# # Copyright (c) 2024–2025, Daily # # SPDX-License-Identifier: BSD 2-Clause License # import argparse import asyncio import os import sys from call_connection_manager import CallConfigManager from dotenv import load_dotenv from loguru import logger from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.adapters.schemas.tools_schema import ToolsSchema from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import EndTaskFrame from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection from pipecat.services.cartesia.tts import CartesiaTTSService from pipecat.services.llm_service import FunctionCallParams from pipecat.services.openai.llm import OpenAILLMService from pipecat.transports.services.daily import DailyParams, DailyTransport load_dotenv(override=True) logger.remove(0) logger.add(sys.stderr, level="DEBUG") daily_api_key = os.getenv("DAILY_API_KEY", "") daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1") async def main( room_url: str, token: str, body: dict, ): # ------------ CONFIGURATION AND SETUP ------------ # Create a config manager using the provided body call_config_manager = CallConfigManager.from_json_string(body) if body else CallConfigManager() # Get important configuration values dialout_settings = call_config_manager.get_dialout_settings() test_mode = call_config_manager.is_test_mode() # ------------ TRANSPORT SETUP ------------ transport_params = DailyParams( api_url=daily_api_url, api_key=daily_api_key, audio_in_enabled=True, audio_out_enabled=True, video_out_enabled=False, vad_analyzer=SileroVADAnalyzer(), transcription_enabled=True, ) # Initialize transport with Daily transport = DailyTransport( room_url, token, "Simple Dial-out Bot", transport_params, ) # Initialize TTS tts = CartesiaTTSService( api_key=os.getenv("CARTESIA_API_KEY", ""), voice_id="b7d50908-b17c-442d-ad8d-810c63997ed9", # Use Helpful Woman voice by default ) # ------------ FUNCTION DEFINITIONS ------------ async def terminate_call(params: FunctionCallParams): """Function the bot can call to terminate the call upon completion of a voicemail message.""" await params.llm.queue_frame(EndTaskFrame(), FrameDirection.UPSTREAM) # Define function schemas for tools terminate_call_function = FunctionSchema( name="terminate_call", description="Call this function to terminate the call.", properties={}, required=[], ) # Create tools schema tools = ToolsSchema(standard_tools=[terminate_call_function]) # ------------ LLM AND CONTEXT SETUP ------------ # Set up the system instruction for the LLM system_instruction = """You are Chatbot, a friendly, helpful robot. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by introducing yourself. If the user ends the conversation, **IMMEDIATELY** call the `terminate_call` function. """ # Initialize LLM llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY")) # Register functions with the LLM llm.register_function("terminate_call", terminate_call) # Create system message and initialize messages list messages = [call_config_manager.create_system_message(system_instruction)] # Initialize LLM context and aggregator context = OpenAILLMContext(messages, tools) context_aggregator = llm.create_context_aggregator(context) # ------------ PIPELINE SETUP ------------ # Build pipeline pipeline = Pipeline( [ transport.input(), # Transport user input context_aggregator.user(), # User responses llm, # LLM tts, # TTS transport.output(), # Transport bot output context_aggregator.assistant(), # Assistant spoken responses ] ) # Create pipeline task task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True)) # ------------ EVENT HANDLERS ------------ @transport.event_handler("on_joined") async def on_joined(transport, data): # Start dialout if needed if not test_mode and dialout_settings: logger.debug("Dialout settings detected; starting dialout") await call_config_manager.start_dialout(transport, dialout_settings) @transport.event_handler("on_dialout_connected") async def on_dialout_connected(transport, data): logger.debug(f"Dial-out connected: {data}") @transport.event_handler("on_dialout_answered") async def on_dialout_answered(transport, data): logger.debug(f"Dial-out answered: {data}") # Automatically start capturing transcription for the participant await transport.capture_participant_transcription(data["sessionId"]) # The bot will wait to hear the user before the bot speaks @transport.event_handler("on_first_participant_joined") async def on_first_participant_joined(transport, participant): if test_mode: logger.debug(f"First participant joined: {participant['id']}") await transport.capture_participant_transcription(participant["id"]) # The bot will wait to hear the user before the bot speaks @transport.event_handler("on_participant_left") async def on_participant_left(transport, participant, reason): logger.debug(f"Participant left: {participant}, reason: {reason}") await task.cancel() # ------------ RUN PIPELINE ------------ if test_mode: logger.debug("Running in test mode (can be tested in Daily Prebuilt)") runner = PipelineRunner() await runner.run(task) if __name__ == "__main__": parser = argparse.ArgumentParser(description="Simple Dial-out Bot") parser.add_argument("-u", "--url", type=str, help="Room URL") parser.add_argument("-t", "--token", type=str, help="Room Token") parser.add_argument("-b", "--body", type=str, help="JSON configuration string") args = parser.parse_args() # Log the arguments for debugging logger.info(f"Room URL: {args.url}") logger.info(f"Token: {args.token}") logger.info(f"Body provided: {bool(args.body)}") asyncio.run(main(args.url, args.token, args.body))