A few Groq-related tweaks:

- Wire up passing speed setting to Groq, even though only a value of 1.0 is supported today
- Update the 55y example to switch voices instead of changing speed
- Add a 55zn example to exercise runtime updates of Groq STT

examples/foundational/55y-update-settings-groq-tts.py

@@ -97,8 +97,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         await task.queue_frames([LLMRunFrame()])
 
         await asyncio.sleep(10)
-        logger.info("Updating Groq TTS settings: speed=1.5")
-        await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSSettings(speed=1.5)))
+        logger.info("Updating Groq TTS settings: voice=troy")
+        await task.queue_frame(TTSUpdateSettingsFrame(delta=GroqTTSSettings(voice="troy")))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):

examples/foundational/55zzn-update-settings-groq-stt.py

@@ -0,0 +1,128 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+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.cartesia.tts import CartesiaTTSService
+from pipecat.services.groq.stt import GroqSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.services.whisper.base_stt import BaseWhisperSTTSettings
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+    ),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    stt = GroqSTTService(
+        api_key=os.getenv("GROQ_API_KEY"),
+    )
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = LLMContext(messages)
+    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,
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMRunFrame()])
+
+        await asyncio.sleep(10)
+        logger.info('Updating Groq STT settings: language="es"')
+        await task.queue_frame(STTUpdateSettingsFrame(delta=BaseWhisperSTTSettings(language="es")))
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+    await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()

src/pipecat/services/groq/tts.py

@@ -152,6 +152,9 @@ class GroqTTSService(TTSService):
                 model=self._settings.model,
                 voice=self._settings.voice,
                 response_format=self._output_format,
+                # Note: as of 2026-02-25, only a speed of 1.0 is supported, but
+                # here we pass it for completeness and future-proofing
+                speed=self._settings.speed,
                 input=text,
             )