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Merge pull request #613 from pipecat-ai/aleix/examples-endframe

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examples: use EndFrame() when the participant leaves
This commit is contained in:
Aleix Conchillo Flaqué
2024-10-18 11:18:26 -07:00
committed by GitHub
parent 020f371ecb 8c006c24a3
commit 9dd3354b89
5 changed files with 52 additions and 42 deletions
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61
README.md
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@@ -51,10 +51,7 @@ Your project may or may not need these, so they're made available as optional re
Here is a very basic Pipecat bot that greets a user when they join a real-time session. We'll use [Daily](https://daily.co) for real-time media transport, and [Cartesia](https://cartesia.ai/) for text-to-speech.
```python
#app.py
import asyncio
import aiohttp
from pipecat.frames.frames import EndFrame, TextFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -64,39 +61,43 @@ from pipecat.services.cartesia import CartesiaTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport
async def main():
async with aiohttp.ClientSession() as session:
# Use Daily as a real-time media transport (WebRTC)
transport = DailyTransport(
room_url=...,
token=...,
bot_name="Bot Name",
params=DailyParams(audio_out_enabled=True))
# Use Daily as a real-time media transport (WebRTC)
transport = DailyTransport(
room_url=...,
token=...,
bot_name="Bot Name",
params=DailyParams(audio_out_enabled=True))
# Use Cartesia for Text-to-Speech
tts = CartesiaTTSService(
api_key=...,
voice_id=...
)
# Use Cartesia for Text-to-Speech
tts = CartesiaTTSService(
api_key=...,
voice_id=...
)
# Simple pipeline that will process text to speech and output the result
pipeline = Pipeline([tts, transport.output()])
# Simple pipeline that will process text to speech and output the result
pipeline = Pipeline([tts, transport.output()])
# Create Pipecat processor that can run one or more pipelines tasks
runner = PipelineRunner()
# Create Pipecat processor that can run one or more pipelines tasks
runner = PipelineRunner()
# Assign the task callable to run the pipeline
task = PipelineTask(pipeline)
# Assign the task callable to run the pipeline
task = PipelineTask(pipeline)
# Register an event handler to play audio when a
# participant joins the transport WebRTC session
@transport.event_handler("on_participant_joined")
async def on_new_participant_joined(transport, participant):
participant_name = participant["info"]["userName"] or ''
# Queue a TextFrame that will get spoken by the TTS service (Cartesia)
await task.queue_frames([TextFrame(f"Hello there, {participant_name}!"), EndFrame()])
# Register an event handler to play audio when a
# participant joins the transport WebRTC session
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
participant_name = participant.get("info", {}).get("userName", "")
# Queue a TextFrame that will get spoken by the TTS service (Cartesia)
await task.queue_frame(TextFrame(f"Hello there, {participant_name}!"))
# Run the pipeline task
await runner.run(task)
# Register an event handler to exit the application when the user leaves.
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.queue_frame(EndFrame())
# Run the pipeline task
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())

13
examples/foundational/01-say-one-thing.py
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@@ -47,10 +47,15 @@ async def main():
# Register an event handler so we can play the audio when the
# participant joins.
@transport.event_handler("on_participant_joined")
async def on_new_participant_joined(transport, participant):
participant_name = participant["info"]["userName"] or ""
await task.queue_frames([TextFrame(f"Hello there, {participant_name}!"), EndFrame()])
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
participant_name = participant.get("info", {}).get("userName", "")
await task.queue_frame(TextFrame(f"Hello there, {participant_name}!"))
# Register an event handler to exit the application when the user leaves.
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.queue_frame(EndFrame())
await runner.run(task)

6
examples/foundational/02-llm-say-one-thing.py
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@@ -57,7 +57,11 @@ async def main():
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
await task.queue_frame(LLMMessagesFrame(messages))
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.queue_frame(EndFrame())
await runner.run(task)

12
examples/foundational/03-still-frame.py
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@@ -9,7 +9,7 @@ import aiohttp
import os
import sys
from pipecat.frames.frames import TextFrame
from pipecat.frames.frames import EndFrame, TextFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
@@ -51,11 +51,11 @@ async def main():
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
# Note that we do not put an EndFrame() item in the pipeline for this demo.
# This means that the bot will stay in the channel until it times out.
# An EndFrame() in the pipeline would cause the transport to shut
# down.
await task.queue_frames([TextFrame("a cat in the style of picasso")])
await task.queue_frame(TextFrame("a cat in the style of picasso"))
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.queue_frame(EndFrame())
await runner.run(task)

2
examples/foundational/06a-image-sync.py
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@@ -129,7 +129,7 @@ async def main():
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
participant_name = participant["info"]["userName"] or ""
participant_name = participant.get("info", {}).get("userName", "")
transport.capture_participant_transcription(participant["id"])
await task.queue_frames([TextFrame(f"Hi there {participant_name}!")])