feat: Separate out streaming route

examples/swarm/swarm.py

@@ -76,9 +76,9 @@ def run(self, agent_name: str, message: str):
             # print(self.client.get_agent(agent_id).tools)
             # TODO: implement with sending multiple messages
             if len(history) == 0:
-                response = self.client.send_message(agent_id=agent_id, message=message, role="user", include_full_message=True)
+                response = self.client.send_message(agent_id=agent_id, message=message, role="user")
             else:
-                response = self.client.send_messages(agent_id=agent_id, messages=history, include_full_message=True)
+                response = self.client.send_messages(agent_id=agent_id, messages=history)
 
             # update history
             history += response.messages

letta/client/client.py

@@ -154,11 +154,10 @@ def send_message(
         stream: Optional[bool] = False,
         stream_steps: bool = False,
         stream_tokens: bool = False,
-        include_full_message: Optional[bool] = False,
     ) -> LettaResponse:
         raise NotImplementedError
 
-    def user_message(self, agent_id: str, message: str, include_full_message: Optional[bool] = False) -> LettaResponse:
+    def user_message(self, agent_id: str, message: str) -> LettaResponse:
         raise NotImplementedError
 
     def create_human(self, name: str, text: str) -> Human:
@@ -839,7 +838,7 @@ def get_in_context_messages(self, agent_id: str) -> List[Message]:
 
     # agent interactions
 
-    def user_message(self, agent_id: str, message: str, include_full_message: Optional[bool] = False) -> LettaResponse:
+    def user_message(self, agent_id: str, message: str) -> LettaResponse:
         """
         Send a message to an agent as a user
 
@@ -850,7 +849,7 @@ def user_message(self, agent_id: str, message: str, include_full_message: Option
         Returns:
             response (LettaResponse): Response from the agent
         """
-        return self.send_message(agent_id, message, role="user", include_full_message=include_full_message)
+        return self.send_message(agent_id=agent_id, message=message, role="user")
 
     def save(self):
         raise NotImplementedError
@@ -937,13 +936,13 @@ def get_messages(
 
     def send_message(
         self,
-        agent_id: str,
         message: str,
         role: str,
+        agent_id: Optional[str] = None,
         name: Optional[str] = None,
+        stream: Optional[bool] = False,
         stream_steps: bool = False,
         stream_tokens: bool = False,
-        include_full_message: bool = False,
     ) -> Union[LettaResponse, Generator[LettaStreamingResponse, None, None]]:
         """
         Send a message to an agent
@@ -964,17 +963,11 @@ def send_message(
         # TODO: figure out how to handle stream_steps and stream_tokens
 
         # When streaming steps is True, stream_tokens must be False
-        request = LettaRequest(
-            messages=messages,
-            stream_steps=stream_steps,
-            stream_tokens=stream_tokens,
-            return_message_object=include_full_message,
-        )
+        request = LettaRequest(messages=messages)
         if stream_tokens or stream_steps:
             from letta.client.streaming import _sse_post
 
-            request.return_message_object = False
-            return _sse_post(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages", request.model_dump(), self.headers)
+            return _sse_post(f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages/stream", request.model_dump(), self.headers)
         else:
             response = requests.post(
                 f"{self.base_url}/{self.api_prefix}/agents/{agent_id}/messages", json=request.model_dump(), headers=self.headers
@@ -2250,7 +2243,6 @@ def send_messages(
         self,
         agent_id: str,
         messages: List[Union[Message | MessageCreate]],
-        include_full_message: Optional[bool] = False,
     ):
         """
         Send pre-packed messages to an agent.
@@ -2271,12 +2263,9 @@ def send_messages(
 
         # format messages
         messages = self.interface.to_list()
-        if include_full_message:
-            letta_messages = messages
-        else:
-            letta_messages = []
-            for m in messages:
-                letta_messages += m.to_letta_message()
+        letta_messages = []
+        for m in messages:
+            letta_messages += m.to_letta_message()
 
         return LettaResponse(messages=letta_messages, usage=usage)
 
@@ -2289,7 +2278,6 @@ def send_message(
         agent_name: Optional[str] = None,
         stream_steps: bool = False,
         stream_tokens: bool = False,
-        include_full_message: Optional[bool] = False,
     ) -> LettaResponse:
         """
         Send a message to an agent
@@ -2338,16 +2326,13 @@ def send_message(
 
         # format messages
         messages = self.interface.to_list()
-        if include_full_message:
-            letta_messages = messages
-        else:
-            letta_messages = []
-            for m in messages:
-                letta_messages += m.to_letta_message()
+        letta_messages = []
+        for m in messages:
+            letta_messages += m.to_letta_message()
 
         return LettaResponse(messages=letta_messages, usage=usage)
 
