Anam

Anam provides real-time interactive avatar video with automatic lip-sync. Add a video avatar to your agent that speaks with natural movements synchronized to your agent’s voice output.

Vision Agents uses Stream Video for real-time WebRTC transport by default. External WebRTC transports are supported as well. Most AI providers offer free tiers to get started.

Anam provides API keys and avatar IDs through their dashboard.

Installation

uv add "vision-agents[anam]"

Quick Start

from vision_agents.core import Agent, User
from vision_agents.plugins import anam, gemini, deepgram, getstream

agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Assistant", id="agent"),
    instructions="You're a friendly AI assistant.",
    llm=gemini.LLM("gemini-3-flash-preview"),
    tts=deepgram.TTS(),
    stt=deepgram.STT(),
    avatar=anam.Avatar(),
)

Set ANAM_API_KEY and ANAM_AVATAR_ID in your environment, or pass them directly to anam.Avatar(...).

Parameters

Name	Type	Default	Description
avatar_id	str	None	Anam avatar ID (defaults to ANAM_AVATAR_ID env var)
api_key	str	None	API key (defaults to ANAM_API_KEY env var)
client_options	ClientOptions	None	Advanced Anam client configuration
connect_timeout	float	None	Seconds to wait for connection (None = wait indefinitely)
session_ready_timeout	float	None	Seconds to wait for session ready (None = wait indefinitely)
width	int	720	Output video width in pixels
height	int	480	Output video height in pixels
fps	int	30	Output video frame rate. Must be > 0.
buffer_seconds	float	1.0	Max video buffer depth in seconds ahead of audio playback. Must be > 0.

How It Works

1. Agent TTS audio is resampled to 24 kHz mono and streamed to Anam
2. Anam generates lip-synced avatar video and audio from the input
3. Avatar video and audio frames are streamed back to call participants via Stream Edge
4. When a user starts speaking, the avatar is automatically interrupted

With Realtime LLMs

Anam also works with realtime speech-to-speech models. It subscribes to both TTS audio events and realtime audio output, so you can swap in a realtime LLM without any changes to the avatar setup.

from vision_agents.plugins import anam, gemini

agent = Agent(
    llm=gemini.Realtime(),
    avatar=anam.Avatar(),
    ...
)

Next Steps

Build a Voice Agent

Get started with voice

Build a Video Agent

Add video processing

Build Your Own Avatar

Subclass the Avatar base class