This commit is contained in:
Typer_Body
2026-05-26 02:28:01 +08:00
parent b5c43cc113
commit 5d4e40459f
59 changed files with 795 additions and 329 deletions

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"""
Monitoring helper for recording events during pipeline execution.
This module provides convenient methods to record monitoring data
without cluttering the main pipeline code.
"""
from __future__ import annotations
import traceback
import typing
import time
import json
if typing.TYPE_CHECKING:
from ..core import app
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
class MonitoringHelper:
"""Helper class for monitoring operations"""
@staticmethod
async def record_query_start(
ap: app.Application,
query: pipeline_query.Query,
bot_id: str,
bot_name: str,
pipeline_id: str,
pipeline_name: str,
runner_name: str | None = None,
) -> str:
"""Record the start of query processing, returns message_id"""
try:
# Check if session exists, if not, record session start
session_id = f'{query.launcher_type}_{query.launcher_id}'
# Get sender name from message event
sender_name = None
if hasattr(query, 'message_event'):
if hasattr(query.message_event, 'sender'):
if hasattr(query.message_event.sender, 'nickname'):
sender_name = query.message_event.sender.nickname
elif hasattr(query.message_event.sender, 'member_name'):
sender_name = query.message_event.sender.member_name
# Try to record message
# Use JSON serialization to preserve message chain structure (including image URLs, etc.)
if hasattr(query, 'message_chain') and hasattr(query.message_chain, 'model_dump'):
message_content = json.dumps(query.message_chain.model_dump(), ensure_ascii=False)
else:
message_content = str(query)
# Variables will be updated in record_query_success after preproc stage sets them
# Here we just record None, the full variables will be set when query completes
message_id = await ap.monitoring_service.record_message(
bot_id=bot_id,
bot_name=bot_name,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
message_content=message_content,
session_id=session_id,
status='pending',
level='info',
platform=query.launcher_type.value
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
runner_name=runner_name,
variables=None, # Will be updated in record_query_success
)
# Update session activity or create new session if it doesn't exist
# Always pass pipeline info to handle pipeline switches
session_updated = await ap.monitoring_service.update_session_activity(
session_id,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
)
if not session_updated:
# Session doesn't exist, create it
await ap.monitoring_service.record_session_start(
session_id=session_id,
bot_id=bot_id,
bot_name=bot_name,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
platform=query.launcher_type.value
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
)
return message_id
except Exception as e:
ap.logger.error(f'Failed to record query start: {e}')
return ''
@staticmethod
async def record_query_success(
ap: app.Application,
message_id: str,
query: pipeline_query.Query | None = None,
):
"""Record successful query processing by updating message status and variables"""
try:
if message_id:
# Serialize query.variables (filtering out internal variables)
query_variables_str = None
if query and hasattr(query, 'variables') and query.variables:
filtered_vars = {k: v for k, v in query.variables.items() if not k.startswith('_')}
if filtered_vars:
try:
query_variables_str = json.dumps(filtered_vars, ensure_ascii=False, default=str)
except Exception:
pass
await ap.monitoring_service.update_message_status(
message_id=message_id,
status='success',
variables=query_variables_str,
)
except Exception as e:
ap.logger.error(f'Failed to record query success: {e}')
@staticmethod
async def record_query_response(
ap: app.Application,
query: pipeline_query.Query,
bot_id: str,
bot_name: str,
pipeline_id: str,
pipeline_name: str,
runner_name: str | None = None,
):
"""Record bot response message to monitoring"""
try:
session_id = f'{query.launcher_type}_{query.launcher_id}'
# Get sender name from message event
sender_name = None
if hasattr(query, 'message_event'):
if hasattr(query.message_event, 'sender'):
if hasattr(query.message_event.sender, 'nickname'):
sender_name = query.message_event.sender.nickname
elif hasattr(query.message_event.sender, 'member_name'):
sender_name = query.message_event.sender.member_name
# Extract response content from resp_message_chain
if hasattr(query, 'resp_message_chain') and query.resp_message_chain:
# Serialize the last response message chain
last_resp = query.resp_message_chain[-1]
if hasattr(last_resp, 'model_dump'):
message_content = json.dumps(last_resp.model_dump(), ensure_ascii=False)
