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June 21, 2024 00:59
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Anthropic Claude Sonnet 3.5 inventing new ice cream flavors (Pipecat voice bot)
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import asyncio | |
import aiohttp | |
import os | |
import sys | |
from pipecat.frames.frames import LLMMessagesFrame | |
from pipecat.pipeline.pipeline import Pipeline | |
from pipecat.pipeline.runner import PipelineRunner | |
from pipecat.pipeline.task import PipelineParams, PipelineTask | |
from pipecat.processors.aggregators.llm_response import ( | |
LLMAssistantResponseAggregator, LLMUserResponseAggregator) | |
from pipecat.services.cartesia import CartesiaTTSService | |
from pipecat.services.anthropic import AnthropicLLMService | |
from pipecat.transports.services.daily import DailyParams, DailyTransport | |
from pipecat.vad.silero import SileroVADAnalyzer | |
from runner import configure | |
from loguru import logger | |
from dotenv import load_dotenv | |
load_dotenv(override=True) | |
logger.remove(0) | |
logger.add(sys.stderr, level="DEBUG") | |
async def main(room_url: str, token): | |
async with aiohttp.ClientSession() as session: | |
transport = DailyTransport( | |
room_url, | |
token, | |
"Respond bot", | |
DailyParams( | |
audio_out_enabled=True, | |
transcription_enabled=True, | |
vad_enabled=True, | |
vad_analyzer=SileroVADAnalyzer() | |
) | |
) | |
tts = CartesiaTTSService( | |
api_key=os.getenv("CARTESIA_API_KEY"), | |
voice_name=sys.argv[1] if len(sys.argv) > 1 else "British Lady" | |
) | |
llm = AnthropicLLMService( | |
api_key=os.getenv("ANTHROPIC_API_KEY"), | |
model="claude-3-5-sonnet-20240620", | |
temperature=1.0 | |
) | |
# todo: think more about how to handle system prompts in a more general way. OpenAI, | |
# Google, and Anthropic all have slightly different approaches to providing a system | |
# prompt. | |
messages = [ | |
{ | |
"role": "system", | |
"content": ( | |
"You are participating in a friendly competition to invent creative " | |
"new ice cream flavors. Say the craziest flavor you can think of " | |
"then wait for your opponent to come up with a different crazy flavor. " | |
"then respond with another flavor idea. Repeat forever. Say only the " | |
"ice cream flavors and nothing else. End each ice cream flavor statement " | |
"with an exclamation mark! Go ..." | |
) | |
}, | |
] | |
tma_in = LLMUserResponseAggregator(messages) | |
tma_out = LLMAssistantResponseAggregator(messages) | |
pipeline = Pipeline([ | |
transport.input(), # Transport user input | |
tma_in, # User responses | |
llm, # LLM | |
tts, # TTS | |
transport.output(), # Transport bot output | |
tma_out, # Assistant spoken responses | |
tma_trim | |
]) | |
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True)) | |
# When a participant joins, start transcription for that participant so the | |
# bot can "hear" and respond to them. | |
@ transport.event_handler("on_participant_joined") | |
async def on_participant_joined(transport, participant): | |
transport.capture_participant_transcription(participant["id"]) | |
# When the first participant joins, the bot should introduce itself. | |
@ transport.event_handler("on_first_participant_joined") | |
async def on_first_participant_joined(transport, participant): | |
await task.queue_frames([LLMMessagesFrame(messages)]) | |
runner = PipelineRunner() | |
await runner.run(task) | |
if __name__ == "__main__": | |
(url, token) = configure() | |
asyncio.run(main(url, token)) | |
# '{"action":"app-message","data":{"metrics":{"ttfb":[{"name":"AnthropicLLMService#0","time":0.5975627899169922}]},"type":"pipecat-metrics"},"fromId":"592d3489-90ba-401d-a760-c1a863d64a4a","callFrameId":"17189290998160.035120590426112264"}' | |
# [Durian and Limburger Cheese Charcoal Activated Tar Twist!] | |
# [Fermented Fish Sauce and Ghost Pepper Bubblegum Cotton Candy Nightmare!] | |
# [Spoiled Yogurt and Ghost Pepper Gummy Bear Blizzard!] |
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