[WHAT] Fast LLM inference via Groq API (chat) + Ollama (embeddings) [HOW] Groq for chat completions (llama-3.3-70b-versatile), Ollama nomic-embed-text for embeddings [WHEN] Need fast inference, embedding text for RAG, chat completions [WHY] Groq provides fastest LLM inference; Ollama handles local embeddings (Groq has no embedding API) Triggers: "groq embed", "groq chat", "groq complete", "embed with groq", "fast llm"
Scanned 9/20/2026
Install to Claude Code
npx -y skills add lev-os/agents --skill groq --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Groq?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/lev-os-groq)More formats (shields.io, HTML) on the badges page.
---
name: groq
description: |
[WHAT] Fast LLM inference via Groq API (chat) + Ollama (embeddings)
[HOW] Groq for chat completions (llama-3.3-70b-versatile), Ollama nomic-embed-text for embeddings
[WHEN] Need fast inference, embedding text for RAG, chat completions
[WHY] Groq provides fastest LLM inference; Ollama handles local embeddings (Groq has no embedding API)
Triggers: "groq embed", "groq chat", "groq complete", "embed with groq", "fast llm"
---
# groq
Fast LLM inference via Groq API for chat, Ollama for embeddings.
## Setup
**Environment:**
- `GROQ_API_KEY` - Required for chat completions
- Ollama running locally for embeddings (`ollama serve`)
**Install dependencies:**
```bash
cd ~/.claude/skills/groq
pip install groq requests
```
**Pull embedding model (first time):**
```bash
ollama pull nomic-embed-text
```
## Usage
### Chat Completion
```bash
# Simple chat
./scripts/chat.py "Explain quantum computing in 2 sentences"
# With system prompt
./scripts/chat.py "Write a haiku" --system "You are a poet"
# Different model
./scripts/chat.py "Hello" --model llama-3.1-8b-instant
# JSON output
./scripts/chat.py "List 3 colors as JSON array" --json
```
### Embeddings
```bash
# Embed text (returns JSON array of floats)
./scripts/embed.sh "Hello world"
# Embed from stdin
echo "Some text to embed" | ./scripts/embed.sh
# Python direct
./scripts/embed.py "Hello world"
```
## Models
### Chat Models (Groq)
| Model | Context | Speed | Use Case |
|-------|---------|-------|----------|
| `llama-3.3-70b-versatile` | 128k | Fast | Default, general purpose |
| `llama-3.1-8b-instant` | 128k | Fastest | Simple tasks |
| `llama3-70b-8192` | 8k | Fast | Legacy |
| `gemma2-9b-it` | 8k | Fast | Instruction following |
### Embedding Model (Ollama)
| Model | Dimensions | Notes |
|-------|------------|-------|
| `nomic-embed-text` | 768 | Local, fast, good quality |
## Output Format
### Chat
Plain text response to stdout. Errors to stderr.
### Embed
JSON array of floats:
```json
[0.123, -0.456, 0.789, ...]
```
## When to Use
| Scenario | Command |
|----------|---------|
| Quick question | `./scripts/chat.py "What is X?"` |
| Code generation | `./scripts/chat.py "Write Python for Y"` |
| Embed for RAG | `./scripts/embed.sh "document text"` |
| Batch embed | `cat docs.txt \| while read line; do ./scripts/embed.sh "$line"; done` |
## Error Handling
- Missing `GROQ_API_KEY`: Chat fails with clear error
- Ollama not running: Embed falls back to error message
- Rate limits: Groq has generous limits but will return 429 if exceeded
## Related Skills
| Skill | Use When |
|-------|----------|
| **oracle** | Need GPT-5, Claude, multi-model comparison |
| **lev-find** | Unified search with embeddings already indexed |
| **brave-search** | Web search, not embeddings |
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!