fix: add temp hack to gracefully handle parallel tool calling (#2654)

letta/agents/letta_agent.py

@@ -821,6 +821,9 @@ class LettaAgent(BaseAgent):
         """
         tool_call_name = tool_call.function.name
         tool_call_args_str = tool_call.function.arguments
+        # Temp hack to gracefully handle parallel tool calling attempt, only take first one
+        if "}{" in tool_call_args_str:
+            tool_call_args_str = tool_call_args_str.split("}{", 1)[0] + "}"
 
         try:
             tool_args = json.loads(tool_call_args_str)

letta/interfaces/anthropic_streaming_interface.py

@@ -379,7 +379,7 @@ class AnthropicStreamingInterface:
             group: List[Union[ReasoningMessage, HiddenReasoningMessage]], group_type: str
         ) -> Union[TextContent, ReasoningContent, RedactedReasoningContent]:
             if group_type == "reasoning":
-                reasoning_text = "".join(chunk.reasoning for chunk in group)
+                reasoning_text = "".join(chunk.reasoning for chunk in group).strip()
                 is_native = any(chunk.source == "reasoner_model" for chunk in group)
                 signature = next((chunk.signature for chunk in group if chunk.signature is not None), None)
                 if is_native:

letta/interfaces/openai_streaming_interface.py

@@ -32,6 +32,7 @@ class OpenAIStreamingInterface:
         self.function_args_buffer = None
         self.function_id_buffer = None
         self.last_flushed_function_name = None
+        self.last_flushed_function_id = None
 
         # Buffer to hold function arguments until inner thoughts are complete
         self.current_function_arguments = ""
@@ -53,14 +54,14 @@ class OpenAIStreamingInterface:
         self.reasoning_messages = []
 
     def get_reasoning_content(self) -> List[TextContent]:
-        content = "".join(self.reasoning_messages)
+        content = "".join(self.reasoning_messages).strip()
         return [TextContent(text=content)]
 
     def get_tool_call_object(self) -> ToolCall:
         """Useful for agent loop"""
         function_name = self.last_flushed_function_name if self.last_flushed_function_name else self.function_name_buffer
         return ToolCall(
-            id=self.letta_message_id,
+            id=self.last_flushed_function_id,
             function=FunctionCall(arguments=self.current_function_arguments, name=function_name),
         )
 
@@ -184,6 +185,8 @@ class OpenAIStreamingInterface:
 
                                     # Record what the last function name we flushed was
                                     self.last_flushed_function_name = self.function_name_buffer
+                                    if self.last_flushed_function_id is None:
+                                        self.last_flushed_function_id = self.function_id_buffer
                                     # Clear the buffer
                                     self.function_name_buffer = None
                                     self.function_id_buffer = None