revert langchain changes

Author: alexander-alderman-webb

sentry_sdk/integrations/langchain.py

@@ -15,7 +15,6 @@
     normalize_message_roles,
     set_data_normalized,
     truncate_and_annotate_messages,
-    transform_content_part,
 )
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.integrations import DidNotEnable, Integration
@@ -129,39 +128,6 @@ def _get_ai_system(all_params: "Dict[str, Any]") -> "Optional[str]":
 }
 
 
-def _transform_langchain_content_block(
-    content_block: "Dict[str, Any]",
-) -> "Dict[str, Any]":
-    """
-    Transform a LangChain content block using the shared transform_content_part function.
-
-    Returns the original content block if transformation is not applicable
-    (e.g., for text blocks or unrecognized formats).
-    """
-    result = transform_content_part(content_block)
-    return result if result is not None else content_block
-
-
-def _transform_langchain_message_content(content: "Any") -> "Any":
-    """
-    Transform LangChain message content, handling both string content and
-    list of content blocks.
-    """
-    if isinstance(content, str):
-        return content
-
-    if isinstance(content, (list, tuple)):
-        transformed = []
-        for block in content:
-            if isinstance(block, dict):
-                transformed.append(_transform_langchain_content_block(block))
-            else:
-                transformed.append(block)
-        return transformed
-
-    return content
-
-
 # Contextvar to track agent names in a stack for re-entrant agent support
 _agent_stack: "contextvars.ContextVar[Optional[List[Optional[str]]]]" = (
     contextvars.ContextVar("langchain_agent_stack", default=None)
@@ -313,9 +279,7 @@ def _handle_error(self, run_id: "UUID", error: "Any") -> None:
             del self.span_map[run_id]
 
     def _normalize_langchain_message(self, message: "BaseMessage") -> "Any":
-        # Transform content to handle multimodal data (images, audio, video, files)
-        transformed_content = _transform_langchain_message_content(message.content)
-        parsed = {"role": message.type, "content": transformed_content}
+        parsed = {"role": message.type, "content": message.content}
         parsed.update(message.additional_kwargs)
         return parsed