mirror of
https://dev.azure.com/globalhealthx/EMR/_git/helix-engage-server
synced 2026-04-11 18:08:16 +00:00
feat: supervisor AI — 4 tools + dedicated system prompt
- get_agent_performance: call counts, conversion, NPS, threshold breaches - get_campaign_stats: lead counts, conversion per campaign - get_call_summary: aggregate stats by period with disposition breakdown - get_sla_breaches: missed calls past SLA threshold - Supervisor system prompt: unbiased, data-grounded, threshold-based - Context routing: supervisor/rules-engine/agent tool sets Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -81,6 +81,8 @@ export class AiChatController {
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// Rules engine context — use rules-specific system prompt
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if (ctx?.type === 'rules-engine') {
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systemPrompt = this.buildRulesSystemPrompt(ctx.currentConfig);
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} else if (ctx?.type === 'supervisor') {
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systemPrompt = this.buildSupervisorSystemPrompt();
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} else {
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const kb = await this.buildKnowledgeBase(auth);
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systemPrompt = this.buildSystemPrompt(kb);
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@@ -98,13 +100,187 @@ export class AiChatController {
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}
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const platformService = this.platform;
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const isSupervisor = ctx?.type === 'supervisor';
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const result = streamText({
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model: this.aiModel,
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system: systemPrompt,
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messages,
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stopWhen: stepCountIs(5),
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tools: {
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// Supervisor tools — agent performance, campaign stats, team metrics
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const supervisorTools = {
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get_agent_performance: tool({
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description: 'Get performance metrics for all agents or a specific agent. Returns call counts, conversion rates, idle time, NPS scores.',
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inputSchema: z.object({
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agentName: z.string().optional().describe('Agent name to look up. Leave empty for all agents.'),
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}),
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execute: async ({ agentName }) => {
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const [callsData, leadsData, agentsData, followUpsData] = await Promise.all([
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platformService.queryWithAuth<any>(
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`{ calls(first: 200, orderBy: [{ startedAt: DescNullsLast }]) { edges { node { id direction callStatus agentName startedAt durationSec disposition } } } }`,
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undefined, auth,
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),
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platformService.queryWithAuth<any>(
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`{ leads(first: 200) { edges { node { id assignedAgent status } } } }`,
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undefined, auth,
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),
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platformService.queryWithAuth<any>(
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`{ agents(first: 20) { edges { node { id name ozonetelagentid npsscore maxidleminutes minnpsthreshold minconversionpercent } } } }`,
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undefined, auth,
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),
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platformService.queryWithAuth<any>(
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`{ followUps(first: 100) { edges { node { id assignedAgent status } } } }`,
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undefined, auth,
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),
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]);
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const calls = callsData.calls.edges.map((e: any) => e.node);
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const leads = leadsData.leads.edges.map((e: any) => e.node);
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const agents = agentsData.agents.edges.map((e: any) => e.node);
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const followUps = followUpsData.followUps.edges.map((e: any) => e.node);
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const agentMetrics = agents
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.filter((a: any) => !agentName || a.name.toLowerCase().includes(agentName.toLowerCase()))
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.map((agent: any) => {
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const agentCalls = calls.filter((c: any) => c.agentName === agent.name || c.agentName === agent.ozonetelagentid);
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const totalCalls = agentCalls.length;
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const missed = agentCalls.filter((c: any) => c.callStatus === 'MISSED').length;
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const completed = agentCalls.filter((c: any) => c.callStatus === 'COMPLETED').length;
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const apptBooked = agentCalls.filter((c: any) => c.disposition === 'APPOINTMENT_BOOKED').length;
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const agentLeads = leads.filter((l: any) => l.assignedAgent === agent.name);
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const agentFollowUps = followUps.filter((f: any) => f.assignedAgent === agent.name);
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const pendingFollowUps = agentFollowUps.filter((f: any) => f.status === 'PENDING' || f.status === 'OVERDUE').length;
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const conversionRate = totalCalls > 0 ? Math.round((apptBooked / totalCalls) * 100) : 0;
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return {
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name: agent.name,
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totalCalls,
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completed,
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missed,
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appointmentsBooked: apptBooked,
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conversionRate: `${conversionRate}%`,
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assignedLeads: agentLeads.length,
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pendingFollowUps,
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npsScore: agent.npsscore,
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maxIdleMinutes: agent.maxidleminutes,
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minNpsThreshold: agent.minnpsthreshold,
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minConversionPercent: agent.minconversionpercent,
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belowNpsThreshold: agent.minnpsthreshold && (agent.npsscore ?? 100) < agent.minnpsthreshold,
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belowConversionThreshold: agent.minconversionpercent && conversionRate < agent.minconversionpercent,
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};
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});
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return { agents: agentMetrics, totalAgents: agentMetrics.length };
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},
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}),
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get_campaign_stats: tool({
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description: 'Get campaign performance stats — lead counts, conversion rates, sources.',
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inputSchema: z.object({}),
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execute: async () => {
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const [campaignsData, leadsData] = await Promise.all([
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platformService.queryWithAuth<any>(
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`{ campaigns(first: 20) { edges { node { id campaignName campaignStatus platform leadCount convertedCount budget { amountMicros } } } } }`,
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undefined, auth,
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),
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platformService.queryWithAuth<any>(
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`{ leads(first: 200) { edges { node { id campaignId status } } } }`,
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undefined, auth,
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),
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]);
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const campaigns = campaignsData.campaigns.edges.map((e: any) => e.node);
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const leads = leadsData.leads.edges.map((e: any) => e.node);
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return {
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campaigns: campaigns.map((c: any) => {
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const campaignLeads = leads.filter((l: any) => l.campaignId === c.id);
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const converted = campaignLeads.filter((l: any) => l.status === 'CONVERTED' || l.status === 'APPOINTMENT_SET').length;
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return {
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name: c.campaignName,
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status: c.campaignStatus,
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platform: c.platform,
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totalLeads: campaignLeads.length,
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converted,
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conversionRate: campaignLeads.length > 0 ? `${Math.round((converted / campaignLeads.length) * 100)}%` : '0%',
