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examples(foundational/14l-function-calling-gemini-noaa-api): uses noa…
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examples/foundational/14l-function-calling-gemini-noaa-api.py
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# | ||
# Copyright (c) 2024, Daily | ||
# | ||
# SPDX-License-Identifier: BSD 2-Clause License | ||
# | ||
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import asyncio | ||
import os | ||
import sys | ||
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import aiohttp | ||
from dotenv import load_dotenv | ||
from loguru import logger | ||
from runner import configure | ||
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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.services.cartesia import CartesiaTTSService | ||
from pipecat.services.deepgram import DeepgramTTSService | ||
from pipecat.services.google import GoogleLLMService, GoogleLLMContext | ||
from pipecat.services.openai import OpenAILLMContext | ||
from pipecat.transports.services.daily import DailyParams, DailyTransport | ||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor | ||
from pipecat.frames.frames import ( | ||
LLMMessagesFrame, | ||
Frame, | ||
FunctionCallInProgressFrame, | ||
FunctionCallResultFrame, | ||
) | ||
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try: | ||
from noaa_sdk import NOAA | ||
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except ModuleNotFoundError as e: | ||
logger.error(f"Exception: {e}") | ||
logger.error("In order to run this example, please run `pip install noaa_sdk` and try again.") | ||
raise Exception(f"Missing module: {e}") | ||
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load_dotenv(override=True) | ||
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logger.remove(0) | ||
logger.add(sys.stderr, level="DEBUG") | ||
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system_prompt = """\ | ||
You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions. | ||
Your response will be turned into speech so use only simple words and punctuation. | ||
You have access to two tools: get_weather and get_postalcode. | ||
You can respond to questions about the weather using the get_weather tool. | ||
When you are asked about the weather, infer from the location what the postal code is and use that as the zip_code argument in the get_weather tool. | ||
""" | ||
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# Not necessary for function calling, but useful in observation | ||
# and debugging | ||
class functionCallPipecatObserver(FrameProcessor): | ||
def __init__(self): | ||
super().__init__() | ||
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async def process_frame(self, frame: Frame, direction: FrameDirection): | ||
await super().process_frame(frame, direction) | ||
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if isinstance(frame, FunctionCallInProgressFrame): | ||
await self.push_frame(frame) | ||
elif isinstance(frame, FunctionCallResultFrame): | ||
logger.info(f"Function {frame.function_name} returned: {frame.result}") | ||
await self.push_frame(frame) | ||
else: | ||
await self.push_frame(frame, direction) | ||
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async def get_noaa_simple_weather(zip_code: str, **kwargs): | ||
logger.debug(f"noaa get simple weather for {zip_code}") | ||
n = NOAA() | ||
observations = n.get_observations(postalcode=zip_code, country="US", num_of_stations=1) | ||
for observation in observations: | ||
description = observation["textDescription"] | ||
celcius_temp = observation["temperature"]["value"] | ||
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fahrenheit_temp = (celcius_temp * 9 / 5) + 32 | ||
return description, fahrenheit_temp | ||
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async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback): | ||
location = arguments["location"] | ||
logger.debug(f"get_weather location: {location}") | ||
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if len(location) == 5 and location.isdigit(): | ||
description, fahrenheit_temp = await get_noaa_simple_weather(location) | ||
else: | ||
return await result_callback( | ||
f"I'm sorry, I can't get the weather for {location} right now. Can you ask again please?" | ||
) | ||
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await result_callback( | ||
f"The weather in {location} is currently {round(fahrenheit_temp)} degrees and {description}." | ||
) | ||
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async def get_postalcode(function_name, tool_call_id, arguments, llm, context, result_callback): | ||
location = arguments["location"] | ||
await result_callback(f"{location}") | ||
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async def main(): | ||
async with aiohttp.ClientSession() as session: | ||
(room_url, token) = await configure(session) | ||
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transport = DailyTransport( | ||
room_url, | ||
token, | ||
"weather bot", | ||
DailyParams( | ||
audio_out_enabled=True, | ||
transcription_enabled=True, | ||
vad_enabled=True, | ||
vad_analyzer=SileroVADAnalyzer(), | ||
), | ||
) | ||
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tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en") | ||
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llm = GoogleLLMService( | ||
model="gemini-1.5-flash-latest", | ||
api_key=os.getenv("GOOGLE_API_KEY"), | ||
) | ||
llm.register_function("get_weather", get_weather) | ||
llm.register_function("get_postalcode", get_postalcode) | ||
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tools = [ | ||
{ | ||
"function_declarations": [ | ||
{ | ||
"name": "get_weather", | ||
"description": "Get the current weather", | ||
"parameters": { | ||
"type": "object", | ||
"properties": { | ||
"location": { | ||
"type": "string", | ||
"description": "The location for the weather request. Must be a ZIP code.", | ||
}, | ||
}, | ||
"required": ["location"], | ||
}, | ||
}, | ||
{ | ||
"name": "get_postalcode", | ||
"description": "Get the postal code of a location.", | ||
"parameters": { | ||
"type": "object", | ||
"properties": { | ||
"location": { | ||
"type": "string", | ||
"description": "The location to provide a postalcode for.", | ||
}, | ||
"zip": { | ||
"type": "string", | ||
"description": "Infer the postalcode from the location. Your options are any number between 00602 and 99999. Only respond with the 5 digit postal code.", | ||
}, | ||
}, | ||
"required": ["location"], | ||
}, | ||
}, | ||
] | ||
} | ||
] | ||
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messages = [ | ||
{"role": "system", "content": system_prompt}, | ||
{ | ||
"role": "user", | ||
"content": "Say hello and offer to provide weather information for anywhere in the United States of America.", | ||
}, | ||
] | ||
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context = OpenAILLMContext(messages, tools) | ||
context_aggregator = llm.create_context_aggregator(context) | ||
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functionCallObserver = functionCallPipecatObserver() | ||
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pipeline = Pipeline( | ||
[ | ||
transport.input(), | ||
context_aggregator.user(), | ||
functionCallObserver, | ||
llm, | ||
tts, | ||
transport.output(), | ||
context_aggregator.assistant(), | ||
] | ||
) | ||
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task = PipelineTask( | ||
pipeline, | ||
PipelineParams( | ||
allow_interruptions=True, | ||
enable_metrics=True, | ||
enable_usage_metrics=True, | ||
), | ||
) | ||
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@transport.event_handler("on_first_participant_joined") | ||
async def on_first_participant_joined(transport, participant): | ||
await transport.capture_participant_transcription(participant["id"]) | ||
# Kick off the conversation. | ||
await task.queue_frames([context_aggregator.user().get_context_frame()]) | ||
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runner = PipelineRunner() | ||
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await runner.run(task) | ||
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if __name__ == "__main__": | ||
asyncio.run(main()) |
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