fix(models): propagate Anthropic finish reasons

Author: MukundaKatta

src/google/adk/models/anthropic_llm.py

@@ -134,10 +134,14 @@ def to_google_genai_finish_reason(
     anthropic_stop_reason: Optional[str],
 ) -> types.FinishReason:
   if anthropic_stop_reason in ["end_turn", "stop_sequence", "tool_use"]:
-    return "STOP"
+    return types.FinishReason.STOP
+  if anthropic_stop_reason == "pause_turn":
+    return types.FinishReason.STOP
   if anthropic_stop_reason == "max_tokens":
-    return "MAX_TOKENS"
-  return "FINISH_REASON_UNSPECIFIED"
+    return types.FinishReason.MAX_TOKENS
+  if anthropic_stop_reason == "refusal":
+    return types.FinishReason.SAFETY
+  return types.FinishReason.FINISH_REASON_UNSPECIFIED
 
 
 def _is_image_part(part: types.Part) -> bool:
@@ -343,8 +347,7 @@ def message_to_generate_content_response(
               message.usage.input_tokens + message.usage.output_tokens
           ),
       ),
-      # TODO: Deal with these later.
-      # finish_reason=to_google_genai_finish_reason(message.stop_reason),
+      finish_reason=to_google_genai_finish_reason(message.stop_reason),
   )
 
 
@@ -547,6 +550,7 @@ async def _generate_content_streaming(
     redacted_thinking_blocks: dict[int, str] = {}
     input_tokens = 0
     output_tokens = 0
+    finish_reason: types.FinishReason | None = None
 
     async for event in raw_stream:
       if event.type == "message_start":
@@ -603,6 +607,7 @@ async def _generate_content_streaming(
 
       elif event.type == "message_delta":
         output_tokens = event.usage.output_tokens
+        finish_reason = to_google_genai_finish_reason(event.delta.stop_reason)
 
     # Build the final aggregated response with all content.
     all_parts: list[types.Part] = []
@@ -644,6 +649,7 @@ async def _generate_content_streaming(
             candidates_token_count=output_tokens,
             total_token_count=input_tokens + output_tokens,
         ),
+        finish_reason=finish_reason,
         partial=False,
     )
 

tests/unittests/models/test_anthropic_llm.py

@@ -28,6 +28,7 @@
 from google.adk.models.anthropic_llm import content_to_message_param
 from google.adk.models.anthropic_llm import function_declaration_to_tool_param
 from google.adk.models.anthropic_llm import part_to_message_block
+from google.adk.models.anthropic_llm import to_google_genai_finish_reason
 from google.adk.models.llm_request import LlmRequest
 from google.adk.models.llm_response import LlmResponse
 from google.genai import types
@@ -139,6 +140,23 @@ def test_supported_models():
   assert models[1] == r"claude-.*-4.*"
 
 
+@pytest.mark.parametrize(
+    ("stop_reason", "expected"),
+    [
+        ("end_turn", types.FinishReason.STOP),
+        ("stop_sequence", types.FinishReason.STOP),
+        ("tool_use", types.FinishReason.STOP),
+        ("pause_turn", types.FinishReason.STOP),
+        ("max_tokens", types.FinishReason.MAX_TOKENS),
+        ("refusal", types.FinishReason.SAFETY),
+        (None, types.FinishReason.FINISH_REASON_UNSPECIFIED),
+        ("unknown_reason", types.FinishReason.FINISH_REASON_UNSPECIFIED),
+    ],
+)
+def test_to_google_genai_finish_reason(stop_reason, expected):
+  assert to_google_genai_finish_reason(stop_reason) == expected
+
+
 function_declaration_test_cases = [
     (
         "function_with_no_parameters",
@@ -1350,6 +1368,54 @@ async def test_non_streaming_does_not_pass_stream_param():
   mock_client.messages.create.assert_called_once()
   _, kwargs = mock_client.messages.create.call_args
   assert "stream" not in kwargs
+  assert responses[0].finish_reason == types.FinishReason.STOP
+
+
+@pytest.mark.asyncio
+async def test_streaming_sets_finish_reason_from_message_delta():
+  llm = AnthropicLlm(model="claude-sonnet-4-20250514")
+
+  events = [
+      MagicMock(
+          type="message_start",
+          message=MagicMock(usage=MagicMock(input_tokens=5, output_tokens=0)),
+      ),
+      MagicMock(
+          type="content_block_start",
+          index=0,
+          content_block=anthropic_types.TextBlock(text="", type="text"),
+      ),
+      MagicMock(
+          type="content_block_delta",
+          index=0,
+          delta=anthropic_types.TextDelta(text="Hello", type="text_delta"),
+      ),
+      MagicMock(type="content_block_stop", index=0),
+      MagicMock(
+          type="message_delta",
+          delta=MagicMock(stop_reason="max_tokens"),
+          usage=MagicMock(output_tokens=3),
+      ),
+      MagicMock(type="message_stop"),
+  ]
+
+  mock_client = MagicMock()
+  mock_client.messages.create = AsyncMock(
+      return_value=_make_mock_stream_events(events)
+  )
+
+  llm_request = LlmRequest(
+      model="claude-sonnet-4-20250514",
+      contents=[Content(role="user", parts=[Part.from_text(text="Hi")])],
+      config=types.GenerateContentConfig(system_instruction="Test"),
+  )
+
+  with mock.patch.object(llm, "_anthropic_client", mock_client):
+    responses = [
+        r async for r in llm.generate_content_async(llm_request, stream=True)
+    ]
+
+  assert responses[-1].finish_reason == types.FinishReason.MAX_TOKENS
 
 
 def test_part_to_message_block_function_call_preserves_valid_id():