fix: openai chat message dump logic

python/openai/openai_frontend/engine/triton_engine.py

@@ -118,8 +118,7 @@ async def chat(
         self._validate_chat_request(request, metadata)
 
         conversation = [
-            {"role": str(message.role), "content": str(message.content)}
-            for message in request.messages
+            message.model_dump(exclude_none=True) for message in request.messages
         ]
         add_generation_prompt = True
 

python/openai/openai_frontend/schemas/openai.py

@@ -193,6 +193,8 @@ class Detail(Enum):
 
 
 class ImageUrl(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     url: AnyUrl = Field(
         ..., description="Either a URL of the image or the base64 encoded image data."
     )
@@ -203,6 +205,8 @@ class ImageUrl(BaseModel):
 
 
 class ChatCompletionRequestMessageContentPartImage(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     type: Type = Field(..., description="The type of the content part.")
     image_url: ImageUrl
 
@@ -212,6 +216,8 @@ class Type1(Enum):
 
 
 class ChatCompletionRequestMessageContentPartText(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     type: Type1 = Field(..., description="The type of the content part.")
     text: str = Field(..., description="The text content.")
 
@@ -224,6 +230,8 @@ def __str__(self):
 
 
 class ChatCompletionRequestSystemMessage(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     content: str = Field(..., description="The contents of the system message.")
     role: Role = Field(
         ..., description="The role of the messages author, in this case `system`."
@@ -264,6 +272,8 @@ def __str__(self):
 
 
 class ChatCompletionRequestToolMessage(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     role: Role3 = Field(
         ..., description="The role of the messages author, in this case `tool`."
     )
@@ -281,6 +291,8 @@ def __str__(self):
 
 
 class ChatCompletionRequestFunctionMessage(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     role: Role4 = Field(
         ..., description="The role of the messages author, in this case `function`."
     )
@@ -656,6 +668,8 @@ class ChatCompletionRequestMessageContentPart(RootModel):
 
 
 class ChatCompletionRequestUserMessage(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     content: Union[str, List[ChatCompletionRequestMessageContentPart]] = Field(
         ..., description="The contents of the user message.\n"
     )
@@ -768,6 +782,8 @@ class CreateChatCompletionFunctionResponse(BaseModel):
 
 
 class ChatCompletionRequestAssistantMessage(BaseModel):
+    model_config = ConfigDict(use_enum_values=True)
+
     content: Optional[str] = Field(
         None,
         description="The contents of the assistant message. Required unless `tool_calls` or `function_call` is specified.\n",

python/openai/tests/test_chat_completions.py

@@ -86,6 +86,37 @@ def test_chat_completions_system_prompt_only(self, client, model: str):
         assert message["content"].strip()
         assert message["role"] == "assistant"
 
+    def test_chat_completions_user_prompt_str(self, client, model: str):
+        # No system prompt provided
+        messages = [{"role": "user", "content": "What is machine learning?"}]
+
+        response = client.post(
+            "/v1/chat/completions", json={"model": model, "messages": messages}
+        )
+
+        assert response.status_code == 200
+        message = response.json()["choices"][0]["message"]
+        assert message["content"].strip()
+        assert message["role"] == "assistant"
+
+    def test_chat_completions_user_prompt_dict(self, client, model: str):
+        # No system prompt provided
+        messages = [
+            {
+                "role": "user",
+                "content": [{"type": "text", "text": "What is machine learning?"}],
+            }
+        ]
+
+        response = client.post(
+            "/v1/chat/completions", json={"model": model, "messages": messages}
+        )
+
+        assert response.status_code == 200
+        message = response.json()["choices"][0]["message"]
+        assert message["content"].strip()
+        assert message["role"] == "assistant"
+
     @pytest.mark.parametrize(
         "param_key, param_value",
         [