-    def user_message(self, agent_id: str, message: str, include_full_message: Optional[bool] = False) -> LettaResponse:
+    def user_message(self, agent_id: str, message: str) -> LettaResponse:
         """
         Send a message to an agent as a user
 
@@ -2359,7 +2344,7 @@ def user_message(self, agent_id: str, message: str, include_full_message: Option
             response (LettaResponse): Response from the agent
         """
         self.interface.clear()
-        return self.send_message(role="user", agent_id=agent_id, message=message, include_full_message=include_full_message)
+        return self.send_message(role="user", agent_id=agent_id, message=message)
 
     def run_command(self, agent_id: str, command: str) -> LettaResponse:
         """
@@ -2951,7 +2936,6 @@ def get_messages(
             after=after,
             limit=limit,
             reverse=True,
-            return_message_object=True,
         )
 
     def list_blocks(self, label: Optional[str] = None, templates_only: Optional[bool] = True) -> List[Block]:

letta/schemas/letta_request.py

@@ -8,33 +8,21 @@
 
 class LettaRequest(BaseModel):
     messages: Union[List[MessageCreate], List[Message]] = Field(..., description="The messages to be sent to the agent.")
-    run_async: bool = Field(default=False, description="Whether to asynchronously send the messages to the agent.")  # TODO: implement
-
-    stream_steps: bool = Field(
-        default=False, description="Flag to determine if the response should be streamed. Set to True for streaming agent steps."
-    )
-    stream_tokens: bool = Field(
-        default=False,
-        description="Flag to determine if individual tokens should be streamed. Set to True for token streaming (requires stream_steps = True).",
-    )
-
-    return_message_object: bool = Field(
-        default=False,
-        description="Set True to return the raw Message object. Set False to return the Message in the format of the Letta API.",
-    )
 
     # Flags to support the use of AssistantMessage message types
 
-    use_assistant_message: bool = Field(
-        default=False,
-        description="[Only applicable if return_message_object is False] If true, returns AssistantMessage objects when the agent calls a designated message tool. If false, return FunctionCallMessage objects for all tool calls.",
-    )
-
-    assistant_message_function_name: str = Field(
+    assistant_message_tool_name: str = Field(
         default=DEFAULT_MESSAGE_TOOL,
-        description="[Only applicable if use_assistant_message is True] The name of the designated message tool.",
+        description="The name of the designated message tool.",
     )
-    assistant_message_function_kwarg: str = Field(
+    assistant_message_tool_kwarg: str = Field(
         default=DEFAULT_MESSAGE_TOOL_KWARG,
-        description="[Only applicable if use_assistant_message is True] The name of the message argument in the designated message tool.",
+        description="The name of the message argument in the designated message tool.",
+    )
+
+
+class LettaStreamingRequest(LettaRequest):
+    stream_tokens: bool = Field(
+        default=False,
+        description="Flag to determine if individual tokens should be streamed. Set to True for token streaming (requires stream_steps = True).",
     )

letta/schemas/message.py

@@ -134,8 +134,8 @@ def to_json(self):
     def to_letta_message(
         self,
         assistant_message: bool = False,
-        assistant_message_function_name: str = DEFAULT_MESSAGE_TOOL,
-        assistant_message_function_kwarg: str = DEFAULT_MESSAGE_TOOL_KWARG,
+        assistant_message_tool_name: str = DEFAULT_MESSAGE_TOOL,
+        assistant_message_tool_kwarg: str = DEFAULT_MESSAGE_TOOL_KWARG,
     ) -> List[LettaMessage]:
         """Convert message object (in DB format) to the style used by the original Letta API"""
 
@@ -156,7 +156,7 @@ def to_letta_message(
                 for tool_call in self.tool_calls:
                     # If we're supporting using assistant message,
                     # then we want to treat certain function calls as a special case
-                    if assistant_message and tool_call.function.name == assistant_message_function_name:
+                    if assistant_message and tool_call.function.name == assistant_message_tool_name:
                         # We need to unpack the actual message contents from the function call
                         try:
                             func_args = json.loads(tool_call.function.arguments)

letta/server/rest_api/interface.py

@@ -271,9 +271,8 @@ def __init__(
         self,
         multi_step=True,
         # Related to if we want to try and pass back the AssistantMessage as a special case function
-        use_assistant_message=False,
-        assistant_message_function_name=DEFAULT_MESSAGE_TOOL,
-        assistant_message_function_kwarg=DEFAULT_MESSAGE_TOOL_KWARG,
+        assistant_message_tool_name=DEFAULT_MESSAGE_TOOL,
+        assistant_message_tool_kwarg=DEFAULT_MESSAGE_TOOL_KWARG,
         # Related to if we expect inner_thoughts to be in the kwargs
         inner_thoughts_in_kwargs=True,
         inner_thoughts_kwarg=INNER_THOUGHTS_KWARG,
@@ -287,7 +286,7 @@ def __init__(
         self.streaming_chat_completion_mode_function_name = None  # NOTE: sadly need to track state during stream
         # If chat completion mode, we need a special stream reader to
         # turn function argument to send_message into a normal text stream
-        self.streaming_chat_completion_json_reader = FunctionArgumentsStreamHandler(json_key=assistant_message_function_kwarg)
+        self.streaming_chat_completion_json_reader = FunctionArgumentsStreamHandler(json_key=assistant_message_tool_kwarg)
 
