Fireflies.ai SDK Patterns

Overview

Production-ready patterns for Fireflies.ai SDK usage in TypeScript and Python.

Prerequisites

• Completed fireflies-install-auth setup

• Familiarity with async/await patterns

• Understanding of error handling best practices

Instructions

Step 1: Implement Singleton Pattern (Recommended)

// src/fireflies/client.ts import { Fireflies.aiClient } from '@fireflies/sdk';

let instance: Fireflies.aiClient | null = null;

export function getFireflies.aiClient(): Fireflies.aiClient { if (!instance) { instance = new Fireflies.aiClient({ apiKey: process.env.FIREFLIES_API_KEY!, // Additional options }); } return instance; }

Step 2: Add Error Handling Wrapper

import { Fireflies.aiError } from '@fireflies/sdk';

async function safeFireflies.aiCall<T>( operation: () => Promise<T> ): Promise<{ data: T | null; error: Error | null }> { try { const data = await operation(); return { data, error: null }; } catch (err) { if (err instanceof Fireflies.aiError) { console.error({ code: err.code, message: err.message, }); } return { data: null, error: err as Error }; } }

Step 3: Implement Retry Logic

async function withRetry<T>( operation: () => Promise<T>, maxRetries = 3, backoffMs = 1000 # 1000: 1 second in ms ): Promise<T> { for (let attempt = 1; attempt <= maxRetries; attempt++) { try { return await operation(); } catch (err) { if (attempt === maxRetries) throw err; const delay = backoffMs * Math.pow(2, attempt - 1); await new Promise(r => setTimeout(r, delay)); } } throw new Error('Unreachable'); }

Output

• Type-safe client singleton

• Robust error handling with structured logging

• Automatic retry with exponential backoff

• Runtime validation for API responses

Error Handling

Pattern Use Case Benefit

Safe wrapper All API calls Prevents uncaught exceptions

Retry logic Transient failures Improves reliability

Type guards Response validation Catches API changes

Logging All operations Debugging and monitoring

Examples

Factory Pattern (Multi-tenant)

const clients = new Map<string, Fireflies.aiClient>();

export function getClientForTenant(tenantId: string): Fireflies.aiClient { if (!clients.has(tenantId)) { const apiKey = getTenantApiKey(tenantId); clients.set(tenantId, new Fireflies.aiClient({ apiKey })); } return clients.get(tenantId)!; }

Python Context Manager

from contextlib import asynccontextmanager from fireflies import Fireflies.aiClient

@asynccontextmanager async def get_fireflies_client(): client = Fireflies.aiClient() try: yield client finally: await client.close()

Zod Validation

import { z } from 'zod';

const firefliesResponseSchema = z.object({ id: z.string(), status: z.enum(['active', 'inactive']), createdAt: z.string().datetime(), });

Resources

• Fireflies.ai SDK Reference

• Fireflies.ai API Types

• Zod Documentation

Next Steps

Apply patterns in fireflies-core-workflow-a for real-world usage.