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20 Commits

Author SHA1 Message Date
Chad Bailey
1472a3abb8 attempt at 2 pipelines 2025-02-24 21:25:13 +00:00
Dominic
3745078bf1 Fixed logic 2025-02-24 10:44:07 -08:00
Dominic
1a2c98f70b Starting to add logic for native audio input for flash lite 2025-02-24 10:28:28 -08:00
Dominic
e988ce6838 Forgot to use the same logic for the openai bot 2025-02-22 14:52:53 -08:00
Dominic
546c97e75b Simplified logic for dialin 2025-02-22 14:49:33 -08:00
Dominic
410a6b9238 moved terminate call to handlers class 2025-02-22 14:38:14 -08:00
Dominic
281b56e5de Updated prompt for non gemini bot to look for more voicemail examples, plus added logic to detect if we're doing dialin or not to avoid a non-fatal dialin related error 2025-02-21 16:19:59 -08:00
Dominic
c66042afb6 Fixed import ordering 2025-02-20 14:56:45 -08:00
Dominic Stewart
61f8e54dec Merge branch 'main' into dom/gemini-system-prompt-switching 2025-02-20 14:48:45 -08:00
Dominic
390adf193a Added a few more things to detect in the prompt 2025-02-20 14:44:12 -08:00
Dominic
68587ca4e9 Updated the code to use the correct prompt broken down into smaller pieces 2025-02-20 14:28:02 -08:00
Dominic
b71ad2d082 I think this works 2025-02-20 09:42:19 -08:00
Dominic
781652f4f9 Improvement 2025-02-20 09:27:34 -08:00
Dominic
621813571a This works 2025-02-19 20:24:27 -08:00
Dominic
ceefea8d63 Changed example to use gemini 2.0 flash lite 2025-02-18 19:08:22 -08:00
Dominic
1974474480 Updated the readme 2025-02-18 18:16:27 -08:00
Dominic
160d054aa5 Updated the readme 2025-02-18 18:10:34 -08:00
Dominic
4718f68717 Based on feedback, made the gemini file something that can be called separately 2025-02-18 18:04:29 -08:00
Dominic
3a781c786c Fixed typo 2025-02-17 10:22:06 -08:00
Dominic
a066e2bcfd Updated example to use Gemini 2025-02-17 10:17:59 -08:00
161 changed files with 702 additions and 1269 deletions

