Fireflies.ai Performance Tuning

Overview

Optimize Fireflies.ai transcript retrieval and meeting data processing. Focus on GraphQL query efficiency, transcript caching, and webhook throughput for high-volume meeting analytics pipelines.

Prerequisites

• Fireflies.ai API key with GraphQL access

• Node.js 18+ with GraphQL client

• Understanding of meeting transcript structure

• Redis available for transcript caching (recommended)

Instructions

Step 1: Optimize GraphQL Queries with Field Selection

// Only request fields you need - transcripts can be large const LIGHT_TRANSCRIPT_QUERY = query GetTranscripts($limit: Int) { transcripts(limit: $limit) { id title date duration organizer_email participants } };

// Full transcript only when needed const FULL_TRANSCRIPT_QUERY = query GetTranscript($id: String!) { transcript(id: $id) { id title sentences { speaker_name text start_time end_time } action_items summary { overview keywords } } };

async function getTranscriptSummaries(limit = 50) { return graphqlClient.request(LIGHT_TRANSCRIPT_QUERY, { limit }); }

Step 2: Cache Transcripts with TTL

import { LRUCache } from 'lru-cache';

const transcriptCache = new LRUCache<string, any>({ max: 200, # HTTP 200 OK ttl: 1000 * 60 * 30, // 30 min - transcripts are immutable # 1000: 1 second in ms });

async function getCachedTranscript(id: string) { const cached = transcriptCache.get(id); if (cached) return cached;

const result = await graphqlClient.request(FULL_TRANSCRIPT_QUERY, { id }); transcriptCache.set(id, result.transcript); return result.transcript; }

Step 3: Batch Process Meeting Data

async function batchProcessMeetings( meetingIds: string[], concurrency = 3 ) { const results: any[] = []; for (let i = 0; i < meetingIds.length; i += concurrency) { const batch = meetingIds.slice(i, i + concurrency); const batchResults = await Promise.all( batch.map(id => getCachedTranscript(id)) ); results.push(...batchResults); // Respect rate limits: 50 req/min if (i + concurrency < meetingIds.length) { await new Promise(r => setTimeout(r, 1200)); # 1200 = configured value } } return results; }

Step 4: Efficient Webhook Processing

import { createHmac } from 'crypto';

// Process webhooks asynchronously with a queue const webhookQueue: any[] = [];

async function handleWebhook(payload: any) { // Acknowledge immediately webhookQueue.push(payload); // Process in background setImmediate(() => processWebhookQueue()); }

async function processWebhookQueue() { while (webhookQueue.length > 0) { const event = webhookQueue.shift(); if (event.event_type === 'Transcription completed') { // Pre-cache the transcript await getCachedTranscript(event.meeting_id); } } }

Error Handling

Issue Cause Solution

GraphQL timeout Requesting full transcript list Use pagination with limit param

Rate limit 429 Over 50 requests/minute Add 1.2s delay between batches

Large response OOM Fetching all sentences Stream sentences or paginate

Stale webhook data Cache not warmed Pre-fetch on webhook events

Examples

Meeting Analytics Pipeline

async function analyzeMeetingTrends(days = 30) { const since = new Date(Date.now() - days * 86400000).toISOString(); # 86400000 = configured value const summaries = await getTranscriptSummaries(200); # HTTP 200 OK

const recent = summaries.transcripts.filter( (t: any) => new Date(t.date) > new Date(since) );

return { totalMeetings: recent.length, avgDuration: recent.reduce((s: number, t: any) => s + t.duration, 0) / recent.length, topParticipants: countParticipants(recent), }; }

Resources

• Fireflies GraphQL API

• Fireflies Rate Limits

Output

• Configuration files or code changes applied to the project

• Validation report confirming correct implementation

• Summary of changes made and their rationale