feat: Add presence heartbeat for Matrix online status
- matrix-gateway: POST /internal/matrix/presence/online endpoint - usePresenceHeartbeat hook with activity tracking - Auto away after 5 min inactivity - Offline on page close/visibility change - Integrated in MatrixChatRoom component
This commit is contained in:
Apple
239
services/usage-engine/aggregators.py
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239
services/usage-engine/aggregators.py
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"""
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Usage Data Aggregators
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Queries and aggregates usage data from database
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"""
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import asyncpg
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from datetime import datetime, timedelta
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from typing import Optional, List
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from models import (
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UsageSummary,
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ModelUsage,
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AgentUsage,
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ToolUsage,
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UsageQueryRequest
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)
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class UsageAggregator:
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"""Aggregates usage data for reporting"""
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def __init__(self, db_pool: asyncpg.Pool):
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self.db_pool = db_pool
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async def get_summary(
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self,
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microdao_id: Optional[str] = None,
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agent_id: Optional[str] = None,
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period_hours: int = 24
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) -> UsageSummary:
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"""Get aggregated usage summary"""
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period_start = datetime.utcnow() - timedelta(hours=period_hours)
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period_end = datetime.utcnow()
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async with self.db_pool.acquire() as conn:
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# LLM stats
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llm_stats = await conn.fetchrow("""
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SELECT
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COUNT(*) as calls,
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SUM(total_tokens) as tokens_total,
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SUM(prompt_tokens) as tokens_prompt,
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SUM(completion_tokens) as tokens_completion,
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AVG(latency_ms) as latency_avg
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FROM usage_llm
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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AND ($4::text IS NULL OR agent_id = $4)
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""", period_start, period_end, microdao_id, agent_id)
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# Tool stats
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tool_stats = await conn.fetchrow("""
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SELECT
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COUNT(*) as calls,
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SUM(CASE WHEN success THEN 1 ELSE 0 END) as success,
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SUM(CASE WHEN NOT success THEN 1 ELSE 0 END) as failed,
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AVG(latency_ms) as latency_avg
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FROM usage_tool
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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AND ($4::text IS NULL OR agent_id = $4)
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""", period_start, period_end, microdao_id, agent_id)
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# Agent stats
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agent_stats = await conn.fetchrow("""
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SELECT
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COUNT(*) as invocations,
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SUM(CASE WHEN success THEN 1 ELSE 0 END) as success,
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SUM(CASE WHEN NOT success THEN 1 ELSE 0 END) as failed
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FROM usage_agent
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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AND ($4::text IS NULL OR agent_id = $4)
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""", period_start, period_end, microdao_id, agent_id)
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# Message stats
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message_stats = await conn.fetchrow("""
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SELECT
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COUNT(*) as sent,
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SUM(message_length) as total_length
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FROM usage_message
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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""", period_start, period_end, microdao_id)
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return UsageSummary(
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period_start=period_start,
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period_end=period_end,
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microdao_id=microdao_id,
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agent_id=agent_id,
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llm_calls_total=llm_stats['calls'] or 0,
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llm_tokens_total=llm_stats['tokens_total'] or 0,
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llm_tokens_prompt=llm_stats['tokens_prompt'] or 0,
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llm_tokens_completion=llm_stats['tokens_completion'] or 0,
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llm_latency_avg_ms=float(llm_stats['latency_avg'] or 0),
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tool_calls_total=tool_stats['calls'] or 0,
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tool_calls_success=tool_stats['success'] or 0,
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tool_calls_failed=tool_stats['failed'] or 0,
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tool_latency_avg_ms=float(tool_stats['latency_avg'] or 0),
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agent_invocations_total=agent_stats['invocations'] or 0,
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agent_invocations_success=agent_stats['success'] or 0,
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agent_invocations_failed=agent_stats['failed'] or 0,
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messages_sent=message_stats['sent'] or 0,
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messages_total_length=message_stats['total_length'] or 0
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)
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async def get_model_breakdown(
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self,
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microdao_id: Optional[str] = None,
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period_hours: int = 24
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) -> List[ModelUsage]:
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"""Get usage breakdown by model"""
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period_start = datetime.utcnow() - timedelta(hours=period_hours)