View File

@@ -5,35 +5,10 @@ All notable changes to **Pipecat** will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
## Unreleased
### Added
- Pipecat version will now be logged on every application startup. This will
help us identify what version we are running in case of any issues.
- Added a new `StopFrame` which can be used to stop a pipeline task while
keeping the frame processors running. The frame processors could then be used
in a different pipeline. The difference between a `StopFrame` and a
`StopTaskFrame` is that, as with `EndFrame` and `EndTaskFrame`, the
`StopFrame` is pushed from the task and the `StopTaskFrame` is pushed upstream
inside the pipeline by any processor.
- Added a new `PipelineTask` parameter `observers` that replaces the previous
`PipelineParams.observers`.
- Added a new `PipelineTask` parameter `check_dangling_tasks` to enable or
disable checking for frame processors' dangling tasks when the Pipeline
finishes running.
- Added new `on_completion_timeout` event for LLM services (all OpenAI-based
services, Anthropic and Google). Note that this event will only get triggered
if LLM timeouts are setup and if the timeout was reached. It can be useful to
retrigger another completion and see if the timeout was just a blip.
- Added new log observers `LLMLogObserver` and `TranscriptionLogObserver` that
can be useful for debugging your pipelines.
- Added `room_url` property to `DailyTransport`.
- Added `addons` argument to `DeepgramSTTService`.
@@ -42,23 +17,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Changed
- ⚠️ `PipelineTask` now requires keyword arguments (except for the first one for
the pipeline).
- The base `TTSService` class now strips leading newlines before sending text
to the TTS provider. This change is to solve issues where some TTS providers,
like Azure, would not output text due to newlines.
- `GrokLLMSService` now uses `grok-2` as the default model.
- `AnthropicLLMService` now uses `claude-3-7-sonnet-20250219` as the default
model.
- `RimeHttpTTSService` needs an `aiohttp.ClientSession` to be passed to the
constructor as all the other HTTP-based services.
- `RimeHttpTTSService` doesn't use a default voice anymore.
- `DeepgramSTTService` now uses the new `nova-3` model by default. If you want
to use the previous model you can pass `LiveOptions(model="nova-2-general")`.
(see https://deepgram.com/learn/introducing-nova-3-speech-to-text-api)
@@ -67,47 +25,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
stt = DeepgramSTTService(..., live_options=LiveOptions(model="nova-2-general"))
```
### Deprecated
- `PipelineParams.observers` is now deprecated, you the new `PipelineTask`
parameter `observers`.
### Removed
- Remove `TransportParams.audio_out_is_live` since it was not being used at all.
### Fixed
- Fixed an `AudioContextWordTTSService` issue that would cause an `EndFrame` to
disconnect from the TTS service before audio from all the contexts was
received. This affected services like Cartesia and Rime.
- Fixed an issue that was not allowing to pass an `OpenAILLMContext` to create
`GoogleLLMService`'s context aggregators.
- Fixed a `ElevenLabsTTSService`, `FishAudioTTSService`, `LMNTTTSService` and
`PlayHTTTSService` issue that was resulting in audio requested before an
interruption being played after an interruption.
- Fixed `match_endofsentence` support for ellipses.
- Fixed an issue that would cause undesired interruptions via
`EmulateUserStartedSpeakingFrame` when only interim transcriptions (i.e. no
final transcriptions) where received.
- Fixed an issue where `EndTaskFrame` was not triggering
`on_client_disconnected` or closing the WebSocket in FastAPI.
- Fixed an issue in `DeepgramSTTService` where the `sample_rate` passed to the
`LiveOptions` was not being used, causing the service to use the default
sample rate of pipeline.
- Fixed a context aggregator issue that would not append the LLM text response
to the context if a function call happened in the same LLM turn.
- Fixed an issue that was causing HTTP TTS services to push `TTSStoppedFrame`
more than once.
- Fixed a `FishAudioTTSService` issue where `TTSStoppedFrame` was not being
pushed.

View File

@@ -3,10 +3,10 @@ coverage~=7.6.12
grpcio-tools~=1.67.1
pip-tools~=7.4.1
pre-commit~=4.0.1
pyright~=1.1.394
pyright~=1.1.393
pytest~=8.3.4
pytest-asyncio~=0.25.3
ruff~=0.9.7
pytest-asyncio~=0.25.2
ruff~=0.9.5
setuptools~=70.0.0
setuptools_scm~=8.1.0
python-dotenv~=1.0.1

View File

@@ -18,9 +18,6 @@ AZURE_DALLE_API_KEY=...
AZURE_DALLE_ENDPOINT=https://...
AZURE_DALLE_MODEL=...
# Cartesia
CARTESIA_API_KEY=...
# Daily
DAILY_API_KEY=...
DAILY_SAMPLE_ROOM_URL=https://...

View File

@@ -17,7 +17,7 @@ from runner import configure
from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame, TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.cartesia import CartesiaTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport

View File

@@ -119,7 +119,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -124,7 +124,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@audiobuffer.event_handler("on_audio_data")
async def on_audio_data(buffer, audio, sample_rate, num_channels):

View File

@@ -70,7 +70,7 @@ async def main(room_url: str, token: str):
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -62,7 +62,7 @@ async def main(room_url: str, token: str):
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -18,7 +18,8 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.fal import FalImageGenService
from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.local.tk import TkLocalTransport
load_dotenv(override=True)
@@ -33,9 +34,7 @@ async def main():
transport = TkLocalTransport(
tk_root,
TkTransportParams(
camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024
),
TransportParams(camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024),
)
imagegen = FalImageGenService(

View File

@@ -44,8 +44,7 @@ async def main():
runner = PipelineRunner()
task = PipelineTask(
Pipeline([imagegen, transport.output()]),
params=PipelineParams(enable_metrics=True),
Pipeline([imagegen, transport.output()]), PipelineParams(enable_metrics=True)
)
@transport.event_handler("on_first_participant_joined")

View File

@@ -30,7 +30,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia import CartesiaHttpTTSService
from pipecat.services.fal import FalImageGenService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.local.tk import TkLocalTransport, TkOutputTransport
load_dotenv(override=True)
@@ -151,7 +152,7 @@ async def main():
transport = TkLocalTransport(
tk_root,
TkTransportParams(
TransportParams(
audio_out_enabled=True,
camera_out_enabled=True,
camera_out_width=1024,

View File

@@ -105,10 +105,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
PipelineParams(enable_metrics=True, enable_usage_metrics=True),
)
@transport.event_handler("on_first_participant_joined")

View File

@@ -127,7 +127,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -76,7 +76,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -74,7 +74,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -79,7 +79,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -103,7 +103,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -81,7 +81,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -74,7 +74,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -74,7 +74,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -75,7 +75,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -77,7 +77,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -83,7 +83,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -81,7 +81,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -81,7 +81,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -75,7 +75,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -80,7 +80,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -71,7 +71,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -88,7 +88,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -81,7 +81,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -79,7 +79,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -80,7 +80,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -76,7 +76,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -74,7 +74,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -74,7 +74,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -251,7 +251,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -74,7 +74,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -78,11 +78,7 @@ async def main():
runner = PipelineRunner()
task = PipelineTask(
pipeline,
params=PipelineParams(
audio_in_sample_rate=24000,
audio_out_sample_rate=24000,
),
pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
)
await runner.run(task)

View File

@@ -24,7 +24,8 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.local.tk import TkLocalTransport
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
@@ -66,7 +67,7 @@ async def main():
tk_transport = TkLocalTransport(
tk_root,
TkTransportParams(
TransportParams(
audio_out_enabled=True,
camera_out_enabled=True,
camera_out_is_live=True,
@@ -82,11 +83,7 @@ async def main():
pipeline = Pipeline([daily_transport.input(), MirrorProcessor(), tk_transport.output()])
task = PipelineTask(
pipeline,
params=PipelineParams(
audio_in_sample_rate=24000,
audio_out_sample_rate=24000,
),
pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
)
async def run_tk():

View File

@@ -76,7 +76,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -112,7 +112,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -99,13 +99,7 @@ async def main():
