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Remove 31 example and update 17 example

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This commit is contained in:
Mark Backman
2025-01-17 11:21:13 -05:00
parent 93743fdcbc
commit 66b56b1edf
3 changed files with 36 additions and 158 deletions
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5
CHANGELOG.md
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@@ -9,9 +9,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Added
- Added foundational example `31-user-idle.py` demonstrating how to use
`UserIdleProcessor` for handling user inactivity.
- Introduced pipeline frame observers. Observers can view all the frames that go
through the pipeline without the need to inject processors in the
pipeline. This can be useful, for example, to implement frame loggers or
@@ -59,6 +56,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Changed
- Updated the `17-detect-user-idle.py` to show how to use the `retry_count`.
- Enhanced `UserIdleProcessor` with retry counting functionality. Callbacks now
support an optional `retry_count` parameter to implement escalating responses
to user inactivity.

44
examples/foundational/17-detect-user-idle.py
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@@ -14,7 +14,7 @@ from loguru import logger
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMMessagesFrame
from pipecat.frames.frames import EndFrame, LLMMessagesFrame, TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -63,16 +63,36 @@ async def main():
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
async def user_idle_callback(user_idle: UserIdleProcessor):
messages.append(
{
"role": "system",
"content": "Ask the user if they are still there and try to prompt for some input, but be short.",
}
)
await user_idle.push_frame(LLMMessagesFrame(messages))
async def handle_user_idle(processor: UserIdleProcessor, retry_count: int) -> bool:
if retry_count == 1:
# First attempt: Add a gentle prompt to the conversation
messages.append(
{
"role": "system",
"content": "The user has been quiet for a while. Politely and concisely ask if they're still there.",
}
)
await user_idle.push_frame(LLMMessagesFrame(messages))
return True
elif retry_count == 2:
# Second attempt: More direct prompt
messages.append(
{
"role": "system",
"content": "The user is still inactive. Concisely ask if they would like to continue the conversation.",
}
)
await user_idle.push_frame(LLMMessagesFrame(messages))
return True
else:
# Third attempt: End the conversation
await user_idle.push_frame(
TTSSpeakFrame("It seems like you're busy right now. Have a nice day!")
)
await task.queue_frame(EndFrame())
return False
user_idle = UserIdleProcessor(callback=user_idle_callback, timeout=5.0)
user_idle = UserIdleProcessor(callback=handle_user_idle, timeout=5.0)
pipeline = Pipeline(
[
@@ -102,6 +122,10 @@ async def main():
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.queue_frame(EndFrame())
runner = PipelineRunner()
await runner.run(task)

145
examples/foundational/31-user-idle.py
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@@ -1,145 +0,0 @@
#
# Copyright (c) 2024–2025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import os
import sys
import aiohttp
from dotenv import load_dotenv
from loguru import logger
from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.processors.user_idle_processor import UserIdleProcessor
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
# Example callback using the new style with retry control
async def handle_user_idle(processor: UserIdleProcessor, retry_count: int) -> bool:
if retry_count == 1:
# First attempt: Add a gentle prompt to the conversation
messages.append(
{
"role": "system",
"content": "The user has been quiet for a while. Politely and concisely ask if they're still there.",
}
)
await task.queue_frames([context_aggregator.user().get_context_frame()])
return True
elif retry_count == 2:
# Second attempt: More direct prompt
messages.append(
{
"role": "system",
"content": "The user is still inactive. Concisely ask if they would like to continue the conversation.",
}
)
await task.queue_frames([context_aggregator.user().get_context_frame()])
return True
else:
# Third attempt: End the conversation
await task.queue_frames(
[TTSSpeakFrame("It seems like you're busy right now. Have a nice day!")]
)
await asyncio.sleep(3)
await task.queue_frame(EndFrame())
return False
async def main():
global task, messages, context_aggregator # Make these accessible to the idle handler
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(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_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4")
messages = [
{
"role": "system",
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
},
]
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
# Create the idle processor
idle_processor = UserIdleProcessor(
callback=handle_user_idle,
timeout=5.0, # 5 seconds of inactivity before triggering
)
pipeline = Pipeline(
[
transport.input(), # Transport user input
idle_processor, # Add the idle processor
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
report_only_initial_ttfb=True,
),
)
@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.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.queue_frame(EndFrame())
runner = PipelineRunner()
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())