Update examples to use the class Settings alias
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@@ -22,9 +22,9 @@ from pipecat.processors.aggregators.llm_response_universal import (
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings
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from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings
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from pipecat.services.google.tts import GeminiTTSService, GeminiTTSSettings
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from pipecat.services.google.llm import GoogleLLMService
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from pipecat.services.google.stt import GoogleSTTService
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from pipecat.services.google.tts import GeminiTTSService
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from pipecat.transcriptions.language import Language
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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@@ -54,7 +54,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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logger.info(f"Starting bot with Gemini TTS")
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stt = GoogleSTTService(
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settings=GoogleSTTSettings(
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settings=GoogleSTTService.Settings(
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languages=[Language.EN_US],
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),
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credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
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@@ -62,7 +62,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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tts = GeminiTTSService(
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credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
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settings=GeminiTTSSettings(
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settings=GeminiTTSService.Settings(
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model="gemini-2.5-flash-tts",
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voice="Charon",
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language=Language.EN_US,
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@@ -73,7 +73,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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llm = GoogleLLMService(
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api_key=os.getenv("GOOGLE_API_KEY"),
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model="gemini-2.5-flash",
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settings=GoogleLLMSettings(
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settings=GoogleLLMService.Settings(
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system_instruction="""You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
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IMPORTANT: You're using Gemini TTS which supports expressive markup tags. You can use these tags in your responses:
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