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
allow_interruptions=True,
enable_metrics=True,
),
)
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -153,13 +153,7 @@ If you need to use a tool, simply use the tool. Do not tell the user the tool yo
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
allow_interruptions=True,
enable_metrics=True,
),
)
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -152,7 +152,7 @@ indicate you should use the get_image tool are:
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -116,7 +116,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -113,7 +113,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -117,7 +117,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -116,7 +116,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -116,7 +116,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -123,7 +123,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -123,7 +123,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -117,7 +117,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -83,7 +83,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -133,7 +133,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -126,7 +126,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -85,13 +85,7 @@ async def main():
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
allow_interruptions=True,
enable_metrics=True,
),
)
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
# When a participant joins, start transcription for that participant so the
# bot can "hear" and respond to them.

View File

@@ -108,7 +108,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
report_only_initial_ttfb=True,

View File

@@ -38,6 +38,7 @@ async def main():
"GStreamer",
DailyParams(
audio_out_enabled=True,
audio_out_is_live=True,
camera_out_enabled=True,
camera_out_width=1280,
camera_out_height=720,

View File

@@ -16,13 +16,10 @@ from runner import configure
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import TranscriptionMessage, TranscriptionUpdateFrame
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.transcript_processor import TranscriptProcessor
from pipecat.services.deepgram import DeepgramSTTService
from pipecat.services.openai_realtime_beta import (
InputAudioTranscription,
OpenAIRealtimeBetaLLMService,
@@ -143,29 +140,21 @@ Remember, your responses should be short. Just one or two sentences, usually."""
tools,
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
# Create transcript processor and handler
transcript = TranscriptProcessor()
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
transcript.user(), # User transcripts
context_aggregator.user(),
llm, # LLM
context_aggregator.assistant(),
transcript.assistant(), # Assistant transcripts
transport.output(), # Transport bot output
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
@@ -173,16 +162,9 @@ Remember, your responses should be short. Just one or two sentences, usually."""
),
)
# Register event handler for transcript updates
@transcript.event_handler("on_transcript_update")
async def on_transcript_update(processor, frame):
logger.debug(f"Received transcript update with {len(frame.messages)} new messages")
for msg in frame.messages:
logger.debug(msg)
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
# await transport.capture_participant_transcription(participant["id"])
await transport.capture_participant_transcription(participant["id"])
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])

View File

@@ -212,7 +212,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -237,7 +237,7 @@ Remember, your responses should be short. Just one or two sentences, usually."""
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -209,7 +209,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -263,7 +263,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -87,7 +87,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
# We just use 16000 because that's what Tavus is expecting and
# we avoid resampling.
audio_in_sample_rate=16000,

View File

@@ -145,7 +145,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -138,7 +138,6 @@ class OutputGate(FrameProcessor):
self._gate_open = start_open
self._frames_buffer = []
self._notifier = notifier
self._gate_task = None
def close_gate(self):
self._gate_open = False
@@ -179,13 +178,10 @@ class OutputGate(FrameProcessor):
async def _start(self):
self._frames_buffer = []
if not self._gate_task:
self._gate_task = self.create_task(self._gate_task_handler())
self._gate_task = self.create_task(self._gate_task_handler())
async def _stop(self):
if self._gate_task:
await self.cancel_task(self._gate_task)
self._gate_task = None
await self.cancel_task(self._gate_task)
async def _gate_task_handler(self):
while True:
@@ -355,7 +351,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -342,7 +342,6 @@ class OutputGate(FrameProcessor):
self._gate_open = start_open
self._frames_buffer = []
self._notifier = notifier
self._gate_task = None
def close_gate(self):
self._gate_open = False
@@ -383,13 +382,10 @@ class OutputGate(FrameProcessor):
async def _start(self):
self._frames_buffer = []
if not self._gate_task:
self._gate_task = self.create_task(self._gate_task_handler())
self._gate_task = self.create_task(self._gate_task_handler())
async def _stop(self):
if self._gate_task:
await self.cancel_task(self._gate_task)
self._gate_task = None
await self.cancel_task(self._gate_task)
async def _gate_task_handler(self):
while True:
@@ -564,7 +560,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -25,8 +25,10 @@ from pipecat.frames.frames import (
InputAudioRawFrame,
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
LLMMessagesFrame,
StartFrame,
StartInterruptionFrame,
StopInterruptionFrame,
SystemFrame,
TextFrame,
TranscriptionFrame,
@@ -553,7 +555,6 @@ class OutputGate(FrameProcessor):
self._notifier = notifier
self._context = context
self._transcription_buffer = user_transcription_buffer
self._gate_task = None
def close_gate(self):
self._gate_open = False
@@ -601,13 +602,10 @@ class OutputGate(FrameProcessor):
async def _start(self):
self._frames_buffer = []
if not self._gate_task:
self._gate_task = self.create_task(self._gate_task_handler())
self._gate_task = self.create_task(self._gate_task_handler())
async def _stop(self):
if self._gate_task:
await self.cancel_task(self._gate_task)
self._gate_task = None
await self.cancel_task(self._gate_task)
async def _gate_task_handler(self):
while True:
@@ -742,7 +740,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -87,7 +87,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -122,7 +122,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -354,7 +354,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -63,7 +63,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -89,7 +89,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -120,7 +120,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -79,7 +79,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -106,7 +106,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -1,5 +1,5 @@
#
# Copyright (c) 2024-2025, Daily
# Copyright (c) 2024, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
@@ -34,7 +34,7 @@ search_tool = {"google_search": {}}
tools = [search_tool]
system_instruction = """
You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting.
You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting.
Always use the google search API to retrieve the latest news. You must also use it to check which day is today.
@@ -93,7 +93,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -83,7 +83,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
),

View File

@@ -150,7 +150,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -150,7 +150,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -178,7 +178,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -18,10 +18,12 @@ from pipecat.frames.frames import (
BotStartedSpeakingFrame,
BotStoppedSpeakingFrame,
Frame,
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
LLMTextFrame,
StartInterruptionFrame,
)
from pipecat.observers.base_observer import BaseObserver
from pipecat.observers.loggers.llm_log_observer import LLMLogObserver
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -71,6 +73,38 @@ class DebugObserver(BaseObserver):
logger.info(f"🤖 BOT STOP SPEAKING: {src} {arrow} {dst} at {time_sec:.2f}s")
class LLMLogObserver(BaseObserver):
"""Observer to log LLM activity to the console.
Logs all frame instances of:
- LLMFullResponseStartFrame (only from LLM service)
- LLMTextFrame
- LLMFullResponseEndFrame (only from LLM service)
This allows you to track when the LLM starts responding, what it generates, and when it finishes.
Log format: [LLM EVENT]: [details] at [timestamp]s
"""
async def on_push_frame(
self,
src: FrameProcessor,
dst: FrameProcessor,
frame: Frame,
direction: FrameDirection,
timestamp: int,
):
time_sec = timestamp / 1_000_000_000
# Only log start/end frames from OpenAILLMService
if isinstance(frame, (LLMFullResponseStartFrame, LLMFullResponseEndFrame)):
if isinstance(src, OpenAILLMService):
event = "START" if isinstance(frame, LLMFullResponseStartFrame) else "END"
logger.info(f"🧠 LLM {event} RESPONSE at {time_sec:.2f}s")
# Log all LLMTextFrames
elif isinstance(frame, LLMTextFrame):
logger.info(f"🧠 LLM GENERATING: {frame.text!r} at {time_sec:.2f}s")
async def main():
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(session)
@@ -117,13 +151,13 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
report_only_initial_ttfb=True,
observers=[DebugObserver(), LLMLogObserver()],
),
observers=[DebugObserver(), LLMLogObserver()],
)
