Agents Overview

STELLA supports multiple agent types, each designed for different use cases. All agents connect to LiveKit rooms for real-time voice and data communication.

Agent Types

Agent	Description	Best For
stella-v2	Streamlined 5-stage pipeline with deterministic arbitration and configurable pipeline	Configurable deployments, lower latency, predictable behavior
stella-agent	Full-featured agent with LLM-based aggregation pipeline	Production conversations requiring high quality
stella-light-agent	Lightweight agent with simplified pipeline	Quick responses, lower resource usage
echo-agent	Simple test agent that echoes back messages	Testing and development

Architecture

All STELLA agents follow a similar pipeline architecture and can be configured with Plans — JSON-based conversation blueprints that define states, tasks, and data collection. See the Plan Structure documentation for details.

┌─────────────────────────────────────────────────────────────────┐
│                        Agent Pipeline                           │
│                                                                 │
│  ┌──────────┐    ┌──────────┐    ┌──────────┐    ┌──────────┐  │
│  │  Audio   │ -> │   STT    │ -> │   LLM    │ -> │   TTS    │  │
│  │  Input   │    │ (Speech  │    │(Response │    │  (Text   │  │
│  │(LiveKit) │    │  to Text)│    │Generation│    │ to Speech│  │
│  └──────────┘    └──────────┘    └──────────┘    └──────────┘  │
│                                                       │         │
│                                                       ▼         │
│                                              ┌──────────────┐   │
│                                              │ Audio Output │   │
│                                              │  (LiveKit)   │   │
│                                              └──────────────┘   │
└─────────────────────────────────────────────────────────────────┘

Choosing an Agent

stella-v2

Use stella-v2 when you need:

• Configurable pipeline with visual Pipeline Configurator
• Lower response latency (deterministic arbitration instead of LLM synthesis)
• Predictable, debuggable expert conflict resolution
• Reusable pipeline configurations across deployments
• Bridge generation for reduced perceived latency in voice conversations

stella-agent

Use the full-featured stella-agent when you need:

• High-quality speech recognition
• Advanced conversation capabilities
• Custom tool integration
• Complex dialogue flows
• Production deployments

stella-light-agent

Use stella-light-agent when you need:

• Faster response times
• Lower resource consumption
• Simpler conversations
• Development and testing

echo-agent

Use echo-agent for:

• Testing LiveKit connectivity
• Verifying audio pipeline
• Development debugging

Common Configuration

All agents support these common environment variables:

Variable	Description	Required
LIVEKIT_URL	LiveKit server URL	Yes
LIVEKIT_API_KEY	LiveKit API key	Yes
LIVEKIT_API_SECRET	LiveKit API secret	Yes
OPENAI_API_KEY	OpenAI API key for LLM	Yes
ROOM_NAME	LiveKit room to join	Yes
PARTICIPANT_IDENTITY	Agent's identity in the room	Yes

Resource Requirements

Agent	CPU Request	CPU Limit	Memory Request	Memory Limit
stella-v2	500m	2000m	512Mi	2Gi
stella-agent	250m	1000m	512Mi	2Gi
stella-light-agent	100m	500m	256Mi	1Gi
echo-agent	50m	200m	128Mi	512Mi

Lifecycle

1. Created: Backend creates a Kubernetes pod with agent configuration
2. Starting: Agent initializes and connects to LiveKit room
3. Running: Agent processes audio and responds to participants
4. Stopping: Graceful shutdown when session ends or agent is stopped
5. Terminated: Pod is deleted, resources freed

Next Steps

• stella-v2 - Streamlined pipeline with configurator
• stella-agent - Full-featured agent details
• stella-light-agent - Lightweight agent details
• echo-agent - Test agent details
• Agent SDK - Build custom agents