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feat: support export message history

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WangCham
2026-02-08 10:19:27 +08:00
parent 59d55b382d
commit 6d858475d7
8 changed files with 691 additions and 15 deletions
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97
src/langbot/pkg/api/http/controller/groups/monitoring.py
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@@ -323,3 +323,100 @@ class MonitoringRouterGroup(group.RouterGroup):
return self.error(message=f'Message {message_id} not found', code=404)
return self.success(data=details)
@self.route('/export', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
async def export_data() -> tuple[str, int]:
"""Export monitoring data as CSV"""
# Parse query parameters
export_type = quart.request.args.get('type', 'messages')
bot_ids = quart.request.args.getlist('botId')
pipeline_ids = quart.request.args.getlist('pipelineId')
start_time_str = quart.request.args.get('startTime')
end_time_str = quart.request.args.get('endTime')
limit = int(quart.request.args.get('limit', 100000))
# Parse datetime
start_time = parse_iso_datetime(start_time_str)
end_time = parse_iso_datetime(end_time_str)
# Get data based on export type
if export_type == 'messages':
data = await self.ap.monitoring_service.export_messages(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = ['id', 'timestamp', 'bot_id', 'bot_name', 'pipeline_id', 'pipeline_name',
'runner_name', 'message_content', 'message_text', 'session_id', 'status', 'level',
'platform', 'user_id']
elif export_type == 'llm-calls':
data = await self.ap.monitoring_service.export_llm_calls(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = ['id', 'timestamp', 'model_name', 'input_tokens', 'output_tokens',
'total_tokens', 'duration_ms', 'cost', 'status', 'bot_id', 'bot_name',
'pipeline_id', 'pipeline_name', 'session_id', 'message_id', 'error_message']
elif export_type == 'embedding-calls':
data = await self.ap.monitoring_service.export_embedding_calls(
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = ['id', 'timestamp', 'model_name', 'prompt_tokens', 'total_tokens',
'duration_ms', 'input_count', 'status', 'error_message', 'knowledge_base_id',
'query_text', 'session_id', 'message_id', 'call_type']
elif export_type == 'errors':
data = await self.ap.monitoring_service.export_errors(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = ['id', 'timestamp', 'error_type', 'error_message', 'bot_id', 'bot_name',
'pipeline_id', 'pipeline_name', 'session_id', 'message_id', 'stack_trace']
elif export_type == 'sessions':
data = await self.ap.monitoring_service.export_sessions(
bot_ids=bot_ids if bot_ids else None,
pipeline_ids=pipeline_ids if pipeline_ids else None,
start_time=start_time,
end_time=end_time,
limit=limit,
)
headers = ['session_id', 'bot_id', 'bot_name', 'pipeline_id', 'pipeline_name',
'message_count', 'start_time', 'last_activity', 'is_active',
'platform', 'user_id']
else:
return self.error(message=f'Invalid export type: {export_type}', code=400)
# Generate CSV content with UTF-8 BOM for Excel compatibility
import io
output = io.StringIO()
# Write UTF-8 BOM for Excel
output.write('\ufeff')
# Write header
output.write(','.join(headers) + '\n')
# Escape and write each row
for row in data:
escaped_values = []
for header in headers:
value = row.get(header, '')
escaped_values.append(self.ap.monitoring_service._escape_csv_field(value))
output.write(','.join(escaped_values) + '\n')
csv_content = output.getvalue()
# Return as file download
response = await quart.make_response(csv_content)
response.headers['Content-Type'] = 'text/csv; charset=utf-8'
response.headers['Content-Disposition'] = f'attachment; filename="monitoring-{export_type}-{int(datetime.datetime.now().timestamp())}.csv"'
return response, 200