feat: complete phase 4 -- conversation replay API + analytics dashboard
- Replay models: StepType enum, ReplayStep, ReplayPage frozen dataclasses
- Checkpoint transformer: PostgresSaver JSONB -> structured timeline steps
- Replay API: GET /api/conversations (paginated), GET /api/replay/{thread_id}
- Analytics models: AgentUsage, InterruptStats, AnalyticsResult
- Analytics event recorder: Protocol + PostgresAnalyticsRecorder + NoOp
- Analytics queries: resolution_rate, agent_usage, escalation_rate, cost, interrupts
- Analytics API: GET /api/analytics?range=Xd with envelope response
- DB migration: analytics_events table + conversations column additions
- 74 new tests, 399 total passing, 92.87% coverage
This commit is contained in:
Yaojia Wang
177
backend/app/analytics/queries.py
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177
backend/app/analytics/queries.py
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"""Analytics query functions -- all async, take pool + range_days."""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from app.analytics.models import AgentUsage, AnalyticsResult, InterruptStats
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if TYPE_CHECKING:
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from psycopg_pool import AsyncConnectionPool
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_RESOLUTION_RATE_SQL = """
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SELECT
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CASE WHEN COUNT(*) = 0 THEN 0.0
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ELSE COUNT(*) FILTER (WHERE resolution_type = 'resolved')::float / COUNT(*)
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END AS rate
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FROM conversations
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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"""
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_ESCALATION_RATE_SQL = """
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SELECT
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CASE WHEN COUNT(*) = 0 THEN 0.0
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ELSE COUNT(*) FILTER (WHERE resolution_type = 'escalated')::float / COUNT(*)
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END AS rate
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FROM conversations
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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"""
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_TOTAL_CONVERSATIONS_SQL = """
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SELECT COUNT(*) AS total
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FROM conversations
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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"""
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_AVG_TURNS_SQL = """
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SELECT COALESCE(AVG(turn_count), 0.0) AS avg_turns
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FROM conversations
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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"""
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_COST_PER_CONVERSATION_SQL = """
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SELECT COALESCE(AVG(total_cost_usd), 0.0) AS avg_cost
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FROM conversations
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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"""
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_AGENT_USAGE_SQL = """
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SELECT
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agent,
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COUNT(*) AS count,
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ROUND(COUNT(*) * 100.0 / NULLIF(SUM(COUNT(*)) OVER (), 0), 2) AS percentage
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FROM (
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SELECT UNNEST(agents_used) AS agent
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FROM conversations
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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AND agents_used IS NOT NULL
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) sub
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GROUP BY agent
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ORDER BY count DESC
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"""
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_INTERRUPT_STATS_SQL = """
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SELECT
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COUNT(*) FILTER (WHERE event_type = 'interrupt') AS total,
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COUNT(*) FILTER (WHERE event_type = 'interrupt' AND success = TRUE) AS approved,
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COUNT(*) FILTER (WHERE event_type = 'interrupt' AND success = FALSE
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AND error_message IS NULL) AS rejected,
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COUNT(*) FILTER (WHERE event_type = 'interrupt' AND error_message = 'expired') AS expired
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FROM analytics_events
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WHERE created_at >= NOW() - INTERVAL '%(days)s days'
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"""
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async def resolution_rate(pool: AsyncConnectionPool, range_days: int) -> float:
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"""Return the fraction of resolved conversations in the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_RESOLUTION_RATE_SQL, {"days": range_days})
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row = await cursor.fetchone()
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if not row:
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return 0.0
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return float(row.get("rate") or 0.0)
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async def escalation_rate(pool: AsyncConnectionPool, range_days: int) -> float:
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"""Return the fraction of escalated conversations in the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_ESCALATION_RATE_SQL, {"days": range_days})
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row = await cursor.fetchone()
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if not row:
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return 0.0
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return float(row.get("rate") or 0.0)
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async def _total_conversations(pool: AsyncConnectionPool, range_days: int) -> int:
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"""Return the total number of conversations in the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_TOTAL_CONVERSATIONS_SQL, {"days": range_days})
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row = await cursor.fetchone()
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if not row:
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return 0
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return int(row.get("total") or 0)
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async def _avg_turns(pool: AsyncConnectionPool, range_days: int) -> float:
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"""Return the average turn count per conversation in the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_AVG_TURNS_SQL, {"days": range_days})
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row = await cursor.fetchone()
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if not row:
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return 0.0
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return float(row.get("avg_turns") or 0.0)
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async def cost_per_conversation(pool: AsyncConnectionPool, range_days: int) -> float:
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"""Return the average cost per conversation in the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_COST_PER_CONVERSATION_SQL, {"days": range_days})
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row = await cursor.fetchone()
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if not row:
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return 0.0
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return float(row.get("avg_cost") or 0.0)
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async def agent_usage(pool: AsyncConnectionPool, range_days: int) -> tuple[AgentUsage, ...]:
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"""Return per-agent usage statistics for the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_AGENT_USAGE_SQL, {"days": range_days})
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rows = await cursor.fetchall()
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if not rows:
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return ()
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return tuple(
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AgentUsage(
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agent=row["agent"],
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count=int(row["count"]),
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percentage=float(row["percentage"]),
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)
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for row in rows
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)
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async def interrupt_stats(pool: AsyncConnectionPool, range_days: int) -> InterruptStats:
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"""Return interrupt approval/rejection statistics for the given range."""
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async with pool.connection() as conn:
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cursor = await conn.execute(_INTERRUPT_STATS_SQL, {"days": range_days})
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row = await cursor.fetchone()
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if not row:
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return InterruptStats()
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return InterruptStats(
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total=int(row.get("total") or 0),
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approved=int(row.get("approved") or 0),
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rejected=int(row.get("rejected") or 0),
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expired=int(row.get("expired") or 0),
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)
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async def get_analytics(pool: AsyncConnectionPool, range_days: int) -> AnalyticsResult:
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"""Aggregate all analytics metrics into a single AnalyticsResult."""
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res_rate, esc_rate, cost, usage, i_stats, total, avg_t = (
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await resolution_rate(pool, range_days),
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await escalation_rate(pool, range_days),
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await cost_per_conversation(pool, range_days),
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await agent_usage(pool, range_days),
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await interrupt_stats(pool, range_days),
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await _total_conversations(pool, range_days),
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await _avg_turns(pool, range_days),
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)
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return AnalyticsResult(
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range=f"{range_days}d",
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total_conversations=total,
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resolution_rate=res_rate,
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escalation_rate=esc_rate,
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avg_turns_per_conversation=avg_t,
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avg_cost_per_conversation_usd=cost,
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agent_usage=usage,
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interrupt_stats=i_stats,
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)
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