fix(#5818): Force to use string serializer for deepseek function call…

…ing (#5824)

Co-authored-by: Engel Nyst <[email protected]>

openhands/core/message.py

@@ -62,6 +62,8 @@ class Message(BaseModel):
     # - tool execution result (to LLM)
     tool_call_id: str | None = None
     name: str | None = None  # name of the tool
+    # force string serializer
+    force_string_serializer: bool = False
 
     @property
     def contains_image(self) -> bool:
@@ -73,7 +75,9 @@ def serialize_model(self) -> dict:
         # - into a single string: for providers that don't support list of content items (e.g. no vision, no tool calls)
         # - into a list of content items: the new APIs of providers with vision/prompt caching/tool calls
         # NOTE: remove this when litellm or providers support the new API
-        if self.cache_enabled or self.vision_enabled or self.function_calling_enabled:
+        if not self.force_string_serializer and (
+            self.cache_enabled or self.vision_enabled or self.function_calling_enabled
+        ):
             return self._list_serializer()
         # some providers, like HF and Groq/llama, don't support a list here, but a single string
         return self._string_serializer()

openhands/llm/llm.py

@@ -122,6 +122,12 @@ def __init__(
         if self.is_function_calling_active():
             logger.debug('LLM: model supports function calling')
 
+        # Compatibility flag: use string serializer for DeepSeek models
+        # See this issue: https://github.com/All-Hands-AI/OpenHands/issues/5818
+        self._use_string_serializer = False
+        if 'deepseek' in self.config.model:
+            self._use_string_serializer = True
+
         # if using a custom tokenizer, make sure it's loaded and accessible in the format expected by litellm
         if self.config.custom_tokenizer is not None:
             self.tokenizer = create_pretrained_tokenizer(self.config.custom_tokenizer)
@@ -618,6 +624,8 @@ def format_messages_for_llm(self, messages: Message | list[Message]) -> list[dic
             message.cache_enabled = self.is_caching_prompt_active()
             message.vision_enabled = self.vision_is_active()
             message.function_calling_enabled = self.is_function_calling_active()
+            if 'deepseek' in self.config.model:
+                message.force_string_serializer = True
 
         # let pydantic handle the serialization
         return [message.model_dump() for message in messages]