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Pipecat voice agent routing
Point Pipecat OpenAI services at Speko: one base URL and one key across speech-to-text, the LLM and text-to-speech.
Services
| Stage | Class | Route | Routable |
|---|---|---|---|
| Speech-to-text | OpenAISTTService | /v1/audio/transcriptions | 15 of 16 |
| LLM | OpenAILLMService | /v1/chat/completions | 16 of 17 |
| Text-to-speech | OpenAITTSService | /v1/audio/speech | 15 of 17 |
Setup
mkdir speko-pipecat && cd speko-pipecat
uv init --bare --python 3.11
uv add "pipecat-ai[openai,silero,webrtc,runner]~=1.6.0" "python-dotenv>=1.0,<2"
export SPEKO_API_KEY=sk_live_...Catalog
curl -s https://api.speko.ai/v1/modelsResponse
{"data": [{"id": "deepgram:nova-3", "object": "model", "provider": "Deepgram",
"model": "Nova-3", "api": "stt", "routable": true}]}Bot
"""Minimal Pipecat WebRTC bot using Speko's OpenAI-compatible API."""
from __future__ import annotations
import os
from dotenv import load_dotenv
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.worker import PipelineParams, PipelineWorker
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
LLMContextAggregatorPair,
LLMUserAggregatorParams,
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.openai.stt import OpenAISTTService
from pipecat.services.openai.tts import OpenAITTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.workers.runner import WorkerRunner
load_dotenv()
SPEKO_API_KEY = os.getenv("SPEKO_API_KEY")
SPEKO_BASE_URL = "https://api.speko.ai/v1"
SPEKO_OBJECTIVE = os.getenv("SPEKO_OBJECTIVE", "balanced")
SPEKO_LANGUAGE = os.getenv("SPEKO_LANGUAGE", "en")
if not SPEKO_API_KEY:
raise RuntimeError("SPEKO_API_KEY is required")
transport_params = {
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
),
}
def language_from_env() -> Language | str:
"""Preserve regional tags within the router's enabled primary languages."""
primary = SPEKO_LANGUAGE.split("-", 1)[0].lower()
if primary not in {"en", "es"}:
raise ValueError("SPEKO_LANGUAGE must use the enabled en or es primary tag")
try:
return Language(SPEKO_LANGUAGE)
except ValueError:
return SPEKO_LANGUAGE
async def run_bot(
transport: BaseTransport,
runner_args: RunnerArguments,
) -> None:
stt = OpenAISTTService(
api_key=SPEKO_API_KEY,
base_url=SPEKO_BASE_URL,
settings=OpenAISTTService.Settings(
model="auto",
language=language_from_env(),
),
)
llm = OpenAILLMService(
api_key=SPEKO_API_KEY,
base_url=SPEKO_BASE_URL,
default_headers={"X-Speko-Objective": SPEKO_OBJECTIVE},
settings=OpenAILLMService.Settings(
model="auto",
system_instruction="You are a helpful assistant in a voice conversation.",
),
)
tts = OpenAITTSService(
api_key=SPEKO_API_KEY,
base_url=SPEKO_BASE_URL,
# Speko returns 24 kHz mono PCM for routed TTS.
sample_rate=24000,
settings=OpenAITTSService.Settings(
model="auto",
voice="alloy",
),
)
context = LLMContext()
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(
vad_analyzer=SileroVADAnalyzer(),
),
)
pipeline = Pipeline(
[
transport.input(),
stt,
user_aggregator,
llm,
tts,
transport.output(),
assistant_aggregator,
]
)
worker = PipelineWorker(
pipeline,
params=PipelineParams(enable_metrics=True),
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport: BaseTransport, client: object) -> None:
del transport, client
context.add_message(
{
"role": "developer",
"content": "Introduce yourself in one short sentence.",
}
)
await worker.queue_frames([LLMRunFrame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport: BaseTransport, client: object) -> None:
del transport, client
await worker.cancel()
runner = WorkerRunner(handle_sigint=runner_args.handle_sigint)
await runner.add_workers(worker)
await runner.run()
async def bot(runner_args: RunnerArguments) -> None:
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()Run
uv run python bot.py -t webrtc
# Then open http://localhost:7860, click Connect, and start talking.Override per request
import os
from pipecat.services.openai.llm import OpenAILLMService
llm = OpenAILLMService(
api_key=os.environ["SPEKO_API_KEY"],
base_url="https://api.speko.ai/v1",
default_headers={"X-Speko-Objective": "latency"},
settings=OpenAILLMService.Settings(model="auto"),
)Pin one provider
import os
from pipecat.services.openai.tts import OpenAITTSService
tts = OpenAITTSService(
api_key=os.environ["SPEKO_API_KEY"],
base_url="https://api.speko.ai/v1",
sample_rate=24000,
# The id pins the provider. The voice stays a preset name, and the router
# swaps in that provider's own default voice.
settings=OpenAITTSService.Settings(model="cartesia:sonic-3.5", voice="alloy"),
)Limits
| A voice outside the 13 OpenAI presets | The service yields an ErrorFrame before any request. Pin the provider in model instead. |
|---|---|
| No SileroVADAnalyzer in the aggregator | This speech-to-text is segmented and produces nothing without one. |
| default_headers on the STT or TTS service | Not carried: both build their own client. Those two stages read the key. |
| PipelineTask, PipelineRunner | Deprecated since Pipecat 1.3 and removed in 2.0. The file above uses PipelineWorker. |
Reference
| Quickstart | Routing headers, response headers, errors |
|---|---|
| LiveKit | The same wiring in an AgentSession |
| Models | The measured rows the ranking reads |
| Pipecat | Framework documentation |