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StephaneWambaStephaneWamba
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feat(analytics): Implement comprehensive analytics dashboard with charts and metrics
- Add analytics API endpoints (overview, conversations, agents, costs, crm) - Add Chat Service internal endpoint for message listing - Install recharts library for data visualization - Create date range picker component with presets - Implement overview metrics component (KPI cards) - Add conversation chart (line chart) for trends - Add channel distribution component (pie chart) - Create agent performance table component - Add cost analysis component - Implement CRM insights component with bar chart - Build main analytics page integrating all components - Add analytics API client with React Query hooks
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‎.github/workflows/deploy-voice-agent.yml‎

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run: |
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python -c "import sys; sys.path.insert(0, 'src'); import main; import agent; import config; print('✅ All imports successful')"
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‎.wrangler/state/v3/r2/miniflare-R2BucketObject/4534d7bd76a0dcb5f5462e95cc632631af3e413cc1308bd62ead8c1decc06389.sqlite-shm‎

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‎.wrangler/state/v3/r2/miniflare-R2BucketObject/4534d7bd76a0dcb5f5462e95cc632631af3e413cc1308bd62ead8c1decc06389.sqlite-wal‎

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‎create-workflow-example.json‎

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‎database/supabase/migrations/010_workflows.sql‎

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‎database/supabase/migrations/011_notifications.sql‎

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‎database/supabase/migrations/012_add_agent_avatar_url.sql‎

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‎frontend/app/api/analytics/agents/route.ts‎

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/**
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* Analytics Agents API
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* Returns agent performance metrics
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*/
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import { NextRequest, NextResponse } from 'next/server'
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import { withAuth } from '@/lib/api/middleware'
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import { createClient } from '@/lib/supabase/server'
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import { logger } from '@/lib/utils/logger'
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const CHAT_SERVICE_URL = process.env.CHAT_SERVICE_URL || 'http://localhost:4004'
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export async function GET(request: NextRequest) {
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return withAuth(request, async (req, ctx) => {
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try {
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if (!ctx.companyId) {
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return NextResponse.json({ error: 'Company ID required' }, { status: 400 })
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}
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const supabase = await createClient()
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const searchParams = req.nextUrl.searchParams
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const startDate = searchParams.get('startDate')
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const endDate = searchParams.get('endDate')
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// Get agents from Supabase
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const { data: agents, error: agentsError } = await supabase
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.from('agent_configs')
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.select('id, name, enabled')
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.eq('company_id', ctx.companyId)
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.eq('enabled', true)
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if (agentsError) {
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logger.warn('Failed to fetch agents', { error: agentsError })
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}
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if (!agents || agents.length === 0) {
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return NextResponse.json({ agents: [] })
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}
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// Get access token for Chat Service
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const {
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data: { session },
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} = await supabase.auth.getSession()
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if (!session?.access_token) {
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return NextResponse.json({ error: 'No session token' }, { status: 401 })
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}
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// Fetch conversations from Chat Service
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const conversationsResponse = await fetch(
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`${CHAT_SERVICE_URL}/api/conversations?limit=1000`,
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{
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headers: {
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Authorization: `Bearer ${session.access_token}`,
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},
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}
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)
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if (!conversationsResponse.ok) {
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throw new Error('Failed to fetch conversations')
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}
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const conversationsData = await conversationsResponse.json()
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let conversations = conversationsData.conversations || []
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// Filter by date range if provided
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if (startDate || endDate) {
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conversations = conversations.filter((conv: { started_at: string }) => {
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const convDate = new Date(conv.started_at)
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if (startDate && convDate < new Date(startDate)) return false
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if (endDate && convDate > new Date(endDate)) return false
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return true
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})
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}
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// Fetch messages for response time and satisfaction
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const messagesResponse = await fetch(
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`${CHAT_SERVICE_URL}/api/internal/messages/list?limit=1000`,
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{
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headers: {
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Authorization: `Bearer ${process.env.INTERNAL_SERVICE_TOKEN || ''}`,
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'Content-Type': 'application/json',
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},
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method: 'POST',
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body: JSON.stringify({
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companyId: ctx.companyId,
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limit: 1000,
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startDate,
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endDate,
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}),
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}
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)
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const messages = messagesResponse.ok
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? (await messagesResponse.json()).messages || []
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: []
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// Calculate metrics per agent
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const agentMetrics = agents.map((agent) => {
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const agentConversations = conversations.filter(
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(c: { agent_id: string }) => c.agent_id === agent.id
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)
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const agentMessages = messages.filter(
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(m: { conversation_id: string; sender_type: string; ai_metadata?: { response_time_ms?: number }; metadata?: { sentiment?: { sentiment: string } } }) => {
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const conv = conversations.find((c: { _id: string; agent_id: string }) =>
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String(c._id) === m.conversation_id && c.agent_id === agent.id
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)
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return conv && m.sender_type === 'agent'
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}
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)
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// Calculate average response time
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const messagesWithResponseTime = agentMessages.filter(
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(m: { ai_metadata?: { response_time_ms?: number } }) => m.ai_metadata?.response_time_ms
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)
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const avgResponseTime =
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messagesWithResponseTime.length > 0
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? Math.round(
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messagesWithResponseTime.reduce(
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(sum: number, m: { ai_metadata: { response_time_ms: number } }) =>
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sum + (m.ai_metadata.response_time_ms || 0),
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0
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) / messagesWithResponseTime.length
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)
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: 0
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// Calculate satisfaction
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const messagesWithSentiment = agentMessages.filter(
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(m: { metadata?: { sentiment?: { sentiment: string } } }) =>
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m.metadata?.sentiment?.sentiment
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)
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const satisfaction =
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messagesWithSentiment.length > 0
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? Math.round(
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(messagesWithSentiment.filter(
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(m: { metadata: { sentiment: { sentiment: string } } }) =>
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m.metadata.sentiment.sentiment === 'positive'
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).length /
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messagesWithSentiment.length) *
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100
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)
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: 0
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return {
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agentId: agent.id,
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agentName: agent.name || 'Unnamed Agent',
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conversationCount: agentConversations.length,
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avgResponseTime,
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satisfaction,
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}
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})
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// Sort by conversation count (top performers first)
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agentMetrics.sort((a, b) => b.conversationCount - a.conversationCount)
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return NextResponse.json({ agents: agentMetrics })
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} catch (error) {
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logger.error('Analytics agents error', { error })
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return NextResponse.json(
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{ error: 'Failed to fetch agent analytics' },
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{ status: 500 }
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)
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}
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}, { requireCompany: true })
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}
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‎frontend/app/api/analytics/conversations/route.ts‎

