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

chore: migrate server to logger (#5725)

Browse Source 
make server use logger
This commit is contained in:
Kian Jones
2025-10-23 18:35:55 -07:00
committed by Caren Thomas
parent 6e2c002af3
commit 009cd05cce
1 changed files with 6 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
letta/server/server.py
View File

@@ -938,11 +938,10 @@ class SyncServer(object):
async with asyncio.timeout(constants.GET_PROVIDERS_TIMEOUT_SECONDS):
return await provider.list_llm_models_async()
except asyncio.TimeoutError:
warnings.warn(f"Timeout while listing LLM models for provider {provider}")
logger.warning(f"Timeout while listing LLM models for provider {provider}")
return []
except Exception as e:
traceback.print_exc()
warnings.warn(f"Error while listing LLM models for provider {provider}: {e}")
logger.exception(f"Error while listing LLM models for provider {provider}: {e}")
return []
# Execute all provider model listing tasks concurrently
@@ -981,10 +980,7 @@ class SyncServer(object):
# All providers now have list_embedding_models_async
return await provider.list_embedding_models_async()
except Exception as e:
import traceback
traceback.print_exc()
warnings.warn(f"An error occurred while listing embedding models for provider {provider}: {e}")
logger.exception(f"An error occurred while listing embedding models for provider {provider}: {e}")
return []
# Execute all provider model listing tasks concurrently
@@ -1514,7 +1510,7 @@ class SyncServer(object):
# supports_token_streaming = ["openai", "anthropic", "xai", "deepseek"]
supports_token_streaming = ["openai", "anthropic", "deepseek"] # TODO re-enable xAI once streaming is patched
if stream_tokens and (llm_config.model_endpoint_type not in supports_token_streaming):
warnings.warn(
logger.warning(
f"Token streaming is only supported for models with type {' or '.join(supports_token_streaming)} in the model_endpoint: agent has endpoint type {llm_config.model_endpoint_type} and {llm_config.model_endpoint}. Setting stream_tokens to False."
)
stream_tokens = False
@@ -1616,10 +1612,7 @@ class SyncServer(object):
except HTTPException:
raise
except Exception as e:
print(e)
import traceback
traceback.print_exc()
logger.exception(f"Error sending message to agent: {e}")
raise HTTPException(status_code=500, detail=f"{e}")
@trace_method
@@ -1649,7 +1642,7 @@ class SyncServer(object):
llm_config = letta_multi_agent.agent_state.llm_config
supports_token_streaming = ["openai", "anthropic", "deepseek"]
if stream_tokens and (llm_config.model_endpoint_type not in supports_token_streaming):
warnings.warn(
logger.warning(
f"Token streaming is only supported for models with type {' or '.join(supports_token_streaming)} in the model_endpoint: agent has endpoint type {llm_config.model_endpoint_type} and {llm_config.model_endpoint}. Setting stream_tokens to False."
)
stream_tokens = False