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hush/nova3
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mb/fix-mis
| Author | SHA1 | Date | |
|---|---|---|---|
|
4249abc849 |
48
.github/workflows/android.yaml
vendored
48
.github/workflows/android.yaml
vendored
@@ -1,48 +0,0 @@
|
||||
name: android
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- "examples/simple-chatbot/client/android/**"
|
||||
pull_request:
|
||||
branches:
|
||||
- "**"
|
||||
paths:
|
||||
- "examples/simple-chatbot/client/android/**"
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
sdk_git_ref:
|
||||
type: string
|
||||
description: "Which git ref of the app to build"
|
||||
|
||||
concurrency:
|
||||
group: build-android-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
sdk:
|
||||
name: "Simple chatbot demo"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout repo
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ github.event.inputs.sdk_git_ref || github.ref }}
|
||||
|
||||
- name: "Install Java"
|
||||
uses: actions/setup-java@v4
|
||||
with:
|
||||
distribution: 'temurin'
|
||||
java-version: '17'
|
||||
|
||||
- name: Build demo app
|
||||
working-directory: examples/simple-chatbot/client/android
|
||||
run: ./gradlew :simple-chatbot-client:assembleDebug
|
||||
|
||||
- name: Upload demo APK
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: Simple Chatbot Android Client
|
||||
path: examples/simple-chatbot/client/android/simple-chatbot-client/build/outputs/apk/debug/simple-chatbot-client-debug.apk
|
||||
54
.github/workflows/coverage.yaml
vendored
54
.github/workflows/coverage.yaml
vendored
@@ -1,54 +0,0 @@
|
||||
name: coverage
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
pull_request:
|
||||
branches:
|
||||
- "**"
|
||||
paths-ignore:
|
||||
- "docs/**"
|
||||
|
||||
jobs:
|
||||
coverage:
|
||||
name: "Coverage"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout repo
|
||||
uses: actions/checkout@v4
|
||||
- name: Set up Python
|
||||
id: setup_python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: "3.10"
|
||||
- name: Cache virtual environment
|
||||
uses: actions/cache@v3
|
||||
with:
|
||||
# We are hashing dev-requirements.txt and test-requirements.txt which
|
||||
# contain all dependencies needed to run the tests.
|
||||
key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
|
||||
path: .venv
|
||||
- name: Install system packages
|
||||
id: install_system_packages
|
||||
run: |
|
||||
sudo apt-get install -y portaudio19-dev
|
||||
- name: Setup virtual environment
|
||||
run: |
|
||||
python -m venv .venv
|
||||
- name: Install basic Python dependencies
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r dev-requirements.txt -r test-requirements.txt
|
||||
- name: Run tests with coverage
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
coverage run
|
||||
coverage xml
|
||||
- name: Upload coverage to Codecov
|
||||
uses: codecov/codecov-action@v5
|
||||
with:
|
||||
token: ${{ secrets.CODECOV_TOKEN }}
|
||||
slug: pipecat-ai/pipecat
|
||||
7
.github/workflows/format.yaml
vendored
7
.github/workflows/format.yaml
vendored
@@ -35,12 +35,7 @@ jobs:
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r dev-requirements.txt
|
||||
- name: Ruff formatter
|
||||
id: ruff-format
|
||||
id: ruff
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
ruff format --diff
|
||||
- name: Ruff import linter
|
||||
id: ruff-check
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
ruff check --select I
|
||||
|
||||
4
.github/workflows/tests.yaml
vendored
4
.github/workflows/tests.yaml
vendored
@@ -1,4 +1,4 @@
|
||||
name: tests
|
||||
name: test
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
@@ -49,4 +49,4 @@ jobs:
|
||||
- name: Test with pytest
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
pytest
|
||||
pytest --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
|
||||
|
||||
9
.gitignore
vendored
9
.gitignore
vendored
@@ -28,11 +28,4 @@ share/python-wheels/
|
||||
MANIFEST
|
||||
.DS_Store
|
||||
.env
|
||||
fly.toml
|
||||
|
||||
# Example files
|
||||
pipecat/examples/twilio-chatbot/templates/streams.xml
|
||||
|
||||
# Documentation
|
||||
docs/api/_build/
|
||||
docs/api/api
|
||||
fly.toml
|
||||
@@ -1,7 +0,0 @@
|
||||
repos:
|
||||
- repo: local
|
||||
hooks:
|
||||
- id: ruff-format-hook
|
||||
name: Check ruff formatting
|
||||
entry: sh scripts/pre-commit.sh
|
||||
language: system
|
||||
@@ -1,36 +0,0 @@
|
||||
version: 2
|
||||
|
||||
build:
|
||||
os: ubuntu-22.04
|
||||
tools:
|
||||
python: '3.12'
|
||||
apt_packages:
|
||||
- portaudio19-dev
|
||||
- python3-dev
|
||||
- libasound2-dev
|
||||
jobs:
|
||||
pre_build:
|
||||
- python -m pip install --upgrade pip
|
||||
- pip install wheel setuptools
|
||||
post_build:
|
||||
- echo "Build completed"
|
||||
|
||||
sphinx:
|
||||
configuration: docs/api/conf.py
|
||||
fail_on_warning: false
|
||||
|
||||
python:
|
||||
install:
|
||||
- requirements: docs/api/requirements.txt
|
||||
- method: pip
|
||||
path: .
|
||||
|
||||
search:
|
||||
ranking:
|
||||
api/*: 5
|
||||
getting-started/*: 4
|
||||
guides/*: 3
|
||||
|
||||
submodules:
|
||||
include: all
|
||||
recursive: true
|
||||
755
CHANGELOG.md
755
CHANGELOG.md
@@ -5,768 +5,18 @@ 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).
|
||||
|
||||
## [0.0.57] - 2025-02-14
|
||||
## Unreleased
|
||||
|
||||
### Added
|
||||
|
||||
- Added new `AudioContextWordTTSService`. This is a TTS base class for TTS
|
||||
services that handling multiple separate audio requests.
|
||||
|
||||
- Added new frames `EmulateUserStartedSpeakingFrame` and
|
||||
`EmulateUserStoppedSpeakingFrame` which can be used to emulated VAD behavior
|
||||
without VAD being present or not being triggered.
|
||||
|
||||
- Added a new `audio_in_stream_on_start` field to `TransportParams`.
|
||||
|
||||
- Added a new method `start_audio_in_streaming` in the `BaseInputTransport`.
|
||||
|
||||
- This method should be used to start receiving the input audio in case the
|
||||
field `audio_in_stream_on_start` is set to `false`.
|
||||
|
||||
- Added support for the `RTVIProcessor` to handle buffered audio in `base64`
|
||||
format, converting it into InputAudioRawFrame for transport.
|
||||
|
||||
- Added support for the `RTVIProcessor` to trigger `start_audio_in_streaming`
|
||||
only after the `client-ready` message.
|
||||
|
||||
- Added new `MUTE_UNTIL_FIRST_BOT_COMPLETE` strategy to `STTMuteStrategy`. This
|
||||
strategy starts muted and remains muted until the first bot speech completes,
|
||||
ensuring the bot's first response cannot be interrupted. This complements the
|
||||
existing `FIRST_SPEECH` strategy which only mutes during the first detected
|
||||
bot speech.
|
||||
|
||||
- Added support for Google Cloud Speech-to-Text V2 through `GoogleSTTService`.
|
||||
|
||||
- Added `RimeTTSService`, a new `WordTTSService`. Updated the foundational
|
||||
example `07q-interruptible-rime.py` to use `RimeTTSService`.
|
||||
|
||||
- Added support for Groq's Whisper API through the new `GroqSTTService` and
|
||||
OpenAI's Whisper API through the new `OpenAISTTService`. Introduced a new
|
||||
base class `BaseWhisperSTTService` to handle common Whisper API
|
||||
functionality.
|
||||
|
||||
- Added `PerplexityLLMService` for Perplexity NIM API integration, with an
|
||||
OpenAI-compatible interface. Also, added foundational example
|
||||
`14n-function-calling-perplexity.py`.
|
||||
|
||||
- Added `DailyTransport.update_remote_participants()`. This allows you to update
|
||||
remote participant's settings, like their permissions or which of their
|
||||
devices are enabled. Requires that the local participant have participant
|
||||
admin permission.
|
||||
|
||||
### Changed
|
||||
|
||||
- We don't consider a colon `:` and end of sentence any more.
|
||||
|
||||
- Updated `DailyTransport` to respect the `audio_in_stream_on_start` field,
|
||||
ensuring it only starts receiving the audio input if it is enabled.
|
||||
|
||||
- Updated `FastAPIWebsocketOutputTransport` to send `TransportMessageFrame` and
|
||||
`TransportMessageUrgentFrame` to the serializer.
|
||||
|
||||
- Updated `WebsocketServerOutputTransport` to send `TransportMessageFrame` and
|
||||
`TransportMessageUrgentFrame` to the serializer.
|
||||
|
||||
- Enhanced `STTMuteConfig` to validate strategy combinations, preventing
|
||||
`MUTE_UNTIL_FIRST_BOT_COMPLETE` and `FIRST_SPEECH` from being used together
|
||||
as they handle first bot speech differently.
|
||||
|
||||
- Updated foundational example `07n-interruptible-google.py` to use all Google
|
||||
services.
|
||||
|
||||
- `RimeHttpTTSService` now uses the `mistv2` model by default.
|
||||
|
||||
- Improved error handling in `AzureTTSService` to properly detect and log
|
||||
synthesis cancellation errors.
|
||||
|
||||
- Enhanced `WhisperSTTService` with full language support and improved model
|
||||
documentation.
|
||||
|
||||
- Updated foundation example `14f-function-calling-groq.py` to use
|
||||
`GroqSTTService` for transcription.
|
||||
|
||||
- Updated `GroqLLMService` to use `llama-3.3-70b-versatile` as the default
|
||||
model.
|
||||
|
||||
- `RTVIObserver` doesn't handle `LLMSearchResponseFrame` frames anymore. For
|
||||
now, to handle those frames you need to create a `GoogleRTVIObserver`
|
||||
instead.
|
||||
|
||||
### Deprecated
|
||||
|
||||
- `STTMuteFilter` constructor's `stt_service` parameter is now deprecated and
|
||||
will be removed in a future version. The filter now manages mute state
|
||||
internally instead of querying the STT service.
|
||||
|
||||
- `RTVI.observer()` is now deprecated, instantiate an `RTVIObserver` directly
|
||||
instead.
|
||||
|
||||
- All RTVI frame processors (e.g. `RTVISpeakingProcessor`,
|
||||
`RTVIBotLLMProcessor`) are now deprecated, instantiate an `RTVIObserver`
|
||||
instead.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a `FalImageGenService` issue that was causing the event loop to be
|
||||
blocked while loading the downloadded image.
|
||||
|
||||
- Fixed a `CartesiaTTSService` service issue that would cause audio overlapping
|
||||
in some cases.
|
||||
|
||||
- Fixed a websocket-based service issue (e.g. `CartesiaTTSService`) that was
|
||||
preventing a reconnection after the server disconnected cleanly, which was
|
||||
causing an inifite loop instead.
|
||||
|
||||
- Fixed a `BaseOutputTransport` issue that was causing upstream frames to no be
|
||||
pushed upstream.
|
||||
|
||||
- Fixed multiple issue where user transcriptions where not being handled
|
||||
properly. It was possible for short utterances to not trigger VAD which would
|
||||
cause user transcriptions to be ignored. It was also possible for one or more
|
||||
transcriptions to be generated after VAD in which case they would also be
|
||||
ignored.
|
||||
|
||||
- Fixed an issue that was causing `BotStoppedSpeakingFrame` to be generated too
|
||||
late. This could then cause issues unblocking `STTMuteFilter` later than
|
||||
desired.
|
||||
|
||||
- Fixed an issue that was causing `AudioBufferProcessor` to not record
|
||||
synchronized audio.
|
||||
|
||||
- Fixed an `RTVI` issue that was causing `bot-tts-text` messages to be sent
|
||||
before being processed by the output transport.
|
||||
|
||||
- Fixed an issue[#1192] in 11labs where we are trying to reconnect/disconnect
|
||||
the websocket connection even when the connection is already closed.
|
||||
|
||||
- Fixed an issue where `has_regular_messages` condition was always true in
|
||||
`GoogleLLMContext` due to `Part` having `function_call` & `function_response`
|
||||
with `None` values.
|
||||
|
||||
### Other
|
||||
|
||||
- Added new `instant-voice` example. This example showcases how to enable
|
||||
instant voice communication as soon as a user connects.
|
||||
|
||||
- Added new `local-input-select-stt` example. This examples allows you to play
|
||||
with local audio inputs by slecting them through a nice text interface.
|
||||
|
||||
## [0.0.56] - 2025-02-06
|
||||
|
||||
### Changed
|
||||
|
||||
- Use `gemini-2.0-flash-001` as the default model for `GoogleLLMSerivce`.
|
||||
|
||||
- Improved foundational examples 22b, 22c, and 22d to support function calling.
|
||||
With these base examples, `FunctionCallInProgressFrame` and
|
||||
`FunctionCallResultFrame` will no longer be blocked by the gates.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a `TkLocalTransport` and `LocalAudioTransport` issues that was causing
|
||||
errors on cleanup.
|
||||
|
||||
- Fixed an issue that was causing `tests.utils` import to fail because of
|
||||
logging setup.
|
||||
|
||||
- Fixed a `SentryMetrics` issue that was preventing any metrics to be sent to
|
||||
Sentry and also was preventing from metrics frames to be pushed to the
|
||||
pipeline.
|
||||
|
||||
- Fixed an issue in `BaseOutputTransport` where incoming audio would not be
|
||||
resampled to the desired output sample rate.
|
||||
|
||||
- Fixed an issue with the `TwilioFrameSerializer` and `TelnyxFrameSerializer`
|
||||
where `twilio_sample_rate` and `telnyx_sample_rate` were incorrectly
|
||||
initialized to `audio_in_sample_rate`. Those values currently default to 8000
|
||||
and should be set manually from the serializer constructor if a different
|
||||
value is needed.
