Merge branch 'webb/anthropic/reasoning' into webb/anthropic/streaming-reasoning

Author: alexander-alderman-webb

sentry_sdk/integrations/anthropic.py

@@ -57,8 +57,6 @@
         MessageDeltaEvent,
         MessageStartEvent,
         MessageStopEvent,
-        TextBlock,
-        ToolUseBlock,
     )
 
     if TYPE_CHECKING:
@@ -101,7 +99,7 @@ class _PatchedRawMessageStream(Stream[Any]):
 
         _model: Optional[ModelParam]
         _usage: "_RecordedUsage"
-        _content_blocks: list[dict[str, str]]
+        _content_blocks: "list[dict[str, Any]]"
         _response_id: Optional[str]
         _finish_reason: Optional[str]
 
@@ -111,7 +109,7 @@ class _PatchedMessageStream(MessageStream):
 
         _model: Optional[ModelParam]
         _usage: "_RecordedUsage"
-        _content_blocks: list[dict[str, str]]
+        _content_blocks: "list[dict[str, Any]]"
         _response_id: Optional[str]
         _finish_reason: Optional[str]
 
@@ -121,7 +119,7 @@ class _PatchedRawAsyncMessageStream(AsyncStream[Any]):
 
         _model: Optional[ModelParam]
         _usage: "_RecordedUsage"
-        _content_blocks: list[dict[str, str]]
+        _content_blocks: "list[dict[str, Any]]"
         _response_id: Optional[str]
         _finish_reason: Optional[str]
 
@@ -131,7 +129,7 @@ class _PatchedAsyncMessageStream(AsyncMessageStream):
 
         _model: Optional[ModelParam]
         _usage: "_RecordedUsage"
-        _content_blocks: list[dict[str, str]]
+        _content_blocks: "list[dict[str, Any]]"
         _response_id: Optional[str]
         _finish_reason: Optional[str]
 
@@ -373,10 +371,10 @@ def _collect_ai_data(
     event: "MessageStreamEvent",
     model: "str | None",
     usage: "_RecordedUsage",
-    content_blocks: "list[dict[str, str]]",
+    content_blocks: "list[dict[str, Any]]",
     response_id: "str | None" = None,
     finish_reason: "str | None" = None,
-) -> "tuple[str | None, _RecordedUsage, list[dict[str, str]], str | None, str | None]":
+) -> "tuple[str | None, _RecordedUsage, list[dict[str, Any]], str | None, str | None]":
     """
     Collect model information, token usage, and collect content blocks from the AI streaming response.
     """
@@ -387,16 +385,16 @@ def _collect_ai_data(
                     event.content_block, ThinkingBlock
                 ):
                     content_blocks.append({"type": "thinking", "thinking": ""})
-                elif isinstance(event.content_block, (TextBlock, ToolUseBlock)):
+                elif event.content_block.type in ("text", "tool_use"):
                     content_blocks.append({"type": "text", "text": ""})
             elif event.type == "content_block_delta" and content_blocks:
                 delta = event.delta
                 if ThinkingDelta is not None and isinstance(delta, ThinkingDelta):
                     content_blocks[-1]["thinking"] += delta.thinking
-                elif hasattr(event.delta, "text"):
-                    content_blocks[-1]["text"] += event.delta.text
-                elif hasattr(event.delta, "partial_json"):
-                    content_blocks[-1]["text"] += event.delta.partial_json
+                elif hasattr(delta, "text"):
+                    content_blocks[-1]["text"] += delta.text
+                elif hasattr(delta, "partial_json"):
+                    content_blocks[-1]["text"] += delta.partial_json
             elif event.type == "content_block_stop":
                 pass
 
@@ -723,7 +721,7 @@ def _set_output_data(
     output_tokens: "int | None",
     cache_read_input_tokens: "int | None",
     cache_write_input_tokens: "int | None",
-    content_blocks: "list[dict[str, str]]",
+    content_blocks: "list[dict[str, Any]]",
     response_id: "str | None" = None,
     finish_reason: "str | None" = None,
 ) -> None:
@@ -754,7 +752,7 @@ def _set_output_data(
             if output["type"] == "text":
                 parts.append({"type": "text", "content": output["text"]})
             elif output["type"] == "thinking":
-                parts.append({"type": "reasoning", "content": output.get("thinking")})
+                parts.append({"type": "reasoning", "content": output["thinking"]})
             elif output["type"] == "tool_use":
                 tool_calls.append(output)
 
@@ -1058,7 +1056,7 @@ def _set_streaming_output_data(
     integration: "AnthropicIntegration",
     model: "Optional[str]",
     usage: "_RecordedUsage",
-    content_blocks: "list[dict[str, str]]",
+    content_blocks: "list[dict[str, Any]]",
     response_id: "Optional[str]",
     finish_reason: "Optional[str]",
 ) -> None: