feat: complete phase 5 -- error hardening, frontend, Docker, demo, docs
Backend: - ConversationTracker: Protocol + PostgresConversationTracker for lifecycle tracking - Error handler: ErrorCategory enum, classify_error(), with_retry() exponential backoff - Wire PostgresAnalyticsRecorder + ConversationTracker into ws_handler - Rate limiting (10 msg/10s per thread), edge case hardening - Health endpoint GET /api/health, version 0.5.0 - Demo seed data script + sample OpenAPI spec Frontend (all new): - React Router with NavBar (Chat / Replay / Dashboard / Review) - ReplayListPage + ReplayPage with ReplayTimeline component - DashboardPage with MetricCard, range selector, zero-state - ReviewPage for OpenAPI classification review - ErrorBanner for WebSocket disconnect handling - API client (api.ts) with typed fetch wrappers Infrastructure: - Frontend Dockerfile (multi-stage node -> nginx) - nginx.conf with SPA routing + API/WS proxy - docker-compose.yml with frontend service + healthchecks - .env.example files (root + backend) Documentation: - README.md with quick start and architecture - Agent configuration guide - OpenAPI import guide - Deployment guide - Demo script 48 new tests, 449 total passing, 92.87% coverage
This commit is contained in:
Yaojia Wang
153
backend/fixtures/demo_data.py
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153
backend/fixtures/demo_data.py
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"""Seed script -- inserts sample conversations and analytics events for demo purposes.
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Usage:
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cd backend
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python fixtures/demo_data.py
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"""
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from __future__ import annotations
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import asyncio
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import os
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import sys
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from datetime import datetime, timedelta, timezone
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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import psycopg
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DATABASE_URL = os.environ.get(
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"DATABASE_URL",
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"postgresql://smart_support:dev_password@localhost:5432/smart_support",
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)
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SAMPLE_CONVERSATIONS = [
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{
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"thread_id": "demo-thread-001",
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"agents_used": ["order_agent"],
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"turn_count": 3,
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"total_tokens": 1250,
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"total_cost_usd": 0.00375,
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"resolution_type": "resolved",
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"minutes_ago": 5,
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},
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{
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"thread_id": "demo-thread-002",
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"agents_used": ["order_agent", "refund_agent"],
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"turn_count": 6,
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"total_tokens": 3200,
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"total_cost_usd": 0.0096,
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"resolution_type": "resolved",
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"minutes_ago": 30,
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},
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{
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"thread_id": "demo-thread-003",
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"agents_used": ["general_agent"],
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"turn_count": 2,
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"total_tokens": 800,
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"total_cost_usd": 0.0024,
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"resolution_type": None,
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"minutes_ago": 60,
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},
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{
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"thread_id": "demo-thread-004",
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"agents_used": ["order_agent", "general_agent"],
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"turn_count": 8,
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"total_tokens": 4500,
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"total_cost_usd": 0.0135,
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"resolution_type": "escalated",
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"minutes_ago": 120,
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},
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{
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"thread_id": "demo-thread-005",
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"agents_used": ["refund_agent"],
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"turn_count": 4,
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"total_tokens": 2100,
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"total_cost_usd": 0.0063,
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"resolution_type": "resolved",
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"minutes_ago": 240,
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},
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]
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SAMPLE_EVENTS = [
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{"thread_id": "demo-thread-001", "event_type": "message", "agent_name": "order_agent", "tokens_used": 400, "cost_usd": 0.0012, "success": True},
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{"thread_id": "demo-thread-001", "event_type": "tool_call", "agent_name": "order_agent", "tool_name": "get_order_status", "tokens_used": 0, "cost_usd": 0.0, "success": True},
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{"thread_id": "demo-thread-002", "event_type": "message", "agent_name": "order_agent", "tokens_used": 1600, "cost_usd": 0.0048, "success": True},
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{"thread_id": "demo-thread-002", "event_type": "message", "agent_name": "refund_agent", "tokens_used": 1600, "cost_usd": 0.0048, "success": True},
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{"thread_id": "demo-thread-002", "event_type": "tool_call", "agent_name": "refund_agent", "tool_name": "process_refund", "tokens_used": 0, "cost_usd": 0.0, "success": True},
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{"thread_id": "demo-thread-003", "event_type": "message", "agent_name": "general_agent", "tokens_used": 800, "cost_usd": 0.0024, "success": True},
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{"thread_id": "demo-thread-004", "event_type": "message", "agent_name": "order_agent", "tokens_used": 2000, "cost_usd": 0.006, "success": True},
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{"thread_id": "demo-thread-004", "event_type": "escalation", "agent_name": "general_agent", "tokens_used": 2500, "cost_usd": 0.0075, "success": False},
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{"thread_id": "demo-thread-005", "event_type": "message", "agent_name": "refund_agent", "tokens_used": 2100, "cost_usd": 0.0063, "success": True},
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]
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_INSERT_CONVERSATION = """
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INSERT INTO conversations
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(thread_id, started_at, last_activity, turn_count, agents_used,
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total_tokens, total_cost_usd, resolution_type, ended_at)
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VALUES
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(%(thread_id)s, %(started_at)s, %(last_activity)s, %(turn_count)s,
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%(agents_used)s, %(total_tokens)s, %(total_cost_usd)s,
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%(resolution_type)s, %(ended_at)s)
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ON CONFLICT (thread_id) DO NOTHING
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"""
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_INSERT_EVENT = """
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INSERT INTO analytics_events
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(thread_id, event_type, agent_name, tool_name, tokens_used, cost_usd, success)
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VALUES
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(%(thread_id)s, %(event_type)s, %(agent_name)s, %(tool_name)s,
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%(tokens_used)s, %(cost_usd)s, %(success)s)
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"""
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async def seed() -> None:
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now = datetime.now(tz=timezone.utc)
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async with await psycopg.AsyncConnection.connect(DATABASE_URL) as conn:
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print("Seeding conversations...")
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for conv in SAMPLE_CONVERSATIONS:
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started_at = now - timedelta(minutes=conv["minutes_ago"])
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last_activity = started_at + timedelta(minutes=conv["turn_count"] * 2)
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ended_at = last_activity if conv["resolution_type"] else None
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await conn.execute(
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_INSERT_CONVERSATION,
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{
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"thread_id": conv["thread_id"],
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"started_at": started_at,
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"last_activity": last_activity,
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"turn_count": conv["turn_count"],
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"agents_used": conv["agents_used"],
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"total_tokens": conv["total_tokens"],
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"total_cost_usd": conv["total_cost_usd"],
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"resolution_type": conv["resolution_type"],
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"ended_at": ended_at,
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},
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)
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print(f" Inserted conversation {conv['thread_id']}")
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print("Seeding analytics events...")
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for event in SAMPLE_EVENTS:
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await conn.execute(
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_INSERT_EVENT,
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{
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"thread_id": event["thread_id"],
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"event_type": event["event_type"],
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"agent_name": event.get("agent_name"),
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"tool_name": event.get("tool_name"),
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"tokens_used": event.get("tokens_used", 0),
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"cost_usd": event.get("cost_usd", 0.0),
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"success": event.get("success"),
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},
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)
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print(f" Inserted event {event['event_type']} for {event['thread_id']}")
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await conn.commit()
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print("Done. Demo data seeded successfully.")
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if __name__ == "__main__":
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asyncio.run(seed())
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