# # Copyright (c) 2024, Daily # # SPDX-License-Identifier: BSD 2-Clause License # import asyncio import os import sys import aiohttp from dotenv import load_dotenv from loguru import logger from runner import configure from pipecat.audio.vad.silero import SileroVADAnalyzer 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.conversation_flow import ConversationFlowProcessor from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService from pipecat.services.openai import OpenAILLMService from pipecat.transports.services.daily import DailyParams, DailyTransport load_dotenv(override=True) logger.remove(0) logger.add(sys.stderr, level="DEBUG") # Define our conversation flow flow_config = { "initial_node": "start", "nodes": { "start": { "message": { "role": "assistant", "content": "You are starting a conversation. Ask the user if they'd like to hear a joke or get weather information.", }, "functions": [ { "name": "tell_joke", "description": "User wants to hear a joke", "parameters": {"type": "object", "properties": {}}, }, { "name": "get_weather", "description": "User wants weather information", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The location to get weather for", } }, "required": ["location"], }, }, ], }, "tell_joke": { "message": { "role": "assistant", "content": "Tell a funny, clean joke and then ask if they'd like to hear another joke or get weather information.", }, "functions": [ { "name": "tell_joke", "description": "User wants another joke", "parameters": {"type": "object", "properties": {}}, }, { "name": "get_weather", "description": "User wants weather information", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The location to get weather for", } }, "required": ["location"], }, }, ], "actions": [{"type": "tts.say", "text": "Let me think of a good one..."}], }, "get_weather": { "message": { "role": "assistant", "content": "Provide the weather information and ask if they'd like to hear a joke or check another location's weather.", }, "functions": [ { "name": "tell_joke", "description": "User wants to hear a joke", "parameters": {"type": "object", "properties": {}}, }, { "name": "get_weather", "description": "User wants weather for another location", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The location to get weather for", } }, "required": ["location"], }, }, ], "actions": [ {"type": "tts.say", "text": "Let me check that weather information for you..."} ], }, }, } async def main(): async with aiohttp.ClientSession() as session: (room_url, _) = await configure(session) transport = DailyTransport( room_url, None, "Respond bot", DailyParams( audio_out_enabled=True, vad_enabled=True, vad_analyzer=SileroVADAnalyzer(), vad_audio_passthrough=True, ), ) stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY")) tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4") # Initialize conversation flow processor flow_processor = ConversationFlowProcessor(flow_config) # Create initial context messages = [ { "role": "system", "content": "You are a helpful assistant in a WebRTC call. Your responses will be converted to audio so avoid special characters. Always use the available functions to progress the conversation.", } ] context = OpenAILLMContext(messages) context_aggregator = llm.create_context_aggregator(context) pipeline = Pipeline( [ transport.input(), # Transport user input stt, # STT context_aggregator.user(), # User responses flow_processor, # Conversation flow management llm, # LLM tts, # TTS transport.output(), # Transport bot output context_aggregator.assistant(), # Assistant spoken responses ] ) task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True)) @transport.event_handler("on_first_participant_joined") async def on_first_participant_joined(transport, participant): await transport.capture_participant_transcription(participant["id"]) # Initialize the flow processor await flow_processor.initialize(messages) # Kick off the conversation await task.queue_frames([context_aggregator.user().get_context_frame()]) runner = PipelineRunner() await runner.run(task) if __name__ == "__main__": asyncio.run(main())