Call Transfer demo (#1348)
* Updated code to dial out to an operator, keep track of operator conversation while escalated and then return to conversation when finished * Removed unnecessary imports * Updated bot runner code, added call routing file and then updated the call transfer and voicemail detection examples * Updated the bot files * Made prompt one level higher in the body and an array * Updated call transfer examples to work correctly * Updated gemini voicemail detection example to work * Added twilio bot support back to the bot_runner * Moved some state management, participant management and other logic to the helper file. * Updated comments * Updated env and requirements file * Ran the examples and made sure code works. Still need to work on the prompts a bit * Fixed format issue * Add support to disable summary in call transfer * Added support for operator transfer mode * Updated readme file * Updated readme based on feedback, and handling of various properties in the json to be more flexible for future examples * Updated number of endpoints * Updated readme to remove fly deployment text and replaced with Pipecat Cloud * Starting to tweak function calls and prompts * Updated examples to more consistently call the functions and say what they need to say * Updated examples * Updated examples * Updated examples to work correctly * Add simple bot versions of dialin and dialout * Refactored the bot runner file to make adding future examples easier * Based on feedback, removed examples for multiple LLMs and also adjusted voicemail detection code to be simpler * Made sure to only capture the users transcription once * Updated readme with latest changes * Forgot to update the order of examples in one place * Fixed formatting issue * Adjusted based on james feedback * Changed default_mode to default_calltransfer_mode
This commit is contained in:
Dominic Stewart
187
examples/phone-chatbot/simple_dialout.py
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187
examples/phone-chatbot/simple_dialout.py
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import argparse
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import asyncio
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import os
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import sys
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from call_connection_manager import CallConfigManager
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from dotenv import load_dotenv
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from loguru import logger
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from pipecat.adapters.schemas.function_schema import FunctionSchema
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from pipecat.adapters.schemas.tools_schema import ToolsSchema
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import EndTaskFrame
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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.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.services.ai_services import LLMService
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from pipecat.services.cartesia import CartesiaTTSService
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from pipecat.services.openai import OpenAILLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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load_dotenv(override=True)
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logger.remove(0)
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logger.add(sys.stderr, level="DEBUG")
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daily_api_key = os.getenv("DAILY_API_KEY", "")
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daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
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async def main(
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room_url: str,
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token: str,
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body: dict,
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):
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# ------------ CONFIGURATION AND SETUP ------------
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# Create a config manager using the provided body
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call_config_manager = CallConfigManager.from_json_string(body) if body else CallConfigManager()
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# Get important configuration values
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dialout_settings = call_config_manager.get_dialout_settings()
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test_mode = call_config_manager.is_test_mode()
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# ------------ TRANSPORT SETUP ------------
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transport_params = DailyParams(
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api_url=daily_api_url,
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api_key=daily_api_key,
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audio_in_enabled=True,
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audio_out_enabled=True,
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camera_out_enabled=False,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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transcription_enabled=True,
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)
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# Initialize transport with Daily
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transport = DailyTransport(
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room_url,
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token,
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"Simple Dial-out Bot",
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transport_params,
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)
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# Initialize TTS
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tts = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY", ""),
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voice_id="b7d50908-b17c-442d-ad8d-810c63997ed9", # Use Helpful Woman voice by default
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)
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# ------------ FUNCTION DEFINITIONS ------------
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async def terminate_call(
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function_name, tool_call_id, args, llm: LLMService, context, result_callback
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):
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"""Function the bot can call to terminate the call upon completion of a voicemail message."""
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await llm.queue_frame(EndTaskFrame(), FrameDirection.UPSTREAM)
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# Define function schemas for tools
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terminate_call_function = FunctionSchema(
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name="terminate_call",
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description="Call this function to terminate the call.",
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properties={},
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required=[],
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)
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# Create tools schema
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tools = ToolsSchema(standard_tools=[terminate_call_function])
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# ------------ LLM AND CONTEXT SETUP ------------
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# Set up the system instruction for the LLM
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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. """
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# Initialize LLM
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
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# Register functions with the LLM
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llm.register_function("terminate_call", terminate_call)
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# Create system message and initialize messages list
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messages = [call_config_manager.create_system_message(system_instruction)]
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# Initialize LLM context and aggregator
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context = OpenAILLMContext(messages, tools)
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context_aggregator = llm.create_context_aggregator(context)
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# ------------ PIPELINE SETUP ------------
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# Build pipeline
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pipeline = Pipeline(
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[
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transport.input(), # Transport user input
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context_aggregator.user(), # User responses
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llm, # LLM
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tts, # TTS
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transport.output(), # Transport bot output
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context_aggregator.assistant(), # Assistant spoken responses
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]
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)
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# Create pipeline task
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task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
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# ------------ EVENT HANDLERS ------------
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@transport.event_handler("on_joined")
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async def on_joined(transport, data):
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# Start dialout if needed
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if not test_mode and dialout_settings:
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logger.debug("Dialout settings detected; starting dialout")
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await call_config_manager.start_dialout(transport, dialout_settings)
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@transport.event_handler("on_dialout_connected")
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async def on_dialout_connected(transport, data):
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logger.debug(f"Dial-out connected: {data}")
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@transport.event_handler("on_dialout_answered")
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async def on_dialout_answered(transport, data):
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logger.debug(f"Dial-out answered: {data}")
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# Automatically start capturing transcription for the participant
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await transport.capture_participant_transcription(data["sessionId"])
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# The bot will wait to hear the user before the bot speaks
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@transport.event_handler("on_first_participant_joined")
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async def on_first_participant_joined(transport, participant):
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if test_mode:
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logger.debug(f"First participant joined: {participant['id']}")
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await transport.capture_participant_transcription(participant["id"])
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# The bot will wait to hear the user before the bot speaks
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@transport.event_handler("on_participant_left")
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async def on_participant_left(transport, participant, reason):
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logger.debug(f"Participant left: {participant}, reason: {reason}")
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await task.cancel()
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# ------------ RUN PIPELINE ------------
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if test_mode:
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logger.debug("Running in test mode (can be tested in Daily Prebuilt)")
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runner = PipelineRunner()
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await runner.run(task)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Simple Dial-out Bot")
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parser.add_argument("-u", "--url", type=str, help="Room URL")
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parser.add_argument("-t", "--token", type=str, help="Room Token")
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parser.add_argument("-b", "--body", type=str, help="JSON configuration string")
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args = parser.parse_args()
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# Log the arguments for debugging
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logger.info(f"Room URL: {args.url}")
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logger.info(f"Token: {args.token}")
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logger.info(f"Body provided: {bool(args.body)}")
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asyncio.run(main(args.url, args.token, args.body))
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