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Add LLM client compaction errors to traces (#9474)

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* add llm client errors to traces

* update response json for telemetry

* prevent silent failures and properly log errored responses in streaming path

* remove double logging

---------

Co-authored-by: Amy Guan <amy@letta.com>
Co-authored-by: Kian Jones <kian@letta.com>
This commit is contained in:
amysguan
2026-02-13 15:44:09 -08:00
committed by Caren Thomas
parent 2f76f2c629
commit 80a0d1a95f
2 changed files with 31 additions and 19 deletions
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6
letta/llm_api/llm_client_base.py
View File

@@ -161,7 +161,11 @@ class LLMClientBase:
return
if response_json is None:
return
if error_msg:
response_json = {"error": error_msg, "error_type": error_type}
else:
logger.warning(f"Skipping telemetry: no response_json or error_msg (call_type={self._telemetry_call_type})")
return
try:
pydantic_actor = self.actor.to_pydantic() if hasattr(self.actor, "to_pydantic") else self.actor

44
letta/services/summarizer/summarizer.py
View File

@@ -542,27 +542,35 @@ async def simple_summary(
)
# AnthropicClient.stream_async sets request_data["stream"] = True internally.
stream = await llm_client.stream_async(req_data, summarizer_llm_config)
async for _chunk in interface.process(stream):
# We don't emit anything; we just want the fully-accumulated content.
pass
try:
stream = await llm_client.stream_async(req_data, summarizer_llm_config)
async for _chunk in interface.process(stream):
pass
content_parts = interface.get_content()
text = "".join(part.text for part in content_parts if isinstance(part, TextContent)).strip()
content_parts = interface.get_content()
text = "".join(part.text for part in content_parts if isinstance(part, TextContent)).strip()
# Log telemetry after stream processing
await llm_client.log_provider_trace_async(
request_data=req_data,
response_json={
"content": text,
"model": summarizer_llm_config.model,
"usage": {
"input_tokens": getattr(interface, "input_tokens", None),
"output_tokens": getattr(interface, "output_tokens", None),
await llm_client.log_provider_trace_async(
request_data=req_data,
response_json={
"content": text,
"model": summarizer_llm_config.model,
"usage": {
"input_tokens": getattr(interface, "input_tokens", None),
"output_tokens": getattr(interface, "output_tokens", None),
},
},
},
llm_config=summarizer_llm_config,
)
llm_config=summarizer_llm_config,
)
except Exception as e:
await llm_client.log_provider_trace_async(
request_data=req_data,
response_json=None,
llm_config=summarizer_llm_config,
error_msg=str(e),
error_type=type(e).__name__,
)
raise
if not text:
logger.warning("No content returned from summarizer (streaming path)")