fix: LLMResultChunk cause concatenate str and list exception (#18852)

api/core/model_runtime/model_providers/__base/large_language_model.py

 import time
 import uuid
 from collections.abc import Generator, Sequence
-from typing import Optional, Union
+from typing import Optional, Union, cast
 
 from pydantic import ConfigDict
 
     PriceType,
 )
 from core.model_runtime.model_providers.__base.ai_model import AIModel
+from core.model_runtime.utils.helper import convert_llm_result_chunk_to_str
 from core.plugin.manager.model import PluginModelManager
 
 logger = logging.getLogger(__name__)
                     callbacks=callbacks,
                 )
 
-                assistant_message.content += chunk.delta.message.content
+                text = convert_llm_result_chunk_to_str(chunk.delta.message.content)
+                current_content = cast(str, assistant_message.content)
+                assistant_message.content = current_content + text
                 real_model = chunk.model
                 if chunk.delta.usage:
                     usage = chunk.delta.usage

api/core/model_runtime/utils/helper.py

 import pydantic
 from pydantic import BaseModel
 
+from core.model_runtime.entities.message_entities import PromptMessageContentUnionTypes
+
 
 def dump_model(model: BaseModel) -> dict:
     if hasattr(pydantic, "model_dump"):
         return pydantic.model_dump(model)  # type: ignore
     else:
         return model.model_dump()
+
+
+def convert_llm_result_chunk_to_str(content: None | str | list[PromptMessageContentUnionTypes]) -> str:
+    if content is None:
+        message_text = ""
+    elif isinstance(content, str):
+        message_text = content
+    elif isinstance(content, list):
+        # Assuming the list contains PromptMessageContent objects with a "data" attribute
+        message_text = "".join(
+            item.data if hasattr(item, "data") and isinstance(item.data, str) else str(item) for item in content
+        )
+    else:
+        message_text = str(content)
+    return message_text

api/core/workflow/nodes/llm/node.py

 )
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
+from core.model_runtime.utils.helper import convert_llm_result_chunk_to_str
 from core.plugin.entities.plugin import ModelProviderID
 from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 
     def _handle_invoke_result(self, invoke_result: LLMResult | Generator) -> Generator[NodeEvent, None, None]:
         if isinstance(invoke_result, LLMResult):
-            content = invoke_result.message.content
-            if content is None:
-                message_text = ""
-            elif isinstance(content, str):
-                message_text = content
-            elif isinstance(content, list):
-                # Assuming the list contains PromptMessageContent objects with a "data" attribute
-                message_text = "".join(
-                    item.data if hasattr(item, "data") and isinstance(item.data, str) else str(item) for item in content
-                )
-            else:
-                message_text = str(content)
+            message_text = convert_llm_result_chunk_to_str(invoke_result.message.content)
 
             yield ModelInvokeCompletedEvent(
                 text=message_text,
         usage = None
         finish_reason = None
         for result in invoke_result:
-            text = result.delta.message.content
+            text = convert_llm_result_chunk_to_str(result.delta.message.content)
             full_text += text
 
             yield RunStreamChunkEvent(chunk_content=text, from_variable_selector=[self.node_id, "text"])