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
): 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

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.