Update STT service settings

examples/foundational/07c-interruptible-deepgram-sagemaker.py

@@ -22,9 +22,12 @@ from pipecat.processors.aggregators.llm_response_universal import (
 )
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
-from pipecat.services.aws.llm import AWSBedrockLLMService
+from pipecat.services.aws.llm import AWSBedrockLLMService, AWSBedrockLLMSettings
 from pipecat.services.deepgram.sagemaker.stt import DeepgramSageMakerSTTService
-from pipecat.services.deepgram.sagemaker.tts import DeepgramSageMakerTTSService
+from pipecat.services.deepgram.sagemaker.tts import (
+    DeepgramSageMakerTTSService,
+    DeepgramSageMakerTTSSettings,
+)
 from pipecat.transports.base_transport import BaseTransport, TransportParams
 from pipecat.transports.daily.transport import DailyParams
 from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
@@ -69,14 +72,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     tts = DeepgramSageMakerTTSService(
         endpoint_name=os.getenv("SAGEMAKER_TTS_ENDPOINT_NAME"),
         region=os.getenv("AWS_REGION"),
-        voice="aura-2-andromeda-en",
+        settings=DeepgramSageMakerTTSSettings(
+            voice="aura-2-andromeda-en",
+        ),
     )
 
     llm = AWSBedrockLLMService(
         aws_region=os.getenv("AWS_REGION"),
-        model="us.amazon.nova-pro-v1:0",
-        params=AWSBedrockLLMService.InputParams(temperature=0.8),
         system_instruction="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.",
+        settings=AWSBedrockLLMSettings(
+            model="us.amazon.nova-pro-v1:0",
+            temperature=0.8,
+        ),
     )
 
     context = LLMContext()