refac

backend/open_webui/utils/response.py

@@ -66,6 +66,8 @@ USAGE_COST_KEYS = {
     'completion_cost',
 }
 
+USAGE_SUMMABLE_KEYS = USAGE_TOKEN_KEYS | USAGE_COST_KEYS
+
 USAGE_DETAIL_KEYS = {
     'prompt_tokens_details',
     'completion_tokens_details',
@@ -115,7 +117,7 @@ def merge_usage(current: dict | None, incoming: dict | None) -> dict:
 
     result = {**current_usage, **incoming_usage}
 
-    for key in USAGE_TOKEN_KEYS | USAGE_COST_KEYS:
+    for key in USAGE_SUMMABLE_KEYS:
         if key in current_usage or key in incoming_usage:
             current_value = current_usage.get(key, 0)
             incoming_value = incoming_usage.get(key, 0)
@@ -238,9 +240,10 @@ async def convert_streaming_response_ollama_to_openai(ollama_streaming_response)
         data = json.loads(data)
 
         model = data.get('model', 'ollama')
-        message_content = data.get('message', {}).get('content', None)
-        reasoning_content = data.get('message', {}).get('thinking', None)
-        tool_calls = data.get('message', {}).get('tool_calls', None)
+        message = data.get('message') or {}
+        message_content = message.get('content', None)
+        reasoning_content = message.get('thinking', None)
+        tool_calls = message.get('tool_calls', None)
         openai_tool_calls = None
 
         if tool_calls:
@@ -253,8 +256,9 @@ async def convert_streaming_response_ollama_to_openai(ollama_streaming_response)
         if done:
             usage = convert_ollama_usage_to_openai(data)
 
-        data = openai_chat_chunk_message_template(model, message_content, reasoning_content, openai_tool_calls, usage)
-        data['id'] = completion_id
+        data = openai_chat_chunk_message_template(
+            model, message_content, reasoning_content, openai_tool_calls, usage, message_id=completion_id
+        )
 
         # First chunk must carry delta.role (OpenAI spec).
         if first: