> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-agui.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Atla
> Integrate `Atla` with Agno for real-time monitoring, automated evaluation, and performance analytics of your AI agents.
[Atla](https://www.atla-ai.com/) is an advanced observability platform designed specifically for AI agent monitoring and evaluation.
This integration provides comprehensive insights into agent performance, automated quality assessment, and detailed analytics for production AI systems.
## Prerequisites
* **API Key**: Obtain your API key from the [Atla dashboard](https://app.atla-ai.com)
Install the Atla Insights SDK with Agno support:
```bash theme={null}
uv pip install "atla-insights"
```
## Configuration
Configure your API key as an environment variable:
```bash theme={null}
export ATLA_API_KEY="your_api_key_from_atla_dashboard"
```
## Example
```python theme={null}
from os import getenv
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.hackernews import HackerNewsTools
from atla_insights import configure, instrument_agno
# Step 1: Configure Atla
configure(token=getenv("ATLA_API_KEY"))
# Step 2: Create your Agno agent
agent = Agent(
name="Market Analysis Agent",
model=OpenAIResponses(id="gpt-5.2"),
tools=[HackerNewsTools()],
instructions="Provide professional market analysis with data-driven insights.",
debug_mode=True,
)
# Step 3: Instrument and execute
with instrument_agno("openai"):
response = agent.run("Retrieve the latest news about the stock market.")
print(response.content)
```
Now go to the [Atla dashboard](https://app.atla-ai.com/app/) and view the traces created by your agent. You can visualize the execution flow, monitor performance, and debug issues directly from the Atla dashboard.
