ref(anthropic): Revert input transformation

Author: alexander-alderman-webb

sentry_sdk/integrations/anthropic.py

@@ -12,7 +12,6 @@
     normalize_message_roles,
     truncate_and_annotate_messages,
     get_start_span_function,
-    transform_anthropic_content_part,
 )
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.integrations import _check_minimum_version, DidNotEnable, Integration
@@ -323,27 +322,6 @@ def _collect_ai_data(
     )
 
 
-def _transform_anthropic_content_block(
-    content_block: "dict[str, Any]",
-) -> "dict[str, Any]":
-    """
-    Transform an Anthropic content block using the Anthropic-specific transformer,
-    with special handling for Anthropic's text-type documents.
-    """
-    # Handle Anthropic's text-type documents specially (not covered by shared function)
-    if content_block.get("type") == "document":
-        source = content_block.get("source")
-        if isinstance(source, dict) and source.get("type") == "text":
-            return {
-                "type": "text",
-                "text": source.get("data", ""),
-            }
-
-    # Use Anthropic-specific transformation
-    result = transform_anthropic_content_part(content_block)
-    return result if result is not None else content_block
-
-
 def _transform_system_instructions(
     system_instructions: "Union[str, Iterable[TextBlockParam]]",
 ) -> "list[TextPart]":
@@ -401,41 +379,19 @@ def _set_common_input_data(
                 and "content" in message
                 and isinstance(message["content"], (list, tuple))
             ):
-                transformed_content = []
                 for item in message["content"]:
-                    # Skip tool_result items - they can contain images/documents
-                    # with nested structures that are difficult to redact properly
-                    if isinstance(item, dict) and item.get("type") == "tool_result":
-                        continue
-
-                    # Transform content blocks (images, documents, etc.)
-                    transformed_content.append(
-                        _transform_anthropic_content_block(item)
-                        if isinstance(item, dict)
-                        else item
-                    )
-
-                # If there are non-tool-result items, add them as a message
-                if transformed_content:
-                    normalized_messages.append(
-                        {
-                            "role": message.get("role"),
-                            "content": transformed_content,
-                        }
-                    )
+                    if item.get("type") == "tool_result":
+                        normalized_messages.append(
+                            {
+                                "role": GEN_AI_ALLOWED_MESSAGE_ROLES.TOOL,
+                                "content": {  # type: ignore[dict-item]
+                                    "tool_use_id": item.get("tool_use_id"),
+                                    "output": item.get("content"),
+                                },
+                            }
+                        )
             else:
-                # Transform content for non-list messages or assistant messages
-                transformed_message = message.copy()
-                if "content" in transformed_message:
-                    content = transformed_message["content"]
-                    if isinstance(content, (list, tuple)):
-                        transformed_message["content"] = [
-                            _transform_anthropic_content_block(item)
-                            if isinstance(item, dict)
-                            else item
-                            for item in content
-                        ]
-                normalized_messages.append(transformed_message)
+                normalized_messages.append(message)
 
         role_normalized_messages = normalize_message_roles(normalized_messages)
         scope = sentry_sdk.get_current_scope()