diff --git a/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py b/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py
index 302005922c..8b3ce0c448 100644
--- a/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py
+++ b/api/core/ops/arize_phoenix_trace/arize_phoenix_trace.py
@@ -3,7 +3,7 @@ import json
 import logging
 import os
 from datetime import datetime, timedelta
-from typing import Optional, Union, cast
+from typing import Any, Optional, Union, cast
 
 from openinference.semconv.trace import OpenInferenceSpanKindValues, SpanAttributes
 from opentelemetry import trace
@@ -238,7 +238,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
 
                 try:
                     if node_execution.node_type == "llm":
-                        llm_attributes = {
+                        llm_attributes: dict[str, Any] = {
                             SpanAttributes.INPUT_VALUE: json.dumps(process_data.get("prompts", []), ensure_ascii=False),
                         }
                         provider = process_data.get("model_provider")
@@ -247,7 +247,9 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
                             llm_attributes[SpanAttributes.LLM_PROVIDER] = provider
                         if model:
                             llm_attributes[SpanAttributes.LLM_MODEL_NAME] = model
-                        outputs = json.loads(node_execution.outputs).get("usage", {}) if "outputs" in node_execution else {}
+                        outputs = (
+                            json.loads(node_execution.outputs).get("usage", {}) if "outputs" in node_execution else {}
+                        )
                         usage_data = (
                             process_data.get("usage", {}) if "usage" in process_data else outputs.get("usage", {})
                         )
@@ -705,7 +707,7 @@ class ArizePhoenixDataTrace(BaseTraceInstance):
         )
         return workflow_nodes
 
-    def _construct_llm_attributes(self, prompts: dict | list | str) -> dict:
+    def _construct_llm_attributes(self, prompts: dict | list | str | None) -> dict[str, str]:
         """Helper method to construct LLM attributes with passed prompts."""
         attributes = {}
         if isinstance(prompts, list):