Store additional usage details from Anthropic

pydantic_ai_slim/pydantic_ai/models/anthropic.py

@@ -409,13 +409,27 @@ def _map_usage(message: AnthropicMessage | RawMessageStreamEvent) -> usage.Usage
     if response_usage is None:
         return usage.Usage()
 
-    request_tokens = getattr(response_usage, 'input_tokens', None)
+    # Store all integer-typed usage values in the details dict
+    response_usage_dict = response_usage.model_dump()
+    details: dict[str, int] = {}
+    for key, value in response_usage_dict.items():
+        if isinstance(value, int):
+            details[key] = value
+
+    # Usage coming from the RawMessageDeltaEvent doesn't have input token data, hence the getattr call
+    # Tokens are only counted once between input_tokens, cache_creation_input_tokens, and cache_read_input_tokens
+    # This approach maintains request_tokens as the count of all input tokens, with cached counts as details
+    request_tokens = (
+        getattr(response_usage, 'input_tokens', 0)
+        + (getattr(response_usage, 'cache_creation_input_tokens', 0) or 0)  # These can be missing, None, or int
+        + (getattr(response_usage, 'cache_read_input_tokens', 0) or 0)
+    )
 
     return usage.Usage(
-        # Usage coming from the RawMessageDeltaEvent doesn't have input token data, hence this getattr
-        request_tokens=request_tokens,
+        request_tokens=request_tokens or None,
         response_tokens=response_usage.output_tokens,
-        total_tokens=(request_tokens or 0) + response_usage.output_tokens,
+        total_tokens=request_tokens + response_usage.output_tokens,
+        details=details or None,
     )
 
 

tests/models/test_anthropic.py

@@ -141,14 +141,29 @@ async def test_sync_request_text_response(allow_model_requests: None):
 
     result = await agent.run('hello')
     assert result.output == 'world'
-    assert result.usage() == snapshot(Usage(requests=1, request_tokens=5, response_tokens=10, total_tokens=15))
-
+    assert result.usage() == snapshot(
+        Usage(
+            requests=1,
+            request_tokens=5,
+            response_tokens=10,
+            total_tokens=15,
+            details={'input_tokens': 5, 'output_tokens': 10},
+        )
+    )
     # reset the index so we get the same response again
     mock_client.index = 0  # type: ignore
 
     result = await agent.run('hello', message_history=result.new_messages())
     assert result.output == 'world'
-    assert result.usage() == snapshot(Usage(requests=1, request_tokens=5, response_tokens=10, total_tokens=15))
+    assert result.usage() == snapshot(
+        Usage(
+            requests=1,
+            request_tokens=5,
+            response_tokens=10,
+            total_tokens=15,
+            details={'input_tokens': 5, 'output_tokens': 10},
+        )
+    )
     assert result.all_messages() == snapshot(
         [
             ModelRequest(parts=[UserPromptPart(content='hello', timestamp=IsNow(tz=timezone.utc))]),
@@ -167,6 +182,38 @@ async def test_sync_request_text_response(allow_model_requests: None):
     )
 
 
+async def test_async_request_prompt_caching(allow_model_requests: None):
+    c = completion_message(
+        [TextBlock(text='world', type='text')],
+        usage=AnthropicUsage(
+            input_tokens=3,
+            output_tokens=5,
+            cache_creation_input_tokens=4,
+            cache_read_input_tokens=6,
+        ),
+    )
+    mock_client = MockAnthropic.create_mock(c)
+    m = AnthropicModel('claude-3-5-haiku-latest', provider=AnthropicProvider(anthropic_client=mock_client))
+    agent = Agent(m)
+
+    result = await agent.run('hello')
+    assert result.output == 'world'
+    assert result.usage() == snapshot(
+        Usage(
+            requests=1,
+            request_tokens=13,
+            response_tokens=5,
+            total_tokens=18,
+            details={
+                'input_tokens': 3,
+                'output_tokens': 5,
+                'cache_creation_input_tokens': 4,
+                'cache_read_input_tokens': 6,
+            },
+        )
+    )
+
+
 async def test_async_request_text_response(allow_model_requests: None):
     c = completion_message(
         [TextBlock(text='world', type='text')],
@@ -178,7 +225,15 @@ async def test_async_request_text_response(allow_model_requests: None):
 
     result = await agent.run('hello')
     assert result.output == 'world'
-    assert result.usage() == snapshot(Usage(requests=1, request_tokens=3, response_tokens=5, total_tokens=8))
+    assert result.usage() == snapshot(
+        Usage(
+            requests=1,
+            request_tokens=3,
+            response_tokens=5,
+            total_tokens=8,
+            details={'input_tokens': 3, 'output_tokens': 5},
+        )
+    )
 
 
 async def test_request_structured_response(allow_model_requests: None):
@@ -551,7 +606,15 @@ async def my_tool(first: str, second: str) -> int:
             ]
         )
         assert result.is_complete
-        assert result.usage() == snapshot(Usage(requests=2, request_tokens=20, response_tokens=5, total_tokens=25))
+        assert result.usage() == snapshot(
+            Usage(
+                requests=2,
+                request_tokens=20,
+                response_tokens=5,
+                total_tokens=25,
+                details={'input_tokens': 20, 'output_tokens': 5},
+            )
+        )
         assert tool_called