diff --git a/examples/dialin-chatbot/bot_daily.py b/examples/dialin-chatbot/bot_daily.py index b3e4a31b7..f698579fc 100644 --- a/examples/dialin-chatbot/bot_daily.py +++ b/examples/dialin-chatbot/bot_daily.py @@ -1,3 +1,8 @@ +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + import argparse import asyncio import os @@ -5,6 +10,7 @@ import sys from dotenv import load_dotenv from loguru import logger +from openai.types.chat import ChatCompletionToolParam from pipecat.audio.vad.silero import SileroVADAnalyzer from pipecat.frames.frames import EndFrame @@ -12,6 +18,8 @@ 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.services.ai_services import LLMService +from pipecat.services.deepgram import DeepgramSTTService from pipecat.services.elevenlabs import ElevenLabsTTSService from pipecat.services.openai import OpenAILLMService from pipecat.transports.services.daily import DailyDialinSettings, DailyParams, DailyTransport @@ -55,14 +63,44 @@ async def main(room_url: str, token: str, callId: str, callDomain: str): llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o") + content = f""" +You are a delivery service customer support specialist supporting customers with their orders. +Begin with: "Hello, this is Hailey from customer support. What can I help you with today?" + """ + messages = [ { "role": "system", - "content": "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 saying 'Oh, hello! Who dares dial me at this hour?!'.", + "content": content, }, ] - context = OpenAILLMContext(messages) + tools = [ + ChatCompletionToolParam( + type="function", + function={ + "name": "transfer_call", + "description": "Transfer the call to a person. This function is used to connect the call to a real person. Examples of real people are: managers, supervisors, or other customer support specialists. Any person is okay as long as they are not a bot.", + "parameters": { + "type": "object", + "properties": { + "call_id": { + "type": "string", + "description": "This is always {callId}.", + }, + "summary": { + "type": "string", + "description": """ +Provide a concise summary in 3-5 sentences. Highlight any important details or unusual aspects of the conversation. + """, + }, + }, + }, + }, + ) + ] + + context = OpenAILLMContext(messages, tools) context_aggregator = llm.create_context_aggregator(context) pipeline = Pipeline( @@ -87,6 +125,44 @@ async def main(room_url: str, token: str, callId: str, callDomain: str): async def on_participant_left(transport, participant, reason): await task.queue_frame(EndFrame()) + @transport.event_handler("on_dialin_ready") + async def on_dialin_ready(_, sip_endpoint): + logger.info(f"on_dialin_ready: {sip_endpoint}") + + @transport.event_handler("on_dialin_connected") + async def on_dialin_connected(transport, event): + logger.info(f"on_dialin_connected: {event}") + sip_session_id = event["sessionId"] + + async def transfer_call( + function_name, tool_call_id, args, llm: LLMService, context, result_callback + ): + logger.debug(f"transfer_call: {function_name} {tool_call_id} {args}") + + # sip_url = "sip:your_user_name@sip.linphone.org" + + sip_url = ( + f"sip:your_username@dailyco.sip.twilio.com?x-daily_id={room_url.split('/')[-1]}" + ) + + try: + await transport.sip_refer( + settings={ + "sessionId": sip_session_id, + "toEndPoint": sip_url, + } + ) + except Exception as e: + logger.error(f"An error occurred during SIP refer: {e}") + await result_callback({"transfer_call": False}) + + await result_callback({"transfer_call": True}) + + llm.register_function( + function_name="transfer_call", + callback=transfer_call, + ) + runner = PipelineRunner() await runner.run(task) diff --git a/examples/foundational/32-call-transfer.py b/examples/foundational/32-call-transfer.py new file mode 100644 index 000000000..bc9560895 --- /dev/null +++ b/examples/foundational/32-call-transfer.py @@ -0,0 +1,183 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import os +import sys + +from loguru import logger +from openai.types.chat import ChatCompletionToolParam + +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.frames.frames import EndFrame, LLMMessagesFrame +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.services.ai_services import LLMService +from pipecat.services.cartesia import CartesiaTTSService +from pipecat.services.deepgram import DeepgramSTTService +from pipecat.services.openai import OpenAILLMService +from pipecat.transports.services.daily import DailyDialinSettings, DailyParams, DailyTransport + +logger.remove(0) +logger.add(sys.stderr, level="DEBUG") + + +async def main(room_url: str, token: str, call_id: str, call_domain: str): + """Main entrypoint for the voice bot process. + + :param room_url: The Daily.co room URL + :param token: The Daily.co token + :param callId: The call ID from Daily.co + :param callDomain: The domain associated with the call + """ + diallin_settings = DailyDialinSettings(call_id=call_id, call_domain=call_domain) + + transport = DailyTransport( + room_url, + token, + "Chatbot", + DailyParams( + api_url="https://api.daily.co/v1/", + api_key=os.getenv("DAILY_API_KEY", ""), + dialin_settings=diallin_settings, + audio_in_enabled=True, + audio_out_enabled=True, + camera_out_enabled=False, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + transcription_enabled=True, + ), + ) + + cartesia_params = CartesiaTTSService.InputParams( + speed=-0.1, + emotion=["positivity:high", "curiosity"], + language="en", + ) + + tts = CartesiaTTSService( + api_key=os.getenv("CARTESIA_API_KEY", ""), + # Use Helpful Woman voice by default + voice_id="156fb8d2-335b-4950-9cb3-a2d33befec77", + params=cartesia_params, + ) + + llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o") + + tools = [ + ChatCompletionToolParam( + type="function", + function={ + "name": "transfer_call", + "description": "Transfer the call to a person. This function is used to connect the call to a real person. Examples of real people are: managers, supervisors, or other customer support specialists. Any person is okay as long as they are not a bot.", + "parameters": { + "type": "object", + "properties": { + "call_id": { + "type": "string", + "description": "This is always {call_id}.", + }, + "summary": { + "type": "string", + "description": """ +Provide a concise summary in 3-5 sentences. Highlight any important details or unusual aspects of the conversation. + """, + }, + }, + }, + }, + ) + ] + + content = f""" +You are a delivery service customer support specialist supporting customers with their orders. +Begin with: "Hello, this is Hailey from customer support. What can I help you with today?" + """ + + messages = [ + { + "role": "system", + "content": content, + }, + ] + + context = OpenAILLMContext(messages, tools) + context_aggregator = llm.create_context_aggregator(context) + stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) + + pipeline = Pipeline( + [ + transport.input(), + stt, # STT + context_aggregator.user(), + llm, + tts, + transport.output(), + context_aggregator.assistant(), + ] + ) + + task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True)) + + @transport.event_handler("on_first_participant_joined") + async def on_first_participant_joined(_, participant): + logger.info(f"on_first_participant_joined: {participant}") + # await transport.capture_participant_transcription(participant["id"]) Might not need this + await task.queue_frames([LLMMessagesFrame(messages)]) + + @transport.event_handler("on_participant_left") + async def on_participant_left(_, participant, reason): + logger.info(f"on_participant_left: {participant} {reason}") + await task.queue_frame(EndFrame()) + + @transport.event_handler("on_dialin_ready") + async def on_dialin_ready(_, sip_endpoint): + logger.info(f"on_dialin_ready: {sip_endpoint}") + + @transport.event_handler("on_dialin_connected") + async def on_dialin_connected(transport, event): + logger.info(f"on_dialin_connected: {event}") + sip_session_id = event["sessionId"] + + async def transfer_call( + function_name, tool_call_id, args, llm: LLMService, context, result_callback + ): + logger.debug(f"transfer_call: {function_name} {tool_call_id} {args}") + + # sip_url = "sip:your_user_name@sip.linphone.org" + + sip_url = ( + f"sip:your_username@dailyco.sip.twilio.com?x-daily_id={room_url.split('/')[-1]}" + ) + + try: + await transport.sip_refer( + settings={ + "sessionId": sip_session_id, + "toEndPoint": sip_url, + } + ) + except Exception as e: + logger.error(f"An error occurred during SIP refer: {e}") + await result_callback({"transfer_call": False}) + + await result_callback({"transfer_call": True}) + + llm.register_function( + function_name="transfer_call", + callback=transfer_call, + ) + + runner = PipelineRunner() + + await runner.run(task) + + +if __name__ == "__main__": + asyncio.run(main())