Vogent

Vogent uses neural models to predict when a speaker has completed their conversational turn. Provides intelligent turn-taking for natural conversation flow.

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.

Installation

uv add "vision-agents[vogent]"

Quick Start

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

agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Assistant", id="agent"),
    instructions="You are a helpful assistant.",
    llm=gemini.LLM("gemini-3-flash-preview"),
    stt=deepgram.STT(),
    tts=elevenlabs.TTS(),
    turn_detection=vogent.TurnDetection(),
)

Models download automatically on first use.

Parameters

Name	Type	Default	Description
buffer_in_seconds	float	2.0	Audio buffer duration
confidence_threshold	float	0.5	Turn completion threshold (0-1)
sample_rate	int	16000	Audio sample rate

Turn Signals

from vision_agents.core.turn_detection import TurnStarted, TurnEnded
from vision_agents.plugins import vogent

turn_detection = vogent.TurnDetection()

async for signal in turn_detection.output:
    if isinstance(signal, TurnStarted):
        print(f"User started speaking: {signal.participant.user_id}")
    elif isinstance(signal, TurnEnded):
        print(f"User finished speaking: confidence={signal.confidence}")

Next Steps

Build a Voice Agent

Get started with voice

Build a Video Agent

Add video processing