groq-core-workflow-b
Execute Groq secondary workflows: audio transcription (Whisper), vision, text-to-speech, and batch model evaluation. Trigger with phrases like "groq whisper", "groq transcription", "groq audio", "groq vision", "groq TTS", "groq speech".
Best use case
groq-core-workflow-b is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Execute Groq secondary workflows: audio transcription (Whisper), vision, text-to-speech, and batch model evaluation. Trigger with phrases like "groq whisper", "groq transcription", "groq audio", "groq vision", "groq TTS", "groq speech".
Teams using groq-core-workflow-b should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/groq-core-workflow-b/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How groq-core-workflow-b Compares
| Feature / Agent | groq-core-workflow-b | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Execute Groq secondary workflows: audio transcription (Whisper), vision, text-to-speech, and batch model evaluation. Trigger with phrases like "groq whisper", "groq transcription", "groq audio", "groq vision", "groq TTS", "groq speech".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
ChatGPT vs Claude for Agent Skills
Compare ChatGPT and Claude for AI agent skills across coding, writing, research, and reusable workflow execution.
Cursor vs Codex for AI Workflows
Compare Cursor and Codex for AI coding workflows, repository assistance, debugging, refactoring, and reusable developer skills.
SKILL.md Source
# Groq Core Workflow B: Audio, Vision & Speech
## Overview
Beyond chat completions, Groq provides ultra-fast audio transcription (Whisper at 216x real-time), multimodal vision (Llama 4 Scout/Maverick), and text-to-speech. These endpoints use the same `groq-sdk` client.
## Prerequisites
- `groq-sdk` installed, `GROQ_API_KEY` set
- For audio: audio files in supported formats
- For vision: image URLs or base64 images
## Audio Models
| Model ID | Languages | Speed | Best For |
|----------|-----------|-------|----------|
| `whisper-large-v3` | 100+ | 164x real-time | Best accuracy, multilingual |
| `whisper-large-v3-turbo` | 100+ | 216x real-time | Best speed/accuracy balance |
**Supported audio formats**: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm
## Instructions
### Step 1: Audio Transcription (Whisper)
```typescript
import Groq from "groq-sdk";
import fs from "fs";
const groq = new Groq();
// Transcribe audio file
async function transcribe(filePath: string): Promise<string> {
const transcription = await groq.audio.transcriptions.create({
file: fs.createReadStream(filePath),
model: "whisper-large-v3-turbo",
response_format: "json", // or "text" or "verbose_json"
language: "en", // Optional: ISO 639-1 code
});
return transcription.text;
}
// With timestamps (verbose mode)
async function transcribeWithTimestamps(filePath: string) {
const transcription = await groq.audio.transcriptions.create({
file: fs.createReadStream(filePath),
model: "whisper-large-v3-turbo",
response_format: "verbose_json",
timestamp_granularities: ["segment"],
});
return transcription;
// Returns segments with start/end times
}
```
### Step 2: Audio Translation (to English)
```typescript
// Translate any language audio to English text
async function translateAudio(filePath: string): Promise<string> {
const translation = await groq.audio.translations.create({
file: fs.createReadStream(filePath),
model: "whisper-large-v3",
});
return translation.text;
}
```
### Step 3: Vision (Image Understanding)
```typescript
// Analyze images with Llama 4 Scout (up to 5 images per request)
async function analyzeImage(imageUrl: string, question: string) {
const completion = await groq.chat.completions.create({
model: "meta-llama/llama-4-scout-17b-16e-instruct",
messages: [
{
role: "user",
content: [
{ type: "text", text: question },
{ type: "image_url", image_url: { url: imageUrl } },
],
},
],
max_tokens: 1024,
});
return completion.choices[0].message.content;
}
// Multiple images
async function compareImages(urls: string[], prompt: string) {
const imageContent = urls.map((url) => ({
type: "image_url" as const,
image_url: { url },
}));
const completion = await groq.chat.completions.create({
model: "meta-llama/llama-4-scout-17b-16e-instruct",
messages: [{
role: "user",
content: [{ type: "text", text: prompt }, ...imageContent],
}],
max_tokens: 2048,
});
return completion.choices[0].message.content;
}
// Base64 image input
async function analyzeBase64Image(base64Data: string) {
return groq.chat.completions.create({
model: "meta-llama/llama-4-scout-17b-16e-instruct",
messages: [{
role: "user",
content: [
{ type: "text", text: "Describe this image in detail." },
{
type: "image_url",
image_url: { url: `data:image/jpeg;base64,${base64Data}` },
},
],
}],
});
}
```
### Step 4: Text-to-Speech
```typescript
// Generate speech from text
async function textToSpeech(text: string, outputPath: string) {
const response = await groq.audio.speech.create({
model: "playai-tts", // or "playai-tts-arabic"
input: text,
voice: "Arista-PlayAI", // See Groq docs for voice options
response_format: "wav", // wav, mp3, flac, opus, aac
});
const buffer = Buffer.from(await response.arrayBuffer());
fs.writeFileSync(outputPath, buffer);
console.log(`Audio saved to ${outputPath}`);
}
```
### Step 5: Python Audio Transcription
```python
from groq import Groq
client = Groq()
