Add model_name, agent_name, and response_id to RequestUsage for better tracking

docs/usage.md

@@ -54,8 +54,8 @@ The SDK automatically tracks usage for each API request in `request_usage_entrie
 ```python
 result = await Runner.run(agent, "What's the weather in Tokyo?")
 
-for request in enumerate(result.context_wrapper.usage.request_usage_entries):
-    print(f"Request {i + 1}: {request.input_tokens} in, {request.output_tokens} out")
+for i, request in enumerate(result.context_wrapper.usage.request_usage_entries):
+    print(f"Request {i + 1}: Input={request.input_tokens} tokens, Output={request.output_tokens} tokens, metadata={request.metadata}")
 ```
 
 ## Accessing usage with sessions

src/agents/models/interface.py

@@ -36,6 +36,9 @@ def include_data(self) -> bool:
 class Model(abc.ABC):
     """The base interface for calling an LLM."""
 
+    # The model name. Subclasses can set this in __init__.
+    model: str = ""
+
     @abc.abstractmethod
     async def get_response(
         self,

src/agents/run.py

@@ -1402,7 +1402,14 @@ async def _run_single_turn_streamed(
                     usage=usage,
                     response_id=event.response.id,
                 )
-                context_wrapper.usage.add(usage)
+                context_wrapper.usage.add(
+                    usage,
+                    metadata={
+                        "model_name": model.model,
+                        "agent_name": agent.name,
+                        "response_id": event.response.id,
+                    },
+                )
 
             if isinstance(event, ResponseOutputItemDoneEvent):
                 output_item = event.item
@@ -1819,7 +1826,14 @@ async def _get_new_response(
             prompt=prompt_config,
         )
 
-        context_wrapper.usage.add(new_response.usage)
+        context_wrapper.usage.add(
+            new_response.usage,
+            metadata={
+                "model_name": model.model,
+                "agent_name": agent.name,
+                "response_id": new_response.response_id,
+            },
+        )
 
         # If we have run hooks, or if the agent has hooks, we need to call them after the LLM call
         await asyncio.gather(

src/agents/usage.py

@@ -1,4 +1,7 @@
+from __future__ import annotations
+
 from dataclasses import field
+from typing import Any
 
 from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
 from pydantic.dataclasses import dataclass
@@ -23,6 +26,9 @@ class RequestUsage:
     output_tokens_details: OutputTokensDetails
     """Details about the output tokens for this individual request."""
 
+    metadata: dict[str, Any] = field(default_factory=dict)
+    """Additional metadata for this request (e.g., model_name, agent_name, response_id)."""
+
 
 @dataclass
 class Usage:
@@ -70,13 +76,18 @@ def __post_init__(self) -> None:
         if self.output_tokens_details.reasoning_tokens is None:
             self.output_tokens_details = OutputTokensDetails(reasoning_tokens=0)
 
-    def add(self, other: "Usage") -> None:
+    def add(
+        self,
+        other: Usage,
+        metadata: dict[str, Any] | None = None,
+    ) -> None:
         """Add another Usage object to this one, aggregating all fields.
 
         This method automatically preserves request_usage_entries.
 
         Args:
             other: The Usage object to add to this one.
+            metadata: Additional metadata for this request
         """
         self.requests += other.requests if other.requests else 0
         self.input_tokens += other.input_tokens if other.input_tokens else 0
@@ -101,6 +112,7 @@ def add(self, other: "Usage") -> None:
                 total_tokens=other.total_tokens,
                 input_tokens_details=other.input_tokens_details,
                 output_tokens_details=other.output_tokens_details,
+                metadata=metadata or {},
             )
             self.request_usage_entries.append(request_usage)
         elif other.request_usage_entries:

tests/test_usage.py

@@ -21,7 +21,14 @@ def test_usage_add_aggregates_all_fields():
         total_tokens=15,
     )
 
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-1",
+        },
+    )
 
     assert u1.requests == 3
     assert u1.input_tokens == 17
@@ -42,7 +49,14 @@ def test_usage_add_aggregates_with_none_values():
         total_tokens=15,
     )
 
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-1",
+        },
+    )
 
     assert u1.requests == 2
     assert u1.input_tokens == 7
@@ -60,13 +74,21 @@ def test_request_usage_creation():
         total_tokens=300,
         input_tokens_details=InputTokensDetails(cached_tokens=10),
         output_tokens_details=OutputTokensDetails(reasoning_tokens=20),
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-123",
+        },
     )
 
     assert request_usage.input_tokens == 100
     assert request_usage.output_tokens == 200
     assert request_usage.total_tokens == 300
     assert request_usage.input_tokens_details.cached_tokens == 10
     assert request_usage.output_tokens_details.reasoning_tokens == 20
+    assert request_usage.metadata["model_name"] == "gpt-5"
+    assert request_usage.metadata["agent_name"] == "test-agent"
+    assert request_usage.metadata["response_id"] == "resp-123"
 
 
 def test_usage_add_preserves_single_request():
@@ -81,7 +103,14 @@ def test_usage_add_preserves_single_request():
         total_tokens=300,
     )
 
