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Read through this guide to set up Groq & get familiar with how it is used across the different apps.

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Set up Groq

First, create a Groq account or sign in. Next, navigate to the API key page and “Create API key”. Make sure to save this somewhere safe and do not share it with anyone. Once you have your API key, paste it in your .env file: 
GROQ_API_KEY=your_groq_api_key

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Available Models

Groq models are defined in the unified model registry at lib/ai/models.ts. Both models support vision capability.
ModelIDFeatures
Llama 4 Scoutmeta-llama/llama-4-scout-17b-16e-instructVision
Llama 4 Maverickmeta-llama/llama-4-maverick-17b-128e-instructVision

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Apps Using Groq

Groq is integrated through the Vercel AI SDK 6.0. Provider routing is handled by lib/ai/ai-utils.ts using customModel(), getProviderFromModelId(), and getModelInstance().

Chat

Multi-provider chat app — Groq is available as an LLM provider

Audio

Record audio and summarize transcriptions using Groq models

Structured Output

Generate structured JSON output using Groq models

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Structure

The codebase uses Vercel AI SDK 6.0 with a unified model registry instead of direct Groq API calls. Models are registered in lib/ai/models.ts and routing is managed through lib/ai/ai-utils.ts. The typical flow for an AI request:
  1. The user selects a model from the unified model registry
  2. The request is routed through getModelInstance() in lib/ai/ai-utils.ts
  3. The provider is determined via getProviderFromModelId()
  4. The model is instantiated with customModel()
  5. The response is streamed back to the user
  6. Results are stored in Supabase
More information on structure of the codebase can be found here:

Structure

Understand the project structure of the codebase