|
||||
|
||||
### Other
|
||||
|
||||
- Added a new `sentry-metrics` example.
|
||||
|
||||
## [0.0.55] - 2025-02-05
|
||||
|
||||
### Added
|
||||
|
||||
- Added a new `start_metadata` field to `PipelineParams`. The provided metadata
|
||||
will be set to the initial `StartFrame` being pushed from the `PipelineTask`.
|
||||
|
||||
- Added new fields to `PipelineParams` to control audio input and output sample
|
||||
rates for the whole pipeline. This allows controlling sample rates from a
|
||||
single place instead of having to specify sample rates in each
|
||||
service. Setting a sample rate to a service is still possible and will
|
||||
override the value from `PipelineParams`.
|
||||
|
||||
- Introduce audio resamplers (`BaseAudioResampler`). This is just a base class
|
||||
to implement audio resamplers. Currently, two implementations are provided
|
||||
`SOXRAudioResampler` and `ResampyResampler`. A new
|
||||
`create_default_resampler()` has been added (replacing the now deprecated
|
||||
`resample_audio()`).
|
||||
|
||||
- It is now possible to specify the asyncio event loop that a `PipelineTask` and
|
||||
all the processors should run on by passing it as a new argument to the
|
||||
`PipelineRunner`. This could allow running pipelines in multiple threads each
|
||||
one with its own event loop.
|
||||
|
||||
- Added a new `utils.TaskManager`. Instead of a global task manager we now have
|
||||
a task manager per `PipelineTask`. In the previous version the task manager
|
||||
was global, so running multiple simultaneous `PipelineTask`s could result in
|
||||
dangling task warnings which were not actually true. In order, for all the
|
||||
processors to know about the task manager, we pass it through the
|
||||
`StartFrame`. This means that processors should create tasks when they receive
|
||||
a `StartFrame` but not before (because they don't have a task manager yet).
|
||||
|
||||
- Added `TelnyxFrameSerializer` to support Telnyx calls. A full running example
|
||||
has also been added to `examples/telnyx-chatbot`.
|
||||
|
||||
- Allow pushing silence audio frames before `TTSStoppedFrame`. This might be
|
||||
useful for testing purposes, for example, passing bot audio to an STT service
|
||||
which usually needs additional audio data to detect the utterance stopped.
|
||||
|
||||
- `TwilioSerializer` now supports transport message frames. With this we can
|
||||
create Twilio emulators.
|
||||
|
||||
- Added a new transport: `WebsocketClientTransport`.
|
||||
|
||||
- Added a `metadata` field to `Frame` which makes it possible to pass custom
|
||||
data to all frames.
|
||||
|
||||
- Added `test/utils.py` inside of pipecat package.
|
||||
|
||||
### Changed
|
||||
|
||||
- `GatedOpenAILLMContextAggregator` now require keyword arguments. Also, a new
|
||||
`start_open` argument has been added to set the initial state of the gate.
|
||||
|
||||
- Added `organization` and `project` level authentication to
|
||||
`OpenAILLMService`.
|
||||
|
||||
- Improved the language checking logic in `ElevenLabsTTSService` and
|
||||
`ElevenLabsHttpTTSService` to properly handle language codes based on model
|
||||
compatibility, with appropriate warnings when language codes cannot be
|
||||
applied.
|
||||
|
||||
- Updated `GoogleLLMContext` to support pushing `LLMMessagesUpdateFrame`s that
|
||||
contain a combination of function calls, function call responses, system
|
||||
messages, or just messages.
|
||||
|
||||
- `InputDTMFFrame` is now based on `DTMFFrame`. There's also a new
|
||||
`OutputDTMFFrame` frame.
|
||||
|
||||
### Deprecated
|
||||
|
||||
- `resample_audio()` is now deprecated, use `create_default_resampler()`
|
||||
instead.
|
||||
|
||||
### Removed
|
||||
|
||||
- `AudioBufferProcessor.reset_audio_buffers()` has been removed, use
|
||||
`AudioBufferProcessor.start_recording()` and
|
||||
`AudioBufferProcessor.stop_recording()` instead.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a `AudioBufferProcessor` that would cause crackling in some recordings.
|
||||
|
||||
- Fixed an issue in `AudioBufferProcessor` where user callback would not be
|
||||
called on task cancellation.
|
||||
|
||||
- Fixed an issue in `AudioBufferProcessor` that would cause wrong silence
|
||||
padding in some cases.
|
||||
|
||||
- Fixed an issue where `ElevenLabsTTSService` messages would return a 1009
|
||||
websocket error by increasing the max message size limit to 16MB.
|
||||
|
||||
- Fixed a `DailyTransport` issue that would cause events to be triggered before
|
||||
join finished.
|
||||
|
||||
- Fixed a `PipelineTask` issue that was preventing processors to be cleaned up
|
||||
after cancelling the task.
|
||||
|
||||
- Fixed an issue where queuing a `CancelFrame` to a pipeline task would not
|
||||
cause the task to finish. However, using `PipelineTask.cancel()` is still the
|
||||
recommended way to cancel a task.
|
||||
|
||||
### Other
|
||||
|
||||
- Improved Unit Test `run_test()` to use `PipelineTask` and
|
||||
`PipelineRunner`. There's now also some control around `StartFrame` and
|
||||
`EndFrame`. The `EndTaskFrame` has been removed since it doesn't seem
|
||||
necessary with this new approach.
|
||||
|
||||
- Updated `twilio-chatbot` with a few new features: use 8000 sample rate and
|
||||
avoid resampling, a new client useful for stress testing and testing locally
|
||||
without the need to make phone calls. Also, added audio recording on both the
|
||||
client and the server to make sure the audio sounds good.
|
||||
|
||||
- Updated examples to use `task.cancel()` to immediately exit the example when a
|
||||
participant leaves or disconnects, instead of pushing an `EndFrame`. Pushing
|
||||
an `EndFrame` causes the bot to run through everything that is internally
|
||||
queued (which could take some seconds). Note that using `task.cancel()` might
|
||||
not always be the best option and pushing an `EndFrame` could still be
|
||||
desirable to make sure all the pipeline is flushed.
|
||||
|
||||
## [0.0.54] - 2025-01-27
|
||||
|
||||
### Added
|
||||
|
||||
- In order to create tasks in Pipecat frame processors it is now recommended to
|
||||
use `FrameProcessor.create_task()` (which uses the new
|
||||
`utils.asyncio.create_task()`). It takes care of uncaught exceptions, task
|
||||
cancellation handling and task management. To cancel or wait for a task there
|
||||
is `FrameProcessor.cancel_task()` and `FrameProcessor.wait_for_task()`. All of
|
||||
Pipecat processors have been updated accordingly. Also, when a pipeline runner
|
||||
finishes, a warning about dangling tasks might appear, which indicates if any
|
||||
of the created tasks was never cancelled or awaited for (using these new
|
||||
functions).
|
||||
|
||||
- It is now possible to specify the period of the `PipelineTask` heartbeat
|
||||
frames with `heartbeats_period_secs`.
|
||||
|
||||
- Added `DailyMeetingTokenProperties` and `DailyMeetingTokenParams` Pydantic models
|
||||
for meeting token creation in `get_token` method of `DailyRESTHelper`.
|
||||
|
||||
- Added `enable_recording` and `geo` parameters to `DailyRoomProperties`.
|
||||
|
||||
- Added `RecordingsBucketConfig` to `DailyRoomProperties` to upload recordings
|
||||
to a custom AWS bucket.
|
||||
|
||||
### Changed
|
||||
|
||||
- Enhanced `UserIdleProcessor` with retry functionality and control over idle
|
||||
monitoring via new callback signature `(processor, retry_count) -> bool`.
|
||||
Updated the `17-detect-user-idle.py` to show how to use the `retry_count`.
|
||||
|
||||
- Add defensive error handling for `OpenAIRealtimeBetaLLMService`'s audio
|
||||
truncation. Audio truncation errors during interruptions now log a warning
|
||||
and allow the session to continue instead of throwing an exception.
|
||||
|
||||
- Modified `TranscriptProcessor` to use TTS text frames for more accurate assistant
|
||||
transcripts. Assistant messages are now aggregated based on bot speaking boundaries
|
||||
rather than LLM context, providing better handling of interruptions and partial
|
||||
utterances.
|
||||
|
||||
- Updated foundational examples `28a-transcription-processor-openai.py`,
|
||||
`28b-transcript-processor-anthropic.py`, and
|
||||
`28c-transcription-processor-gemini.py` to use the updated
|
||||
`TranscriptProcessor`.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an `GeminiMultimodalLiveLLMService` issue that was preventing the user
|
||||
to push initial LLM assistant messages (using `LLMMessagesAppendFrame`).
|
||||
|
||||
- Added missing `FrameProcessor.cleanup()` calls to `Pipeline`,
|
||||
`ParallelPipeline` and `UserIdleProcessor`.
|
||||
|
||||
- Fixed a type error when using `voice_settings` in `ElevenLabsHttpTTSService`.
|
||||
|
||||
- Fixed an issue where `OpenAIRealtimeBetaLLMService` function calling resulted
|
||||
in an error.
|
||||
|
||||
- Fixed an issue in `AudioBufferProcessor` where the last audio buffer was not
|
||||
being processed, in cases where the `_user_audio_buffer` was smaller than the
|
||||
buffer size.
|
||||
|
||||
### Performance
|
||||
|
||||
- Replaced audio resampling library `resampy` with `soxr`. Resampling a 2:21s
|
||||
audio file from 24KHz to 16KHz took 1.41s with `resampy` and 0.031s with
|
||||
`soxr` with similar audio quality.
|
||||
|
||||
### Other
|
||||
|
||||
- Added initial unit test infrastructure.
|
||||
|
||||
## [0.0.53] - 2025-01-18
|
||||
|
||||
### Added
|
||||
|
||||
- Added `ElevenLabsHttpTTSService` which uses EleveLabs' HTTP API instead of the
|
||||
websocket one.
|
||||
|
||||
- Introduced pipeline frame observers. Observers can view all the frames that go
|
||||
through the pipeline without the need to inject processors in the
|
||||
pipeline. This can be useful, for example, to implement frame loggers or
|
||||
debuggers among other things. The example
|
||||
`examples/foundational/30-observer.py` shows how to add an observer to a
|
||||
pipeline for debugging.
|
||||
|
||||
- Introduced heartbeat frames. The pipeline task can now push periodic
|
||||
heartbeats down the pipeline when `enable_heartbeats=True`. Heartbeats are
|
||||
system frames that are supposed to make it all the way to the end of the
|
||||
pipeline. When a heartbeat frame is received the traversing time (i.e. the
|
||||
time it took to go through the whole pipeline) will be displayed (with TRACE
|
||||
logging) otherwise a warning will be shown. The example
|
||||
`examples/foundational/31-heartbeats.py` shows how to enable heartbeats and
|
||||
forces warnings to be displayed.
|
||||
|
||||
- Added `LLMTextFrame` and `TTSTextFrame` which should be pushed by LLM and TTS
|
||||
services respectively instead of `TextFrame`s.
|
||||
|
||||
- Added `OpenRouter` for OpenRouter integration with an OpenAI-compatible
|
||||
interface. Added foundational example `14m-function-calling-openrouter.py`.
|
||||
|
||||
- Added a new `WebsocketService` based class for TTS services, containing
|
||||
base functions and retry logic.
|
||||
|
||||
- Added `DeepSeekLLMService` for DeepSeek integration with an OpenAI-compatible
|
||||
interface. Added foundational example `14l-function-calling-deepseek.py`.
|
||||
|
||||
- Added `FunctionCallResultProperties` dataclass to provide a structured way to
|
||||
control function call behavior, including:
|
||||
|
||||
- `run_llm`: Controls whether to trigger LLM completion
|
||||
- `on_context_updated`: Optional callback triggered after context update
|
||||
|
||||
- Added a new foundational example `07e-interruptible-playht-http.py` for easy
|
||||
testing of `PlayHTHttpTTSService`.
|
||||
|
||||
- Added support for Google TTS Journey voices in `GoogleTTSService`.
|
||||
|
||||
- Added `29-livekit-audio-chat.py`, as a new foundational examples for
|
||||
`LiveKitTransportLayer`.
|
||||
|
||||
- Added `enable_prejoin_ui`, `max_participants` and `start_video_off` params
|
||||
to `DailyRoomProperties`.
|
||||
|
||||
- Added `session_timeout` to `FastAPIWebsocketTransport` and
|
||||
`WebsocketServerTransport` for configuring session timeouts (in
|
||||
seconds). Triggers `on_session_timeout` for custom timeout handling.
|
||||
See [examples/websocket-server/bot.py](https://github.com/pipecat-ai/pipecat/blob/main/examples/websocket-server/bot.py).
|
||||
|
||||
- Added the new modalities option and helper function to set Gemini output
|
||||
modalities.
|
||||
|
||||
- Added `examples/foundational/26d-gemini-multimodal-live-text.py` which is
|
||||
using Gemini as TEXT modality and using another TTS provider for TTS process.
|
||||
|
||||
### Changed
|
||||
|
||||
- Modified `UserIdleProcessor` to start monitoring only after first
|
||||
conversation activity (`UserStartedSpeakingFrame` or
|
||||
`BotStartedSpeakingFrame`) instead of immediately.
|
||||
|
||||
- Modified `OpenAIAssistantContextAggregator` to support controlled completions
|
||||
and to emit context update callbacks via `FunctionCallResultProperties`.
|
||||
|
||||
- Added `aws_session_token` to the `PollyTTSService`.
|
||||
|
||||
- Changed the default model for `PlayHTHttpTTSService` to `Play3.0-mini-http`.
|
||||
|
||||
- `api_key`, `aws_access_key_id` and `region` are no longer required parameters
|
||||
for the PollyTTSService (AWSTTSService)
|
||||
|
||||
- Added `session_timeout` example in `examples/websocket-server/bot.py` to
|
||||
handle session timeout event.
