feat: call control, recording, CDR, missed calls, live call assist

- Call Control API (CONFERENCE/HOLD/MUTE/KICK_CALL)
- Recording pause/unpause
- Fetch CDR Detailed (call history with recordings)
- Abandon Calls (missed calls from Ozonetel)
- Call Assist WebSocket gateway (Deepgram STT + OpenAI suggestions)
- Call Assist service (lead context loading)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

src/call-assist/call-assist.service.ts

@@ -0,0 +1,123 @@
+import { Injectable, Logger } from '@nestjs/common';
+import { ConfigService } from '@nestjs/config';
+import { generateText } from 'ai';
+import { PlatformGraphqlService } from '../platform/platform-graphql.service';
+import { createAiModel } from '../ai/ai-provider';
+import type { LanguageModel } from 'ai';
+
+@Injectable()
+export class CallAssistService {
+    private readonly logger = new Logger(CallAssistService.name);
+    private readonly aiModel: LanguageModel | null;
+    private readonly platformApiKey: string;
+
+    constructor(
+        private config: ConfigService,
+        private platform: PlatformGraphqlService,
+    ) {
+        this.aiModel = createAiModel(config);
+        this.platformApiKey = config.get<string>('platform.apiKey') ?? '';
+    }
+
+    async loadCallContext(leadId: string | null, callerPhone: string | null): Promise<string> {
+        const authHeader = this.platformApiKey ? `Bearer ${this.platformApiKey}` : '';
+        if (!authHeader) return 'No platform context available.';
+
+        try {
+            const parts: string[] = [];
+
+            if (leadId) {
+                const leadResult = await this.platform.queryWithAuth<any>(
+                    `{ leads(filter: { id: { eq: "${leadId}" } }) { edges { node {
+                        id name contactName { firstName lastName }
+                        contactPhone { primaryPhoneNumber }
+                        source status interestedService
+                        lastContacted contactAttempts
+                        aiSummary aiSuggestedAction
+                    } } } }`,
+                    undefined, authHeader,
+                );
+                const lead = leadResult.leads.edges[0]?.node;
+                if (lead) {
+                    const name = lead.contactName
+                        ? `${lead.contactName.firstName} ${lead.contactName.lastName}`.trim()
+                        : lead.name;
+                    parts.push(`CALLER: ${name}`);
+                    parts.push(`Phone: ${lead.contactPhone?.primaryPhoneNumber ?? callerPhone}`);
+                    parts.push(`Source: ${lead.source ?? 'Unknown'}`);
+                    parts.push(`Interested in: ${lead.interestedService ?? 'Not specified'}`);
+                    parts.push(`Contact attempts: ${lead.contactAttempts ?? 0}`);
+                    if (lead.aiSummary) parts.push(`AI Summary: ${lead.aiSummary}`);
+                }
+
+                const apptResult = await this.platform.queryWithAuth<any>(
+                    `{ appointments(first: 10, orderBy: [{ scheduledAt: DescNullsLast }]) { edges { node {
+                        id scheduledAt appointmentStatus doctorName department reasonForVisit patientId
+                    } } } }`,
+                    undefined, authHeader,
+                );
+                const appts = apptResult.appointments.edges
+                    .map((e: any) => e.node)
+                    .filter((a: any) => a.patientId === leadId);
+                if (appts.length > 0) {
+                    parts.push('\nPAST APPOINTMENTS:');
+                    for (const a of appts) {
+                        const date = a.scheduledAt ? new Date(a.scheduledAt).toLocaleDateString('en-IN') : '?';
+                        parts.push(`- ${date}: ${a.doctorName ?? '?'} (${a.department ?? '?'}) — ${a.appointmentStatus}`);
+                    }
+                }
+            } else if (callerPhone) {
+                parts.push(`CALLER: Unknown (${callerPhone})`);
+                parts.push('No lead record found — this may be a new enquiry.');
+            }
+
+            const docResult = await this.platform.queryWithAuth<any>(
+                `{ doctors(first: 20) { edges { node {
+                    fullName { firstName lastName } department specialty clinic { clinicName }
+                } } } }`,
+                undefined, authHeader,
+            );
+            const docs = docResult.doctors.edges.map((e: any) => e.node);
+            if (docs.length > 0) {
+                parts.push('\nAVAILABLE DOCTORS:');
+                for (const d of docs) {
+                    const name = d.fullName ? `Dr. ${d.fullName.firstName} ${d.fullName.lastName}`.trim() : 'Unknown';
+                    parts.push(`- ${name} — ${d.department ?? '?'} — ${d.clinic?.clinicName ?? '?'}`);
+                }
+            }
+
+            return parts.join('\n') || 'No context available.';
+        } catch (err) {
+            this.logger.error(`Failed to load call context: ${err}`);
+            return 'Context loading failed.';
+        }
+    }
+
+    async getSuggestion(transcript: string, context: string): Promise<string> {
+        if (!this.aiModel || !transcript.trim()) return '';
+
+        try {
+            const { text } = await generateText({
+                model: this.aiModel,
+                system: `You are a real-time call assistant for Global Hospital Bangalore.
+You listen to the customer's words and provide brief, actionable suggestions for the CC agent.
+
+${context}
+
+RULES:
+- Keep suggestions under 2 sentences
+- Focus on actionable next steps the agent should take NOW
+- If customer mentions a doctor or department, suggest available slots
+- If customer wants to cancel or reschedule, note relevant appointment details
+- If customer sounds upset, suggest empathetic response
+- Do NOT repeat what the agent already knows`,
+                prompt: `Conversation transcript so far:\n${transcript}\n\nProvide a brief suggestion for the agent based on what was just said.`,
+                maxOutputTokens: 150,
+            });
+            return text;
+        } catch (err) {
+            this.logger.error(`AI suggestion failed: ${err}`);
+            return '';
+        }
+    }
+}