else:
message_content = str(last_resp)
elif hasattr(query, 'resp_messages') and query.resp_messages:
last_resp = query.resp_messages[-1]
if hasattr(last_resp, 'get_content_platform_message_chain'):
chain = last_resp.get_content_platform_message_chain()
if hasattr(chain, 'model_dump'):
message_content = json.dumps(chain.model_dump(), ensure_ascii=False)
else:
message_content = str(chain)
else:
message_content = str(last_resp)
else:
return # No response to record
await ap.monitoring_service.record_message(
bot_id=bot_id,
bot_name=bot_name,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
message_content=message_content,
session_id=session_id,
status='success',
level='info',
platform=query.launcher_type.value
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
runner_name=runner_name,
role='assistant',
)
except Exception as e:
ap.logger.error(f'Failed to record query response: {e}')
@staticmethod
async def record_query_error(
ap: app.Application,
query: pipeline_query.Query,
bot_id: str,
bot_name: str,
pipeline_id: str,
pipeline_name: str,
error: Exception,
runner_name: str | None = None,
) -> str:
"""Record query processing error, returns message_id"""
try:
session_id = f'{query.launcher_type}_{query.launcher_id}'
# Get sender name from message event
sender_name = None
if hasattr(query, 'message_event'):
if hasattr(query.message_event, 'sender'):
if hasattr(query.message_event.sender, 'nickname'):
sender_name = query.message_event.sender.nickname
elif hasattr(query.message_event.sender, 'member_name'):
sender_name = query.message_event.sender.member_name
# Record error message
message_id = await ap.monitoring_service.record_message(
bot_id=bot_id,
bot_name=bot_name,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
message_content=f'Error: {str(error)}',
session_id=session_id,
status='error',
level='error',
platform=query.launcher_type.value
if hasattr(query.launcher_type, 'value')
else str(query.launcher_type),
user_id=query.sender_id,
user_name=sender_name,
runner_name=runner_name,
)
# Record error log
await ap.monitoring_service.record_error(
bot_id=bot_id,
bot_name=bot_name,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
error_type=type(error).__name__,
error_message=str(error),
session_id=session_id,
stack_trace=traceback.format_exc(),
message_id=message_id,
)
return message_id
except Exception as e:
ap.logger.error(f'Failed to record query error: {e}')
return ''
@staticmethod
async def record_llm_call(
ap: app.Application,
query: pipeline_query.Query,
bot_id: str,
bot_name: str,
pipeline_id: str,
pipeline_name: str,
model_name: str,
input_tokens: int,
output_tokens: int,
duration_ms: int,
status: str = 'success',
cost: float | None = None,
error_message: str | None = None,
message_id: str | None = None,
):
"""Record LLM call"""
try:
session_id = f'{query.launcher_type}_{query.launcher_id}'
await ap.monitoring_service.record_llm_call(
bot_id=bot_id,
bot_name=bot_name,
pipeline_id=pipeline_id,
pipeline_name=pipeline_name,
session_id=session_id,
model_name=model_name,
input_tokens=input_tokens,
output_tokens=output_tokens,
duration=duration_ms,
status=status,
cost=cost,
error_message=error_message,
message_id=message_id,
)
except Exception as e:
ap.logger.error(f'Failed to record LLM call: {e}')
class LLMCallMonitor:
"""Context manager for monitoring LLM calls"""
def __init__(
self,
ap: app.Application,
query: pipeline_query.Query,
bot_id: str,
bot_name: str,
pipeline_id: str,
pipeline_name: str,
model_name: str,
):
self.ap = ap
self.query = query
self.bot_id = bot_id
self.bot_name = bot_name
self.pipeline_id = pipeline_id
self.pipeline_name = pipeline_name
self.model_name = model_name
self.start_time = None
self.input_tokens = 0
self.output_tokens = 0
async def __aenter__(self):
self.start_time = time.time()
return self
async def __aexit__(self, exc_type, exc_val, exc_tb):
duration_ms = int((time.time() - self.start_time) * 1000)
if exc_type is not None:
# Error occurred
await MonitoringHelper.record_llm_call(
ap=self.ap,
query=self.query,
bot_id=self.bot_id,
bot_name=self.bot_name,
pipeline_id=self.pipeline_id,
pipeline_name=self.pipeline_name,
model_name=self.model_name,
input_tokens=self.input_tokens,
output_tokens=self.output_tokens,
duration_ms=duration_ms,
status='error',
error_message=str(exc_val) if exc_val else None,
)
else:
# Success
await MonitoringHelper.record_llm_call(
ap=self.ap,
query=self.query,
bot_id=self.bot_id,
bot_name=self.bot_name,
pipeline_id=self.pipeline_id,
pipeline_name=self.pipeline_name,
model_name=self.model_name,
input_tokens=self.input_tokens,
output_tokens=self.output_tokens,
duration_ms=duration_ms,
status='success',
)
return False # Don't suppress exceptions