|
||||
|
||||
- Changed `InputParams` in
|
||||
`src/pipecat/services/gemini_multimodal_live/gemini.py` to support different
|
||||
modalities.
|
||||
|
||||
- Changed `DeepgramSTTService` to send `finalize` event whenever VAD detects
|
||||
`UserStoppedSpeakingFrame`. This helps in faster transcriptions and clearing
|
||||
the `Deepgram` audio buffer.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue where `DeepgramSTTService` was not generating metrics using
|
||||
pipeline's VAD.
|
||||
|
||||
- Fixed `UserIdleProcessor` not properly propagating `EndFrame`s through the
|
||||
pipeline.
|
||||
|
||||
- Fixed an issue where websocket based TTS services could incorrectly terminate
|
||||
their connection due to a retry counter not resetting.
|
||||
|
||||
- Fixed a `PipelineTask` issue that would cause a dangling task after stopping
|
||||
the pipeline with an `EndFrame`.
|
||||
|
||||
- Fixed an import issue for `PlayHTHttpTTSService`.
|
||||
|
||||
- Fixed an issue where languages couldn't be used with the `PlayHTHttpTTSService`.
|
||||
|
||||
- Fixed an issue where `OpenAIRealtimeBetaLLMService` audio chunks were hitting
|
||||
an error when truncating audio content.
|
||||
|
||||
- Fixed an issue where setting the voice and model for `RimeHttpTTSService`
|
||||
wasn't working.
|
||||
|
||||
- Fixed an issue where `IdleFrameProcessor` and `UserIdleProcessor` were getting
|
||||
initialized before the start of the pipeline.
|
||||
|
||||
## [0.0.52] - 2024-12-24
|
||||
|
||||
### Added
|
||||
|
||||
- Constructor arguments for GoogleLLMService to directly set tools and tool_config.
|
||||
|
||||
- Smart turn detection example (`22d-natural-conversation-gemini-audio.py`) that
|
||||
leverages Gemini 2.0 capabilities ().
|
||||
(see https://x.com/kwindla/status/1870974144831275410)
|
||||
|
||||
- Added `DailyTransport.send_dtmf()` to send dial-out DTMF tones.
|
||||
|
||||
- Added `DailyTransport.sip_call_transfer()` to forward SIP and PSTN calls to
|
||||
another address or number. For example, transfer a SIP call to a different
|
||||
SIP address or transfer a PSTN phone number to a different PSTN phone number.
|
||||
|
||||
- Added `DailyTransport.sip_refer()` to transfer incoming SIP/PSTN calls from
|
||||
outside Daily to another SIP/PSTN address.
|
||||
|
||||
- Added an `auto_mode` input parameter to `ElevenLabsTTSService`. `auto_mode`
|
||||
is set to `True` by default. Enabling this setting disables the chunk
|
||||
schedule and all buffers, which reduces latency.
|
||||
|
||||
- Added `KoalaFilter` which implement on device noise reduction using Koala
|
||||
Noise Suppression.
|
||||
(see https://picovoice.ai/platform/koala/)
|
||||
|
||||
- Added `CerebrasLLMService` for Cerebras integration with an OpenAI-compatible
|
||||
interface. Added foundational example `14k-function-calling-cerebras.py`.
|
||||
|
||||
- Pipecat now supports Python 3.13. We had a dependency on the `audioop` package
|
||||
which was deprecated and now removed on Python 3.13. We are now using
|
||||
`audioop-lts` (https://github.com/AbstractUmbra/audioop) to provide the same
|
||||
functionality.
|
||||
|
||||
- Added timestamped conversation transcript support:
|
||||
|
||||
- New `TranscriptProcessor` factory provides access to user and assistant
|
||||
transcript processors.
|
||||
- `UserTranscriptProcessor` processes user speech with timestamps from
|
||||
transcription.
|
||||
- `AssistantTranscriptProcessor` processes assistant responses with LLM
|
||||
context timestamps.
|
||||
- Messages emitted with ISO 8601 timestamps indicating when they were spoken.
|
||||
- Supports all LLM formats (OpenAI, Anthropic, Google) via standard message
|
||||
format.
|
||||
- New examples: `28a-transcription-processor-openai.py`,
|
||||
`28b-transcription-processor-anthropic.py`, and
|
||||
`28c-transcription-processor-gemini.py`.
|
||||
|
||||
- Add support for more languages to ElevenLabs (Arabic, Croatian, Filipino,
|
||||
Tamil) and PlayHT (Afrikans, Albanian, Amharic, Arabic, Bengali, Croatian,
|
||||
Galician, Hebrew, Mandarin, Serbian, Tagalog, Urdu, Xhosa).
|
||||
|
||||
### Changed
|
||||
|
||||
- `PlayHTTTSService` uses the new v4 websocket API, which also fixes an issue
|
||||
where text inputted to the TTS didn't return audio.
|
||||
|
||||
- The default model for `ElevenLabsTTSService` is now `eleven_flash_v2_5`.
|
||||
|
||||
- `OpenAIRealtimeBetaLLMService` now takes a `model` parameter in the
|
||||
constructor.
|
||||
|
||||
- Updated the default model for the `OpenAIRealtimeBetaLLMService`.
|
||||
|
||||
- Room expiration (`exp`) in `DailyRoomProperties` is now optional (`None`) by
|
||||
default instead of automatically setting a 5-minute expiration time. You must
|
||||
explicitly set expiration time if desired.
|
||||
|
||||
### Deprecated
|
||||
|
||||
- `AWSTTSService` is now deprecated, use `PollyTTSService` instead.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed token counting in `GoogleLLMService`. Tokens were summed incorrectly
|
||||
(double-counted in many cases).
|
||||
|
||||
- Fixed an issue that could cause the bot to stop talking if there was a user
|
||||
interruption before getting any audio from the TTS service.
|
||||
|
||||
- Fixed an issue that would cause `ParallelPipeline` to handle `EndFrame`
|
||||
incorrectly causing the main pipeline to not terminate or terminate too early.
|
||||
|
||||
- Fixed an audio stuttering issue in `FastPitchTTSService`.
|
||||
|
||||
- Fixed a `BaseOutputTransport` issue that was causing non-audio frames being
|
||||
processed before the previous audio frames were played. This will allow, for
|
||||
example, sending a frame `A` after a `TTSSpeakFrame` and the frame `A` will
|
||||
only be pushed downstream after the audio generated from `TTSSpeakFrame` has
|
||||
been spoken.
|
||||
|
||||
- Fixed a `DeepgramSTTService` issue that was causing language to be passed as
|
||||
an object instead of a string resulting in the connection to fail.
|
||||
|
||||
## [0.0.51] - 2024-12-16
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue in websocket-based TTS services that was causing infinite
|
||||
reconnections (Cartesia, ElevenLabs, PlayHT and LMNT).
|
||||
|
||||
## [0.0.50] - 2024-12-11
|
||||
|
||||
### Added
|
||||
|
||||
- Added `GeminiMultimodalLiveLLMService`. This is an integration for Google's
|
||||
Gemini Multimodal Live API, supporting:
|
||||
|
||||
- Real-time audio and video input processing
|
||||
- Streaming text responses with TTS
|
||||
- Audio transcription for both user and bot speech
|
||||
- Function calling
|
||||
- System instructions and context management
|
||||
- Dynamic parameter updates (temperature, top_p, etc.)
|
||||
|
||||
- Added `AudioTranscriber` utility class for handling audio transcription with
|
||||
Gemini models.
|
||||
|
||||
- Added new context classes for Gemini:
|
||||
|
||||
- `GeminiMultimodalLiveContext`
|
||||
- `GeminiMultimodalLiveUserContextAggregator`
|
||||
- `GeminiMultimodalLiveAssistantContextAggregator`
|
||||
- `GeminiMultimodalLiveContextAggregatorPair`
|
||||
|
||||
- Added new foundational examples for `GeminiMultimodalLiveLLMService`:
|
||||
|
||||
- `26-gemini-multimodal-live.py`
|
||||
- `26a-gemini-multimodal-live-transcription.py`
|
||||
- `26b-gemini-multimodal-live-video.py`
|
||||
- `26c-gemini-multimodal-live-video.py`
|
||||
|
||||
- Added `SimliVideoService`. This is an integration for Simli AI avatars.
|
||||
(see https://www.simli.com)
|
||||
|
||||
- Added NVIDIA Riva's `FastPitchTTSService` and `ParakeetSTTService`.
|
||||
(see https://www.nvidia.com/en-us/ai-data-science/products/riva/)
|
||||
|
||||
- Added `IdentityFilter`. This is the simplest frame filter that lets through
|
||||
all incoming frames.
|
||||
|
||||
- New `STTMuteStrategy` called `FUNCTION_CALL` which mutes the STT service
|
||||
during LLM function calls.
|
||||
|
||||
- `DeepgramSTTService` now exposes two event handlers `on_speech_started` and
|
||||
`on_utterance_end` that could be used to implement interruptions. See new
|
||||
example `examples/foundational/07c-interruptible-deepgram-vad.py`.
|
||||
|
||||
- Added `GroqLLMService`, `GrokLLMService`, and `NimLLMService` for Groq, Grok,
|
||||
and NVIDIA NIM API integration, with an OpenAI-compatible interface.
|
||||
|
||||
- New examples demonstrating function calling with Groq, Grok, Azure OpenAI,
|
||||
Fireworks, and NVIDIA NIM: `14f-function-calling-groq.py`,
|
||||
`14g-function-calling-grok.py`, `14h-function-calling-azure.py`,
|
||||
`14i-function-calling-fireworks.py`, and `14j-function-calling-nvidia.py`.
|
||||
|
||||
- In order to obtain the audio stored by the `AudioBufferProcessor` you can now
|
||||
also register an `on_audio_data` event handler. The `on_audio_data` handler
|
||||
will be called every time `buffer_size` (a new constructor argument) is
|
||||
reached. If `buffer_size` is 0 (default) you need to manually get the audio as
|
||||
before using `AudioBufferProcessor.merge_audio_buffers()`.
|
||||
|
||||
```
|
||||
@audiobuffer.event_handler("on_audio_data")
|
||||
async def on_audio_data(processor, audio, sample_rate, num_channels):
|
||||
await save_audio(audio, sample_rate, num_channels)
|
||||
```
|
||||
|
||||
- Added a new RTVI message called `disconnect-bot`, which when handled pushes
|
||||
an `EndFrame` to trigger the pipeline to stop.
|
||||
|
||||
### Changed
|
||||
|
||||
- `STTMuteFilter` now supports multiple simultaneous muting strategies.
|
||||
|
||||
- `XTTSService` language now defaults to `Language.EN`.
|
||||
|
||||
- `SoundfileMixer` doesn't resample input files anymore to avoid startup
|
||||
delays. The sample rate of the provided sound files now need to match the
|
||||
sample rate of the output transport.
|
||||
|
||||
- Input frames (audio, image and transport messages) are now system frames. This
|
||||
means they are processed immediately by all processors instead of being queued
|
||||
internally.
|
||||
|
||||
- Expanded the transcriptions.language module to support a superset of
|
||||
languages.
|
||||
|
||||
- Updated STT and TTS services with language options that match the supported
|
||||
languages for each service.
|
||||
|
||||
- Updated the `AzureLLMService` to use the `OpenAILLMService`. Updated the
|
||||
`api_version` to `2024-09-01-preview`.
|
||||
|
||||
- Updated the `FireworksLLMService` to use the `OpenAILLMService`. Updated the
|
||||
default model to `accounts/fireworks/models/firefunction-v2`.
|
||||
|
||||
- Updated the `simple-chatbot` example to include a Javascript and React client
|
||||
example, using RTVI JS and React.
|
||||
|
||||
### Removed
|
||||
|
||||
- Removed `AppFrame`. This was used as a special user custom frame, but there's
|
||||
actually no use case for that.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a `ParallelPipeline` issue that would cause system frames to be queued.
|
||||
|
||||
- Fixed `FastAPIWebsocketTransport` so it can work with binary data (e.g. using
|
||||
the protobuf serializer).
|
||||
|
||||
- Fixed an issue in `CartesiaTTSService` that could cause previous audio to be
|
||||
received after an interruption.
|
||||
|
||||
- Fixed Cartesia, ElevenLabs, LMNT and PlayHT TTS websocket
|
||||
reconnection. Before, if an error occurred no reconnection was happening.
|
||||
|
||||
- Fixed a `BaseOutputTransport` issue that was causing audio to be discarded
|
||||
after an `EndFrame` was received.
|
||||
|
||||
- Fixed an issue in `WebsocketServerTransport` and `FastAPIWebsocketTransport`
|
||||
that would cause a busy loop when using audio mixer.
|
||||
|
||||
- Fixed a `DailyTransport` and `LiveKitTransport` issue where connections were
|
||||
being closed in the input transport prematurely. This was causing frames
|
||||
queued inside the pipeline being discarded.
|
||||
|
||||
- Fixed an issue in `DailyTransport` that would cause some internal callbacks to
|
||||
not be executed.
|
||||
|
||||
- Fixed an issue where other frames were being processed while a `CancelFrame`
|
||||
was being pushed down the pipeline.
|
||||
|
||||
- `AudioBufferProcessor` now handles interruptions properly.
|
||||
|
||||
- Fixed a `WebsocketServerTransport` issue that would prevent interruptions with
|
||||
`TwilioSerializer` from working.
|
||||
|
||||
- `DailyTransport.capture_participant_video` now allows capturing user's screen
|
||||
share by simply passing `video_source="screenVideo"`.
|
||||
|
||||
- Fixed Google Gemini message handling to properly convert appended messages to
|
||||
Gemini's required format.
|
||||
|
||||
- Fixed an issue with `FireworksLLMService` where chat completions were failing
|
||||
by removing the `stream_options` from the chat completion options.
|
||||
|
||||
## [0.0.49] - 2024-11-17
|
||||
|
||||
### Added
|
||||
|
||||
- Added RTVI `on_bot_started` event which is useful in a single turn
|
||||
interaction.
