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Feat/monitor (#1928)
* feat: add monitor * feat: fix tab * feat: work * feat: not reliable monitor * feat: enhance monitoring page layout with integrated filters and refresh button * feat: add support for runner recording * feat: add jump button & alignment * feat: new * fix: not show query variables in local agent * fix: pnpm lint and python ruff check * fix: ruff fromat * chore: remove unnecessary migration * style: optimize monitoring page layout and fix sticky filter issues - Enhanced metric cards with gradient backgrounds and hover effects - Increased traffic chart height from 200px to 300px - Adjusted grid layout and spacing for better visual appeal - Fixed sticky filter area to properly cover parent padding without transparent gaps - Used negative margins and positioning to eliminate scrolling artifacts - Matched padding/margins with other pages (pipelines, bots) for consistency - Removed duplicate title/subtitle from page content - Added cursor-pointer styling to tab triggers - Removed border between tab list and tab content Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * fix: apply prettier formatting to monitoring components - Fixed indentation and spacing in MetricCard.tsx - Fixed formatting in TrafficChart.tsx - Applied prettier formatting to page.tsx Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * feat: update HomeSidebar to trigger action on child selection and localize monitoring titles * refactor: streamline LLM and embedding invocation methods * feat: add embedding model monitor * fix: database version * chore: simplify pnpm-lock.yaml formatting --------- Co-authored-by: Junyan Qin <rockchinq@gmail.com> Co-authored-by: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
Guanchao Wang
@@ -115,6 +115,25 @@ class RuntimePipeline:
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# Store bound plugins and MCP servers in query for filtering
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query.variables['_pipeline_bound_plugins'] = self.bound_plugins
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query.variables['_pipeline_bound_mcp_servers'] = self.bound_mcp_servers
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# Record query start for monitoring
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try:
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# Get bot name from bot_uuid
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bot_name = 'WebChat'
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if query.bot_uuid:
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try:
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bot = await self.ap.bot_service.get_bot(query.bot_uuid, include_secret=False)
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if bot:
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bot_name = bot.get('name', 'Unknown')
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except Exception:
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pass
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# Store for later use in process_query
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query.variables['_monitoring_bot_name'] = bot_name
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query.variables['_monitoring_pipeline_name'] = self.pipeline_entity.name
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except Exception as e:
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self.ap.logger.error(f'Failed to prepare monitoring data: {e}')
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await self.process_query(query)
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async def _check_output(self, query: pipeline_query.Query, result: pipeline_entities.StageProcessResult):
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@@ -131,7 +150,7 @@ class RuntimePipeline:
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query.message_event, platform_events.GroupMessage
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):
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result.user_notice.insert(0, platform_message.At(target=query.message_event.sender.id))
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if await query.adapter.is_stream_output_supported():
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if await query.adapter.is_stream_output_supported() and query.resp_messages:
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await query.adapter.reply_message_chunk(
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message_source=query.message_event,
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bot_message=query.resp_messages[-1],
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@@ -151,6 +170,37 @@ class RuntimePipeline:
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self.ap.logger.info(result.console_notice)
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if result.error_notice:
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self.ap.logger.error(result.error_notice)
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# Mark query as having error
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query.variables['_monitoring_has_error'] = True
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# Record error to monitoring system
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try:
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bot_name = query.variables.get('_monitoring_bot_name', 'Unknown')
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pipeline_name = query.variables.get('_monitoring_pipeline_name', 'Unknown')
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message_id = query.variables.get('_monitoring_message_id', '')
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session_id = f'{query.launcher_type}_{query.launcher_id}'
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# Update message status to error
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if message_id:
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await self.ap.monitoring_service.update_message_status(
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message_id=message_id,
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status='error',
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level='error',
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)
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# Record error log
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await self.ap.monitoring_service.record_error(
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bot_id=query.bot_uuid or 'unknown',
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bot_name=bot_name,
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pipeline_id=self.pipeline_entity.uuid,
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pipeline_name=pipeline_name,
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error_type='PipelineError',
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error_message=result.error_notice,
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session_id=session_id,
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stack_trace=result.debug_notice if result.debug_notice else None,
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message_id=message_id,
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)
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except Exception as e:
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self.ap.logger.error(f'Failed to record error to monitoring: {e}')
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async def _execute_from_stage(
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self,
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@@ -221,6 +271,34 @@ class RuntimePipeline:
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async def process_query(self, query: pipeline_query.Query):
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"""处理请求"""
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# Get monitoring metadata
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bot_name = query.variables.get('_monitoring_bot_name', 'Unknown')
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pipeline_name = query.variables.get('_monitoring_pipeline_name', 'Unknown')
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# Get runner name from pipeline config
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runner_name = None
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if query.pipeline_config and 'ai' in query.pipeline_config and 'runner' in query.pipeline_config['ai']:
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runner_name = query.pipeline_config['ai']['runner'].get('runner')
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# Record query start and store message_id
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message_id = ''
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try:
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from . import monitoring_helper
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message_id = await monitoring_helper.MonitoringHelper.record_query_start(
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ap=self.ap,
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query=query,
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bot_id=query.bot_uuid or 'unknown',
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bot_name=bot_name,
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pipeline_id=self.pipeline_entity.uuid,
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pipeline_name=pipeline_name,
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runner_name=runner_name,
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)
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# Store message_id in query variables for LLM call monitoring
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query.variables['_monitoring_message_id'] = message_id
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except Exception as e:
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self.ap.logger.error(f'Failed to record query start: {e}')
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try:
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# Get bound plugins for this pipeline
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bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
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@@ -249,10 +327,40 @@ class RuntimePipeline:
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self.ap.logger.debug(f'Processing query {query.query_id}')
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await self._execute_from_stage(0, query)
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# Record query success only if no error occurred during processing
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if not query.variables.get('_monitoring_has_error', False):
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try:
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await monitoring_helper.MonitoringHelper.record_query_success(
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ap=self.ap,
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message_id=message_id,
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query=query,
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)
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except Exception as e:
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self.ap.logger.error(f'Failed to record query success: {e}')
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except Exception as e:
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inst_name = query.current_stage_name if query.current_stage_name else 'unknown'
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self.ap.logger.error(f'Error processing query {query.query_id} stage={inst_name} : {e}')
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self.ap.logger.error(f'Traceback: {traceback.format_exc()}')
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# Record query error
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try:
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from . import monitoring_helper
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await monitoring_helper.MonitoringHelper.record_query_error(
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ap=self.ap,
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query=query,
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bot_id=query.bot_uuid or 'unknown',
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bot_name=bot_name,
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pipeline_id=self.pipeline_entity.uuid,
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pipeline_name=pipeline_name,
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error=e,
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runner_name=runner_name,
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)
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except Exception as me:
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self.ap.logger.error(f'Failed to record query error: {me}')
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finally:
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self.ap.logger.debug(f'Query {query.query_id} processed')
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del self.ap.query_pool.cached_queries[query.query_id]
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