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period_end = datetime.utcnow()
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async with self.db_pool.acquire() as conn:
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rows = await conn.fetch("""
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SELECT
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model,
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provider,
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COUNT(*) as calls,
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SUM(total_tokens) as tokens,
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AVG(latency_ms) as latency_avg
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FROM usage_llm
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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GROUP BY model, provider
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ORDER BY tokens DESC
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LIMIT 20
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""", period_start, period_end, microdao_id)
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return [
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ModelUsage(
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model=row['model'],
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provider=row['provider'],
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calls=row['calls'],
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tokens=row['tokens'] or 0,
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avg_latency_ms=float(row['latency_avg'] or 0)
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)
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for row in rows
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]
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async def get_agent_breakdown(
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self,
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microdao_id: Optional[str] = None,
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period_hours: int = 24
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) -> List[AgentUsage]:
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"""Get usage breakdown by agent"""
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period_start = datetime.utcnow() - timedelta(hours=period_hours)
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period_end = datetime.utcnow()
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async with self.db_pool.acquire() as conn:
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rows = await conn.fetch("""
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SELECT
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a.agent_id,
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COUNT(DISTINCT a.event_id) as invocations,
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COALESCE(SUM(a.llm_calls), 0) as llm_calls,
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COALESCE(SUM(a.tool_calls), 0) as tool_calls,
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COALESCE(llm.tokens, 0) as total_tokens,
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COALESCE(msg.messages, 0) as messages_sent
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FROM usage_agent a
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LEFT JOIN (
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SELECT agent_id, SUM(total_tokens) as tokens
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FROM usage_llm
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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GROUP BY agent_id
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) llm ON llm.agent_id = a.agent_id
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LEFT JOIN (
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SELECT actor_id, COUNT(*) as messages
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FROM usage_message
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WHERE timestamp >= $1 AND timestamp <= $2
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AND actor_type = 'agent'
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AND ($3::text IS NULL OR microdao_id = $3)
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GROUP BY actor_id
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) msg ON msg.actor_id = a.agent_id
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WHERE a.timestamp >= $1 AND a.timestamp <= $2
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AND ($3::text IS NULL OR a.microdao_id = $3)
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GROUP BY a.agent_id, llm.tokens, msg.messages
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ORDER BY invocations DESC
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LIMIT 20
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""", period_start, period_end, microdao_id)
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return [
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AgentUsage(
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agent_id=row['agent_id'],
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invocations=row['invocations'],
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llm_calls=row['llm_calls'],
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tool_calls=row['tool_calls'],
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messages_sent=row['messages_sent'],
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total_tokens=row['total_tokens']
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)
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for row in rows
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]
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async def get_tool_breakdown(
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self,
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microdao_id: Optional[str] = None,
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period_hours: int = 24
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) -> List[ToolUsage]:
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"""Get usage breakdown by tool"""
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period_start = datetime.utcnow() - timedelta(hours=period_hours)
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period_end = datetime.utcnow()
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async with self.db_pool.acquire() as conn:
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rows = await conn.fetch("""
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SELECT
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tool_id,
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tool_name,
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COUNT(*) as calls,
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AVG(CASE WHEN success THEN 1.0 ELSE 0.0 END) as success_rate,
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AVG(latency_ms) as latency_avg
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FROM usage_tool
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WHERE timestamp >= $1 AND timestamp <= $2
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AND ($3::text IS NULL OR microdao_id = $3)
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GROUP BY tool_id, tool_name
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ORDER BY calls DESC
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LIMIT 20
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""", period_start, period_end, microdao_id)
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return [
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ToolUsage(
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tool_id=row['tool_id'],
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tool_name=row['tool_name'],
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calls=row['calls'],
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success_rate=float(row['success_rate'] or 0),
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avg_latency_ms=float(row['latency_avg'] or 0)
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)
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for row in rows
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]
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