|
||||
|
||||
- Added `DailyTransport` events `dialin-connected`, `dialin-stopped`,
|
||||
`dialin-error` and `dialin-warning`. Needs daily-python >= 0.13.0.
|
||||
|
||||
- Added `RimeHttpTTSService` and the `07q-interruptible-rime.py` foundational
|
||||
example.
|
||||
|
||||
- Added `STTMuteFilter`, a general-purpose processor that combines STT
|
||||
muting and interruption control. When active, it prevents both transcription
|
||||
and interruptions during bot speech. The processor supports multiple
|
||||
strategies: `FIRST_SPEECH` (mute only during bot's first
|
||||
speech), `ALWAYS` (mute during all bot speech), or `CUSTOM` (using provided
|
||||
callback).
|
||||
|
||||
- Added `STTMuteFrame`, a control frame that enables/disables speech
|
||||
transcription in STT services.
|
||||
|
||||
@@ -1756,9 +1006,6 @@ async def on_connected(processor):
|
||||
|
||||
### Changed
|
||||
|
||||
- `FrameSerializer.serialize()` and `FrameSerializer.deserialize()` are now
|
||||
`async`.
|
||||
|
||||
- `Filter` has been renamed to `FrameFilter` and it's now under
|
||||
`processors/filters`.
|
||||
|
||||
|
||||
2
LICENSE
2
LICENSE
@@ -1,6 +1,6 @@
|
||||
BSD 2-Clause License
|
||||
|
||||
Copyright (c) 2024–2025, Daily
|
||||
Copyright (c) 2024, Daily
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions are met:
|
||||
|
||||
77
README.md
77
README.md
@@ -2,7 +2,7 @@
|
||||
<img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
|
||||
</div></h1>
|
||||
|
||||
[](https://pypi.org/project/pipecat-ai)  [](https://codecov.io/gh/pipecat-ai/pipecat) [](https://docs.pipecat.ai) [](https://discord.gg/pipecat)
|
||||
[](https://pypi.org/project/pipecat-ai) [](https://discord.gg/pipecat) <a href="https://app.commanddash.io/agent/github_pipecat-ai_pipecat"><img src="https://img.shields.io/badge/AI-Code%20Agent-EB9FDA"></a>
|
||||
|
||||
Pipecat is an open source Python framework for building voice and multimodal conversational agents. It handles the complex orchestration of AI services, network transport, audio processing, and multimodal interactions, letting you focus on creating engaging experiences.
|
||||
|
||||
@@ -13,7 +13,6 @@ Pipecat is an open source Python framework for building voice and multimodal con
|
||||
- **Multimodal Apps**: Combine voice, video, images, and text
|
||||
- **Creative Tools**: [Story-telling experiences](https://storytelling-chatbot.fly.dev/) and social companions
|
||||
- **Business Solutions**: [Customer intake flows](https://www.youtube.com/watch?v=lDevgsp9vn0) and support bots
|
||||
- **Complex conversational flows**: [Refer to Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) to learn more
|
||||
|
||||
## See it in action
|
||||
|
||||
@@ -33,8 +32,6 @@ Pipecat is an open source Python framework for building voice and multimodal con
|
||||
- **Real-time Processing**: Frame-based pipeline architecture for fluid interactions
|
||||
- **Production Ready**: Enterprise-grade WebRTC and Websocket support
|
||||
|
||||
💡 Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
|
||||
|
||||
## Getting started
|
||||
|
||||
You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you’re ready. You can also add a 📞 telephone number, 🖼️ image output, 📺 video input, use different LLMs, and more.
|
||||
@@ -53,21 +50,21 @@ To keep things lightweight, only the core framework is included by default. If y
|
||||
pip install "pipecat-ai[option,...]"
|
||||
```
|
||||
|
||||
### Available services
|
||||
Available options include:
|
||||
|
||||
| Category | Services | Install Command Example |
|
||||
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [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), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
||||
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [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), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
||||
| 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), [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), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
||||
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[google]"` |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
|
||||
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
|
||||
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
||||
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
||||
| Category | Services | Install Command Example |
|
||||
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/api-reference/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/api-reference/services/stt/azure), [Deepgram](https://docs.pipecat.ai/api-reference/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/api-reference/services/stt/gladia), [Whisper](https://docs.pipecat.ai/api-reference/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
||||
| LLMs | [Anthropic](https://docs.pipecat.ai/api-reference/services/llm/anthropic), [Azure](https://docs.pipecat.ai/api-reference/services/llm/azure), [Fireworks AI](https://docs.pipecat.ai/api-reference/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/api-reference/services/llm/gemini), [Ollama](https://docs.pipecat.ai/api-reference/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/api-reference/services/llm/openai), [Together AI](https://docs.pipecat.ai/api-reference/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
||||
| Text-to-Speech | [AWS](https://docs.pipecat.ai/api-reference/services/tts/aws), [Azure](https://docs.pipecat.ai/api-reference/services/tts/azure), [Cartesia](https://docs.pipecat.ai/api-reference/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/services/tts/elevenlabs), [Google](https://docs.pipecat.ai/api-reference/services/tts/google), [LMNT](https://docs.pipecat.ai/api-reference/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/api-reference/services/tts/openai), [PlayHT](https://docs.pipecat.ai/api-reference/services/tts/playht), [Rime](https://docs.pipecat.ai/api-reference/services/tts/rime), [XTTS](https://docs.pipecat.ai/api-reference/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
||||
| Speech-to-Speech | [OpenAI Realtime](https://docs.pipecat.ai/api-reference/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/api-reference/services/transport/daily), WebSocket, Local | `pip install "pipecat-ai[daily]"` |
|
||||
| Video | [Tavus](https://docs.pipecat.ai/api-reference/services/video/tavus) | `pip install "pipecat-ai[tavus]"` |
|
||||
| Vision & Image | [Moondream](https://docs.pipecat.ai/api-reference/services/vision/moondream), [fal](https://docs.pipecat.ai/api-reference/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/api-reference/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/api-reference/utilities/audio/krisp-filter), [Noisereduce](https://docs.pipecat.ai/api-reference/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
||||
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/api-reference/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/api-reference/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
||||
|
||||
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
|
||||
📚 [View full services documentation →](https://docs.pipecat.ai/api-reference/services/supported-services)
|
||||
|
||||
## Code examples
|
||||
|
||||
@@ -81,7 +78,7 @@ Here is a very basic Pipecat bot that greets a user when they join a real-time s
|
||||
```python
|
||||
import asyncio
|
||||
|
||||
from pipecat.frames.frames import TextFrame
|
||||
from pipecat.frames.frames import EndFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
@@ -122,7 +119,7 @@ async def main():
|
||||
# Register an event handler to exit the application when the user leaves.
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
# Run the pipeline task
|
||||
await runner.run(task)
|
||||
@@ -149,40 +146,27 @@ Sign up [here](https://dashboard.daily.co/u/signup) and [create a room](https://
|
||||
|
||||
## Hacking on the framework itself
|
||||
|
||||
_Note: You may need to set up a virtual environment before following these instructions. From the root of the repo:_
|
||||
_Note that you may need to set up a virtual environment before following the instructions below. For instance, you might need to run the following from the root of the repo:_
|
||||
|
||||
```shell
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
```
|
||||
|
||||
Install the development dependencies:
|
||||
From the root of this repo, run the following:
|
||||
|
||||
```shell
|
||||
pip install -r dev-requirements.txt
|
||||
python -m build
|
||||
```
|
||||
|
||||
Install the git pre-commit hooks (these help ensure your code follows project rules):
|
||||
This builds the package. To use the package locally (e.g. to run sample files), run
|
||||
|
||||
```shell
|
||||
pre-commit install
|
||||
pip install --editable ".[option,...]"
|
||||
```
|
||||
|
||||
Install the `pipecat-ai` package locally in editable mode:
|
||||
|
||||
```shell
|
||||
pip install -e .
|
||||
```
|
||||
|
||||
The `-e` or `--editable` option allows you to modify the code without reinstalling.
|
||||
|
||||
To include optional dependencies, add them to the install command. For example:
|
||||
|
||||
```shell
|
||||
pip install -e ".[daily,deepgram,cartesia,openai,silero]" # Updated for the services you're using
|
||||
```
|
||||
|
||||
If you want to use this package from another directory:
|
||||
If you want to use this package from another directory, you can run:
|
||||
|
||||
```shell
|
||||
pip install "path_to_this_repo[option,...]"
|
||||
@@ -193,7 +177,7 @@ pip install "path_to_this_repo[option,...]"
|
||||
From the root directory, run:
|
||||
|
||||
```shell
|
||||
pytest
|
||||
pytest --doctest-modules --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
|
||||
```
|
||||
|
||||
## Setting up your editor
|
||||
@@ -210,7 +194,9 @@ You can use [use-package](https://github.com/jwiegley/use-package) to install [e
|
||||
:hook ((python-mode . lazy-ruff-mode))
|
||||
:config
|
||||
(setq lazy-ruff-format-command "ruff format")
|
||||
(setq lazy-ruff-check-command "ruff check --select I"))
|
||||
(setq lazy-ruff-only-format-block t)
|
||||
(setq lazy-ruff-only-format-region t)
|
||||
(setq lazy-ruff-only-format-buffer t))
|
||||
```
|
||||
|
||||
`ruff` was installed in the `venv` environment described before, so you should be able to use [pyvenv-auto](https://github.com/ryotaro612/pyvenv-auto) to automatically load that environment inside Emacs.
|
||||
@@ -220,6 +206,7 @@ You can use [use-package](https://github.com/jwiegley/use-package) to install [e
|
||||
:ensure t
|
||||
:defer t
|
||||
:hook ((python-mode . pyvenv-auto-run)))
|
||||
|
||||
```
|
||||
|
||||
### Visual Studio Code
|
||||
@@ -234,16 +221,6 @@ Install the
|
||||
}
|
||||
```
|
||||
|
||||
### PyCharm
|
||||
|
||||
`ruff` was installed in the `venv` environment described before, now to enable autoformatting on save, go to `File` -> `Settings` -> `Tools` -> `File Watchers` and add a new watcher with the following settings:
|
||||
|
||||
1. **Name**: `Ruff formatter`
|
||||
2. **File type**: `Python`
|
||||
3. **Working directory**: `$ContentRoot$`
|
||||
4. **Arguments**: `format $FilePath$`
|
||||
5. **Program**: `$PyInterpreterDirectory$/ruff`
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions from the community! Whether you're fixing bugs, improving documentation, or adding new features, here's how you can help:
|
||||
|
||||
11
codecov.yml
11
codecov.yml
@@ -1,11 +0,0 @@
|
||||
coverage:
|
||||
range: 50..90 # coverage lower than 50 is red, higher than 90 green, between color code
|
||||
|
||||
status:
|
||||
project:
|
||||
default:
|
||||
target: auto # auto % coverage target
|
||||
threshold: 5% # allow for 5% reduction of coverage without failing
|
||||
|
||||
# do not run coverage on patch nor changes
|
||||
patch: false
|
||||
@@ -1,12 +1,8 @@
|
||||
build~=1.2.2
|
||||
coverage~=7.6.12
|
||||
grpcio-tools~=1.67.1
|
||||
build~=1.2.1
|
||||
grpcio-tools~=1.62.2
|
||||
pip-tools~=7.4.1
|
||||
pre-commit~=4.0.1
|
||||
pyright~=1.1.393
|
||||
pytest~=8.3.4
|
||||
pytest-asyncio~=0.25.2
|
||||
ruff~=0.9.5
|
||||
setuptools~=70.0.0
|
||||
pyright~=1.1.376
|
||||
pytest~=8.3.2
|
||||
ruff~=0.6.7
|
||||
setuptools~=72.2.0
|
||||
setuptools_scm~=8.1.0
|
||||
python-dotenv~=1.0.1
|
||||
|
||||
@@ -1,20 +0,0 @@
|
||||
# Minimal makefile for Sphinx documentation
|
||||
#
|
||||
|
||||
# You can set these variables from the command line, and also
|
||||
# from the environment for the first two.
|
||||
SPHINXOPTS ?=
|
||||
SPHINXBUILD ?= sphinx-build
|
||||
SOURCEDIR = .
|
||||
BUILDDIR = _build
|
||||
|
||||
# Put it first so that "make" without argument is like "make help".
|
||||
help:
|
||||
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
|
||||
|
||||
.PHONY: help Makefile
|
||||
|
||||
# Catch-all target: route all unknown targets to Sphinx using the new
|
||||
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
|
||||
%: Makefile
|
||||
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
|
||||
@@ -1,109 +0,0 @@
|
||||
# Pipecat Documentation
|
||||
|
||||
This directory contains the source files for auto-generating Pipecat's server API reference documentation.
|
||||
|
||||
## Setup
|
||||
|
||||
1. Install documentation dependencies:
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
2. Make the build scripts executable:
|
||||
|
||||
```bash
|
||||
chmod +x build-docs.sh rtd-test.py
|
||||
```
|
||||
|
||||
## Building Documentation
|
||||
|
||||
From this directory, you can build the documentation in several ways:
|
||||
|
||||
### Local Build
|
||||
|
||||
```bash
|
||||
# Using the build script (automatically opens docs when done)
|
||||
./build-docs.sh
|
||||
|
||||
# Or directly with sphinx-build
|
||||
sphinx-build -b html . _build/html -W --keep-going
|
||||
```
|
||||
|
||||
### ReadTheDocs Test Build
|
||||
|
||||
To test the documentation build process exactly as it would run on ReadTheDocs:
|
||||
|
||||
```bash
|
||||
./rtd-test.py
|
||||
```
|
||||
|
||||
This script:
|
||||
|
||||
- Creates a fresh virtual environment
|
||||
- Installs all dependencies as specified in requirements files
|
||||
- Handles conflicting dependencies (like grpcio versions for Riva and PlayHT)
|
||||
- Builds the documentation in an isolated environment
|
||||
- Provides detailed logging of the build process
|
||||
|
||||
Use this script to verify your documentation will build correctly on ReadTheDocs before pushing changes.