@transport.event_handler("on_first_participant_joined")

View File

@@ -32,7 +32,7 @@ async def main():
pipeline = Pipeline([NullProcessor()])
task = PipelineTask(pipeline, params=PipelineParams(enable_heartbeats=True))
task = PipelineTask(pipeline, PipelineParams(enable_heartbeats=True))
runner = PipelineRunner()

View File

@@ -1,5 +1,5 @@
#
# Copyright (c) 2024-2025, Daily
# Copyright (c) 2024, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
@@ -38,7 +38,7 @@ search_tool = {"google_search_retrieval": {}}
tools = [search_tool]
system_instruction = """
You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting.
You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting.
Always use the google search API to retrieve the latest news. You must also use it to check which day is today.
@@ -117,7 +117,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -230,7 +230,7 @@ Your response will be turned into speech so use only simple words and punctuatio
)
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

View File

@@ -92,8 +92,10 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(allow_interruptions=True),
observers=[rtvi.observer()],
params=PipelineParams(
allow_interruptions=True,
observers=[rtvi.observer()],
),
)
@rtvi.event_handler("on_client_ready")

View File

@@ -140,8 +140,10 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(allow_interruptions=True),
observers=[GoogleRTVIObserver(rtvi)],
PipelineParams(
allow_interruptions=True,
observers=[GoogleRTVIObserver(rtvi)],
),
)
@rtvi.event_handler("on_client_ready")

View File

@@ -346,7 +346,7 @@ async def main():
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=False))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=False))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -113,6 +113,7 @@ We have introduced support for Google's Gemini 2.0 Flash Lite model in this exam
**Quick Start**
To use the Gemini-based bot instead of OpenAI:
```shell
curl -X POST "http://localhost:7860/daily_gemini_start_bot" \ py pipecat
-H "Content-Type: application/json" \
@@ -121,25 +122,24 @@ curl -X POST "http://localhost:7860/daily_gemini_start_bot" \
All request body parameters supported by /daily_start_bot (such as detectVoicemail, dialoutNumber, etc.) are also compatible with /daily_gemini_start_bot.
This example uses context switching to help steer the bot in the right direction. As Flash Lite is a smaller model, breaking the prompt down into smaller piece helps to improve the bot's accuracy.
For example, instead of giving one large prompt like:
```python
system_instruction="""You are a chatbot that needs to detect if you're talking to a voicemail system or human, then either leave a message or have a conversation. If it's voicemail, say "Hello, this is a message..." and hang up. If it's a human, introduce yourself and be helpful until they say goodbye."""
```
We break it into stages:
First prompt focuses only on detection: "Determine if this is voicemail or human"
After detection, we switch to a new context: either "Leave this specific voicemail message" or "Have a conversation with the human".
This example uses context switching to help steer the bot in the right direction. As Flash Lite is a smaller model, getting it to consistently call functions was difficult for these longer prompts. Breaking the prompt
down into smaller pieces helped improve the accuracy of the bot.
**Implementation Details**
The implementation is available in bot_daily_gemini.py and features:
- Staged prompting approach: Breaking down complex tasks into smaller, more focused prompts to improve the lightweight model's performance
- Dynamic context switching: The bot can change its behavior in real-time based on what it detects (voicemail vs. human caller)
- Function-based architecture: Uses function calling to trigger context switches and call termination
Staged prompting approach: Breaking down complex tasks into smaller, more focused prompts to improve the lightweight model's performance
Dynamic context switching: The bot can change its behavior in real-time based on what it detects (voicemail vs. human caller)
Function-based architecture: Uses function calling to trigger context switches and call termination
**Optimizations for Lightweight Models**
Working with Gemini 2.0 Flash Lite required some specific optimizations:
Simplified prompts: Each prompt focuses on a single task with clear instructions
Function-driven state changes: The model calls specific functions to switch between different conversation modes
Reduced context requirements: Each stage maintains only the context needed for its specific purpose
This approach significantly improves the consistency of function calling in this lightweight model, which was challenging with longer, more complex prompts.
### More information

View File

@@ -49,7 +49,7 @@ async def main(
# If you are handling this via Twilio, Telnyx, set this to None
# and handle call-forwarding when on_dialin_ready fires.
# We don't want to specify dial-in settings if we're not dialing in
# We don't want to specify dialin settings if we're not dialing in
dialin_settings = None
if callId and callDomain:
dialin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
@@ -150,7 +150,7 @@ async def main(
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
if dialout_number:
logger.debug("dialout number detected; doing dialout")

View File

@@ -20,6 +20,7 @@ from pipecat.frames.frames import (
EndTaskFrame,
Frame,
InputAudioRawFrame,
StopTaskFrame,
SystemFrame,
TranscriptionFrame,
UserStartedSpeakingFrame,
@@ -44,6 +45,8 @@ logger.add(sys.stderr, level="DEBUG")
daily_api_key = os.getenv("DAILY_API_KEY", "")
daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
system_message = None
class UserAudioCollector(FrameProcessor):
"""This FrameProcessor collects audio frames in a buffer, then adds them to the
@@ -120,21 +123,24 @@ class FunctionHandlers:
self, function_name, tool_call_id, args, llm, context, result_callback
):
"""Function the bot can call to leave a voicemail message."""
message = """You are Chatbot leaving a voicemail message. Say EXACTLY this message and nothing else:
print(f"!!! Got a voicemail response, llm is: {llm}")
system_message = """You are Chatbot leaving a voicemail message. Say EXACTLY this message and nothing else:
"Hello, this is a message for Pipecat example user. This is Chatbot. Please call back on 123-456-7891. Thank you."
After saying this message, call the terminate_call function."""
await self.context_switcher.switch_context(system_instruction=message)
await result_callback("Leaving a voicemail message")
print("!!! about to push stop task frame from voicemail")
await llm.queue_frame(StopTaskFrame(), FrameDirection.UPSTREAM)
print("!!! pushed stop task frame from voicemail")
await result_callback("Goodbye")
async def human_conversation(
self, function_name, tool_call_id, args, llm, context, result_callback
):
"""Function the bot can when it detects it's talking to a human."""
message = """You are Chatbot talking to a human. Be friendly and helpful.
print(f"!!! Got a human response, llm is: {llm}")
system_message = """You are Chatbot talking to a human. Be friendly and helpful.
Start with: "Hello! I'm a friendly chatbot. How can I help you today?"
@@ -147,17 +153,16 @@ class FunctionHandlers:
- "Thank you, that's all I needed"
THEN say: "Thank you for chatting. Goodbye!" and call the terminate_call function."""
await self.context_switcher.switch_context(system_instruction=message)
await result_callback("Talking to the customer")
print("!!! about to push stop task frame from human")
await llm.queue_frame(StopTaskFrame(), FrameDirection.UPSTREAM)
print("!!! pushed stop task frame from human")
await result_callback("Goodbye")
async def terminate_call(
function_name, tool_call_id, args, llm: LLMService, context, result_callback
):
"""Function the bot can call to terminate the call upon completion of the call."""
await llm.queue_frame(EndTaskFrame(), FrameDirection.UPSTREAM)
@@ -173,7 +178,7 @@ async def main(
# If you are handling this via Twilio, Telnyx, set this to None
# and handle call-forwarding when on_dialin_ready fires.
# We don't want to specify dial-in settings if we're not dialing in
# We don't want to specify dialin settings if we're not dialing in
dialin_settings = None
if callId and callDomain:
dialin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
@@ -239,39 +244,88 @@ If it sounds like a human (saying hello, asking questions, etc.), call the funct
DO NOT say anything until you've determined if this is a voicemail or human."""
llm = GoogleLLMService(
greeting_llm = GoogleLLMService(
model="models/gemini-2.0-flash-lite-preview-02-05",
api_key=os.getenv("GOOGLE_API_KEY"),
system_instruction=system_instruction,
tools=tools,
)
context = GoogleLLMContext()
context_aggregator = llm.create_context_aggregator(context)
audio_collector = UserAudioCollector(context, context_aggregator.user())
greeting_context = GoogleLLMContext()
greeting_context_aggregator = greeting_llm.create_context_aggregator(greeting_context)
greeting_audio_collector = UserAudioCollector(
greeting_context, greeting_context_aggregator.user()
)
context_switcher = ContextSwitcher(llm, context_aggregator.user())
context_switcher = ContextSwitcher(greeting_llm, greeting_context_aggregator.user())
handlers = FunctionHandlers(context_switcher)
llm.register_function("switch_to_voicemail_response", handlers.voicemail_response)
llm.register_function("switch_to_human_conversation", handlers.human_conversation)
llm.register_function("terminate_call", terminate_call)
greeting_llm.register_function("switch_to_voicemail_response", handlers.voicemail_response)
greeting_llm.register_function("switch_to_human_conversation", handlers.human_conversation)
greeting_llm.register_function("terminate_call", terminate_call)
pipeline = Pipeline(
greeting_pipeline = Pipeline(
[
transport.input(), # Transport user input
audio_collector, # Collect audio frames
context_aggregator.user(), # User responses
llm, # LLM
greeting_audio_collector, # Collect audio frames
greeting_context_aggregator.user(), # User responses
greeting_llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
greeting_context_aggregator.assistant(), # Assistant spoken responses
]
)
greeting_pipeline_task = PipelineTask(
greeting_pipeline,
PipelineParams(allow_interruptions=True),
)
runner = PipelineRunner()
print("!!! starting greeting")
await runner.run(greeting_pipeline_task)
print("!!! Done with greeting")
# Create conversation pipeline with new system message
conversation_llm = GoogleLLMService(
model="models/gemini-2.0-flash-lite-preview-02-05",
api_key=os.getenv("GOOGLE_API_KEY"),
system_instruction=system_message if system_message else "You are a helpful chatbot.",
tools=[
{
"function_declarations": [
{
"name": "terminate_call",
"description": "Call this function to terminate the call.",
}
]
}
],
)
conversation_llm.register_function("terminate_call", terminate_call)
conversation_context = GoogleLLMContext()
conversation_context_aggregator = conversation_llm.create_context_aggregator(
conversation_context
)
conversation_audio_collector = UserAudioCollector(
conversation_context, conversation_context_aggregator.user()
)
conversation_pipeline = Pipeline(
[
transport.input(), # Transport user input
conversation_audio_collector, # Collect audio frames
conversation_context_aggregator.user(), # User responses
conversation_llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
conversation_context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(allow_interruptions=True),
conversation_task = PipelineTask(
conversation_pipeline,
PipelineParams(allow_interruptions=True),
)
if dialout_number:
@@ -319,11 +373,11 @@ DO NOT say anything until you've determined if this is a voicemail or human."""
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):
await task.cancel()
await conversation_task.cancel()
runner = PipelineRunner()
await runner.run(task)
print("!!! Starting conversation")
await runner.run(conversation_task)
print("!!! Done with conversation")
if __name__ == "__main__":

