API Reference
VoiceGateway exposes three distinct API surfaces, each designed for a different integration point.
API Reference
VoiceGateway exposes three distinct API surfaces, each designed for a different integration point.
Python SDK
The voicegateway.inference module is the public Python surface. It is a drop-in mirror of livekit.agents.inference: change the import line in an existing LiveKit Cloud Inference agent and the rest of the code keeps working. Cost tracking, latency monitoring, and session correlation happen transparently in the middleware.
from livekit.agents import AgentSession
from voicegateway.inference import STT, LLM, TTS
session = AgentSession(
stt=STT("deepgram/nova-3"),
llm=LLM("openai/gpt-4.1-mini"),
tts=TTS("cartesia/sonic-3"),
)Best for: application code, scripts, custom integrations.
HTTP API
The REST API runs on port 8080 (default) via voicegw serve. It provides CRUD operations for providers, models, and projects, plus read-only endpoints for costs, latency, logs, and Prometheus-format metrics. The dashboard frontend consumes this API, and external monitoring tools can scrape /v1/metrics.
curl http://localhost:8080/v1/status
curl http://localhost:8080/v1/costs?period=week&project=my-appBest for: dashboards, monitoring, CI/CD pipelines, multi-language teams.
Dashboard API
The dashboard API is mounted by the daemon (voicegw serve)
under the /api/ prefix on the same port as the HTTP API and the
React SPA. It exposes a smaller set of read-only /api/* endpoints
optimised for the dashboard UI. These endpoints aggregate data
slightly differently from the HTTP API (for example, /api/overview
combines multiple queries into a single response).
curl http://localhost:8080/api/overview
curl http://localhost:8080/api/costs?period=todayBest for: the built-in web dashboard (consumed automatically).
Choosing the Right API
| Use case | API surface |
|---|---|
| Route voice AI requests in Python | Python SDK |
| Manage providers/models/projects remotely | HTTP API |
| Build a custom dashboard or integrate with monitoring | HTTP API |
| Use the built-in web UI | Dashboard API (automatic, served by the daemon) |
| Integrate with AI coding agents | MCP server |