pipecat_voice_chatbot_daily_openai_cartesia_quickstart.py

1import asyncio
2import os
3import sys
4
5from pipecat.frames.frames import EndFrame
6from pipecat.pipeline.pipeline import Pipeline
7from pipecat.pipeline.runner import PipelineRunner
8from pipecat.pipeline.task import PipelineParams, PipelineTask
9from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
10from pipecat.services.cartesia import CartesiaTTSService
11from pipecat.services.openai import OpenAILLMService
12from pipecat.transports.services.daily import DailyParams, DailyTransport
13
14from dotenv import load_dotenv
15
16load_dotenv(override=True)
17
18async def main():
19    async with DailyTransport(
20        room_url=os.getenv("DAILY_SAMPLE_ROOM_URL"),
21        token=None,
22        bot_name="Pipecat Bot",
23        params=DailyParams(audio_out_enabled=True)
24    ) as transport:
25        
26        # Initialize services
27        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
28        tts = CartesiaTTSService(
29            api_key=os.getenv("CARTESIA_API_KEY"),
30            voice_id="79a125e8-cd45-4c13-8a67-2756224abc25",  # British Lady
31        )
32
33        # Set up conversation context
34        messages = [
35            {
36                "role": "system",
37                "content": "You are a helpful assistant. Keep your responses concise and friendly.",
38            },
39        ]
40        context = OpenAILLMContext(messages)
41        context_aggregator = llm.create_context_aggregator(context)
42
43        # Define the pipeline
44        pipeline = Pipeline([
45            transport.input(),   # User audio in
46            context_aggregator.user(),
47            llm,                 # LLM processing
48            tts,                 # Text-to-Speech
49            transport.output(),  # Bot audio out
50            context_aggregator.assistant(),
51        ])
52
53        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
54
55        # Handle the event when a user joins the room
56        @transport.event_handler("on_first_participant_joined")
57        async def on_first_participant_joined(transport, participant):
58            # Kick off the conversation
59            messages.append({"role": "user", "content": "Please introduce yourself."})
60            await task.queue_frames([context_aggregator.user().get_context_frame()])
61
62        runner = PipelineRunner()
63        await runner.run(task)
64
65if __name__ == "__main__":
66    asyncio.run(main())