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/**
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* Analytics Conversations API
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* Returns conversation analytics (timeline, by channel, avg duration)
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*/
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import { NextRequest, NextResponse } from 'next/server'
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import { withAuth } from '@/lib/api/middleware'
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import { createClient } from '@/lib/supabase/server'
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import { logger } from '@/lib/utils/logger'
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const CHAT_SERVICE_URL = process.env.CHAT_SERVICE_URL || 'http://localhost:4004'
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export async function GET(request: NextRequest) {
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return withAuth(request, async (req, ctx) => {
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try {
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if (!ctx.companyId) {
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return NextResponse.json({ error: 'Company ID required' }, { status: 400 })
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}
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const supabase = await createClient()
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const searchParams = req.nextUrl.searchParams
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const startDate = searchParams.get('startDate')
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const endDate = searchParams.get('endDate')
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const groupBy = searchParams.get('groupBy') || 'day'
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// Get access token for Chat Service
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const {
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data: { session },
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} = await supabase.auth.getSession()
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if (!session?.access_token) {
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return NextResponse.json({ error: 'No session token' }, { status: 401 })
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}
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// Fetch conversations from Chat Service
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const convParams = new URLSearchParams()
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if (startDate) convParams.append('startDate', startDate)
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if (endDate) convParams.append('endDate', endDate)
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const conversationsResponse = await fetch(
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`${CHAT_SERVICE_URL}/api/conversations?${convParams.toString()}&limit=1000`,
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{
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headers: {
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Authorization: `Bearer ${session.access_token}`,
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},
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}
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)
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if (!conversationsResponse.ok) {
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throw new Error('Failed to fetch conversations')
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}
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const conversationsData = await conversationsResponse.json()
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let conversations = conversationsData.conversations || []
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// Filter by date range if provided
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if (startDate || endDate) {
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conversations = conversations.filter((conv: { started_at: string }) => {
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const convDate = new Date(conv.started_at)
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if (startDate && convDate < new Date(startDate)) return false
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if (endDate && convDate > new Date(endDate)) return false
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return true
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})
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}
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// Group conversations by date
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const timelineMap = new Map<string, number>()
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const channelMap = new Map<string, number>()
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let totalDuration = 0
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let conversationsWithDuration = 0
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conversations.forEach((conv: { started_at: string; ended_at?: string; channel: string }) => {
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// Timeline grouping
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const date = new Date(conv.started_at)
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let dateKey: string
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if (groupBy === 'week') {
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const weekStart = new Date(date)
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weekStart.setDate(date.getDate() - date.getDay())
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dateKey = weekStart.toISOString().split('T')[0]
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} else if (groupBy === 'month') {
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dateKey = `${date.getFullYear()}-${String(date.getMonth() + 1).padStart(2, '0')}`
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} else {
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dateKey = date.toISOString().split('T')[0]
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}
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timelineMap.set(dateKey, (timelineMap.get(dateKey) || 0) + 1)
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// Channel grouping
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channelMap.set(conv.channel, (channelMap.get(conv.channel) || 0) + 1)
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// Calculate duration
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if (conv.ended_at) {
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const duration = new Date(conv.ended_at).getTime() - new Date(conv.started_at).getTime()
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totalDuration += duration
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conversationsWithDuration++
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}
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})
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// Convert timeline map to array
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const timeline = Array.from(timelineMap.entries())
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.map(([date, count]) => ({ date, count }))
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.sort((a, b) => a.date.localeCompare(b.date))
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// Convert channel map to array
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const byChannel = Array.from(channelMap.entries()).map(([channel, count]) => ({
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channel,
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count,
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}))
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// Calculate average duration in seconds
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const avgDuration = conversationsWithDuration > 0
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? Math.round(totalDuration / conversationsWithDuration / 1000)
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: 0
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return NextResponse.json({
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timeline,
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byChannel,
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avgDuration,
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})
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} catch (error) {
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logger.error('Analytics conversations error', { error })
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return NextResponse.json(
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{ error: 'Failed to fetch conversation analytics' },
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{ status: 500 }
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)
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}
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}, { requireCompany: true })
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}
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