Fimeg/letta-server
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

fix(core): handle None message_ids in context window calculator (#9330)

Browse Source 
* fix(core): always create system message even with _init_with_no_messages

When _init_with_no_messages=True (used by agent import flows), the agent
was created with message_ids=None. If subsequent message initialization
failed, this left orphaned agents that crash when context window is
calculated (TypeError on message_ids[1:]).

Now the system message is always generated and persisted, even when
skipping the rest of the initial message sequence. This ensures every
agent has at least message_ids=[system_message_id].

Fixes Datadog issue 773a24ea-eeb3-11f0-8f9f-da7ad0900000

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix(core): clean up placeholder messages during import and add test

Delete placeholder system messages after imported messages are
successfully created (not before), so agents retain their safety-net
system message if import fails. Also adds a test verifying that
_init_with_no_messages=True still produces a valid context window.

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix(core): add descriptive error for empty message_ids in get_system_message

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

---------

Co-authored-by: Letta <noreply@letta.com>
This commit is contained in:
Kian Jones
2026-02-18 18:40:26 -08:00
committed by Caren Thomas
parent e8d5922ff9
commit e65795b5f1
3 changed files with 59 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files

38
letta/services/agent_manager.py
View File

@@ -24,6 +24,8 @@ from letta.constants import (
INCLUDE_MODEL_KEYWORDS_BASE_TOOL_RULES,
RETRIEVAL_QUERY_DEFAULT_PAGE_SIZE,
)
from letta.errors import LettaAgentNotFoundError, LettaError, LettaInvalidArgumentError
from letta.helpers import ToolRulesSolver
from letta.helpers.datetime_helpers import get_utc_time
from letta.log import get_logger
@@ -598,24 +600,30 @@ class AgentManager:
result.tool_exec_environment_variables = env_vars
result.secrets = env_vars
# initial message sequence (skip if _init_with_no_messages is True)
# initial message sequence (skip non-system messages if _init_with_no_messages is True)
if not _init_with_no_messages:
init_messages = await self._generate_initial_message_sequence_async(
actor,
agent_state=result,
supplied_initial_message_sequence=agent_create.initial_message_sequence,
)
result.message_ids = [msg.id for msg in init_messages]
new_agent.message_ids = [msg.id for msg in init_messages]
await new_agent.update_async(session, no_refresh=True)
else:
init_messages = []
all_messages = await initialize_message_sequence_async(
agent_state=result, memory_edit_timestamp=get_utc_time(), include_initial_boot_message=True
)
init_messages = [
PydanticMessage.dict_to_message(
agent_id=result.id, model=result.llm_config.model, openai_message_dict=all_messages[0]
)
]
# Only create messages if we initialized with messages
if not _init_with_no_messages:
await self.message_manager.create_many_messages_async(
pydantic_msgs=init_messages, actor=actor, project_id=result.project_id, template_id=result.template_id
)
result.message_ids = [msg.id for msg in init_messages]
new_agent.message_ids = [msg.id for msg in init_messages]
await new_agent.update_async(session, no_refresh=True)
await self.message_manager.create_many_messages_async(
pydantic_msgs=init_messages, actor=actor, project_id=result.project_id, template_id=result.template_id
)
# Attach files from sources if this is a template-based creation
# Use the new agent's sources (already copied from template via source_ids)
@@ -1320,6 +1328,11 @@ class AgentManager:
@trace_method
def get_system_message(self, agent_id: str, actor: PydanticUser) -> PydanticMessage:
message_ids = self.get_agent_by_id(agent_id=agent_id, actor=actor).message_ids
if not message_ids:
raise LettaError(
message=f"Agent {agent_id} has no in-context messages. "
"This typically means the agent's system message was not initialized correctly.",
)
return self.message_manager.get_message_by_id(message_id=message_ids[0], actor=actor)
@enforce_types
@@ -1327,6 +1340,11 @@ class AgentManager:
@trace_method
async def get_system_message_async(self, agent_id: str, actor: PydanticUser) -> PydanticMessage:
agent = await self.get_agent_by_id_async(agent_id=agent_id, include_relationships=[], actor=actor)
if not agent.message_ids:
raise LettaError(
message=f"Agent {agent_id} has no in-context messages. "
"This typically means the agent's system message was not initialized correctly.",
)
return await self.message_manager.get_message_by_id_async(message_id=agent.message_ids[0], actor=actor)
# TODO: This is duplicated below

8
letta/services/agent_serialization_manager.py
View File

@@ -755,6 +755,10 @@ class AgentSerializationManager:
agent_db_id = file_to_db_ids[agent_schema.id]
message_file_to_db_ids = {}
# Save placeholder message IDs so we can clean them up after successful import
agent_state = await self.agent_manager.get_agent_by_id_async(agent_db_id, actor)
placeholder_message_ids = list(agent_state.message_ids) if agent_state.message_ids else []
# Create messages for this agent
messages = []
for message_schema in agent_schema.messages:
@@ -780,6 +784,10 @@ class AgentSerializationManager:
# Update agent with the correct message_ids
await self.agent_manager.update_message_ids_async(agent_id=agent_db_id, message_ids=in_context_db_ids, actor=actor)
# Clean up placeholder messages now that import succeeded
for placeholder_id in placeholder_message_ids:
await self.message_manager.delete_message_by_id_async(message_id=placeholder_id, actor=actor)
# 8. Create file-agent relationships (depends on agents and files)
for agent_schema in schema.agents:
if agent_schema.files_agents:

24
tests/test_agent_serialization_v2.py
View File

@@ -1538,7 +1538,29 @@ class TestAgentFileEdgeCases:
imported_agent_id = next(db_id for file_id, db_id in result.id_mappings.items() if file_id == "agent-0")
imported_agent = await server.agent_manager.get_agent_by_id_async(imported_agent_id, other_user)
assert len(imported_agent.message_ids) == 0
assert len(imported_agent.message_ids) == 1
async def test_init_with_no_messages_still_has_system_message(self, server, default_user):
"""Test that _init_with_no_messages=True still creates a system message so context window doesn't crash."""
create_agent_request = CreateAgent(
name="partially_initialized_agent",
system="Test system prompt",
llm_config=LLMConfig.default_config("gpt-4o-mini"),
embedding_config=EmbeddingConfig.default_config(provider="openai"),
initial_message_sequence=[],
)
agent_state = await server.agent_manager.create_agent_async(
agent_create=create_agent_request,
actor=default_user,
_init_with_no_messages=True,
)
assert agent_state.message_ids is not None
assert len(agent_state.message_ids) == 1
context_window = await server.agent_manager.get_context_window(agent_id=agent_state.id, actor=default_user)
assert context_window is not None
async def test_large_agent_file(self, server, agent_serialization_manager, default_user, other_user, weather_tool):
"""Test handling of larger agent files with many messages."""