows input/output/total relative to configured budgets.
+    """
+
+    async def on_content(
+        self,
+        ux: IUXStateDriver,
+        content: Any,
+        agent: Agent,
+        session: Any,
+    ) -> None:
+        """Update usage display immediately when usage content arrives.
+
+        Args:
+            ux: The UX state driver for UI updates.
+            content: A content item from the response.
+            agent: The AI agent.
+            session: The agent session.
+        """
+        if getattr(content, "type", None) == "usage":
+            usage_details = getattr(content, "usage_details", None)
+            if isinstance(usage_details, dict):
+                # Pass through to state driver — the runner handles formatting
+                ux.set_usage_text(self._format_from_details(usage_details))
+
+    @staticmethod
+    def _format_from_details(usage: dict) -> str:
+        """Format usage details dict into display text.
+
+        This is a fallback formatter for when usage arrives as Content
+        before the runner's final response processing.
+        """
+        input_tokens = usage.get("input_token_count", 0) or 0
+        output_tokens = usage.get("output_token_count", 0) or 0
+        total_tokens = usage.get("total_token_count", 0) or input_tokens + output_tokens
+        return f"📊 Tokens — input: {input_tokens:,} | output: {output_tokens:,} | total: {total_tokens:,}"