pipecat pipeline over livekit transport

LIVEKIT_URL=wss://your-project.livekit.cloud
RUMIK_API_KEY=rk_live_•••••••••
RUMIK_GATEWAY_URL=https://silk-api.rumik.ai
DEEPGRAM_API_KEY=•••••••••
OPENAI_API_KEY=sk-•••••••••

import os

from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat_rumik import RumikTTSService

# muga is steered by a [tone] tag, so the LLM must add one. give your LLM this
# system prompt (see /prompting-muga).
SYSTEM_PROMPT = "Start every reply with one tone tag ([happy], [sad], ...). Romanised Hinglish, 1-2 sentences."


async def run_agent(url: str, token: str, room_name: str):
    # livekit is ONLY the transport, pipecat owns the pipeline
    transport = LiveKitTransport(
        url=url,
        token=token,
        room_name=room_name,
        params=LiveKitParams(audio_in_enabled=True, audio_out_enabled=True),
    )

    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
    llm = OpenAILLMService(api_key=os.environ["OPENAI_API_KEY"], model="gpt-4o-mini")
    tts = RumikTTSService(
        api_key=os.environ["RUMIK_API_KEY"],
        gateway_url=os.environ["RUMIK_GATEWAY_URL"],
        settings=RumikTTSService.Settings(model="muga"),
    )

    # livekit in → stt → llm → rumik tts → livekit out
    pipeline = Pipeline([transport.input(), stt, llm, tts, transport.output()])

    await PipelineRunner().run(PipelineTask(pipeline))