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fix function calling examples

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This commit is contained in:
Aleix Conchillo Flaqué
2024-08-17 23:05:11 -07:00
parent ebc4e0924b
commit 6520f20ffe
16 changed files with 121 additions and 140 deletions
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19
examples/foundational/14-function-calling.py
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@@ -13,10 +13,6 @@ from pipecat.frames.frames import TextFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.aggregators.llm_response import (
LLMAssistantContextAggregator,
LLMUserContextAggregator,
)
from pipecat.processors.logger import FrameLogger
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.services.openai import OpenAILLMContext, OpenAILLMService
@@ -36,12 +32,12 @@ logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def start_fetch_weather(llm, function_name):
async def start_fetch_weather(llm, context, function_name):
await llm.push_frame(TextFrame("Let me check on that."))
async def fetch_weather_from_api(llm, function_name, args):
return {"conditions": "nice", "temperature": "75"}
async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
await result_callback({"conditions": "nice", "temperature": "75"})
async def main():
@@ -72,7 +68,6 @@ async def main():
# Register a function_name of None to get all functions
# sent to the same callback with an additional function_name parameter.
llm.register_function(
#"get_current_weather",
None,
fetch_weather_from_api,
start_callback=start_fetch_weather)
@@ -114,17 +109,17 @@ async def main():
]
context = OpenAILLMContext(messages, tools)
tma_in = LLMUserContextAggregator(context)
tma_out = LLMAssistantContextAggregator(context)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline([
fl_in,
transport.input(),
tma_in,
context_aggregator.user(),
llm,
fl_out,
tts,
transport.output(),
tma_out
context_aggregator.assistant(),
])
task = PipelineTask(pipeline)

15
examples/foundational/15-switch-voices.py
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@@ -14,10 +14,6 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_response import (
LLMAssistantContextAggregator,
LLMUserContextAggregator
)
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.filters.function_filter import FunctionFilter
from pipecat.services.cartesia import CartesiaTTSService
@@ -40,10 +36,10 @@ logger.add(sys.stderr, level="DEBUG")
current_voice = "News Lady"
async def switch_voice(llm, args):
async def switch_voice(function_name, tool_call_id, args, llm, context, result_callback):
global current_voice
current_voice = args["voice"]
return {"voice": f"You are now using your {current_voice} voice. Your responses should now be as if you were a {current_voice}."}
await result_callback({"voice": f"You are now using your {current_voice} voice. Your responses should now be as if you were a {current_voice}."})
async def news_lady_filter(frame) -> bool:
@@ -119,12 +115,11 @@ async def main():
]
context = OpenAILLMContext(messages, tools)
tma_in = LLMUserContextAggregator(context)
tma_out = LLMAssistantContextAggregator(context)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline([
transport.input(), # Transport user input
tma_in, # User responses
context_aggregator.user(), # User responses
llm, # LLM
ParallelPipeline( # TTS (one of the following vocies)
[FunctionFilter(news_lady_filter), news_lady], # News Lady voice
@@ -132,7 +127,7 @@ async def main():
[FunctionFilter(barbershop_man_filter), barbershop_man], # Barbershop Man voice
),
transport.output(), # Transport bot output
tma_out # Assistant spoken responses
context_aggregator.assistant(), # Assistant spoken responses
])
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))

15
examples/foundational/15a-switch-languages.py
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@@ -14,10 +14,6 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_response import (
LLMAssistantContextAggregator,
LLMUserContextAggregator
)
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.filters.function_filter import FunctionFilter
from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -41,10 +37,10 @@ logger.add(sys.stderr, level="DEBUG")
current_language = "English"
async def switch_language(llm, args):
async def switch_language(function_name, tool_call_id, args, llm, context, result_callback):
global current_language
current_language = args["language"]
return {"voice": f"Your answers from now on should be in {current_language}."}
await result_callback({"voice": f"Your answers from now on should be in {current_language}."})
async def english_filter(frame) -> bool:
@@ -117,20 +113,19 @@ async def main():
]
context = OpenAILLMContext(messages, tools)
tma_in = LLMUserContextAggregator(context)
tma_out = LLMAssistantContextAggregator(context)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline([
transport.input(), # Transport user input
stt, # STT
tma_in, # User responses
context_aggregator.user(), # User responses
llm, # LLM
ParallelPipeline( # TTS (bot will speak the chosen language)
[FunctionFilter(english_filter), english_tts], # English
[FunctionFilter(spanish_filter), spanish_tts], # Spanish
),
transport.output(), # Transport bot output
tma_out # Assistant spoken responses
context_aggregator.assistant() # Assistant spoken responses
])
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))

8
examples/foundational/19a-tools-anthropic.py
View File

@@ -9,18 +9,16 @@ 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.services.cartesia import CartesiaTTSService
from pipecat.services.anthropic import AnthropicLLMService, AnthropicUserContextAggregator, AnthropicAssistantContextAggregator
from pipecat.services.anthropic import AnthropicLLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
from pipecat.vad.silero import SileroVADAnalyzer
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from runner import configure
@@ -34,7 +32,7 @@ logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def get_weather(function_name, tool_call_id, arguments, context, result_callback):
async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
location = arguments["location"]
await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
@@ -98,7 +96,7 @@ async def main():
pipeline = Pipeline([
transport.input(), # Transport user input
context_aggregator.user(), # User speech to text
context_aggregator.user(), # User spoken responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output

9
examples/foundational/19b-tools-video-anthropic.py
View File

@@ -32,21 +32,16 @@ load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
# logger.add(sys.stderr, level="TRACE")
video_participant_id = None
# globally declare llm so that we can access it in the get_image function
llm = None
async def get_weather(function_name, tool_call_id, arguments, context, result_callback):
async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
location = arguments["location"]
await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
async def get_image(function_name, tool_call_id, arguments, context, result_callback):
global llm
async def get_image(function_name, tool_call_id, arguments, llm, context, result_callback):
question = arguments["question"]
await llm.request_image_frame(user_id=video_participant_id, text_content=question)

8
examples/foundational/19c-tools-togetherai.py
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@@ -35,7 +35,13 @@ logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def get_current_weather(function_name, tool_call_id, arguments, context, result_callback):
async def get_current_weather(
function_name,
tool_call_id,
arguments,
llm,
context,
result_callback):
logger.debug("IN get_current_weather")
location = arguments["location"]
await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")