feat: event bus with Redpanda + AI insight consumer

- EventBusService: Kafka/Redpanda pub/sub with kafkajs, graceful fallback when broker unavailable - Topics: call.completed, call.missed, agent.state - AiInsightConsumer: on call.completed, fetches lead activity → OpenAI generates summary + suggested action → updates Lead entity on platform - Disposition endpoint emits call.completed event after Ozonetel dispose - EventsModule registered as @Global for cross-module injection - Redpanda container added to VPS docker-compose - Docker image rebuilt for linux/amd64 with kafkajs dependency Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-05-18 20:08:19 +00:00 · 2026-03-26 09:38:02 +05:30
parent 3c06a01e7b
commit 3e2e7372cc
8 changed files with 311 additions and 0 deletions
--- a/src/events/consumers/ai-insight.consumer.ts
+++ b/src/events/consumers/ai-insight.consumer.ts
@@ -0,0 +1,119 @@
+import { Injectable, Logger, OnModuleInit } from '@nestjs/common';
+import { ConfigService } from '@nestjs/config';
+import { generateObject } from 'ai';
+import { z } from 'zod';
+import { EventBusService } from '../event-bus.service';
+import { Topics } from '../event-types';
+import type { CallCompletedEvent } from '../event-types';
+import { PlatformGraphqlService } from '../../platform/platform-graphql.service';
+import { createAiModel } from '../../ai/ai-provider';
+import type { LanguageModel } from 'ai';
+
+@Injectable()
+export class AiInsightConsumer implements OnModuleInit {
+    private readonly logger = new Logger(AiInsightConsumer.name);
+    private readonly aiModel: LanguageModel | null;
+
+    constructor(
+        private eventBus: EventBusService,
+        private platform: PlatformGraphqlService,
+        private config: ConfigService,
+    ) {
+        this.aiModel = createAiModel(config);
+    }
+
+    onModuleInit() {
+        this.eventBus.on(Topics.CALL_COMPLETED, (event: CallCompletedEvent) => this.handleCallCompleted(event));
+    }
+
+    private async handleCallCompleted(event: CallCompletedEvent): Promise<void> {
+        if (!event.leadId) {
+            this.logger.debug('[AI-INSIGHT] No leadId — skipping');
+            return;
+        }
+
+        if (!this.aiModel) {
+            this.logger.debug('[AI-INSIGHT] No AI model configured — skipping');
+            return;
+        }
+
+        this.logger.log(`[AI-INSIGHT] Generating insight for lead ${event.leadId}`);
+
+        try {
+            // Fetch lead + all activities
+            const data = await this.platform.query<any>(
+                `{ leads(filter: { id: { eq: "${event.leadId}" } }) { edges { node {
+                    id name contactName { firstName lastName }
+                    status source interestedService
+                    contactAttempts lastContacted
+                } } } }`,
+            );
+            const lead = data?.leads?.edges?.[0]?.node;
+            if (!lead) return;
+
+            const activityData = await this.platform.query<any>(
+                `{ leadActivities(first: 20, filter: { leadId: { eq: "${event.leadId}" } }, orderBy: [{ occurredAt: DescNullsLast }]) {
+                    edges { node { activityType summary occurredAt channel durationSec outcome } }
+                } }`,
+            );
+            const activities = activityData?.leadActivities?.edges?.map((e: any) => e.node) ?? [];
+
+            const leadName = lead.contactName
+                ? `${lead.contactName.firstName ?? ''} ${lead.contactName.lastName ?? ''}`.trim()
+                : lead.name ?? 'Unknown';
+
+            // Build context
+            const activitySummary = activities.map((a: any) =>
+                `${a.activityType}: ${a.summary} (${a.occurredAt ?? 'unknown date'})`,
+            ).join('\n');
+
+            // Generate insight
+            const { object } = await generateObject({
+                model: this.aiModel,
+                schema: z.object({
+                    summary: z.string().describe('2-3 sentence summary of this lead based on all their interactions'),
+                    suggestedAction: z.string().describe('One clear next action for the agent'),
+                }),
+                system: `You are a CRM assistant for Global Hospital Bangalore.
+Generate a brief, actionable insight about this lead based on their interaction history.
+Be specific — reference actual dates, dispositions, and patterns.
+If the lead has booked appointments, mention upcoming ones.
+If they keep calling about the same thing, note the pattern.`,
+                prompt: `Lead: ${leadName}
+Status: ${lead.status ?? 'Unknown'}
+Source: ${lead.source ?? 'Unknown'}
+Interested in: ${lead.interestedService ?? 'Not specified'}
+Contact attempts: ${lead.contactAttempts ?? 0}
+Last contacted: ${lead.lastContacted ?? 'Never'}
+
+Recent activity (newest first):
+${activitySummary || 'No activity recorded'}
+
+Latest call:
+- Direction: ${event.direction}
+- Duration: ${event.durationSec}s
+- Disposition: ${event.disposition}
+- Notes: ${event.notes ?? 'None'}`,
+                maxOutputTokens: 200,
+            });
+
+            // Update lead with new AI insight
+            await this.platform.query<any>(
+                `mutation($id: UUID!, $data: LeadUpdateInput!) { updateLead(id: $id, data: $data) { id } }`,
+                {
+                    id: event.leadId,
+                    data: {
+                        aiSummary: object.summary,
+                        aiSuggestedAction: object.suggestedAction,
+                        lastContacted: new Date().toISOString(),
+                        contactAttempts: (lead.contactAttempts ?? 0) + 1,
+                    },
+                },
+            );
+
+            this.logger.log(`[AI-INSIGHT] Updated lead ${event.leadId}: "${object.summary.substring(0, 60)}..."`);
+        } catch (err: any) {
+            this.logger.error(`[AI-INSIGHT] Failed for lead ${event.leadId}: ${err.message}`);
+        }
+    }
+}