> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentops.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Groq
> AgentOps provides first class support for Groq
[Groq](https://groq.com) accelerates LLM inference with its ultra-fast Language Processing Unit (LPU) that powers Groq Cloud. Explore the [Groq docs](https://console.groq.com/docs/overview) to get started with their developer console.
## Steps to Integrate Groq with AgentOps
```bash pip theme={null}
pip install agentops
```
```bash poetry theme={null}
poetry add agentops
```
```bash pip theme={null}
pip install groq
```
```bash poetry theme={null}
poetry add groq
```
Make sure to call `agentops.init` before calling any `openai`, `cohere`, `crew`, etc models.
```python python theme={null}
from groq import Groq
import agentops
agentops.init()
client = Groq(api_key="your_api_key")
# Your code here...
agentops.end_session('Success')
```
Set your API key as an `.env` variable for easy access.
```python .env theme={null}
AGENTOPS_API_KEY=
GROQ_API_KEY=
```
Read more about environment variables in [Advanced Configuration](/v1/usage/advanced-configuration)
Execute your program and visit [app.agentops.ai/drilldown](https://app.agentops.ai/drilldown) to observe your Agent! 🕵️
After your run, AgentOps prints a clickable url to console linking directly to your session in the Dashboard
## Full Examples
```python sync theme={null}
from groq import Groq
import agentops
agentops.init()
client = Groq(api_key="your_api_key")
response = client.chat.completions.create(
messages=[
{
"role": "user",
"content": "Explain the importance of low latency LLMs",
}
],
model="llama3-8b-8192",
)
print(response.choices[0].message.content)
agentops.end_session('Success')
```
```python async theme={null}
from groq import AsyncGroq
import agentops
import asyncio
async def main() -> None:
agentops.init()
client = AsyncGroq(api_key="your_api_key")
response = await client.chat.completions.create(
messages=[
{
"role": "user",
"content": "Explain the importance of low latency LLMs",
}
],
model="llama3-8b-8192",
)
print(response.choices[0].message.content)
agentops.end_session('Success')
asyncio.run(main())
```
This notebook demonstrates how to use AgentOps with a multi-agent system using Groq.