|
||||
|
||||
## Viewing Documentation
|
||||
|
||||
The built documentation will be available at `_build/html/index.html`. To open:
|
||||
|
||||
```bash
|
||||
# On MacOS
|
||||
open _build/html/index.html
|
||||
|
||||
# On Linux
|
||||
xdg-open _build/html/index.html
|
||||
|
||||
# On Windows
|
||||
start _build/html/index.html
|
||||
```
|
||||
|
||||
## Directory Structure
|
||||
|
||||
```
|
||||
.
|
||||
├── api/ # Auto-generated API documentation
|
||||
├── _build/ # Built documentation
|
||||
├── _static/ # Static files (images, css, etc.)
|
||||
├── conf.py # Sphinx configuration
|
||||
├── index.rst # Main documentation entry point
|
||||
├── requirements-base.txt # Base documentation dependencies
|
||||
├── requirements-riva.txt # Riva-specific dependencies
|
||||
├── requirements-playht.txt # PlayHT-specific dependencies
|
||||
├── build-docs.sh # Local build script
|
||||
└── rtd-test.py # ReadTheDocs test build script
|
||||
```
|
||||
|
||||
## Notes
|
||||
|
||||
- Documentation is auto-generated from Python docstrings
|
||||
- Service modules are automatically detected and included
|
||||
- The build process matches our ReadTheDocs configuration
|
||||
- Warnings are treated as errors (-W flag) to maintain consistency
|
||||
- The --keep-going flag ensures all errors are reported
|
||||
- Dependencies are split into multiple requirements files to handle version conflicts
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
If you encounter missing service modules:
|
||||
|
||||
1. Verify the service is installed with its extras: `pip install pipecat-ai[service-name]`
|
||||
2. Check the build logs for import errors
|
||||
3. Ensure the service module is properly initialized in the package
|
||||
4. Run `./rtd-test.py` to test in an isolated environment matching ReadTheDocs
|
||||
|
||||
For dependency conflicts:
|
||||
|
||||
1. Check the requirements files for version specifications
|
||||
2. Use `rtd-test.py` to verify dependency resolution
|
||||
3. Consider adding service-specific requirements files if needed
|
||||
|
||||
For more information:
|
||||
|
||||
- [ReadTheDocs Configuration](.readthedocs.yaml)
|
||||
- [Sphinx Documentation](https://www.sphinx-doc.org/)
|
||||
@@ -1,10 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
# Clean previous build
|
||||
rm -rf _build
|
||||
|
||||
# Build docs matching ReadTheDocs configuration
|
||||
sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
|
||||
|
||||
# Open docs (MacOS)
|
||||
open _build/html/index.html
|
||||
252
docs/api/conf.py
252
docs/api/conf.py
@@ -1,252 +0,0 @@
|
||||
import logging
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
# Configure logging
|
||||
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
|
||||
logger = logging.getLogger("sphinx-build")
|
||||
|
||||
# Add source directory to path
|
||||
docs_dir = Path(__file__).parent
|
||||
project_root = docs_dir.parent.parent
|
||||
sys.path.insert(0, str(project_root / "src"))
|
||||
|
||||
# Project information
|
||||
project = "pipecat-ai"
|
||||
copyright = "2024, Daily"
|
||||
author = "Daily"
|
||||
|
||||
# General configuration
|
||||
extensions = [
|
||||
"sphinx.ext.autodoc",
|
||||
"sphinx.ext.napoleon",
|
||||
"sphinx.ext.viewcode",
|
||||
"sphinx.ext.intersphinx",
|
||||
]
|
||||
|
||||
# Napoleon settings
|
||||
napoleon_google_docstring = True
|
||||
napoleon_numpy_docstring = False
|
||||
napoleon_include_init_with_doc = True
|
||||
|
||||
# AutoDoc settings
|
||||
autodoc_default_options = {
|
||||
"members": True,
|
||||
"member-order": "bysource",
|
||||
"special-members": "__init__",
|
||||
"undoc-members": True,
|
||||
"exclude-members": "__weakref__",
|
||||
"no-index": True,
|
||||
"show-inheritance": True,
|
||||
}
|
||||
|
||||
# Mock imports for optional dependencies
|
||||
autodoc_mock_imports = [
|
||||
"riva",
|
||||
"livekit",
|
||||
"pyht", # Base PlayHT package
|
||||
"pyht.async_client", # PlayHT specific imports
|
||||
"pyht.client",
|
||||
"pyht.protos",
|
||||
"pyht.protos.api_pb2",
|
||||
"pipecat_ai_playht", # PlayHT wrapper
|
||||
"anthropic",
|
||||
"assemblyai",
|
||||
"boto3",
|
||||
"azure",
|
||||
"cartesia",
|
||||
"deepgram",
|
||||
"elevenlabs",
|
||||
"fal",
|
||||
"gladia",
|
||||
"google",
|
||||
"krisp",
|
||||
"langchain",
|
||||
"lmnt",
|
||||
"noisereduce",
|
||||
"openai",
|
||||
"openpipe",
|
||||
"simli",
|
||||
"soundfile",
|
||||
# Existing mocks
|
||||
"pipecat_ai_krisp",
|
||||
"pyaudio",
|
||||
"_tkinter",
|
||||
"tkinter",
|
||||
"daily",
|
||||
"daily_python",
|
||||
"pydantic.BaseModel",
|
||||
"pydantic.Field",
|
||||
"pydantic._internal._model_construction",
|
||||
"pydantic._internal._fields",
|
||||
]
|
||||
|
||||
# HTML output settings
|
||||
html_theme = "sphinx_rtd_theme"
|
||||
html_static_path = ["_static"]
|
||||
autodoc_typehints = "description"
|
||||
html_show_sphinx = False
|
||||
|
||||
|
||||
def verify_modules():
|
||||
"""Verify that required modules are available."""
|
||||
required_modules = {
|
||||
"services": [
|
||||
"assemblyai",
|
||||
"aws",
|
||||
"cartesia",
|
||||
"deepgram",
|
||||
"google",
|
||||
"lmnt",
|
||||
"riva",
|
||||
"simli",
|
||||
],
|
||||
"serializers": ["livekit"],
|
||||
"vad": ["silero", "vad_analyzer"],
|
||||
"transports": {
|
||||
"services": ["daily", "livekit"],
|
||||
"local": ["audio", "tk"],
|
||||
"network": ["fastapi_websocket", "websocket_server"],
|
||||
},
|
||||
}
|
||||
|
||||
missing = []
|
||||
for category, modules in required_modules.items():
|
||||
if isinstance(modules, dict):
|
||||
# Handle nested structure
|
||||
for subcategory, submodules in modules.items():
|
||||
for module in submodules:
|
||||
try:
|
||||
__import__(f"pipecat.{category}.{subcategory}.{module}")
|
||||
logger.info(
|
||||
f"Successfully imported pipecat.{category}.{subcategory}.{module}"
|
||||
)
|
||||
except (ImportError, TypeError, NameError) as e:
|
||||
missing.append(f"pipecat.{category}.{subcategory}.{module}")
|
||||
logger.warning(
|
||||
f"Optional module not available: pipecat.{category}.{subcategory}.{module} - {str(e)}"
|
||||
)
|
||||
else:
|
||||
# Handle flat structure
|
||||
for module in modules:
|
||||
try:
|
||||
__import__(f"pipecat.{category}.{module}")
|
||||
logger.info(f"Successfully imported pipecat.{category}.{module}")
|
||||
except (ImportError, TypeError, NameError) as e:
|
||||
missing.append(f"pipecat.{category}.{module}")
|
||||
logger.warning(
|
||||
f"Optional module not available: pipecat.{category}.{module} - {str(e)}"
|
||||
)
|
||||
|
||||
if missing:
|
||||
logger.warning(f"Some optional modules are not available: {missing}")
|
||||
|
||||
|
||||
def clean_title(title: str) -> str:
|
||||
"""Automatically clean module titles."""
|
||||
# Remove everything after space (like 'module', 'processor', etc.)
|
||||
title = title.split(" ")[0]
|
||||
|
||||
# Get the last part of the dot-separated path
|
||||
parts = title.split(".")
|
||||
title = parts[-1]
|
||||
|
||||
# Special cases for service names and common acronyms
|
||||
special_cases = {
|
||||
"ai": "AI",
|
||||
"aws": "AWS",
|
||||
"api": "API",
|
||||
"vad": "VAD",
|
||||
"assemblyai": "AssemblyAI",
|
||||
"deepgram": "Deepgram",
|
||||
"elevenlabs": "ElevenLabs",
|
||||
"openai": "OpenAI",
|
||||
"openpipe": "OpenPipe",
|
||||
"playht": "PlayHT",
|
||||
"xtts": "XTTS",
|
||||
"lmnt": "LMNT",
|
||||
}
|
||||
|
||||
# Check if the entire title is a special case
|
||||
if title.lower() in special_cases:
|
||||
return special_cases[title.lower()]
|
||||
|
||||
# Otherwise, capitalize each word
|
||||
words = title.split("_")
|
||||
cleaned_words = []
|
||||
for word in words:
|
||||
if word.lower() in special_cases:
|
||||
cleaned_words.append(special_cases[word.lower()])
|
||||
else:
|
||||
cleaned_words.append(word.capitalize())
|
||||
|
||||
return " ".join(cleaned_words)
|
||||
|
||||
|
||||
def setup(app):
|
||||
"""Generate API documentation during Sphinx build."""
|
||||
from sphinx.ext.apidoc import main
|
||||
|
||||
docs_dir = Path(__file__).parent
|
||||
project_root = docs_dir.parent.parent
|
||||
output_dir = str(docs_dir / "api")
|
||||
source_dir = str(project_root / "src" / "pipecat")
|
||||
|
||||
# Clean existing files
|
||||
if Path(output_dir).exists():
|
||||
import shutil
|
||||
|
||||
shutil.rmtree(output_dir)
|
||||
logger.info(f"Cleaned existing documentation in {output_dir}")
|
||||
|
||||
logger.info(f"Generating API documentation...")
|
||||
logger.info(f"Output directory: {output_dir}")
|
||||
logger.info(f"Source directory: {source_dir}")
|
||||
|
||||
excludes = [
|
||||
str(project_root / "src/pipecat/pipeline/to_be_updated"),
|
||||
str(project_root / "src/pipecat/processors/gstreamer"),
|
||||
str(project_root / "src/pipecat/services/to_be_updated"),
|
||||
str(project_root / "src/pipecat/vad"), # deprecated
|
||||
"**/test_*.py",
|
||||
"**/tests/*.py",
|
||||
]
|
||||
|
||||
try:
|
||||
main(
|
||||
[
|
||||
"-f", # Force overwriting
|
||||
"-e", # Don't generate empty files
|
||||
"-M", # Put module documentation before submodule documentation
|
||||
"--no-toc", # Don't create a table of contents file
|
||||
"--separate", # Put documentation for each module in its own page
|
||||
"--module-first", # Module documentation before submodule documentation
|
||||
"--implicit-namespaces", # Added: Handle implicit namespace packages
|
||||
"-o",
|
||||
output_dir,
|
||||
source_dir,
|
||||
]
|
||||
+ excludes
|
||||
)
|
||||
|
||||
logger.info("API documentation generated successfully!")
|
||||
|
||||
# Process generated RST files to update titles
|
||||
for rst_file in Path(output_dir).glob("**/*.rst"): # Changed to recursive glob
|
||||
content = rst_file.read_text()
|
||||
lines = content.split("\n")
|
||||
|
||||
# Find and clean up the title
|
||||
if lines and "=" in lines[1]: # Title is typically the first line
|
||||
old_title = lines[0]
|
||||
new_title = clean_title(old_title)
|
||||
content = content.replace(old_title, new_title)
|
||||
rst_file.write_text(content)
|
||||
logger.info(f"Updated title: {old_title} -> {new_title}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error generating API documentation: {e}", exc_info=True)
|
||||
|
||||
|
||||
# Run module verification
|
||||
verify_modules()
|
||||
@@ -1,77 +0,0 @@
|
||||
Pipecat API Reference Docs
|
||||
==========================
|
||||
|
||||
Welcome to Pipecat's API reference documentation!
|
||||
|
||||
Pipecat is an open source framework for building voice and multimodal assistants.
|
||||
It provides a flexible pipeline architecture for connecting various AI services,
|
||||
audio processing, and transport layers.
|
||||
|
||||
Quick Links
|
||||
-----------
|
||||
|
||||
* `GitHub Repository <https://github.com/pipecat-ai/pipecat>`_
|
||||
* `Website <https://pipecat.ai>`_
|
||||
|
||||
API Reference
|
||||
-------------
|
||||
|
||||
Core Components
|
||||
~~~~~~~~~~~~~~~
|
||||
|
||||
* :mod:`Frames <pipecat.frames>`
|
||||
* :mod:`Processors <pipecat.processors>`
|
||||
* :mod:`Pipeline <pipecat.pipeline>`
|
||||
|
||||
Audio Processing
|
||||
~~~~~~~~~~~~~~~~
|
||||
|
||||
* :mod:`Audio <pipecat.audio>`
|
||||
|
||||
Services
|
||||
~~~~~~~~
|
||||
|
||||
* :mod:`Services <pipecat.services>`
|
||||
|
||||
Transport & Serialization
|
||||
~~~~~~~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
* :mod:`Transports <pipecat.transports>`
|
||||
* :mod:`Local <pipecat.transports.local>`
|
||||
* :mod:`Network <pipecat.transports.network>`
|
||||
* :mod:`Services <pipecat.transports.services>`
|
||||
* :mod:`Serializers <pipecat.serializers>`
|
||||
|
||||
Utilities
|
||||
~~~~~~~~~
|
||||
|
||||
* :mod:`Clocks <pipecat.clocks>`
|
||||
* :mod:`Metrics <pipecat.metrics>`
|
||||
* :mod:`Sync <pipecat.sync>`
|
||||
* :mod:`Transcriptions <pipecat.transcriptions>`
|
||||
* :mod:`Utils <pipecat.utils>`
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 3
|
||||
:caption: API Reference
|
||||
:hidden:
|
||||
|
||||
Audio <api/pipecat.audio>
|
||||
Clocks <api/pipecat.clocks>
|
||||
Frames <api/pipecat.frames>
|
||||
Metrics <api/pipecat.metrics>
|
||||
Pipeline <api/pipecat.pipeline>
|
||||
Processors <api/pipecat.processors>
|
||||
Serializers <api/pipecat.serializers>
|
||||
Services <api/pipecat.services>
|
||||
Sync <api/pipecat.sync>
|
||||
Transcriptions <api/pipecat.transcriptions>
|
||||
Transports <api/pipecat.transports>
|
||||
Utils <api/pipecat.utils>
|
||||
|
||||
Indices and tables
|
||||
==================
|
||||
|
||||
* :ref:`genindex`
|
||||
* :ref:`modindex`
|
||||
* :ref:`search`
|
||||
@@ -1,35 +0,0 @@
|
||||
@ECHO OFF
|
||||
|
||||
pushd %~dp0
|
||||
|
||||
REM Command file for Sphinx documentation
|
||||
|
||||
if "%SPHINXBUILD%" == "" (
|
||||
set SPHINXBUILD=sphinx-build
|
||||
)
|
||||
set SOURCEDIR=.
|
||||
set BUILDDIR=_build
|
||||
|
||||
%SPHINXBUILD% >NUL 2>NUL
|
||||
if errorlevel 9009 (
|
||||
echo.
|
||||
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
|
||||
echo.installed, then set the SPHINXBUILD environment variable to point
|
||||
echo.to the full path of the 'sphinx-build' executable. Alternatively you
|
||||
echo.may add the Sphinx directory to PATH.
|
||||
echo.
|
||||
echo.If you don't have Sphinx installed, grab it from
|
||||
echo.https://www.sphinx-doc.org/
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if "%1" == "" goto help
|
||||
|
||||
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
|
||||
goto end
|
||||
|
||||
:help
|
||||
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
|
||||
|
||||
:end
|
||||
popd
|
||||
@@ -1,40 +0,0 @@
|
||||
# Sphinx dependencies
|
||||
sphinx>=8.1.3
|
||||
sphinx-rtd-theme
|
||||
sphinx-markdown-builder
|
||||
sphinx-autodoc-typehints
|
||||
toml
|
||||
|
||||
# Install all extras individually to ensure they're properly resolved
|
||||
pipecat-ai[anthropic]
|
||||
pipecat-ai[assemblyai]
|
||||
pipecat-ai[aws]
|
||||
pipecat-ai[azure]
|
||||
pipecat-ai[canonical]
|
||||
pipecat-ai[cartesia]
|
||||
pipecat-ai[daily]
|
||||
pipecat-ai[deepgram]
|
||||
pipecat-ai[elevenlabs]
|
||||
pipecat-ai[fal]
|
||||
pipecat-ai[fireworks]
|
||||
pipecat-ai[gladia]
|
||||
pipecat-ai[google]
|
||||
pipecat-ai[grok]
|
||||
pipecat-ai[groq]
|
||||
# pipecat-ai[krisp] # Mocked instead
|
||||
pipecat-ai[langchain]
|
||||
pipecat-ai[livekit]
|
||||
pipecat-ai[lmnt]
|
||||
pipecat-ai[local]
|
||||
pipecat-ai[moondream]
|
||||
pipecat-ai[nim]
|
||||
pipecat-ai[noisereduce]
|
||||
pipecat-ai[openai]
|
||||
# pipecat-ai[openpipe]
|
||||
# pipecat-ai[playht] # Mocked due to grpcio conflict with riva
|
||||
pipecat-ai[riva]
|
||||
pipecat-ai[silero]
|
||||
pipecat-ai[simli]
|
||||
pipecat-ai[soundfile]
|
||||
pipecat-ai[websocket]
|
||||
pipecat-ai[whisper]
|
||||
@@ -1,38 +0,0 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
# Configuration
|
||||
DOCS_DIR=$(pwd)
|
||||
PROJECT_ROOT=$(cd ../../ && pwd)
|
||||
TEST_DIR="/tmp/rtd-test-$(date +%Y%m%d_%H%M%S)"
|
||||
|
||||
echo "Creating test directory: $TEST_DIR"
|
||||
mkdir -p "$TEST_DIR"
|
||||
cd "$TEST_DIR"
|
||||
|
||||
# Create virtual environment
|
||||
python -m venv venv
|
||||
source venv/bin/activate
|
||||
|
||||
echo "Installing build dependencies..."
|
||||
pip install --upgrade pip wheel setuptools
|
||||
|
||||
echo "Installing documentation dependencies..."
|
||||
pip install -r "$DOCS_DIR/requirements.txt"
|
||||
|
||||
echo "Building documentation..."
|
||||
cd "$DOCS_DIR"
|
||||
sphinx-build -b html . "_build/html"
|
||||
|
||||
echo "Build complete. Check _build/html directory for output."
|
||||
|
||||
# Print summary
|
||||
echo -e "\n=== Build Summary ==="
|
||||
echo "Documentation: $DOCS_DIR/_build/html"
|
||||
echo "Test environment: $TEST_DIR"
|
||||
echo -e "\nTo view the documentation:"
|
||||
echo "open $DOCS_DIR/_build/html/index.html"
|
||||
|
||||
# Print installed packages for verification
|
||||
echo -e "\n=== Installed Packages ==="
|
||||
pip freeze | grep -E "sphinx|pipecat"
|
||||
@@ -96,6 +96,9 @@ Notable control frames:
|
||||
|
||||
## 7. Special Purpose Frames
|
||||
|
||||
### AppFrame
|
||||
Base class for application-specific custom frames.
|
||||
|
||||
### MetricsFrame
|
||||
Contains performance metrics data.
|
||||
|
||||
|
||||
@@ -54,33 +54,5 @@ TAVUS_API_KEY=...
|
||||
TAVUS_REPLICA_ID=...
|
||||
TAVUS_PERSONA_ID=...
|
||||
|
||||
# Simli
|
||||
SIMLI_API_KEY=...
|
||||
SIMLI_FACE_ID=...
|
||||
|
||||
# Krisp
|
||||
KRISP_MODEL_PATH=...
|
||||
|
||||
# DeepSeek
|
||||
DEEPSEEK_API_KEY=...
|
||||
|
||||
# Groq
|
||||
GROQ_API_KEY=...
|
||||
|
||||
# Grok
|
||||
GROK_API_KEY=...
|
||||
|
||||
# Together.ai
|
||||
TOGETHER_API_KEY=...
|
||||
|
||||
# Cerebras
|
||||
CEREBRAS_API_KEY=...
|
||||
|
||||
# Fish Audio
|
||||
FISH_API_KEY=...
|
||||
|
||||
# Assembly AI
|
||||
ASSEMBLYAI_API_KEY=...
|
||||
|
||||
# OpenRouter
|
||||
OPENROUTER_API_KEY=...
|
||||
#Krisp
|
||||
KRISP_MODEL_PATH=...
|
||||
@@ -39,10 +39,9 @@ Next, follow the steps in the README for each demo.
|
||||
| [Translation Chatbot](translation-chatbot) | Listens for user speech, then translates that speech to Spanish and speaks the translation back. Demonstrates multi-participant use-cases. | Deepgram, Azure, OpenAI, Daily, Daily Prebuilt UI |
|
||||
| [Moondream Chatbot](moondream-chatbot) | Demonstrates how to add vision capabilities to GPT4. **Note: works best with a GPU** | Deepgram, ElevenLabs, OpenAI, Moondream, Daily, Daily Prebuilt UI |
|
||||
| [Patient intake](patient-intake) | A chatbot that can call functions in response to user input. | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI |
|
||||
| [Phone Chatbot](phone-chatbot) | A chatbot that connects to PSTN/SIP phone calls, powered by Daily or Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
|
||||
| [Dialin Chatbot](dialin-chatbot) | A chatbot that connects to an incoming phone call from Daily or Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
|
||||
| [Twilio Chatbot](twilio-chatbot) | A chatbot that connects to an incoming phone call from Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
|
||||
| [studypal](studypal) | A chatbot to have a conversation about any article on the web | |
|
||||
| [WebSocket Chatbot Server](websocket-server) | A real-time websocket server that handles audio streaming and bot interactions with speech-to-text and text-to-speech capabilities. | Cartesia, Deepgram, OpenAI, Websockets |
|
||||
|
||||
> [!IMPORTANT]
|
||||
> These example projects use Daily as a WebRTC transport and can be joined using their hosted Prebuilt UI.
|
||||
|
||||
@@ -1,45 +0,0 @@
|
||||
# Bot ready signaling
|
||||
|
||||
A simple Pipecat example demonstrating how to handle signaling between the client and the bot,
|
||||
ensuring that the bot starts sending audio only when the client is available,
|
||||
thereby avoiding the risk of cutting off the beginning of the audio.
|
||||
|
||||
## Quick Start
|
||||
|
||||
### First, start the bot server:
|
||||
|
||||
1. Navigate to the server directory:
|
||||
```bash
|
||||
cd server
|
||||
```
|
||||
2. Create and activate a virtual environment:
|
||||
```bash
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate # On Windows: venv\Scripts\activate
|
||||
```
|
||||
3. Install requirements:
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
4. Copy env.example to .env and configure:
|
||||
- Add your API keys
|
||||
5. Start the server:
|
||||
```bash
|
||||
python server.py
|
||||
```
|
||||
|
||||
### Next, connect using the client app:
|
||||
|
||||
For client-side setup, refer to the [JavaScript Guide](client/javascript/README.md).
|
||||
|
||||
## Important Note
|
||||
|
||||
Ensure the bot server is running before using any client implementations.
|
||||
|
||||
## Requirements
|
||||
|
||||
- Python 3.10+
|
||||
- Node.js 16+ (for JavaScript)
|
||||
- Daily API key
|
||||
- Cartesia API key
|
||||
- Modern web browser with WebRTC support
|
||||
@@ -1,27 +0,0 @@
|
||||
# JavaScript Implementation
|
||||
|
||||
Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
|
||||
|
||||
## Setup
|
||||
|
||||
1. Run the bot server. See the [server README](../../README).
|
||||
|
||||
2. Navigate to the `client/javascript` directory:
|
||||
|
||||
```bash
|
||||
cd client/javascript
|
||||
```
|
||||
|
||||
3. Install dependencies:
|
||||
|
||||
```bash
|
||||
npm install
|
||||
```
|
||||
|
||||
4. Run the client app:
|
||||
|
||||
```
|
||||
npm run dev
|
||||
```
|
||||
|
||||
5. Visit http://localhost:5173 in your browser.
|
||||
@@ -1,34 +0,0 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>AI Chatbot</title>
|
||||
</head>
|
||||
|
||||
<body>
|
||||
<div class="container">
|
||||
<div class="status-bar">
|
||||
<div class="status">
|
||||
Status: <span id="connection-status">Disconnected</span>
|
||||
</div>
|
||||
<div class="controls">
|
||||
<button id="connect-btn">Connect</button>
|
||||
<button id="disconnect-btn" disabled>Disconnect</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<audio id="bot-audio" autoplay></audio>
|
||||
|
||||
<div class="debug-panel">
|
||||
<h3>Debug Info</h3>
|
||||
<div id="debug-log"></div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script type="module" src="/src/app.js"></script>
|
||||
<link rel="stylesheet" href="/src/style.css">
|
||||
</body>
|
||||
|
||||
</html>
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,20 +0,0 @@
|
||||
{
|
||||
"name": "client",
|
||||
"version": "1.0.0",
|
||||
"main": "index.js",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "vite build",
|
||||
"preview": "vite preview"
|
||||
},
|
||||
"keywords": [],
|
||||
"author": "",
|
||||
"license": "ISC",
|
||||
"description": "",
|
||||
"devDependencies": {
|
||||
"vite": "^6.0.9"
|
||||
},
|
||||
"dependencies": {
|
||||
"@daily-co/daily-js": "0.74.0"
|
||||
}
|
||||
}
|
||||
@@ -1,216 +0,0 @@
|
||||
/**
|
||||
* Copyright (c) 2024–2025, Daily
|
||||
*
|
||||
* SPDX-License-Identifier: BSD 2-Clause License
|
||||
*/
|
||||
|
||||
import Daily from "@daily-co/daily-js";
|
||||
|
||||
/**
|
||||
* ChatbotClient handles the connection and media management for a real-time
|
||||
* voice interaction with an AI bot.
|
||||
*/
|
||||
class ChatbotClient {
|
||||
constructor() {
|
||||
// Initialize client state
|
||||
this.dailyCallObject = null;
|
||||
this.setupDOMElements();
|
||||
this.setupEventListeners();
|
||||
}
|
||||
|
||||
/**
|
||||
* Set up references to DOM elements and create necessary media elements
|
||||
*/
|
||||
setupDOMElements() {
|
||||
// Get references to UI control elements
|
||||
this.connectBtn = document.getElementById('connect-btn');
|
||||
this.disconnectBtn = document.getElementById('disconnect-btn');
|
||||
this.statusSpan = document.getElementById('connection-status');
|
||||
this.debugLog = document.getElementById('debug-log');
|
||||
|
||||
// Create an audio element for bot's voice output
|
||||
this.botAudio = document.createElement('audio');
|
||||
this.botAudio.autoplay = true;
|
||||
this.botAudio.playsInline = true;
|
||||
document.body.appendChild(this.botAudio);
|
||||
}
|
||||
|
||||
/**
|
||||
* Set up event listeners for connect/disconnect buttons
|
||||
*/
|
||||
setupEventListeners() {
|
||||
this.connectBtn.addEventListener('click', () => this.connect());
|
||||
this.disconnectBtn.addEventListener('click', () => this.disconnect());
|
||||
}
|
||||
|
||||
/**
|
||||
* Add a timestamped message to the debug log
|
||||
*/
|
||||
log(message) {
|
||||
const entry = document.createElement('div');
|
||||
entry.textContent = `${new Date().toISOString()} - ${message}`;
|
||||
|
||||
// Add styling based on message type
|
||||
if (message.startsWith('User: ')) {
|
||||
entry.style.color = '#2196F3'; // blue for user
|
||||
} else if (message.startsWith('Bot: ')) {
|
||||
entry.style.color = '#4CAF50'; // green for bot
|
||||
}
|
||||
|
||||
this.debugLog.appendChild(entry);
|
||||
this.debugLog.scrollTop = this.debugLog.scrollHeight;
|
||||
console.log(message);
|
||||
}
|
||||
|
||||
/**
|
||||
* Update the connection status display
|
||||
*/
|
||||
updateStatus(status) {
|
||||
this.statusSpan.textContent = status;
|
||||
this.log(`Status: ${status}`);
|
||||
}
|
||||
|
||||
handleEventToConsole (evt) {
|
||||
this.log(`Received event: ${evt.action}`);
|
||||
};
|
||||
|
||||
/**
|
||||
* Set up listeners for track events (start/stop)
|
||||
* This handles new tracks being added during the session
|
||||
*/
|
||||
setupTrackListeners() {
|
||||
if (!this.dailyCallObject) return;
|
||||
|
||||
this.dailyCallObject.on("joined-meeting", () => {
|
||||
this.updateStatus('Connected');
|
||||
this.connectBtn.disabled = true;
|
||||
this.disconnectBtn.disabled = false;
|
||||
this.log('Client connected');
|
||||
});
|
||||
this.dailyCallObject.on("track-started", (evt) => {
|
||||
if (evt.track.kind === "audio" && evt.participant.local === false) {
|
||||
this.log("Audio track started.")
|
||||
this.setupAudioTrack(evt.track);
|
||||
}
|
||||
});
|
||||
this.dailyCallObject.on("track-stopped", this.handleEventToConsole.bind(this));
|
||||
this.dailyCallObject.on("participant-joined", this.handleEventToConsole.bind(this));
|
||||
this.dailyCallObject.on("participant-updated", this.handleEventToConsole.bind(this));
|
||||
this.dailyCallObject.on("participant-left", () => {
|
||||
// When the bot leaves, we are also disconnecting from the call
|
||||
this.disconnect()
|
||||
});
|
||||
this.dailyCallObject.on("left-meeting", () => {
|
||||
this.updateStatus('Disconnected');
|
||||
this.connectBtn.disabled = false;
|
||||
this.disconnectBtn.disabled = true;
|
||||
this.log('Client disconnected');
|
||||
});
|
||||
this.dailyCallObject.on("error", this.handleEventToConsole.bind(this));
|
||||
}
|
||||
|
||||
/**
|
||||
* Set up an audio track for playback
|
||||
* Handles both initial setup and track updates
|
||||
*/
|
||||
setupAudioTrack(track) {
|
||||
this.log(`Setting up audio track, track state: ${track.readyState}, muted: ${track.muted}`);
|
||||
|
||||
// Check if we're already playing this track
|
||||
if (this.botAudio.srcObject) {
|
||||
const oldTrack = this.botAudio.srcObject.getAudioTracks()[0];
|
||||
if (oldTrack?.id === track.id) return;
|
||||
}
|
||||
// Create a new MediaStream with the track and set it as the audio source
|
||||
this.botAudio.srcObject = new MediaStream([track]);
|
||||
this.botAudio.onplaying = async (event) => {
|
||||
this.log("onplaying")
|
||||
this.log("Will send the audio message to play the audio at the next tick")
|
||||
this.dailyCallObject.sendAppMessage("playable")
|
||||
}
|
||||
}
|
||||
|
||||
async fetchRoomInfo() {
|
||||
let connectUrl = '/connect'
|
||||
let res = await fetch(connectUrl, {
|
||||
method: "POST",
|
||||
mode: "cors",
|
||||
headers: new Headers({
|
||||
"Content-Type": "application/json"
|
||||
}),
|
||||
})
|
||||
if (res.ok) {
|
||||
return res.json();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize and connect to the bot
|
||||
* This sets up the RTVI client, initializes devices, and establishes the connection
|
||||
*/
|
||||
async connect() {
|
||||
try {
|
||||
// Initialize the client
|
||||
this.dailyCallObject = Daily.createCallObject({
|
||||
subscribeToTracksAutomatically: true,
|
||||
});
|
||||
|
||||
// Set up listeners for media track events
|
||||
this.setupTrackListeners();
|
||||
|
||||
this.log('Creating the bot...');
|
||||
let roomInfo = await this.fetchRoomInfo()
|
||||
|
||||
// Connect to the bot
|
||||
this.log('Connecting to bot...');
|
||||
// Only for making debugger easier
|
||||
window.callObject = this.dailyCallObject;
|
||||
await this.dailyCallObject.join({
|
||||
url: roomInfo.room_url,
|
||||
});
|
||||
|
||||
this.log('Connection complete');
|
||||
} catch (error) {
|
||||
// Handle any errors during connection
|
||||
this.log(`Error connecting: ${error.message}`);
|
||||
this.log(`Error stack: ${error.stack}`);
|
||||
this.updateStatus('Error');
|
||||
|
||||
// Clean up if there's an error
|
||||
if (this.dailyCallObject) {
|
||||
try {
|
||||
await this.dailyCallObject.leave();
|
||||
} catch (disconnectError) {
|
||||
this.log(`Error during disconnect: ${disconnectError.message}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Disconnect from the bot and clean up media resources
|
||||
*/
|
||||
async disconnect() {
|
||||
if (this.dailyCallObject) {
|
||||
try {
|
||||
// Disconnect the RTVI client
|
||||
await this.dailyCallObject.leave();
|
||||
await this.dailyCallObject.destroy();
|
||||
this.dailyCallObject = null;
|
||||
|
||||
// Clean up audio
|
||||
if (this.botAudio.srcObject) {
|
||||
this.botAudio.srcObject.getTracks().forEach((track) => track.stop());
|
||||
this.botAudio.srcObject = null;
|
||||
}
|
||||
} catch (error) {
|
||||
this.log(`Error disconnecting: ${error.message}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Initialize the client when the page loads
|
||||
window.addEventListener('DOMContentLoaded', () => {
|
||||
new ChatbotClient();
|
||||
});
|
||||
@@ -1,98 +0,0 @@
|
||||
body {
|
||||
margin: 0;
|
||||
padding: 20px;
|
||||
font-family: Arial, sans-serif;
|
||||
background-color: #f0f0f0;
|
||||
}
|
||||
|
||||
.container {
|
||||
max-width: 1200px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
.status-bar {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
padding: 10px;
|
||||
background-color: #fff;
|
||||
border-radius: 8px;
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
.controls button {
|
||||
padding: 8px 16px;
|
||||
margin-left: 10px;
|
||||
border: none;
|
||||
border-radius: 4px;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
#connect-btn {
|
||||
background-color: #4caf50;
|
||||
color: white;
|
||||
}
|
||||
|
||||
#disconnect-btn {
|
||||
background-color: #f44336;
|
||||
color: white;
|
||||
}
|
||||
|
||||
button:disabled {
|
||||
opacity: 0.5;
|
||||
cursor: not-allowed;
|
||||
}
|
||||
|
||||
.main-content {
|
||||
background-color: #fff;
|
||||
border-radius: 8px;
|
||||
padding: 20px;
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
.bot-container {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
}
|
||||
|
||||
#bot-video-container {
|
||||
width: 640px;
|
||||
height: 360px;
|
||||
background-color: #e0e0e0;
|
||||
border-radius: 8px;
|
||||
margin: 20px auto;
|
||||
overflow: hidden;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
#bot-video-container video {
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
object-fit: cover;
|
||||
}
|
||||
|
||||
.debug-panel {
|
||||
background-color: #fff;
|
||||
border-radius: 8px;
|
||||
padding: 20px;
|
||||
}
|
||||
|
||||
.debug-panel h3 {
|
||||
margin: 0 0 10px 0;
|
||||
font-size: 16px;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
#debug-log {
|
||||
height: 200px;
|
||||
overflow-y: auto;
|
||||
background-color: #f8f8f8;
|
||||
padding: 10px;
|
||||
border-radius: 4px;
|
||||
font-family: monospace;
|
||||
font-size: 12px;
|
||||
line-height: 1.4;
|
||||
}
|
||||
@@ -1,13 +0,0 @@
|
||||
import { defineConfig } from 'vite';
|
||||
|
||||
export default defineConfig({
|
||||
server: {
|
||||
proxy: {
|
||||
// Proxy /api requests to the backend server
|
||||
'/connect': {
|
||||
target: 'http://0.0.0.0:7860', // Replace with your backend URL
|
||||
changeOrigin: true,
|
||||
},
|
||||
},
|
||||
},
|
||||
});
|
||||
@@ -1,50 +0,0 @@
|
||||
# Bot ready signaling Server
|
||||
|
||||
A FastAPI server that manages bot instances and provide endpoint for Pipecat client connections.
|
||||
|
||||
## Endpoints
|
||||
|
||||
- `POST /connect` - Pipecat client connection endpoint
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Copy `env.example` to `.env` and configure:
|
||||
|
||||
```ini
|
||||
# Required API Keys
|
||||
DAILY_API_KEY= # Your Daily API key
|
||||
CARTESIA_API_KEY= # Your Cartesia API key
|
||||
|
||||
# Optional Configuration
|
||||
DAILY_API_URL= # Optional: Daily API URL (defaults to https://api.daily.co/v1)
|
||||
DAILY_SAMPLE_ROOM_URL= # Optional: Fixed room URL for development
|
||||
HOST= # Optional: Host address (defaults to 0.0.0.0)
|
||||
FAST_API_PORT= # Optional: Port number (defaults to 7860)
|
||||
```
|
||||
|
||||
## Running the Server
|
||||
|
||||
Set up and activate your virtual environment:
|
||||
|
||||
```bash
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate # On Windows: venv\Scripts\activate
|
||||
```
|
||||
|
||||
Install dependencies:
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
If you want to use the local version of `pipecat` in this repo rather than the last published version, also run:
|
||||
|
||||
```bash
|
||||
pip install --editable "../../../[daily,cartesia,openai]"
|
||||
```
|
||||
|
||||
Run the server:
|
||||
|
||||
```bash
|
||||
python server.py
|
||||
```
|
||||
@@ -1,3 +0,0 @@
|
||||
DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
|
||||
DAILY_API_KEY=
|
||||
CARTESIA_API_KEY=
|
||||
@@ -1,4 +0,0 @@
|
||||
python-dotenv
|
||||
fastapi[all]
|
||||
uvicorn
|
||||
pipecat-ai[daily,cartesia,openai]
|
||||
@@ -1,64 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import os
|
||||
from typing import Optional
|
||||
|
||||
import aiohttp
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
|
||||
|
||||
|
||||
async def configure(aiohttp_session: aiohttp.ClientSession):
|
||||
(url, token, _) = await configure_with_args(aiohttp_session)
|
||||
return (url, token)
|
||||
|
||||
|
||||
async def configure_with_args(
|
||||
aiohttp_session: aiohttp.ClientSession, parser: Optional[argparse.ArgumentParser] = None
|
||||
):
|
||||
if not parser:
|
||||
parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
|
||||
parser.add_argument(
|
||||
"-u", "--url", type=str, required=False, help="URL of the Daily room to join"
|
||||
)
|
||||
parser.add_argument(
|
||||
"-k",
|
||||
"--apikey",
|
||||
type=str,
|
||||
required=False,
|
||||
help="Daily API Key (needed to create an owner token for the room)",
|
||||
)
|
||||
|
||||
args, unknown = parser.parse_known_args()
|
||||
|
||||
url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
|
||||
key = args.apikey or os.getenv("DAILY_API_KEY")
|
||||
|
||||
if not url:
|
||||
raise Exception(
|
||||
"No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
|
||||
)
|
||||
|
||||
if not key:
|
||||
raise Exception(
|
||||
"No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
|
||||
)
|
||||
|
||||
daily_rest_helper = DailyRESTHelper(
|
||||
daily_api_key=key,
|
||||
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
|
||||
aiohttp_session=aiohttp_session,
|
||||
)
|
||||
|
||||
# Create a meeting token for the given room with an expiration 1 hour in
|
||||
# the future.
|
||||
expiry_time: float = 60 * 60
|
||||
|
||||
token = await daily_rest_helper.get_token(url, expiry_time)
|
||||
|
||||
return (url, token, args)
|
||||
@@ -1,147 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import os
|
||||
import subprocess
|
||||
from contextlib import asynccontextmanager
|
||||
from typing import Any, Dict
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from fastapi import FastAPI, HTTPException, Request
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
|
||||
|
||||
# Load environment variables from .env file
|
||||
load_dotenv(override=True)
|
||||
|
||||
# Dictionary to track bot processes: {pid: (process, room_url)}
|
||||
bot_procs = {}
|
||||
|
||||
# Store Daily API helpers
|
||||
daily_helpers = {}
|
||||
|
||||
|
||||
def cleanup():
|
||||
"""Cleanup function to terminate all bot processes.
|
||||
|
||||
Called during server shutdown.
|
||||
"""
|
||||
for entry in bot_procs.values():
|
||||
proc = entry[0]
|
||||
proc.terminate()
|
||||
proc.wait()
|
||||
|
||||
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
"""FastAPI lifespan manager that handles startup and shutdown tasks.
|
||||
|
||||
- Creates aiohttp session
|
||||
- Initializes Daily API helper
|
||||
- Cleans up resources on shutdown
|
||||
"""
|
||||
aiohttp_session = aiohttp.ClientSession()
|
||||
daily_helpers["rest"] = DailyRESTHelper(
|
||||
daily_api_key=os.getenv("DAILY_API_KEY", ""),
|
||||
daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
|
||||
aiohttp_session=aiohttp_session,
|
||||
)
|
||||
yield
|
||||
await aiohttp_session.close()
|
||||
cleanup()
|
||||
|
||||
|
||||
# Initialize FastAPI app with lifespan manager
|
||||
app = FastAPI(lifespan=lifespan)
|
||||
|
||||
# Configure CORS to allow requests from any origin
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_credentials=True,
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
|
||||
async def create_room_and_token() -> tuple[str, str]:
|
||||
"""Helper function to create a Daily room and generate an access token.
