Agent skill
groq-hello-world
Create a minimal working Groq chat completion example. Use when starting a new Groq integration, testing your setup, or learning basic Groq API patterns. Trigger with phrases like "groq hello world", "groq example", "groq quick start", "simple groq code".
Install this agent skill to your Project
npx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/main/plugins/saas-packs/groq-pack/skills/groq-hello-world
SKILL.md
Groq Hello World
Overview
Build a minimal chat completion with Groq's LPU inference API. Groq uses an OpenAI-compatible endpoint, so the API shape is familiar -- but responses arrive 10-50x faster than GPU-based providers.
Prerequisites
groq-sdkinstalled (npm install groq-sdk)GROQ_API_KEYenvironment variable set- Completed
groq-install-authsetup
Instructions
Step 1: Basic Chat Completion (TypeScript)
import Groq from "groq-sdk";
const groq = new Groq();
async function main() {
const completion = await groq.chat.completions.create({
model: "llama-3.3-70b-versatile",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "What is Groq's LPU and why is it fast?" },
],
});
console.log(completion.choices[0].message.content);
console.log(`Tokens: ${completion.usage?.total_tokens}`);
}
main().catch(console.error);
Step 2: Streaming Response
async function streamExample() {
const stream = await groq.chat.completions.create({
model: "llama-3.3-70b-versatile",
messages: [
{ role: "user", content: "Explain quantum computing in 3 sentences." },
],
stream: true,
});
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content || "";
process.stdout.write(content);
}
console.log(); // newline
}
Step 3: Python Equivalent
from groq import Groq
client = Groq()
completion = client.chat.completions.create(
model="llama-3.3-70b-versatile",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is Groq's LPU and why is it fast?"},
],
)
print(completion.choices[0].message.content)
print(f"Tokens: {completion.usage.total_tokens}")
Step 4: Try Different Models
// Speed tier -- fastest responses (~560 tok/s)
const fast = await groq.chat.completions.create({
model: "llama-3.1-8b-instant",
messages: [{ role: "user", content: "Hello!" }],
});
// Quality tier -- best reasoning (~280 tok/s)
const quality = await groq.chat.completions.create({
model: "llama-3.3-70b-versatile",
messages: [{ role: "user", content: "Explain monads in Haskell." }],
});
// Vision tier -- multimodal understanding
const vision = await groq.chat.completions.create({
model: "meta-llama/llama-4-scout-17b-16e-instruct",
messages: [{
role: "user",
content: [
{ type: "text", text: "Describe this image." },
{ type: "image_url", image_url: { url: "https://example.com/photo.jpg" } },
],
}],
});
Available Models (Current)
| Model ID | Params | Context | Speed | Best For |
|---|---|---|---|---|
llama-3.1-8b-instant |
8B | 128K | ~560 tok/s | Classification, extraction, fast tasks |
llama-3.3-70b-versatile |
70B | 128K | ~280 tok/s | General purpose, reasoning, code |
llama-3.3-70b-specdec |
70B | 128K | Faster | Same quality, speculative decoding |
meta-llama/llama-4-scout-17b-16e-instruct |
17Bx16E | 128K | ~460 tok/s | Vision, multimodal |
meta-llama/llama-4-maverick-17b-128e-instruct |
17Bx128E | 128K | — | Best multimodal quality |
Response Structure
interface ChatCompletion {
id: string; // "chatcmpl-xxx"
object: "chat.completion";
created: number; // Unix timestamp
model: string; // Actual model used
choices: [{
index: number;
message: { role: "assistant"; content: string };
finish_reason: "stop" | "length" | "tool_calls";
}];
usage: {
prompt_tokens: number;
completion_tokens: number;
total_tokens: number;
queue_time: number; // Groq-specific: seconds in queue
prompt_time: number; // Groq-specific: seconds for prompt
completion_time: number; // Groq-specific: seconds for completion
total_time: number; // Groq-specific: total processing seconds
};
}
Error Handling
| Error | Cause | Solution |
|---|---|---|
401 Invalid API Key |
Key not set or invalid | Check GROQ_API_KEY env var |
model_not_found |
Typo in model ID or deprecated model | Check model list at console.groq.com/docs/models |
429 Rate limit |
Free tier: 30 RPM on large models | Wait for retry-after header value |
context_length_exceeded |
Prompt + max_tokens > model context | Reduce prompt size or set lower max_tokens |
Resources
Next Steps
Proceed to groq-local-dev-loop for development workflow setup.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
dockerfile-generator
Dockerfile Generator - Auto-activating skill for DevOps Basics. Triggers on: dockerfile generator, dockerfile generator Part of the DevOps Basics skill category.
branch-naming-helper
Branch Naming Helper - Auto-activating skill for DevOps Basics. Triggers on: branch naming helper, branch naming helper Part of the DevOps Basics skill category.
readme-generator
Readme Generator - Auto-activating skill for DevOps Basics. Triggers on: readme generator, readme generator Part of the DevOps Basics skill category.
makefile-generator
Makefile Generator - Auto-activating skill for DevOps Basics. Triggers on: makefile generator, makefile generator Part of the DevOps Basics skill category.
gitignore-generator
Gitignore Generator - Auto-activating skill for DevOps Basics. Triggers on: gitignore generator, gitignore generator Part of the DevOps Basics skill category.
pre-commit-hook-setup
Pre Commit Hook Setup - Auto-activating skill for DevOps Basics. Triggers on: pre commit hook setup, pre commit hook setup Part of the DevOps Basics skill category.
Didn't find tool you were looking for?