Groq SDK Patterns

Groq SDK Patterns

Overview

Production patterns for the groq-sdk package. The Groq SDK mirrors the OpenAI SDK interface (chat.completions.create), so patterns feel familiar but must account for Groq-specific behavior: extreme speed (500+ tok/​s), aggressive rate limits on free tier, and unique response metadata like queue_time and completion_time.

Prerequisites

• groq-sdk installed
• Understanding of async/​await and error handling
• Familiarity with OpenAI SDK patterns (Groq is API-compatible)

Instructions

Step 1: Typed Client Singleton

// src/​groq/​client.ts
import Groq from "groq-sdk";

let _client: Groq | null = null;

export function getGroq(): Groq {
  if (!_client) {
    _client = new Groq({
      apiKey: process.env.GROQ_API_KEY,
      maxRetries: 3,
      timeout: 30_000,
    });
  }
  return _client;
}

Step 2: Type-Safe Completion Wrapper

import Groq from "groq-sdk";
import type { ChatCompletionMessageParam } from "groq-sdk/​resources/​chat/​completions";

const groq = getGroq();

interface CompletionResult {
  content: string;
  model: string;
  tokens: { prompt: number; completion: number; total: number };
  timing: { queueMs: number; totalMs: number; tokensPerSec: number };
}

async function complete(
  messages: ChatCompletionMessageParam[],
  model = "llama-3.3-70b-versatile",
  options?: { maxTokens?: number; temperature?: number }
): Promise<CompletionResult> {
  const response = await groq.chat.completions.create({
    model,
    messages,
    max_tokens: options?.maxTokens ?? 1024,
    temperature: options?.temperature ?? 0.7,
  });

  const usage = response.usage!;
  return {
    content: response.choices[0].message.content || "",
    model: response.model,
    tokens: {
      prompt: usage.prompt_tokens,
      completion: usage.completion_tokens,
      total: usage.total_tokens,
    },
    timing: {
      queueMs: (usage.queue_time ?? 0) * 1000,
      totalMs: (usage.total_time ?? 0) * 1000,
      tokensPerSec: usage.completion_tokens / ((usage.completion_time ?? 1) || 1),
    },
  };
}

Step 3: Streaming with Typed Events

async function* streamCompletion(
  messages: ChatCompletionMessageParam[],
  model = "llama-3.3-70b-versatile"
): AsyncGenerator<string> {
  const stream = await groq.chat.completions.create({
    model,
    messages,
    stream: true,
    max_tokens: 2048,
  });

  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content;
    if (content) yield content;
  }
}

// Usage
async function printStream(prompt: string) {
  const messages: ChatCompletionMessageParam[] = [
    { role: "user", content: prompt },
  ];

  for await (const token of streamCompletion(messages)) {
    process.stdout.write(token);
  }
}

Step 4: Error Handling with Groq Error Types

import Groq from "groq-sdk";

async function safeComplete(
  messages: ChatCompletionMessageParam[],
  model = "llama-3.3-70b-versatile"
): Promise<{ data: CompletionResult | null; error: string | null }> {
  try {
    const data = await complete(messages, model);
    return { data, error: null };
  } catch (err) {
    if (err instanceof Groq.APIError) {
      // Groq SDK throws typed API errors
      if (err.status === 429) {
        const retryAfter = err.headers?.["retry-after"];
        return { data: null, error: `Rate limited. Retry after ${retryAfter}s` };
      }
      if (err.status === 401) {
        return { data: null, error: "Invalid API key. Check GROQ_API_KEY." };
      }
      return { data: null, error: `API error ${err.status}: ${err.message}` };
    }
    if (err instanceof Groq.APIConnectionError) {
      return { data: null, error: "Network error connecting to api.groq.com" };
    }
    throw err; // Unknown error, let it propagate
  }
}

Step 5: Retry with Exponential Backoff

async function withRetry<T>(
  operation: () => Promise<T>,
  maxRetries = 3,
  baseDelayMs = 1000
): Promise<T> {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await operation();
    } catch (err) {
      if (err instanceof Groq.APIError && err.status === 429) {
        const retryAfter = parseInt(err.headers?.["retry-after"] || "0");
        const delay = retryAfter > 0
          ? retryAfter * 1000
          : baseDelayMs * Math.pow(2, attempt) + Math.random() * 500;
        console.warn(`Rate limited. Waiting ${(delay / 1000).toFixed(1)}s...`);
        await new Promise((r) => setTimeout(r, delay));
        continue;
      }
      throw err; // Non-retryable error
    }
  }
  throw new Error(`Failed after ${maxRetries} retries`);
}

Step 6: Python Patterns

# Synchronous client
from groq import Groq

client = Groq()  # Reads GROQ_API_KEY from env

completion = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[{"role": "user", "content": "Hello"}],
)

# Async client
from groq import AsyncGroq

async_client = AsyncGroq()

async def async_complete(prompt: str) -> str:
    completion = await async_client.chat.completions.create(
        model="llama-3.3-70b-versatile",
        messages=[{"role": "user", "content": prompt}],
    )
    return completion.choices[0].message.content

# Streaming
stream = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[{"role": "user", "content": "Hello"}],
    stream=True,
)
for chunk in stream:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="")

Step 7: Multi-Tenant Client Factory

const clients = new Map<string, Groq>();

export function getClientForTenant(tenantId: string, apiKey: string): Groq {
  if (!clients.has(tenantId)) {
    clients.set(tenantId, new Groq({ apiKey, maxRetries: 3 }));
  }
  return clients.get(tenantId)!;
}

Key SDK Differences from OpenAI

Error Handling

Resources

• Groq TypeScript SDK
• Groq API Reference
• Groq Error Codes

Next Steps

Apply patterns in groq-core-workflow-a for real-world chat completions.