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fix: remove redundant letta message conversion (#6538)

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cthomas
2025-12-05 22:55:16 -08:00
committed by Caren Thomas
parent 4916d281ce
commit b67347dff2
1 changed files with 4 additions and 11 deletions
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15
letta/agents/letta_agent_v3.py
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@@ -73,7 +73,6 @@ class LettaAgentV3(LettaAgentV2):
def _initialize_state(self):
super()._initialize_state()
self._require_tool_call = False
self.response_messages_for_metadata = [] # Separate accumulator for streaming job metadata
# Approximate token count for the *current* in-context buffer, used
# only for proactive summarization / eviction logic. This is derived
# from per-step usage but can be updated after summarization without
@@ -118,6 +117,7 @@ class LettaAgentV3(LettaAgentV2):
"""
self._initialize_state()
request_span = self._request_checkpoint_start(request_start_timestamp_ns=request_start_timestamp_ns)
response_letta_messages = []
in_context_messages, input_messages_to_persist = await _prepare_in_context_messages_no_persist_async(
input_messages, self.agent_state, self.message_manager, self.actor, run_id
@@ -128,7 +128,6 @@ class LettaAgentV3(LettaAgentV2):
input_messages_to_persist = [input_messages_to_persist[0]]
in_context_messages = in_context_messages + input_messages_to_persist
response_letta_messages = []
for i in range(max_steps):
if i == 1 and follow_up_messages:
input_messages_to_persist = follow_up_messages
@@ -235,6 +234,7 @@ class LettaAgentV3(LettaAgentV2):
"""
self._initialize_state()
request_span = self._request_checkpoint_start(request_start_timestamp_ns=request_start_timestamp_ns)
response_letta_messages = []
first_chunk = True
if stream_tokens:
@@ -273,6 +273,7 @@ class LettaAgentV3(LettaAgentV2):
request_start_timestamp_ns=request_start_timestamp_ns,
)
async for chunk in response:
response_letta_messages.append(chunk)
if first_chunk:
request_span = self._request_checkpoint_ttft(request_span, request_start_timestamp_ns)
yield f"data: {chunk.model_dump_json()}\n\n"
@@ -358,14 +359,7 @@ class LettaAgentV3(LettaAgentV2):
# Cleanup and finalize (only runs if no exception occurred)
try:
if run_id:
letta_messages = Message.to_letta_messages_from_list(
self.response_messages_for_metadata, # Use separate accumulator to preserve all messages
use_assistant_message=False, # NOTE: set to false
reverse=False,
# text_is_assistant_message=(self.agent_state.agent_type == AgentType.react_agent),
text_is_assistant_message=True,
)
result = LettaResponse(messages=letta_messages, stop_reason=self.stop_reason, usage=self.usage)
result = LettaResponse(messages=response_letta_messages, stop_reason=self.stop_reason, usage=self.usage)
if self.job_update_metadata is None:
self.job_update_metadata = {}
self.job_update_metadata["result"] = result.model_dump(mode="json")
@@ -659,7 +653,6 @@ class LettaAgentV3(LettaAgentV2):
new_message_idx = len(input_messages_to_persist) if input_messages_to_persist else 0
self.response_messages.extend(aggregated_persisted[new_message_idx:])
self.response_messages_for_metadata.extend(aggregated_persisted[new_message_idx:]) # Track for job metadata
if llm_adapter.supports_token_streaming():
if tool_calls: