Merge branch 'main' of github.com:pipecat-ai/pipecat

This commit is contained in:
Matej Marinko
2025-06-12 11:32:38 +02:00
355 changed files with 17096 additions and 6988 deletions

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@@ -6,11 +6,13 @@ on:
- main
paths:
- "examples/simple-chatbot/client/android/**"
- "examples/p2p-webrtc/video-transform/client/android/**"
pull_request:
branches:
- "**"
paths:
- "examples/simple-chatbot/client/android/**"
- "examples/p2p-webrtc/video-transform/client/android/**"
workflow_dispatch:
inputs:
sdk_git_ref:
@@ -23,7 +25,7 @@ concurrency:
jobs:
sdk:
name: "Simple chatbot demo"
name: "Demo apps"
runs-on: ubuntu-latest
steps:
- name: Checkout repo
@@ -37,12 +39,22 @@ jobs:
distribution: 'temurin'
java-version: '17'
- name: Build demo app
- name: "Example app: Simple Chatbot"
working-directory: examples/simple-chatbot/client/android
run: ./gradlew :simple-chatbot-client:assembleDebug
- name: Upload demo APK
- name: Upload Simple Chatbot APK
uses: actions/upload-artifact@v4
with:
name: Simple Chatbot Android Client
path: examples/simple-chatbot/client/android/simple-chatbot-client/build/outputs/apk/debug/simple-chatbot-client-debug.apk
- name: "Example app: Small WebRTC Client"
working-directory: examples/p2p-webrtc/video-transform/client/android
run: ./gradlew :small-webrtc-client:assembleDebug
- name: Upload Small WebRTC APK
uses: actions/upload-artifact@v4
with:
name: Small WebRTC Android Client
path: examples/p2p-webrtc/video-transform/client/android/small-webrtc-client/build/outputs/apk/debug/small-webrtc-client-debug.apk

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@@ -5,7 +5,177 @@ 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]
## [0.0.71] - 2025-06-10
### Added
- Adds a parameter called `additional_span_attributes` to PipelineTask that
lets you add any additional attributes you'd like to the conversation span.
### Fixed
- Fixed an issue with `CartesiaSTTService` initialization.
## [0.0.70] - 2025-06-10
### Added
- Added `ExotelFrameSerializer` to handle telephony calls via Exotel.
- Added the option `informal` to `TranslationConfig` on Gladia config.
Allowing to force informal language forms when available.
- Added `CartesiaSTTService` which is a websocket based implementation to
transcribe audio. Added a foundational example in
`13f-cartesia-transcription.py`
- Added an `websocket` example, showing how to use the new Pipecat client
`WebsocketTransport` to connect with Pipecat `FastAPIWebsocketTransport` or
`WebsocketServerTransport`.
- Added language support to `RimeHttpTTSService`. Extended languages to include
German and French for both `RimeTTSService` and `RimeHttpTTSService`.
### Changed
- Upgraded `daily-python` to 0.19.2.
- Make `PipelineTask.add_observer()` synchronous. This allows callers to call it
before doing the work of running the `PipelineTask` (i.e. without invoking
`PipelineTask.set_event_loop()` first).
- Pipecat 0.0.69 forced `uvloop` event loop on Linux on macOS. Unfortunately,
this is causing issue in some systems. So, `uvloop` is not enabled by default
anymore. If you want to use `uvloop` you can just set the `asyncio` event
policy before starting your agent with:
```python
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
```
### Fixed
- Fixed an issue with various TTS services that would cause audio glitches at
the start of every bot turn.
- Fixed an `ElevenLabsTTSService` issue where a context warning was printed
when pushing a `TTSSpeakFrame`.
- Fixed an `AssemblyAISTTService` issue that could cause unexpected behavior
when yielding empty `Frame()`s.
- Fixed an issue where `OutputAudioRawFrame.transport_destination` was being
reset to `None` instead of retaining its intended value before sending the
audio frame to `write_audio_frame`.
- Fixed a typo in Livekit transport that prevented initialization.
## [0.0.69] - 2025-06-02 "AI Engineer World's Fair release" ✨
### Added
- Added a new frame `FunctionCallsStartedFrame`. This frame is pushed both
upstream and downstream from the LLM service to indicate that one or more
function calls are going to be executed.
- Added LLM services `on_function_calls_started` event. This event will be
triggered when the LLM service receives function calls from the model and is
going to start executing them.
- Function calls can now be executed sequentially (in the order received in the
completion) by passing `run_in_parallel=False` when creating your LLM
service. By default, if the LLM completion returns 2 or more function calls
they run concurrently. In both cases, concurrently and sequentially, a new LLM
completion will run when the last function call finishes.
- Added OpenTelemetry tracing for `GeminiMultimodalLiveLLMService` and
`OpenAIRealtimeBetaLLMService`.
- Added initial support for interruption strategies, which determine if the user
should interrupt the bot while the bot is speaking. Interruption strategies
can be based on factors such as audio volume or the number of words spoken by
the user. These can be specified via the new `interruption_strategies` field
in `PipelineParams`. A new `MinWordsInterruptionStrategy` strategy has been
introduced which triggers an interruption if the user has spoken a minimum
number of words. If no interruption strategies are specified, the normal
interruption behavior applies. If multiple strategies are provided, the first
one that evaluates to true will trigger the interruption.
- `BaseInputTransport` now handles `StopFrame`. When a `StopFrame` is received
the transport will pause sending frames downstream until a new `StartFrame` is
received. This allows the transport to be reused (keeping the same connection)
in a different pipeline.
- Updated AssemblyAI STT service to support their latest streaming
speech-to-text model with improved transcription latency and endpointing.
- You can now access STT service results through the new
`TranscriptionFrame.result` and `InterimTranscriptionFrame.result` field. This
is useful in case you use some specific settings for the STT and you want to
access the STT results.
- The examples runner is now public from the `pipecat.examples` package. This
allows everyone to build their own examples and run them easily.
- It is now possible to push `OutputDTMFFrame` or `OutputDTMFUrgentFrame` with
`DailyTransport`. This will be sent properly if a Daily dial-out connection
has been established.
- Added `OutputDTMFUrgentFrame` to send a DTMF keypress quickly. The previous
`OutputDTMFFrame` queues the keypress with the rest of data frames.
- Added `DTMFAggregator`, which aggregates keypad presses into
`TranscriptionFrame`s. Aggregation occurs after a timeout, termination key
press, or user interruption. You can specify the prefix of the
`TranscriptionFrame`.
- Added new functions `DailyTransport.start_transcription()` and
`DailyTransport.stop_transcription()` to be able to start and stop Daily
transcription dynamically (maybe with different settings).
### Changed
- Reverted the default model for `GeminiMultimodalLiveLLMService` back to
`models/gemini-2.0-flash-live-001`.
`gemini-2.5-flash-preview-native-audio-dialog` has inconsistent performance.
You can opt in to using this model by setting the `model` arg.
- Function calls are now cancelled by default if there's an interruption. To
disable this behavior you can set `cancel_on_interruption=False` when
registering the function call. Since function calls are executed as tasks you
can tell if a function call has been cancelled by catching the
`asyncio.CancelledError` exception (and don't forget to raise it again!).
- Updated OpenTelemetry tracing attribute `metrics.ttfb_ms` to `metrics.ttfb`.
The attribute reports TTFB in seconds.
### Deprecated
- `DailyTransport.send_dtmf()` is deprecated, push an `OutputDTMFFrame` or an
`OutputDTMFUrgentFrame` instead.
### Fixed
- Fixed an issue with `ElevenLabsTTSService` where long responses would
continue generating output even after an interruption.
- Fixed an issue with the `OpenAILLMContext` where non-Roman characters were
being incorrectly encoded as Unicode escape sequences. This was a logging
issue and did not impact the actual conversation.
- In `AWSBedrockLLMService`, worked around a possible bug in AWS Bedrock where
a `toolConfig` is required if there has been previous tool use in the
messages array. This workaround includes a no_op factory function call is
used to satisfy the requirement.
- Fixed `WebsocketClientTransport` to use `FrameProcessorSetup.task_manager`
instead of `StartFrame.task_manager`.
### Performance
- Use `uvloop` as the new event loop on Linux and macOS systems.
## [0.0.68] - 2025-05-28
### Added
@@ -89,6 +259,17 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Changed
- Upgraded `daily-python` to 0.19.1.
- ⚠️ Updated `SmallWebRTCTransport` to align with how other transports handle
`on_client_disconnected`. Now, when the connection is closed and no reconnection
is attempted, `on_client_disconnected` is called instead of `on_client_close`. The
`on_client_close` callback is no longer used, use `on_client_disconnected` instead.
- Check if `PipelineTask` has already been cancelled.
- Don't raise an exception if event handler is not registered.
- Upgraded `deepgram-sdk` to 4.1.0.
- Updated `GoogleTTSService` to use Google's streaming TTS API. The default
@@ -147,6 +328,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Fixed
- Fixed a `DailyTransport` issue that was not allow capturing video frames if
framerate was greater than zero.
- Fixed a `DeegramSTTService` connection issue when the user provided their own
`LiveOptions`.
@@ -173,6 +357,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
### Other
- It is now possible to run all (or most) foundational example with multiple
transports. By default, they run with P2P (Peer-To-Peer) WebRTC so you can try
everything locally. You can also run them with Daily or even with a Twilio
phone number.
- Added foundation examples `07y-interruptible-minimax.py` and
`07z-interruptible-sarvam.py`to show how to use the `MiniMaxHttpTTSService`
and `SarvamTTSService`, respectively.

4
MANIFEST.in Normal file
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@@ -0,0 +1,4 @@
prune docs
prune examples
prune scripts
prune tests

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@@ -53,7 +53,7 @@ You can connect to Pipecat from any platform using our official SDKs:
| Category | Services |
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [FastPitch (NVIDIA)](https://docs.pipecat.ai/server/services/tts/fastpitch), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) |

View File

@@ -16,23 +16,25 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.piper.tts import PiperTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_out_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
"webrtc": lambda: TransportParams(audio_out_enabled=True),
}
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
@@ -47,12 +49,12 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,24 +16,25 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.rime.tts import RimeHttpTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_out_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
"webrtc": lambda: TransportParams(audio_out_enabled=True),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
),
)
# Create an HTTP session
async with aiohttp.ClientSession() as session:
tts = RimeHttpTTSService(
@@ -49,12 +50,12 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

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@@ -15,23 +15,25 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_out_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
"webrtc": lambda: TransportParams(audio_out_enabled=True),
}
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
@@ -45,12 +47,12 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -77,37 +77,36 @@ async def configure_livekit():
async def main():
async with aiohttp.ClientSession() as session:
(url, token, room_name) = await configure_livekit()
(url, token, room_name) = await configure_livekit()
transport = LiveKitTransport(
url=url,
token=token,
room_name=room_name,
params=LiveKitParams(audio_out_enabled=True),
)
transport = LiveKitTransport(
url=url,
token=token,
room_name=room_name,
params=LiveKitParams(audio_out_enabled=True),
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
runner = PipelineRunner()
runner = PipelineRunner()
task = PipelineTask(Pipeline([tts, transport.output()]))
task = PipelineTask(Pipeline([tts, transport.output()]))
# Register an event handler so we can play the audio when the
# participant joins.
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant_id):
await asyncio.sleep(1)
await task.queue_frame(
TextFrame(
"Hello there! How are you doing today? Would you like to talk about the weather?"
)
# Register an event handler so we can play the audio when the
# participant joins.
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant_id):
await asyncio.sleep(1)
await task.queue_frame(
TextFrame(
"Hello there! How are you doing today? Would you like to talk about the weather?"
)
)
await runner.run(task)
await runner.run(task)
if __name__ == "__main__":

View File

@@ -15,23 +15,25 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.riva.tts import FastPitchTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_out_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
"webrtc": lambda: TransportParams(audio_out_enabled=True),
}
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
tts = FastPitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
@@ -42,12 +44,12 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,23 +16,25 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_out_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
"webrtc": lambda: TransportParams(audio_out_enabled=True),
}
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
@@ -55,12 +57,12 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,25 +16,31 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.fal.image import FalImageGenService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
"webrtc": lambda: TransportParams(
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
}
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
@@ -54,18 +60,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -15,25 +15,31 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.google.image import GoogleImageGenService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
"webrtc": lambda: TransportParams(
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
}
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
imagegen = GoogleImageGenService(
api_key=os.getenv("GOOGLE_API_KEY"),
@@ -54,18 +60,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -5,10 +5,17 @@
#
import argparse
import asyncio
import os
from contextlib import asynccontextmanager
from typing import Dict
import uvicorn
from dotenv import load_dotenv
from fastapi import BackgroundTasks, FastAPI
from fastapi.responses import RedirectResponse
from loguru import logger
from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.pipeline.pipeline import Pipeline
@@ -20,14 +27,29 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.network.webrtc_connection import IceServer, SmallWebRTCConnection
load_dotenv(override=True)
app = FastAPI()
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# Store connections by pc_id
pcs_map: Dict[str, SmallWebRTCConnection] = {}
ice_servers = [
IceServer(
urls="stun:stun.l.google.com:19302",
)
]
# Mount the frontend at /
app.mount("/client", SmallWebRTCPrebuiltUI)
async def run_example(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Starting bot")
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
@@ -88,10 +110,6 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
@@ -99,7 +117,58 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
await runner.run(task)
if __name__ == "__main__":
from run import main
@app.get("/", include_in_schema=False)
async def root_redirect():
return RedirectResponse(url="/client/")
main()
@app.post("/api/offer")
async def offer(request: dict, background_tasks: BackgroundTasks):
pc_id = request.get("pc_id")
if pc_id and pc_id in pcs_map:
pipecat_connection = pcs_map[pc_id]
logger.info(f"Reusing existing connection for pc_id: {pc_id}")
await pipecat_connection.renegotiate(
sdp=request["sdp"],
type=request["type"],
restart_pc=request.get("restart_pc", False),
)
else:
pipecat_connection = SmallWebRTCConnection(ice_servers)
await pipecat_connection.initialize(sdp=request["sdp"], type=request["type"])
@pipecat_connection.event_handler("closed")
async def handle_disconnected(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Discarding peer connection for pc_id: {webrtc_connection.pc_id}")
pcs_map.pop(webrtc_connection.pc_id, None)
# Run example function with SmallWebRTC transport arguments.
background_tasks.add_task(run_example, pipecat_connection)
answer = pipecat_connection.get_answer()
# Updating the peer connection inside the map
pcs_map[answer["pc_id"]] = pipecat_connection
return answer
@asynccontextmanager
async def lifespan(app: FastAPI):
yield # Run app
coros = [pc.disconnect() for pc in pcs_map.values()]
await asyncio.gather(*coros)
pcs_map.clear()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
parser.add_argument(
"--host", default="localhost", help="Host for HTTP server (default: localhost)"
)
parser.add_argument(
"--port", type=int, default=7860, help="Port for HTTP server (default: 7860)"
)
args = parser.parse_args()
uvicorn.run(app, host=args.host, port=args.port)

View File

@@ -9,11 +9,11 @@ import os
import sys
import aiohttp
from daily_runner import configure
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.daily_runner import configure
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask

View File

@@ -10,7 +10,6 @@ import json
import os
import sys
import aiohttp
from deepgram import LiveOptions
from dotenv import load_dotenv
from livekit import api
@@ -104,101 +103,100 @@ async def configure_livekit():
async def main():
async with aiohttp.ClientSession() as session:
(url, token, room_name) = await configure_livekit()
(url, token, room_name) = await configure_livekit()
transport = LiveKitTransport(
url=url,
token=token,
room_name=room_name,
params=LiveKitParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
transport = LiveKitTransport(
url=url,
token=token,
room_name=room_name,
params=LiveKitParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"),
live_options=LiveOptions(
vad_events=True,
),
)
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"),
live_options=LiveOptions(
vad_events=True,
),
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
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.",
},
]
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)
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
runner = PipelineRunner()
runner = PipelineRunner()
task = PipelineTask(
Pipeline(
[
transport.input(),
stt,
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
],
),
params=PipelineParams(
allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
),
)
task = PipelineTask(
Pipeline(
[
transport.input(),
stt,
context_aggregator.user(),
llm,
tts,
transport.output(),
context_aggregator.assistant(),
],
),
params=PipelineParams(
allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
),
)
# Register an event handler so we can play the audio when the
# participant joins.
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant_id):
await asyncio.sleep(1)
await task.queue_frame(
TextFrame(
"Hello there! How are you doing today? Would you like to talk about the weather?"
)
# Register an event handler so we can play the audio when the
# participant joins.
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant_id):
await asyncio.sleep(1)
await task.queue_frame(
TextFrame(
"Hello there! How are you doing today? Would you like to talk about the weather?"
)
)
# Register an event handler to receive data from the participant via text chat
# in the LiveKit room. This will be used to as transcription frames and
# interrupt the bot and pass it to llm for processing and
# then pass back to the participant as audio output.
@transport.event_handler("on_data_received")
async def on_data_received(transport, data, participant_id):
logger.info(f"Received data from participant {participant_id}: {data}")
# convert data from bytes to string
json_data = json.loads(data)
# Register an event handler to receive data from the participant via text chat
# in the LiveKit room. This will be used to as transcription frames and
# interrupt the bot and pass it to llm for processing and
# then pass back to the participant as audio output.
@transport.event_handler("on_data_received")
async def on_data_received(transport, data, participant_id):
logger.info(f"Received data from participant {participant_id}: {data}")
# convert data from bytes to string
json_data = json.loads(data)
await task.queue_frames(
[
BotInterruptionFrame(),
UserStartedSpeakingFrame(),
TranscriptionFrame(
user_id=participant_id,
timestamp=json_data["timestamp"],
text=json_data["message"],
),
UserStoppedSpeakingFrame(),
],
)
await task.queue_frames(
[
BotInterruptionFrame(),
UserStartedSpeakingFrame(),
TranscriptionFrame(
user_id=participant_id,
timestamp=json_data["timestamp"],
text=json_data["message"],
),
UserStoppedSpeakingFrame(),
],
)
await runner.run(task)
await runner.run(task)
if __name__ == "__main__":

View File

@@ -1,111 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import os
import sys
import aiohttp
from daily_runner import configure
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
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.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService, Language, LiveOptions
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def main():
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(session)
transport = DailyTransport(
room_url,
token,
"Respond bot",
DailyParams(
audio_in_enabled=True,
audio_in_passthrough=False,
audio_out_enabled=True,
audio_out_sample_rate=16000,
transcription_enabled=False,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"),
live_options=LiveOptions(language=Language.EN),
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
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)
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=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_audio(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.cancel()
runner = PipelineRunner()
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -28,9 +28,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaHttpTTSService
from pipecat.services.fal.image import FalImageGenService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -64,7 +63,26 @@ class MonthPrepender(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_out_enabled=True,
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
"webrtc": lambda: TransportParams(
audio_out_enabled=True,
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
"""Run the Calendar Month Narration bot using WebRTC transport.
Args:
@@ -73,17 +91,6 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
"""
logger.info(f"Starting bot")
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
),
)
# Create an HTTP session for API calls
async with aiohttp.ClientSession() as session:
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
@@ -159,18 +166,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
# Run the pipeline
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -26,9 +26,9 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -53,17 +53,30 @@ class MetricsLogger(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -117,17 +130,13 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -26,9 +26,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -68,20 +67,31 @@ class ImageSyncAggregator(FrameProcessor):
await self.push_frame(frame)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_width=1024,
video_out_height=1024,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -139,17 +149,13 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaHttpTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -88,18 +100,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -27,9 +27,9 @@ from pipecat.processors.aggregators.llm_response import (
from pipecat.processors.frameworks.langchain import LangchainProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -43,17 +43,30 @@ def get_session_history(session_id: str) -> BaseChatMessageHistory:
return message_store[session_id]
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -120,18 +133,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -24,23 +24,34 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"),
@@ -101,18 +112,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -85,18 +98,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,24 +19,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
@@ -92,18 +105,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.playht.tts import PlayHTHttpTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = PlayHTHttpTTSService(
@@ -89,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,25 +19,37 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.playht.tts import PlayHTTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = PlayHTTTSService(
@@ -91,18 +103,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.azure.llm import AzureLLMService
from pipecat.services.azure.stt import AzureSTTService
from pipecat.services.azure.tts import AzureTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = AzureSTTService(
api_key=os.getenv("AZURE_SPEECH_API_KEY"),
region=os.getenv("AZURE_SPEECH_REGION"),
@@ -95,18 +107,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.openai.stt import OpenAISTTService
from pipecat.services.openai.tts import OpenAITTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = OpenAISTTService(
api_key=os.getenv("OPENAI_API_KEY"),
model="gpt-4o-transcribe",
@@ -90,18 +102,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,25 +19,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openpipe.llm import OpenPipeLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -94,18 +106,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,25 +19,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.xtts.tts import XTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
# Create an HTTP session
async with aiohttp.ClientSession() as session:
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -92,18 +104,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -20,25 +20,37 @@ from pipecat.services.gladia.config import GladiaInputParams, LanguageConfig
from pipecat.services.gladia.stt import GladiaSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = GladiaSTTService(
api_key=os.getenv("GLADIA_API_KEY", ""),
params=GladiaInputParams(
@@ -97,17 +109,13 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.lmnt.tts import LmntTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = LmntTTSService(api_key=os.getenv("LMNT_API_KEY"), voice_id="morgan")
@@ -85,18 +97,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,25 +19,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.groq.llm import GroqLLMService
from pipecat.services.groq.stt import GroqSTTService
from pipecat.services.groq.tts import GroqTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY"))
llm = GroqLLMService(
@@ -89,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -17,25 +17,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.aws.llm import AWSBedrockLLMService
from pipecat.services.aws.stt import AWSTranscribeSTTService
from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = AWSTranscribeSTTService()
tts = AWSPollyTTSService(
@@ -92,18 +104,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,25 +19,37 @@ from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.google.stt import GoogleSTTService
from pipecat.services.google.tts import GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = GoogleSTTService(
params=GoogleSTTService.InputParams(languages=Language.EN_US),
credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
@@ -93,18 +105,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.assemblyai.stt import AssemblyAISTTService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = AssemblyAISTTService(
api_key=os.getenv("ASSEMBLYAI_API_KEY"),
@@ -90,18 +103,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,26 +19,40 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=KrispFilter(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=KrispFilter(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=KrispFilter(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=KrispFilter(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
@@ -87,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -19,24 +19,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.rime.tts import RimeHttpTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
@@ -93,18 +106,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.rime.tts import RimeTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = RimeTTSService(
@@ -88,18 +100,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,31 +16,39 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.nim.llm import NimLLMService
from pipecat.services.riva.stt import (
ParakeetSTTService,
RivaSegmentedSTTService,
RivaSTTService,
)
from pipecat.services.riva.tts import FastPitchTTSService, RivaTTSService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.services.riva.stt import RivaSTTService
from pipecat.services.riva.tts import RivaTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = RivaSTTService(api_key=os.getenv("NVIDIA_API_KEY"))
llm = NimLLMService(api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct")
@@ -89,18 +97,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -32,9 +32,9 @@ from pipecat.processors.frame_processor import FrameProcessor
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.google.tts import GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -191,17 +191,30 @@ class TanscriptionContextFixup(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
@@ -261,18 +274,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.fish.tts import FishAudioTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -11,15 +11,14 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.ultravox.stt import UltravoxSTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -36,17 +35,30 @@ ultravox_processor = UltravoxSTTService(
)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
tts = CartesiaTTSService(
api_key=os.environ.get("CARTESIA_API_KEY"),
@@ -77,18 +89,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -88,18 +101,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,25 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.neuphonic.tts import NeuphonicTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = NeuphonicTTSService(
@@ -88,18 +100,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,24 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.fal.stt import FalSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = FalSTTService(
api_key=os.getenv("FAL_KEY"),
@@ -90,18 +103,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -20,27 +20,40 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.minimax.tts import MiniMaxHttpTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = MiniMaxHttpTTSService(
@@ -94,18 +107,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -20,24 +20,38 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.sarvam.tts import SarvamTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
# Create an HTTP session
async with aiohttp.ClientSession() as session:
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -92,18 +106,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -20,9 +20,8 @@ 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.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -47,21 +46,33 @@ class MirrorProcessor(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
pipeline = Pipeline([transport.input(), MirrorProcessor(), transport.output()])
@@ -77,18 +88,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -11,6 +11,7 @@ import tkinter as tk
from dotenv import load_dotenv
from loguru import logger
from pipecat.examples.run import maybe_capture_participant_camera
from pipecat.frames.frames import (
Frame,
InputAudioRawFrame,
@@ -22,10 +23,9 @@ 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.base_transport import TransportParams
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -50,21 +50,33 @@ class MirrorProcessor(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
}
p2p_transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
tk_root = tk.Tk()
tk_root.title("Local Mirror")
@@ -80,11 +92,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
),
)
@p2p_transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
pipeline = Pipeline([p2p_transport.input(), MirrorProcessor(), tk_transport.output()])
pipeline = Pipeline([transport.input(), MirrorProcessor(), tk_transport.output()])
task = PipelineTask(
pipeline,
@@ -97,12 +105,22 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
tk_root.update_idletasks()
await asyncio.sleep(0.1)
runner = PipelineRunner(handle_sigint=False)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
await maybe_capture_participant_camera(transport, client, framerate=30)
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=handle_sigint)
await asyncio.gather(runner.run(task), run_tk())
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -20,25 +20,37 @@ from pipecat.processors.filters.wake_check_filter import WakeCheckFilter
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -84,18 +96,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -30,9 +30,9 @@ from pipecat.processors.logger import FrameLogger
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -78,17 +78,30 @@ class InboundSoundEffectWrapper(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -141,18 +154,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
@@ -22,9 +23,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.moondream.vision import MoondreamService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -47,21 +47,27 @@ class UserImageRequester(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# Get WebRTC peer connection ID
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
user_response = UserResponseAggregator()
@@ -99,27 +105,26 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
await maybe_capture_participant_camera(transport, client)
# Set the participant ID in the image requester
image_requester.set_participant_id(webrtc_peer_id)
client_id = get_transport_client_id(transport, client)
image_requester.set_participant_id(client_id)
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
@@ -22,9 +23,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -47,21 +47,27 @@ class UserImageRequester(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# Get WebRTC peer connection ID
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
user_response = UserResponseAggregator()
@@ -102,27 +108,26 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
await maybe_capture_participant_camera(transport, client)
# Set the participant ID in the image requester
image_requester.set_participant_id(webrtc_peer_id)
client_id = get_transport_client_id(transport, client)
image_requester.set_participant_id(client_id)
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
@@ -22,9 +23,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -47,21 +47,27 @@ class UserImageRequester(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# Get WebRTC peer connection ID
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
user_response = UserResponseAggregator()
@@ -102,27 +108,26 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
await maybe_capture_participant_camera(transport, client)
# Set the participant ID in the image requester
image_requester.set_participant_id(webrtc_peer_id)
client_id = get_transport_client_id(transport, client)
image_requester.set_participant_id(client_id)
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.frames.frames import Frame, TextFrame, UserImageRequestFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
@@ -22,9 +23,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -47,21 +47,27 @@ class UserImageRequester(FrameProcessor):
await self.push_frame(frame, direction)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# Get WebRTC peer connection ID
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
user_response = UserResponseAggregator()
@@ -102,27 +108,26 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
await maybe_capture_participant_camera(transport, client)
# Set the participant ID in the image requester
image_requester.set_participant_id(webrtc_peer_id)
client_id = get_transport_client_id(transport, client)
image_requester.set_participant_id(client_id)
# Welcome message
await tts.say("Hi there! Feel free to ask me what I see.")
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,9 +16,9 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.whisper.stt import WhisperSTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -31,16 +31,27 @@ class TranscriptionLogger(FrameProcessor):
print(f"Transcription: {frame.text}")
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = WhisperSTTService()
@@ -53,18 +64,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,9 +16,9 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.deepgram.stt import DeepgramSTTService, Language, LiveOptions
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -31,13 +31,18 @@ class TranscriptionLogger(FrameProcessor):
print(f"Transcription: {frame.text}")
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_in_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True),
"webrtc": lambda: TransportParams(audio_in_enabled=True),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(audio_in_enabled=True),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"),
@@ -53,18 +58,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,9 +16,9 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.gladia import GladiaSTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -31,13 +31,18 @@ class TranscriptionLogger(FrameProcessor):
print(f"Transcription: {frame.text}")
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_in_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True),
"webrtc": lambda: TransportParams(audio_in_enabled=True),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(audio_in_enabled=True),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = GladiaSTTService(
api_key=os.getenv("GLADIA_API_KEY"),
@@ -53,18 +58,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -23,9 +23,9 @@ from pipecat.services.gladia.config import (
)
from pipecat.services.gladia.stt import GladiaSTTService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -40,13 +40,18 @@ class TranscriptionLogger(FrameProcessor):
print(f"Translation ({frame.language}): {frame.text}")
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_in_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True),
"webrtc": lambda: TransportParams(audio_in_enabled=True),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(audio_in_enabled=True),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = GladiaSTTService(
api_key=os.getenv("GLADIA_API_KEY"),
@@ -74,18 +79,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -16,9 +16,9 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.assemblyai.stt import AssemblyAISTTService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -31,13 +31,18 @@ class TranscriptionLogger(FrameProcessor):
print(f"Transcription: {frame.text}")
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_in_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True),
"webrtc": lambda: TransportParams(audio_in_enabled=True),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(audio_in_enabled=True),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = AssemblyAISTTService(
api_key=os.getenv("ASSEMBLYAI_API_KEY"),
@@ -52,18 +57,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,9 +18,9 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.whisper.stt import MLXModel, WhisperSTTServiceMLX
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -52,16 +52,27 @@ class TranscriptionLogger(FrameProcessor):
self._last_transcription_time = time.time()
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = WhisperSTTServiceMLX(model=MLXModel.LARGE_V3_TURBO)
@@ -80,18 +91,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -0,0 +1,71 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import argparse
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.frames.frames import Frame, TranscriptionFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.services.cartesia.stt import CartesiaSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
class TranscriptionLogger(FrameProcessor):
async def process_frame(self, frame: Frame, direction: FrameDirection):
await super().process_frame(frame, direction)
if isinstance(frame, TranscriptionFrame):
print(f"Transcription: {frame.text}")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_in_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True),
"webrtc": lambda: TransportParams(audio_in_enabled=True),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = CartesiaSTTService(
api_key=os.getenv("CARTESIA_API_KEY"),
base_url=os.getenv("CARTESIA_BASE_URL"),
)
tl = TranscriptionLogger()
pipeline = Pipeline([transport.input(), stt, tl])
task = PipelineTask(pipeline)
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from pipecat.examples.run import main
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,45 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
async def fetch_restaurant_recommendation(params: FunctionCallParams):
await params.result_callback({"name": "The Golden Dragon"})
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -58,6 +74,11 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# You can also 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", fetch_weather_from_api)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
@@ -75,7 +96,18 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
},
required=["location", "format"],
)
tools = ToolsSchema(standard_tools=[weather_function])
restaurant_function = FunctionSchema(
name="get_restaurant_recommendation",
description="Get a restaurant recommendation",
properties={
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
},
required=["location"],
)
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
messages = [
{
@@ -118,18 +150,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -21,9 +21,9 @@ from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -33,17 +33,34 @@ async def get_weather(params: FunctionCallParams):
await params.result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
async def fetch_restaurant_recommendation(params: FunctionCallParams):
await params.result_callback({"name": "The Golden Dragon"})
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -53,9 +70,11 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
)
llm = AnthropicLLMService(
api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-7-sonnet-latest"
api_key=os.getenv("ANTHROPIC_API_KEY"),
model="claude-3-7-sonnet-latest",
)
llm.register_function("get_weather", get_weather)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
weather_function = FunctionSchema(
name="get_weather",
@@ -68,7 +87,18 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
},
required=["location"],
)
tools = ToolsSchema(standard_tools=[weather_function])
restaurant_function = FunctionSchema(
name="get_restaurant_recommendation",
description="Get a restaurant recommendation",
properties={
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
},
required=["location"],
)
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
# todo: test with very short initial user message
@@ -111,18 +141,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -14,6 +14,7 @@ from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,15 +23,14 @@ from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# Global variable to store the peer connection ID
webrtc_peer_id = ""
# Global variable to store the client ID
client_id = ""
async def get_weather(params: FunctionCallParams):
@@ -40,11 +40,11 @@ async def get_weather(params: FunctionCallParams):
async def get_image(params: FunctionCallParams):
question = params.arguments["question"]
logger.debug(f"Requesting image with user_id={webrtc_peer_id}, question={question}")
logger.debug(f"Requesting image with user_id={client_id}, question={question}")
# Request the image frame
await params.llm.request_image_frame(
user_id=webrtc_peer_id,
user_id=client_id,
function_name=params.function_name,
tool_call_id=params.tool_call_id,
text_content=question,
@@ -59,21 +59,27 @@ async def get_image(params: FunctionCallParams):
)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
global webrtc_peer_id
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -174,24 +180,26 @@ If you need to use a tool, simply use the tool. Do not tell the user the tool yo
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
await maybe_capture_participant_camera(transport, client)
global client_id
client_id = get_transport_client_id(transport, client)
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.together.llm import TogetherLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -61,6 +73,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -111,18 +127,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -14,6 +14,7 @@ from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
@@ -22,15 +23,14 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# Global variable to store the peer connection ID
webrtc_peer_id = ""
# Global variable to store the client ID
client_id = ""
async def get_weather(params: FunctionCallParams):
@@ -40,11 +40,11 @@ async def get_weather(params: FunctionCallParams):
async def get_image(params: FunctionCallParams):
question = params.arguments["question"]
logger.debug(f"Requesting image with user_id={webrtc_peer_id}, question={question}")
logger.debug(f"Requesting image with user_id={client_id}, question={question}")
# Request the image frame
await params.llm.request_image_frame(
user_id=webrtc_peer_id,
user_id=client_id,
function_name=params.function_name,
tool_call_id=params.tool_call_id,
text_content=question,
@@ -59,21 +59,27 @@ async def get_image(params: FunctionCallParams):
)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
global webrtc_peer_id
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -157,24 +163,26 @@ indicate you should use the get_image tool are:
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
await maybe_capture_participant_camera(transport, client)
global client_id
client_id = get_transport_client_id(transport, client)
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -14,6 +14,7 @@ from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.frames.frames import TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
@@ -23,30 +24,32 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# Global variable to store the peer connection ID
webrtc_peer_id = ""
# Global variable to store the client ID
client_id = ""
async def get_weather(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
location = params.arguments["location"]
await params.result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
async def fetch_restaurant_recommendation(params: FunctionCallParams):
await params.result_callback({"name": "The Golden Dragon"})
async def get_image(params: FunctionCallParams):
question = params.arguments["question"]
logger.debug(f"Requesting image with user_id={webrtc_peer_id}, question={question}")
logger.debug(f"Requesting image with user_id={client_id}, question={question}")
# Request the image frame
await params.llm.request_image_frame(
user_id=webrtc_peer_id,
user_id=client_id,
function_name=params.function_name,
tool_call_id=params.tool_call_id,
text_content=question,
@@ -61,21 +64,27 @@ async def get_image(params: FunctionCallParams):
)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
global webrtc_peer_id
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -87,6 +96,11 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
llm.register_function("get_weather", get_weather)
llm.register_function("get_image", get_image)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_weather",
@@ -104,6 +118,17 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
},
required=["location", "format"],
)
restaurant_function = FunctionSchema(
name="get_restaurant_recommendation",
description="Get a restaurant recommendation",
properties={
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
},
required=["location"],
)
get_image_function = FunctionSchema(
name="get_image",
description="Get an image from the video stream.",
@@ -115,14 +140,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
},
required=["question"],
)
tools = ToolsSchema(standard_tools=[weather_function, get_image_function])
tools = ToolsSchema(standard_tools=[weather_function, get_image_function, restaurant_function])
system_prompt = """\
You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions.
Your response will be turned into speech so use only simple words and punctuation.
You have access to two tools: get_weather and get_image.
You have access to three tools: get_weather, get_restaurant_recommendation, and get_image.
You can respond to questions about the weather using the get_weather tool.
@@ -167,24 +192,26 @@ indicate you should use the get_image tool are:
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected: {client}")
await maybe_capture_participant_camera(transport, client)
global client_id
client_id = get_transport_client_id(transport, client)
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -23,29 +23,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.groq.llm import GroqLLMService
from pipecat.services.groq.stt import GroqSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY"), model="distil-whisper-large-v3-en")
@@ -61,6 +73,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -120,18 +136,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -21,9 +21,9 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.grok.llm import GrokLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -32,17 +32,30 @@ async def fetch_weather_from_api(params: FunctionCallParams):
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -113,18 +126,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.azure.llm import AzureLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -62,6 +74,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -119,18 +135,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.fireworks.llm import FireworksLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -61,6 +73,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -118,18 +134,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.nim.llm import NimLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -59,6 +71,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -116,18 +132,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.cerebras.llm import CerebrasLLMService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -58,6 +70,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -126,18 +142,14 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepseek.llm import DeepSeekLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -58,6 +70,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -126,18 +142,14 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.azure.tts import AzureTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openrouter.llm import OpenRouterLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -62,6 +74,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -120,18 +136,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -25,25 +25,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.perplexity.llm import PerplexityLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -94,18 +106,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
from pipecat.services.google.llm_openai import GoogleLLMOpenAIBetaService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -58,6 +70,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -115,18 +131,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
from pipecat.services.google.llm_vertex import GoogleVertexLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -54,15 +66,19 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
)
llm = GoogleVertexLLMService(
# credentials="<json-credentials>",
credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
params=GoogleVertexLLMService.InputParams(
project_id="<google-project-id>",
)
),
)
# You can aslo 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", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -121,18 +137,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,29 +22,41 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.qwen.llm import QwenLLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def fetch_weather_from_api(params: FunctionCallParams):
await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -59,6 +71,10 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# sent to the same callback with an additional function_name parameter.
llm.register_function("get_current_weather", fetch_weather_from_api)
@llm.event_handler("on_function_calls_started")
async def on_function_calls_started(service, function_calls):
await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -118,18 +134,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -21,9 +21,9 @@ from pipecat.services.aws.llm import AWSBedrockLLMService
from pipecat.services.aws.stt import AWSTranscribeSTTService
from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -32,17 +32,34 @@ async def fetch_weather_from_api(params: FunctionCallParams):
await params.result_callback({"conditions": "nice", "temperature": "75"})
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
async def fetch_restaurant_recommendation(params: FunctionCallParams):
await params.result_callback({"name": "The Golden Dragon"})
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = AWSTranscribeSTTService()
@@ -61,6 +78,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# You can also 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", fetch_weather_from_api)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
weather_function = FunctionSchema(
name="get_current_weather",
@@ -78,7 +96,18 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
},
required=["location", "format"],
)
tools = ToolsSchema(standard_tools=[weather_function])
restaurant_function = FunctionSchema(
name="get_restaurant_recommendation",
description="Get a restaurant recommendation",
properties={
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
},
required=["location"],
)
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
messages = [
{
@@ -122,18 +151,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -22,9 +22,9 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -54,17 +54,30 @@ async def barbershop_man_filter(frame) -> bool:
return current_voice == "Barbershop Man"
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -151,18 +164,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -23,9 +23,9 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -49,17 +49,30 @@ async def spanish_filter(frame) -> bool:
return current_language == "Spanish"
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(
api_key=os.getenv("DEEPGRAM_API_KEY"), live_options=LiveOptions(language="multi")
@@ -139,18 +152,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -18,26 +18,37 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.services.daily import DailyTransportMessageFrame
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams, DailyTransportMessageFrame
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = DeepgramTTSService(
@@ -124,18 +135,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -20,25 +20,37 @@ from pipecat.processors.user_idle_processor import UserIdleProcessor
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -121,18 +133,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -13,26 +13,35 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.gstreamer.pipeline_source import GStreamerPipelineSource
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
async def run_bot(webrtc_connection: SmallWebRTCConnection, args: argparse.Namespace):
logger.info(f"Starting bot with video input: {args.input}")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
"webrtc": lambda: TransportParams(
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
)
async def run_example(transport: BaseTransport, args: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot with video input: {args.input}")
gst = GStreamerPipelineSource(
pipeline=f"filesrc location={args.input}",
@@ -51,15 +60,15 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, args: argparse.Names
task = PipelineTask(pipeline)
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
parser.add_argument("-i", "--input", type=str, required=True, help="Input video file")
main(parser)
main(run_example, parser=parser, transport_params=transport_params)

View File

@@ -13,27 +13,33 @@ from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.gstreamer.pipeline_source import GStreamerPipelineSource
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
"webrtc": lambda: TransportParams(
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot with video test source")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
)
gst = GStreamerPipelineSource(
pipeline='videotestsrc ! capsfilter caps="video/x-raw,width=1280,height=720,framerate=30/1"',
out_params=GStreamerPipelineSource.OutputParams(
@@ -50,12 +56,12 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
task = PipelineTask(pipeline)
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -14,11 +14,12 @@ from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import TranscriptionMessage
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.llm_service import FunctionCallParams
from pipecat.services.openai_realtime_beta import (
InputAudioNoiseReduction,
@@ -27,9 +28,9 @@ from pipecat.services.openai_realtime_beta import (
SemanticTurnDetection,
SessionProperties,
)
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -46,6 +47,10 @@ async def fetch_weather_from_api(params: FunctionCallParams):
)
async def fetch_restaurant_recommendation(params: FunctionCallParams):
await params.result_callback({"name": "The Golden Dragon"})
weather_function = FunctionSchema(
name="get_current_weather",
description="Get the current weather",
@@ -63,22 +68,47 @@ weather_function = FunctionSchema(
required=["location", "format"],
)
restaurant_function = FunctionSchema(
name="get_restaurant_recommendation",
description="Get a restaurant recommendation",
properties={
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
},
required=["location"],
)
# Create tools schema
tools = ToolsSchema(standard_tools=[weather_function])
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
session_properties = SessionProperties(
input_audio_transcription=InputAudioTranscription(),
# Set openai TurnDetection parameters. Not setting this at all will turn it
@@ -88,7 +118,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# turn_detection=False,
input_audio_noise_reduction=InputAudioNoiseReduction(type="near_field"),
# tools=tools,
instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI.
instructions="""You are a helpful and friendly AI.
Act like a human, but remember that you aren't a human and that you can't do human
things in the real world. Your voice and personality should be warm and engaging, with a lively and
@@ -97,10 +127,14 @@ playful tone.
If interacting in a non-English language, start by using the standard accent or dialect familiar to
the user. Talk quickly. You should always call a function if you can. Do not refer to these rules,
even if you're asked about them.
-
You are participating in a voice conversation. Keep your responses concise, short, and to the point
unless specifically asked to elaborate on a topic.
You have access to the following tools:
- get_current_weather: Get the current weather for a given location.
- get_restaurant_recommendation: Get a restaurant recommendation for a given location.
Remember, your responses should be short. Just one or two sentences, usually.""",
)
@@ -113,6 +147,9 @@ Remember, your responses should be short. Just one or two sentences, usually."""
# you can either register a single function for all function calls, or specific functions
# llm.register_function(None, fetch_weather_from_api)
llm.register_function("get_current_weather", fetch_weather_from_api)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
transcript = TranscriptProcessor()
# Create a standard OpenAI LLM context object using the normal messages format. The
# OpenAIRealtimeBetaLLMService will convert this internally to messages that the
@@ -139,7 +176,9 @@ Remember, your responses should be short. Just one or two sentences, usually."""
transport.input(), # Transport user input
context_aggregator.user(),
llm, # LLM
transcript.user(), # Placed after the LLM, as LLM pushes TranscriptionFrames downstream
transport.output(), # Transport bot output
transcript.assistant(), # After the transcript output, to time with the audio output
context_aggregator.assistant(),
]
)
@@ -163,18 +202,23 @@ Remember, your responses should be short. Just one or two sentences, usually."""
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
# Register event handler for transcript updates
@transcript.event_handler("on_transcript_update")
async def on_transcript_update(processor, frame):
for msg in frame.messages:
if isinstance(msg, TranscriptionMessage):
timestamp = f"[{msg.timestamp}] " if msg.timestamp else ""
line = f"{timestamp}{msg.role}: {msg.content}"
logger.info(f"Transcript: {line}")
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -14,7 +14,6 @@ from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -25,9 +24,9 @@ from pipecat.services.openai_realtime_beta import (
InputAudioTranscription,
SessionProperties,
)
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -44,6 +43,10 @@ async def fetch_weather_from_api(params: FunctionCallParams):
)
async def fetch_restaurant_recommendation(params: FunctionCallParams):
await params.result_callback({"name": "The Golden Dragon"})
# Define weather function using standardized schema
weather_function = FunctionSchema(
name="get_current_weather",
@@ -62,22 +65,47 @@ weather_function = FunctionSchema(
required=["location", "format"],
)
restaurant_function = FunctionSchema(
name="get_restaurant_recommendation",
description="Get a restaurant recommendation",
properties={
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
},
required=["location"],
)
# Create tools schema
tools = ToolsSchema(standard_tools=[weather_function])
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
session_properties = SessionProperties(
input_audio_transcription=InputAudioTranscription(model="whisper-1"),
# Set openai TurnDetection parameters. Not setting this at all will turn it
@@ -86,7 +114,7 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
# Or set to False to disable openai turn detection and use transport VAD
# turn_detection=False,
# tools=tools,
instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI.
instructions="""You are a helpful and friendly AI.
Act like a human, but remember that you aren't a human and that you can't do human
things in the real world. Your voice and personality should be warm and engaging, with a lively and
@@ -99,6 +127,10 @@ even if you're asked about them.
You are participating in a voice conversation. Keep your responses concise, short, and to the point
unless specifically asked to elaborate on a topic.
You have access to the following tools:
- get_current_weather: Get the current weather for a given location.
- get_restaurant_recommendation: Get a restaurant recommendation for a given location.
Remember, your responses should be short. Just one or two sentences, usually.""",
)
@@ -112,6 +144,7 @@ Remember, your responses should be short. Just one or two sentences, usually."""
# you can either register a single function for all function calls, or specific functions
# llm.register_function(None, fetch_weather_from_api)
llm.register_function("get_current_weather", fetch_weather_from_api)
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
# Create a standard OpenAI LLM context object using the normal messages format. The
# OpenAIRealtimeBetaLLMService will convert this internally to messages that the
@@ -162,18 +195,14 @@ Remember, your responses should be short. Just one or two sentences, usually."""
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -25,9 +25,9 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -164,22 +164,33 @@ tools = [
]
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
global tts
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
@@ -228,18 +239,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -15,7 +15,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,9 +29,9 @@ from pipecat.services.openai_realtime_beta import (
SessionProperties,
TurnDetection,
)
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -153,17 +152,30 @@ tools = [
]
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -237,18 +249,14 @@ Remember, your responses should be short. Just one or two sentences, usually."""
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -25,9 +25,9 @@ from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -159,20 +159,33 @@ tools = [
]
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
global tts
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -225,18 +238,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -15,6 +15,7 @@ from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -25,19 +26,16 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
video_participant_id = None
BASE_FILENAME = "/tmp/pipecat_conversation_"
tts = None
webrtc_peer_id = ""
# Global variable to store the client ID
client_id = ""
async def fetch_weather_from_api(params: FunctionCallParams):
@@ -54,11 +52,11 @@ async def fetch_weather_from_api(params: FunctionCallParams):
async def get_image(params: FunctionCallParams):
question = params.arguments["question"]
logger.debug(f"Requesting image with user_id={webrtc_peer_id}, question={question}")
logger.debug(f"Requesting image with user_id={client_id}, question={question}")
# Request the image frame
await params.llm.request_image_frame(
user_id=webrtc_peer_id,
user_id=client_id,
function_name=params.function_name,
tool_call_id=params.tool_call_id,
text_content=question,
@@ -96,7 +94,6 @@ async def save_conversation(params: FunctionCallParams):
async def load_conversation(params: FunctionCallParams):
global tts
filename = params.arguments["filename"]
logger.debug(f"loading conversation from {filename}")
try:
@@ -221,21 +218,27 @@ tools = [
]
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
global tts, webrtc_peer_id
webrtc_peer_id = webrtc_connection.pc_id
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
}
logger.info(f"Starting bot with peer_id: {webrtc_peer_id}")
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_in_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
@@ -282,24 +285,26 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
await maybe_capture_participant_camera(transport, client)
global client_id
client_id = get_transport_client_id(transport, client)
# Kick off the conversation.
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -17,16 +17,15 @@ from loguru import logger
from pipecat.adapters.schemas.function_schema import FunctionSchema
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
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.services.aws_nova_sonic.aws import AWSNovaSonicLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -170,17 +169,30 @@ tools = ToolsSchema(
)
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
logger.info(f"Starting bot")
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
),
)
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
# Specify initial system instruction.
# HACK: note that, for now, we need to inject a special bit of text into this instruction to
@@ -250,18 +262,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -103,7 +103,7 @@ async def main():
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner()
await runner.run(task)

View File

@@ -20,29 +20,39 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.tavus.video import TavusVideoService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
async with aiohttp.ClientSession() as session:
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
vad_analyzer=SileroVADAnalyzer(),
video_out_width=1280,
video_out_height=720,
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
@@ -108,18 +118,14 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
@transport.event_handler("on_client_closed")
async def on_client_closed(transport, client):
logger.info(f"Client closed connection")
await task.cancel()
runner = PipelineRunner(handle_sigint=False)
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from run import main
from pipecat.examples.run import main
main()
main(run_example, transport_params=transport_params)

View File

@@ -1,123 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import asyncio
import os
import sys
import aiohttp
from daily_runner import configure
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
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.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.tavus.video import TavusVideoService
from pipecat.transports.services.daily import DailyParams, DailyTransport
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def main():
async with aiohttp.ClientSession() as session:
(room_url, token) = await configure(session)
transport = DailyTransport(
room_url,
token,
"Pipecat bot",
DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
video_out_enabled=True,
video_out_is_live=True,
vad_analyzer=SileroVADAnalyzer(),
video_out_width=1280,
video_out_height=720,
),
)
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab",
)
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
tavus = TavusVideoService(
api_key=os.getenv("TAVUS_API_KEY"),
replica_id=os.getenv("TAVUS_REPLICA_ID"),
session=session,
)
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)
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt, # STT
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
tavus, # Tavus output layer
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
audio_in_sample_rate=16000,
audio_out_sample_rate=24000,
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):
# Kick off the conversation.
messages.append(
{
"role": "system",
"content": "Start by greeting the user and ask how you can help.",
}
)
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.cancel()
runner = PipelineRunner(handle_sigint=False)
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())

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