> ## Documentation Index
> Fetch the complete documentation index at: https://anam.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Python Quickstart

> Stream an Anam avatar in a Python application

This quickstart shows you how to connect to an Anam persona and receive audio and video frames.

## Prerequisites

* An Anam API key ([get one here](/api-key))
* A persona ID from [Anam Lab](https://lab.anam.ai)
* The `anam` package installed (`pip install anam`)

## Connect and stream

```python theme={"system"}
import asyncio
from anam import AnamClient

async def main():
    client = AnamClient(
        api_key="your-api-key",
        persona_id="your-persona-id",
    )

    async with client.connect() as session:
        async def consume_video():
            async for frame in session.video_frames():
                img = frame.to_ndarray(format="rgb24")
                print(f"Video: {frame.width}x{frame.height}")

        async def consume_audio():
            async for frame in session.audio_frames():
                samples = frame.to_ndarray()
                print(f"Audio: {samples.size} samples")

        await asyncio.gather(consume_video(), consume_audio())

asyncio.run(main())
```

This connects to the persona and prints frame metadata as it arrives. Replace the `print` calls with your own rendering logic.

<Warning>
  Never expose your API key in client-side code. The Python SDK is designed for server-side use. See [Usage in Production](/production) for session token patterns.
</Warning>

## Send a message

You can send text to the persona during a session:

```python theme={"system"}
async with client.connect() as session:
    await session.talk("Hello, tell me about yourself.")
```

## Use the event-driven API

If you prefer callbacks over async iterators:

```python theme={"system"}
from anam import AnamClient, AnamEvent

client = AnamClient(
    api_key="your-api-key",
    persona_id="your-persona-id",
)

@client.on(AnamEvent.CONNECTION_ESTABLISHED)
async def on_connected():
    print("Connected to persona")

@client.on(AnamEvent.MESSAGE_STREAM_EVENT_RECEIVED)
async def on_message(event):
    print(f"{event.role}: {event.content}")

await client.connect()
```

## Next steps

<CardGroup cols={2}>
  <Card title="GitHub Repository" icon="github" href="https://github.com/anam-org/python-sdk">
    Source code, full API reference, and examples
  </Card>

  <Card title="Cookbook: Python BYO LLM" icon="book-open" href="https://anam.ai/cookbook/python-byo-llm">
    Bring your own LLM with the Python SDK
  </Card>
</CardGroup>