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Include deprecation warnings for LLMUserResponseAggregator and LLMAssistantResponseAggregator

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This commit is contained in:
Mark Backman
2025-01-08 18:14:29 -05:00
parent 39c6446bdc
commit 3d5f640bab
4 changed files with 30 additions and 21 deletions
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16
examples/foundational/07p-interruptible-krisp.py
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@@ -14,14 +14,10 @@ from loguru import logger
from runner import configure
from pipecat.audio.filters.krisp_filter import KrispFilter
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.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -63,18 +59,18 @@ async def main():
},
]
tma_in = LLMUserResponseAggregator(messages)
tma_out = LLMAssistantResponseAggregator(messages)
context = OpenAILLMContext(messages)
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
tts, # TTS
transport.output(), # Transport bot output
tma_out, # Assistant spoken responses
context_aggregator.assistant(), # Assistant spoken responses
]
)
@@ -84,7 +80,7 @@ async def main():
async def on_first_participant_joined(transport, participant):
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMMessagesFrame(messages)])
await task.queue_frames([context_aggregator.user().get_context_frame()])
runner = PipelineRunner()

16
examples/foundational/21-tavus-layer.py
View File

@@ -14,14 +14,10 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
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.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.deepgram import DeepgramSTTService
from pipecat.services.openai import OpenAILLMService
@@ -74,19 +70,19 @@ async def main():
},
]
tma_in = LLMUserResponseAggregator(messages)
tma_out = LLMAssistantResponseAggregator(messages)
context = OpenAILLMContext(messages)
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
tts, # TTS
tavus, # Tavus output layer
transport.output(), # Transport bot output
tma_out, # Assistant spoken responses
context_aggregator.assistant(), # Assistant spoken responses
]
)
@@ -120,7 +116,7 @@ async def main():
messages.append(
{"role": "system", "content": "Please introduce yourself to the user."}
)
await task.queue_frames([LLMMessagesFrame(messages)])
await task.queue_frames([context_aggregator.user().get_context_frame()])
runner = PipelineRunner()