         self._chunks = deque()
         self._event = asyncio.Event()  # Use an event to notify when chunks are available
@@ -300,9 +299,9 @@ def __init__(
         self.multi_step_gen_indicator = MessageStreamStatus.done_generation
 
         # Support for AssistantMessage
-        self.use_assistant_message = use_assistant_message
-        self.assistant_message_function_name = assistant_message_function_name
-        self.assistant_message_function_kwarg = assistant_message_function_kwarg
+        self.use_assistant_message = False  # TODO: Remove this
+        self.assistant_message_tool_name = assistant_message_tool_name
+        self.assistant_message_tool_kwarg = assistant_message_tool_kwarg
 
         # Support for inner_thoughts_in_kwargs
         self.inner_thoughts_in_kwargs = inner_thoughts_in_kwargs
@@ -455,17 +454,14 @@ def _process_chunk_to_letta_style(
 
                 # If we get a "hit" on the special keyword we're looking for, we want to skip to the next chunk
                 # TODO I don't think this handles the function name in multi-pieces problem. Instead, we should probably reset the streaming_chat_completion_mode_function_name when we make this hit?
-                # if self.streaming_chat_completion_mode_function_name == self.assistant_message_function_name:
-                if tool_call.function.name == self.assistant_message_function_name:
+                # if self.streaming_chat_completion_mode_function_name == self.assistant_message_tool_name:
+                if tool_call.function.name == self.assistant_message_tool_name:
                     self.streaming_chat_completion_json_reader.reset()
                     # early exit to turn into content mode
                     return None
 
                 # if we're in the middle of parsing a send_message, we'll keep processing the JSON chunks
-                if (
-                    tool_call.function.arguments
-                    and self.streaming_chat_completion_mode_function_name == self.assistant_message_function_name
-                ):
+                if tool_call.function.arguments and self.streaming_chat_completion_mode_function_name == self.assistant_message_tool_name:
                     # Strip out any extras tokens
                     cleaned_func_args = self.streaming_chat_completion_json_reader.process_json_chunk(tool_call.function.arguments)
                     # In the case that we just have the prefix of something, no message yet, then we should early exit to move to the next chunk
@@ -500,9 +496,6 @@ def _process_chunk_to_letta_style(
                     )
 
             elif self.inner_thoughts_in_kwargs and tool_call.function:
-                if self.use_assistant_message:
-                    raise NotImplementedError("inner_thoughts_in_kwargs with use_assistant_message not yet supported")
-
                 processed_chunk = None
 
                 if tool_call.function.name:
@@ -909,13 +902,13 @@ def function_message(self, msg: str, msg_obj: Optional[Message] = None):
 
                     if (
                         self.use_assistant_message
-                        and function_call.function.name == self.assistant_message_function_name
-                        and self.assistant_message_function_kwarg in func_args
+                        and function_call.function.name == self.assistant_message_tool_name
+                        and self.assistant_message_tool_kwarg in func_args
                     ):
                         processed_chunk = AssistantMessage(
                             id=msg_obj.id,
                             date=msg_obj.created_at,
-                            assistant_message=func_args[self.assistant_message_function_kwarg],
+                            assistant_message=func_args[self.assistant_message_tool_kwarg],
                         )
                     else:
                         processed_chunk = FunctionCallMessage(

letta/server/rest_api/routers/openai/assistants/threads.py

@@ -161,7 +161,6 @@ def list_messages(
         before=before_uuid,
         order_by="created_at",
         reverse=reverse,
-        return_message_object=True,
     )
     assert isinstance(json_messages, List)
     assert all([isinstance(message, Message) for message in json_messages])

letta/server/rest_api/routers/openai/chat_completions/chat_completions.py

@@ -68,7 +68,6 @@ async def create_chat_completion(
             stream_tokens=True,
             # Turn on ChatCompletion mode (eg remaps send_message to content)
             chat_completion_mode=True,
-            return_message_object=False,
         )
 
     else:
@@ -86,7 +85,6 @@ async def create_chat_completion(
             # Turn streaming OFF
             stream_steps=False,
             stream_tokens=False,
-            return_message_object=False,
         )
         # print(response_messages)