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-1",
+        },
+    )
 
     # Should preserve the request usage details
     assert len(u1.request_usage_entries) == 1
@@ -91,6 +120,9 @@ def test_usage_add_preserves_single_request():
     assert request_usage.total_tokens == 300
     assert request_usage.input_tokens_details.cached_tokens == 10
     assert request_usage.output_tokens_details.reasoning_tokens == 20
+    assert request_usage.metadata["model_name"] == "gpt-5"
+    assert request_usage.metadata["agent_name"] == "test-agent"
+    assert request_usage.metadata["response_id"] == "resp-1"
 
 
 def test_usage_add_ignores_zero_token_requests():
@@ -105,7 +137,14 @@ def test_usage_add_ignores_zero_token_requests():
         total_tokens=0,
     )
 
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-1",
+        },
+    )
 
     # Should not create a request_usage_entry for zero tokens
     assert len(u1.request_usage_entries) == 0
@@ -123,7 +162,14 @@ def test_usage_add_ignores_multi_request_usage():
         total_tokens=300,
     )
 
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-1",
+        },
+    )
 
     # Should not create a request usage entry for multi-request usage
     assert len(u1.request_usage_entries) == 0
@@ -141,7 +187,14 @@ def test_usage_add_merges_existing_request_usage_entries():
         output_tokens_details=OutputTokensDetails(reasoning_tokens=20),
         total_tokens=300,
     )
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "agent-1",
+            "response_id": "resp-1",
+        },
+    )
 
     # Create second usage with request_usage_entries
     u3 = Usage(
@@ -153,7 +206,14 @@ def test_usage_add_merges_existing_request_usage_entries():
         total_tokens=125,
     )
 
-    u1.add(u3)
+    u1.add(
+        u3,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "agent-2",
+            "response_id": "resp-2",
+        },
+    )
 
     # Should have both request_usage_entries
     assert len(u1.request_usage_entries) == 2
@@ -163,12 +223,16 @@ def test_usage_add_merges_existing_request_usage_entries():
     assert first.input_tokens == 100
     assert first.output_tokens == 200
     assert first.total_tokens == 300
+    assert first.metadata["agent_name"] == "agent-1"
+    assert first.metadata["response_id"] == "resp-1"
 
     # Second request
     second = u1.request_usage_entries[1]
     assert second.input_tokens == 50
     assert second.output_tokens == 75
     assert second.total_tokens == 125
+    assert second.metadata["agent_name"] == "agent-2"
+    assert second.metadata["response_id"] == "resp-2"
 
 
 def test_usage_add_with_pre_existing_request_usage_entries():
@@ -184,7 +248,14 @@ def test_usage_add_with_pre_existing_request_usage_entries():
         output_tokens_details=OutputTokensDetails(reasoning_tokens=20),
         total_tokens=300,
     )
-    u1.add(u2)
+    u1.add(
+        u2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "agent-1",
+            "response_id": "resp-1",
+        },
+    )
 
     # Create another usage with request_usage_entries
     u3 = Usage(
@@ -197,7 +268,14 @@ def test_usage_add_with_pre_existing_request_usage_entries():
     )
 
     # Add u3 to u1
-    u1.add(u3)
+    u1.add(
+        u3,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "agent-2",
+            "response_id": "resp-2",
+        },
+    )
 
     # Should have both request_usage_entries
     assert len(u1.request_usage_entries) == 2
@@ -227,7 +305,14 @@ def test_anthropic_cost_calculation_scenario():
         output_tokens_details=OutputTokensDetails(reasoning_tokens=0),
         total_tokens=150_000,
     )
-    usage.add(req1)
+    usage.add(
+        req1,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-1",
+        },
+    )
 
     # Second request: 150K input tokens
     req2 = Usage(
@@ -238,7 +323,14 @@ def test_anthropic_cost_calculation_scenario():
         output_tokens_details=OutputTokensDetails(reasoning_tokens=0),
         total_tokens=225_000,
     )
-    usage.add(req2)
+    usage.add(
+        req2,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-2",
+        },
+    )
 
     # Third request: 80K input tokens
     req3 = Usage(
@@ -249,7 +341,14 @@ def test_anthropic_cost_calculation_scenario():
         output_tokens_details=OutputTokensDetails(reasoning_tokens=0),
         total_tokens=120_000,
     )
-    usage.add(req3)
+    usage.add(
+        req3,
+        metadata={
+            "model_name": "gpt-5",
+            "agent_name": "test-agent",
+            "response_id": "resp-3",
+        },
+    )
 
     # Verify aggregated totals
     assert usage.requests == 3