Allow more flexible assistant and system response (#1256)

python/sglang/srt/openai_api/adapter.py

@@ -844,8 +844,23 @@ def v1_chat_generate_request(
         if not isinstance(request.messages, str):
             # Apply chat template and its stop strings.
             if chat_template_name is None:
+                openai_compatible_messages = []
+                for message in request.messages:
+                    if isinstance(message.content, str):
+                        openai_compatible_messages.append(
+                            {"role": message.role, "content": message.content}
+                        )
+                    else:
+                        content_list = message.dict()["content"]
+                        for content in content_list:
+                            if content["type"] == "text":
+                                openai_compatible_messages.append(
+                                    {"role": message.role, "content": content["text"]}
+                                )
                 prompt_ids = tokenizer_manager.tokenizer.apply_chat_template(
-                    request.messages, tokenize=True, add_generation_prompt=True
+                    openai_compatible_messages,
+                    tokenize=True,
+                    add_generation_prompt=True,
                 )
                 stop = request.stop
                 image_data = None

python/sglang/srt/openai_api/protocol.py

@@ -200,11 +200,6 @@ class CompletionStreamResponse(BaseModel):
     usage: Optional[UsageInfo] = None
 
 
-class ChatCompletionMessageGenericParam(BaseModel):
-    role: Literal["system", "assistant"]
-    content: str
-
-
 class ChatCompletionMessageContentTextPart(BaseModel):
     type: Literal["text"]
     text: str
@@ -225,6 +220,11 @@ ChatCompletionMessageContentPart = Union[
 ]
 
 
+class ChatCompletionMessageGenericParam(BaseModel):
+    role: Literal["system", "assistant"]
+    content: Union[str, List[ChatCompletionMessageContentTextPart]]
+
+
 class ChatCompletionMessageUserParam(BaseModel):
     role: Literal["user"]
     content: Union[str, List[ChatCompletionMessageContentPart]]