Add GroqSTTService, BaseWhisperSTTService, and refactor OpenAISTTService
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@@ -20,7 +20,7 @@ from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.services.cartesia import CartesiaTTSService
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from pipecat.services.groq import GroqLLMService
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from pipecat.services.groq import GroqLLMService, GroqSTTService
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from pipecat.services.openai import OpenAILLMContext
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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@@ -50,20 +50,20 @@ async def main():
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"Respond bot",
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DailyParams(
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audio_out_enabled=True,
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transcription_enabled=True,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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vad_audio_passthrough=True,
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),
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)
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stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY"), model="distil-whisper-large-v3-en")
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tts = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY"),
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voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
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)
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llm = GroqLLMService(
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api_key=os.getenv("GROQ_API_KEY"), model="llama3-groq-70b-8192-tool-use-preview"
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)
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llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY"), model="llama-3.3-70b-versatile")
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# Register a function_name of None to get all functions
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# sent to the same callback with an additional function_name parameter.
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llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
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@@ -105,6 +105,7 @@ async def main():
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pipeline = Pipeline(
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[
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transport.input(),
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stt,
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context_aggregator.user(),
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llm,
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tts,
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