Agent Framework plugin for Runway Characters Avatar
Project description
livekit-plugins-runway
LiveKit Agents plugin for Runway Characters avatar integration.
Your LiveKit agent owns the full conversational AI pipeline (STT, LLM, TTS). Runway provides the visual layer — audio in, avatar video out.
Installation
pip install livekit-plugins-runway
Usage
from livekit.agents import AgentSession, Agent, RoomOutputOptions
from livekit.plugins import runway
async def entrypoint(ctx):
session = AgentSession()
avatar = runway.AvatarSession(
avatar_id="your-custom-avatar-id",
# api_key defaults to RUNWAYML_API_SECRET env var
)
await avatar.start(session, room=ctx.room)
await session.start(
agent=Agent(instructions="Talk to me!"),
room=ctx.room,
room_output_options=RoomOutputOptions(audio_enabled=False),
)
Using a preset avatar
avatar = runway.AvatarSession(
preset_id="runway-preset-slug",
)
With a session duration limit
avatar = runway.AvatarSession(
avatar_id="your-custom-avatar-id",
max_duration=300,
)
Configuration
| Parameter | Env var | Description |
|---|---|---|
api_key |
RUNWAYML_API_SECRET |
Runway API key |
api_url |
RUNWAYML_BASE_URL |
API base URL (default: https://api.dev.runwayml.com) |
avatar_id |
— | Custom avatar ID (mutually exclusive with preset_id) |
preset_id |
— | Preset avatar slug (mutually exclusive with avatar_id) |
max_duration |
— | Maximum session duration in seconds |
LiveKit credentials (LIVEKIT_URL, LIVEKIT_API_KEY, LIVEKIT_API_SECRET) are read from environment variables or can be passed to avatar.start().
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Publisher:
publish.yml on livekit/agents
-
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Statement type:
https://in-toto.io/Statement/v1 -
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Access:
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github-hosted -
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