# Transcribe
with open("audio.mp3", "rb") as file:
transcription = client.audio.transcriptions.create(
file=("audio.mp3", file),
model="whisper-large-v3-turbo",
response_format="verbose_json",
)
print(transcription.text)
for segment in transcription.segments:
print(f"[{segment.start:.1f}s - {segment.end:.1f}s] {segment.text}")
```
### Step 6: Model Benchmarking
```typescript
// Compare models on same prompt for speed vs quality
async function benchmarkModels(prompt: string) {
const models = [
"llama-3.1-8b-instant",
"llama-3.3-70b-versatile",
"llama-3.3-70b-specdec",
];
for (const model of models) {
const start = performance.now();
const result = await groq.chat.completions.create({
model,
messages: [{ role: "user", content: prompt }],
max_tokens: 200,
});
const elapsed = performance.now() - start;
const tps = result.usage!.completion_tokens / ((result.usage as any).completion_time || 1);
console.log(
`${model.padEnd(45)} | ${elapsed.toFixed(0)}ms | ${tps.toFixed(0)} tok/s | ${result.usage!.total_tokens} tokens`
);
}
}
```
## Vision Model Limits
- Maximum 5 images per request
- Supported formats: JPEG, PNG, GIF, WebP
- Images fetched from URL or embedded as base64
- Vision models also support tool use, JSON mode, and streaming
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| `Invalid file format` | Unsupported audio type | Convert to mp3/wav/flac first |
| `File too large` | Audio exceeds 25MB | Split into smaller chunks |
| `model_not_found` | Vision model ID wrong | Use full path: `meta-llama/llama-4-scout-17b-16e-instruct` |
| `max_images_exceeded` | >5 images in request | Reduce to 5 or fewer images |
| `429` on Whisper | Audio RPM limit hit | Queue transcription requests |
## Resources
- [Groq Speech-to-Text](https://console.groq.com/docs/speech-to-text)
- [Groq Text-to-Speech](https://console.groq.com/docs/text-to-speech)
- [Groq Vision](https://console.groq.com/docs/vision)
- [Groq Models](https://console.groq.com/docs/models)
## Next Steps
For common errors and troubleshooting, see `groq-common-errors`.Related Skills
calendar-to-workflow
Converts calendar events and schedules into Claude Code workflows, meeting prep documents, and standup notes. Use when the user mentions calendar events, meeting prep, standup generation, or scheduling workflows. Trigger with phrases like "prep for my meetings", "generate standup notes", "create workflow from calendar", or "summarize today's schedule".
workhuman-core-workflow-b
Workhuman core workflow b for employee recognition and rewards API. Use when integrating Workhuman Social Recognition, or building recognition workflows with HRIS systems. Trigger: "workhuman core workflow b".
workhuman-core-workflow-a
Workhuman core workflow a for employee recognition and rewards API. Use when integrating Workhuman Social Recognition, or building recognition workflows with HRIS systems. Trigger: "workhuman core workflow a".
wispr-core-workflow-b
Wispr Flow core workflow b for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr core workflow b".
wispr-core-workflow-a
Wispr Flow core workflow a for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr core workflow a".
windsurf-core-workflow-b
Execute Windsurf's secondary workflow: Workflows, Memories, and reusable automation. Use when creating reusable Cascade workflows, managing persistent memories, or automating repetitive development tasks. Trigger with phrases like "windsurf workflow", "windsurf automation", "windsurf memories", "cascade workflow", "windsurf slash command".
windsurf-core-workflow-a
Execute Windsurf's primary workflow: Cascade Write mode for multi-file agentic coding. Use when building features, refactoring across files, or performing complex code tasks. Trigger with phrases like "windsurf cascade write", "windsurf agentic coding", "windsurf multi-file edit", "cascade write mode", "windsurf build feature".
webflow-core-workflow-b
Execute Webflow secondary workflows — Sites management, Pages API, Forms submissions, Ecommerce (products/orders/inventory), and Custom Code via the Data API v2. Use when managing sites, reading pages, handling form data, or working with Webflow Ecommerce products and orders. Trigger with phrases like "webflow sites", "webflow pages", "webflow forms", "webflow ecommerce", "webflow products", "webflow orders".
webflow-core-workflow-a
Execute the primary Webflow workflow — CMS content management: list collections, CRUD items, publish items, and manage content lifecycle via the Data API v2. Use when working with Webflow CMS collections and items, managing blog posts, team members, or any dynamic content. Trigger with phrases like "webflow CMS", "webflow collections", "webflow items", "create webflow content", "manage webflow CMS", "webflow content management".
veeva-core-workflow-b
Veeva Vault core workflow b for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva core workflow b".
veeva-core-workflow-a
Veeva Vault core workflow a for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva core workflow a".
vastai-core-workflow-b
Execute Vast.ai secondary workflow: multi-instance orchestration, spot recovery, and cost optimization. Use when running distributed training, handling spot preemption, or optimizing GPU spend across multiple instances. Trigger with phrases like "vastai distributed training", "vastai spot recovery", "vastai multi-gpu", "vastai cost optimization".