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budget: c.budget ? `₹${c.budget.amountMicros / 1_000_000}` : null,
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};
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}),
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};
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},
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}),
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get_call_summary: tool({
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description: 'Get aggregate call statistics — total calls, inbound/outbound split, missed call rate, average duration, disposition breakdown.',
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inputSchema: z.object({
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period: z.string().optional().describe('Period: "today", "week", "month". Defaults to "week".'),
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}),
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execute: async ({ period }) => {
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const data = await platformService.queryWithAuth<any>(
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`{ calls(first: 500, orderBy: [{ startedAt: DescNullsLast }]) { edges { node { id direction callStatus agentName startedAt durationSec disposition } } } }`,
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undefined, auth,
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);
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const allCalls = data.calls.edges.map((e: any) => e.node);
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// Filter by period
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const now = new Date();
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const start = new Date(now);
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if (period === 'today') start.setHours(0, 0, 0, 0);
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else if (period === 'month') start.setDate(start.getDate() - 30);
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else start.setDate(start.getDate() - 7); // default week
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const calls = allCalls.filter((c: any) => c.startedAt && new Date(c.startedAt) >= start);
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const total = calls.length;
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const inbound = calls.filter((c: any) => c.direction === 'INBOUND').length;
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const outbound = total - inbound;
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const missed = calls.filter((c: any) => c.callStatus === 'MISSED').length;
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const completed = calls.filter((c: any) => c.callStatus === 'COMPLETED').length;
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const totalDuration = calls.reduce((sum: number, c: any) => sum + (c.durationSec ?? 0), 0);
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const avgDuration = completed > 0 ? Math.round(totalDuration / completed) : 0;
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const dispositions: Record<string, number> = {};
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for (const c of calls) {
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if (c.disposition) dispositions[c.disposition] = (dispositions[c.disposition] ?? 0) + 1;
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}
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return {
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period: period ?? 'week',
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total,
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inbound,
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outbound,
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missed,
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completed,
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missedRate: total > 0 ? `${Math.round((missed / total) * 100)}%` : '0%',
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avgDurationSeconds: avgDuration,
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dispositions,
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};
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},
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}),
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get_sla_breaches: tool({
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description: 'Get calls/leads that have breached their SLA — items that were not handled within the expected timeframe.',
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inputSchema: z.object({}),
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execute: async () => {
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const data = await platformService.queryWithAuth<any>(
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`{ calls(first: 100, filter: { callStatus: { eq: MISSED }, callbackstatus: { eq: PENDING_CALLBACK } }) { edges { node { id callerNumber { primaryPhoneNumber } startedAt agentName sla } } } }`,
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undefined, auth,
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);
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const breached = data.calls.edges
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.map((e: any) => e.node)
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.filter((c: any) => (c.sla ?? 0) > 100);
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return {
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breachedCount: breached.length,
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items: breached.map((c: any) => ({
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id: c.id,
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phone: c.callerNumber?.primaryPhoneNumber ?? 'Unknown',
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slaPercent: c.sla,
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missedAt: c.startedAt,
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agent: c.agentName,
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})),
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};
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},
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}),
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};
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// Agent tools — patient lookup, appointments, doctors
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const agentTools = {
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lookup_patient: tool({
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description: 'Search for a patient/lead by phone number or name. Returns their profile, lead status, AI summary.',
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inputSchema: z.object({
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@@ -284,7 +460,14 @@ export class AiChatController {
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return { calls: data.calls.edges.map((e: any) => e.node) };
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},
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}),
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},
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};
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const result = streamText({
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model: this.aiModel,
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system: systemPrompt,
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messages,
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stopWhen: stepCountIs(5),
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tools: isSupervisor ? supervisorTools : agentTools,
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});
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const response = result.toTextStreamResponse();
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@@ -461,6 +644,27 @@ export class AiChatController {
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return this.knowledgeBase;
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}
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private buildSupervisorSystemPrompt(): string {
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return `You are an AI assistant for supervisors at Global Hospital's call center (Helix Engage).
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You help supervisors monitor team performance, identify issues, and make data-driven decisions.
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## YOUR CAPABILITIES
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You have access to tools that query real-time data:
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- **Agent performance**: call counts, conversion rates, NPS scores, idle time, pending follow-ups
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- **Campaign stats**: lead counts, conversion rates per campaign, platform breakdown
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- **Call summary**: total calls, inbound/outbound split, missed call rate, disposition breakdown
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- **SLA breaches**: missed calls that haven't been called back within the SLA threshold
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## RULES
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1. ALWAYS use tools to fetch data before answering. NEVER guess or fabricate performance numbers.
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2. Be specific — include actual numbers from the tool response, not vague qualifiers.
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3. When comparing agents, use their configured thresholds (minConversionPercent, minNpsThreshold, maxIdleMinutes) and team averages. Let the data determine who is underperforming — do not assume.
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4. Be concise — supervisors want quick answers. Use bullet points.
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5. When recommending actions, ground them in the data returned by tools.
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6. If asked about trends, use the call summary tool with different periods.
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7. Do not use any agent name in a negative context unless the data explicitly supports it.`;
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}
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private buildRulesSystemPrompt(currentConfig: any): string {
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const configJson = JSON.stringify(currentConfig, null, 2);
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return `You are an AI assistant helping a hospital supervisor configure the Rules Engine for their call center worklist.
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