View File

@@ -77,7 +77,7 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):

View File

@@ -90,7 +90,7 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(allow_interruptions=True, enable_metrics=True),
PipelineParams(allow_interruptions=True, enable_metrics=True),
)
@transport.event_handler("on_first_participant_joined")

View File

@@ -172,12 +172,12 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
observers=[RTVIObserver(rtvi)],
),
observers=[RTVIObserver(rtvi)],
)
await task.queue_frame(quiet_frame)

View File

@@ -198,12 +198,12 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,
observers=[RTVIObserver(rtvi)],
),
observers=[RTVIObserver(rtvi)],
)
await task.queue_frame(quiet_frame)

View File

@@ -104,7 +104,7 @@ async def main(room_url, token=None):
main_task = PipelineTask(
main_pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=True,
enable_metrics=True,
enable_usage_metrics=True,

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@@ -155,10 +155,8 @@ Your task is to help the user understand and learn from this article in 2 senten
task = PipelineTask(
pipeline,
params=PipelineParams(
audio_out_sample_rate=44100,
allow_interruptions=True,
enable_metrics=True,
PipelineParams(
audio_out_sample_rate=44100, allow_interruptions=True, enable_metrics=True
),
)

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@@ -183,12 +183,12 @@ async def main():
task = PipelineTask(
pipeline,
params=PipelineParams(
PipelineParams(
allow_interruptions=False, # We don't want to interrupt the translator bot
enable_metrics=True,
enable_usage_metrics=True,
observers=[RTVIObserver(rtvi)],
),
observers=[RTVIObserver(rtvi)],
)
@transport.event_handler("on_first_participant_joined")

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@@ -108,9 +108,7 @@ async def run_bot(websocket_client: WebSocket, stream_sid: str, testing: bool):
task = PipelineTask(
pipeline,
params=PipelineParams(
audio_in_sample_rate=8000,
audio_out_sample_rate=8000,
allow_interruptions=True,
audio_in_sample_rate=8000, audio_out_sample_rate=8000, allow_interruptions=True
),
)

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@@ -142,9 +142,7 @@ async def run_client(client_name: str, server_url: str, duration_secs: int):
task = PipelineTask(
pipeline,
params=PipelineParams(
audio_in_sample_rate=8000,
audio_out_sample_rate=8000,
allow_interruptions=True,
audio_in_sample_rate=8000, audio_out_sample_rate=8000, allow_interruptions=True
),
)

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