Parlot

Parlot shows whether production voice agents actually work — turns, handoffs, and goal completion with an evidence trail — not just that the pipeline returned 200s.

Call parlotize() once at startup. MIT OpenTelemetry instrumentation for LiveKit Agents (and LangGraph when you already run voice).

Docs: parlot.ai/docs · Product: parlot.ai

Install

pip install "parlot[livekit]"
# or: pip install "parlot[langgraph]"
# or: pip install "parlot[all]"

Or install an instrumentation package directly:

pip install parlot-instrumentation-livekit
# or: pip install parlot-instrumentation-langgraph

Instrument (LiveKit)

Call parlotize("…") before constructing AgentSession, then await ctx.connect() before session.start():

from parlot.instrumentation.livekit import parlotize

parlotize("my-agent")

from livekit.agents import AgentSession, JobContext


async def entrypoint(ctx: JobContext):
    await ctx.connect()

    session = AgentSession(...)
    await session.start(agent=..., room=ctx.room)

Configure

export PARLOT_ENDPOINT=https://ingest.parlot.ai
export PARLOT_API_KEY=<org-scoped-key>

Mint the API key in Parlot Settings → API Keys.

Next

• Quick Start
• LiveKit guide
• LangGraph guide
• GitHub