|
||||
|
||||
Returns:
|
||||
tuple[str, str]: A tuple containing (room_url, token)
|
||||
|
||||
Raises:
|
||||
HTTPException: If room creation or token generation fails
|
||||
"""
|
||||
room = await daily_helpers["rest"].create_room(DailyRoomParams())
|
||||
if not room.url:
|
||||
raise HTTPException(status_code=500, detail="Failed to create room")
|
||||
|
||||
token = await daily_helpers["rest"].get_token(room.url)
|
||||
if not token:
|
||||
raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
|
||||
|
||||
return room.url, token
|
||||
|
||||
|
||||
@app.post("/connect")
|
||||
async def bot_connect(request: Request) -> Dict[Any, Any]:
|
||||
"""Connect endpoint that creates a room and returns connection credentials.
|
||||
|
||||
This endpoint is called by client to establish a connection.
|
||||
|
||||
Returns:
|
||||
Dict[Any, Any]: Authentication bundle containing room_url and token
|
||||
|
||||
Raises:
|
||||
HTTPException: If room creation, token generation, or bot startup fails
|
||||
"""
|
||||
print("Creating room for RTVI connection")
|
||||
room_url, token = await create_room_and_token()
|
||||
print(f"Room URL: {room_url}")
|
||||
|
||||
# Start the bot process
|
||||
try:
|
||||
bot_file = "signalling_bot"
|
||||
proc = subprocess.Popen(
|
||||
[f"python3 -m {bot_file} -u {room_url} -t {token}"],
|
||||
shell=True,
|
||||
bufsize=1,
|
||||
cwd=os.path.dirname(os.path.abspath(__file__)),
|
||||
)
|
||||
bot_procs[proc.pid] = (proc, room_url)
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
|
||||
|
||||
# Return the authentication bundle in format expected by DailyTransport
|
||||
return {"room_url": room_url, "token": token}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
|
||||
# Parse command line arguments for server configuration
|
||||
default_host = os.getenv("HOST", "0.0.0.0")
|
||||
default_port = int(os.getenv("FAST_API_PORT", "7860"))
|
||||
|
||||
parser = argparse.ArgumentParser(description="Daily Travel Companion FastAPI server")
|
||||
parser.add_argument("--host", type=str, default=default_host, help="Host address")
|
||||
parser.add_argument("--port", type=int, default=default_port, help="Port number")
|
||||
parser.add_argument("--reload", action="store_true", help="Reload code on change")
|
||||
|
||||
config = parser.parse_args()
|
||||
|
||||
# Start the FastAPI server
|
||||
uvicorn.run(
|
||||
"server:app",
|
||||
host=config.host,
|
||||
port=config.port,
|
||||
reload=config.reload,
|
||||
)
|
||||
@@ -1,95 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
from dataclasses import dataclass
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame, TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
@dataclass
|
||||
class SilenceFrame(OutputAudioRawFrame):
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
sample_rate: int,
|
||||
duration: float,
|
||||
):
|
||||
# Initialize the parent class with the silent frame's data
|
||||
super().__init__(
|
||||
audio=self.create_silent_audio_frame(sample_rate, 1, duration).audio,
|
||||
sample_rate=sample_rate,
|
||||
num_channels=1,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def create_silent_audio_frame(
|
||||
sample_rate: int, num_channels: int, duration: float
|
||||
) -> AudioRawFrame:
|
||||
"""Create an AudioRawFrame containing silence."""
|
||||
frame_size = num_channels * 2 # 2 bytes per sample for 16-bit audio
|
||||
total_frames = int(sample_rate * duration)
|
||||
total_bytes = total_frames * frame_size
|
||||
silent_audio = bytes(total_bytes) # Create a byte array filled with zeros
|
||||
return AudioRawFrame(audio=silent_audio, sample_rate=sample_rate, num_channels=num_channels)
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
|
||||
)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
|
||||
)
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
task = PipelineTask(Pipeline([tts, transport.output()]))
|
||||
|
||||
# Register an event handler so we can play the audio when we receive a specific message
|
||||
@transport.event_handler("on_app_message")
|
||||
async def on_app_message(transport, message, sender):
|
||||
logger.debug(f"Received app message: {message} - {sender}")
|
||||
if "playable" not in message:
|
||||
return
|
||||
await task.queue_frames(
|
||||
[
|
||||
SilenceFrame(
|
||||
sample_rate=task.params.audio_out_sample_rate,
|
||||
duration=0.5,
|
||||
),
|
||||
TTSSpeakFrame(f"Hello there, how are you doing today ?"),
|
||||
EndFrame(),
|
||||
]
|
||||
)
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -15,7 +15,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -65,6 +65,7 @@ async def main():
|
||||
# English
|
||||
#
|
||||
voice_id="cgSgspJ2msm6clMCkdW9",
|
||||
aiohttp_session=session,
|
||||
#
|
||||
# Spanish
|
||||
#
|
||||
@@ -96,15 +97,15 @@ async def main():
|
||||
call completion, CanonicalMetrics will send the audio buffer to Canonical for
|
||||
analysis. Visit https://voice.canonical.chat to learn more.
|
||||
"""
|
||||
audio_buffer_processor = AudioBufferProcessor(num_channels=2)
|
||||
audio_buffer_processor = AudioBufferProcessor()
|
||||
canonical = CanonicalMetricsService(
|
||||
audio_buffer_processor=audio_buffer_processor,
|
||||
aiohttp_session=session,
|
||||
api_key=os.getenv("CANONICAL_API_KEY"),
|
||||
api_url=os.getenv("CANONICAL_API_URL"),
|
||||
call_id=str(uuid.uuid4()),
|
||||
assistant="pipecat-chatbot",
|
||||
assistant_speaks_first=True,
|
||||
context=context,
|
||||
)
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
@@ -123,20 +124,17 @@ async def main():
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await audio_buffer_processor.start_recording()
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
print(f"Participant left: {participant}")
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
@transport.event_handler("on_call_state_updated")
|
||||
async def on_call_state_updated(transport, state):
|
||||
if state == "left":
|
||||
# Here we don't want to cancel, we just want to finish sending
|
||||
# whatever is queued, so we use an EndFrame().
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -53,3 +53,4 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
|
||||
token = await daily_rest_helper.get_token(url, expiry_time)
|
||||
|
||||
return (url, token)
|
||||
return (url, token)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,23 +1,22 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import datetime
|
||||
import io
|
||||
import os
|
||||
import sys
|
||||
import wave
|
||||
|
||||
import aiofiles
|
||||
import aiohttp
|
||||
import datetime
|
||||
import wave
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -33,17 +32,15 @@ logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def save_audio(audio: bytes, sample_rate: int, num_channels: int):
|
||||
if len(audio) > 0:
|
||||
async def save_audio(audiobuffer):
|
||||
if audiobuffer.has_audio():
|
||||
merged_audio = audiobuffer.merge_audio_buffers()
|
||||
filename = f"conversation_recording{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.wav"
|
||||
with io.BytesIO() as buffer:
|
||||
with wave.open(buffer, "wb") as wf:
|
||||
wf.setsampwidth(2)
|
||||
wf.setnchannels(num_channels)
|
||||
wf.setframerate(sample_rate)
|
||||
wf.writeframes(audio)
|
||||
async with aiofiles.open(filename, "wb") as file:
|
||||
await file.write(buffer.getvalue())
|
||||
with wave.open(filename, "wb") as wf:
|
||||
wf.setnchannels(2)
|
||||
wf.setsampwidth(2)
|
||||
wf.setframerate(audiobuffer._sample_rate)
|
||||
wf.writeframes(merged_audio)
|
||||
print(f"Merged audio saved to {filename}")
|
||||
else:
|
||||
print("No audio data to save")
|
||||
@@ -82,6 +79,7 @@ async def main():
|
||||
# English
|
||||
#
|
||||
voice_id="cgSgspJ2msm6clMCkdW9",
|
||||
aiohttp_session=session,
|
||||
#
|
||||
# Spanish
|
||||
#
|
||||
@@ -108,10 +106,7 @@ async def main():
|
||||
context = OpenAILLMContext(messages)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
# NOTE: Watch out! This will save all the conversation in memory. You
|
||||
# can pass `buffer_size` to get periodic callbacks.
|
||||
audiobuffer = AudioBufferProcessor()
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # microphone
|
||||
@@ -126,20 +121,16 @@ async def main():
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@audiobuffer.event_handler("on_audio_data")
|
||||
async def on_audio_data(buffer, audio, sample_rate, num_channels):
|
||||
await save_audio(audio, sample_rate, num_channels)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await audiobuffer.start_recording()
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
print(f"Participant left: {participant}")
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
await save_audio(audiobuffer)
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
aiofiles
|
||||
python-dotenv
|
||||
fastapi[all]
|
||||
uvicorn
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,21 +1,22 @@
|
||||
import argparse
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
import argparse
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.frames.frames import LLMMessagesFrame, EndFrame
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -75,17 +76,15 @@ async def main(room_url: str, token: str):
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
@transport.event_handler("on_call_state_updated")
|
||||
async def on_call_state_updated(transport, state):
|
||||
if state == "left":
|
||||
# Here we don't want to cancel, we just want to finish sending
|
||||
# whatever is queued, so we use an EndFrame().
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
@@ -1,27 +1,29 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import argparse
|
||||
import os
|
||||
import subprocess
|
||||
import os
|
||||
|
||||
from contextlib import asynccontextmanager
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from fastapi import FastAPI, HTTPException, Request
|
||||
from fastapi import FastAPI, Request, HTTPException
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from pipecat.transports.services.helpers.daily_rest import (
|
||||
DailyRESTHelper,
|
||||
DailyRoomObject,
|
||||
DailyRoomParams,
|
||||
DailyRoomProperties,
|
||||
DailyRoomParams,
|
||||
)
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
|
||||
|
||||
@@ -2,11 +2,12 @@ import os
|
||||
|
||||
import aiohttp
|
||||
import modal
|
||||
from bot import _voice_bot_process
|
||||
from fastapi import HTTPException
|
||||
from fastapi.responses import JSONResponse
|
||||
from loguru import logger
|
||||
|
||||
from bot import _voice_bot_process
|
||||
|
||||
MAX_SESSION_TIME = 15 * 60 # 15 minutes
|
||||
|
||||
app = modal.App("pipecat-modal")
|
||||
|
||||
@@ -5,15 +5,6 @@ import sys
|
||||
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 import CartesiaTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -21,6 +12,16 @@ logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def main(room_url: str, token: str):
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
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 import CartesiaTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
token,
|
||||
@@ -74,11 +75,11 @@ async def main(room_url: str, token: str):
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
python-dotenv==1.0.1
|
||||
modal==0.71.3
|
||||
pipecat-ai[daily,silero,cartesia,openai]==0.0.52
|
||||
fastapi==0.115.6
|
||||
aiohttp==3.11.11
|
||||
modal==0.65.48
|
||||
pipecat-ai[daily,silero,cartesia,openai]==0.0.48
|
||||
fastapi==0.115.4
|
||||
aiohttp==3.10.10
|
||||
85
examples/dialin-chatbot/README.md
Normal file
85
examples/dialin-chatbot/README.md
Normal file
@@ -0,0 +1,85 @@
|
||||
<div align="center">
|
||||
<img alt="pipecat" width="300px" height="auto" src="image.png">
|
||||
</div>
|
||||
|
||||
# Dialin example
|
||||
|
||||
Example project that demonstrates how to add phone number dialin to your Pipecat bots. We include examples for both Daily (`bot_daily.py`) and Twilio (`bot_twilio.py`), depending on who you want to use as a phone vendor.
|
||||
|
||||
- 🔁 Transport: Daily WebRTC
|
||||
- 💬 Speech-to-Text: Deepgram via Daily transport
|
||||
- 🤖 LLM: GPT4-o / OpenAI
|
||||
- 🔉 Text-to-Speech: ElevenLabs
|
||||
|
||||
#### Should I use Daily or Twilio as a vendor?
|
||||
|
||||
If you're starting from scratch, using Daily to provision phone numbers alongside Daily as a transport offers some convenience (such as automatic call forwarding.)
|
||||
|
||||
If you already have Twilio numbers and workflows that you want to connect to your Pipecat bots, there is some additional configuration required (you'll need to create a `on_dialin_ready` and use the Twilio client to trigger the forward.)
|
||||
|
||||
You can read more about this, as well as see respective walkthroughs in our docs.
|
||||
|
||||
## Setup
|
||||
|
||||
```shell
|
||||
# Install the requirements
|
||||
pip install -r requirements.txt
|
||||
|
||||
# Setup your env
|
||||
mv env.example .env
|
||||
```
|
||||
|
||||
## Using Daily numbers
|
||||
|
||||
Run `bot_runner.py` to handle incoming HTTP requests:
|
||||
|
||||
`python bot_runner.py --host localhost`
|
||||
|
||||
Then target the following URL:
|
||||
|
||||
`POST /daily_start_bot`
|
||||
|
||||
For more configuration options, please consult Daily's API documentation.
|
||||
|
||||
|
||||
## Using Twilio numbers
|
||||
|
||||
As above, but target the following URL:
|
||||
|
||||
`POST /twilio_start_bot`
|
||||
|
||||
For more configuration options, please consult Twilio's API documentation.
|
||||
|
||||
## Deployment example
|
||||
|
||||
A Dockerfile is included in this demo for convenience. Here is an example of how to build and deploy your bot to [fly.io](https://fly.io).
|
||||
|
||||
*Please note: This demo spawns agents as subprocesses for convenience / demonstration purposes. You would likely not want to do this in production as it would limit concurrency to available system resources. For more information on how to deploy your bots using VMs, refer to the Pipecat documentation.*
|
||||
|
||||
### Build the docker image
|
||||
|
||||
`docker build -t tag:project .`
|
||||
|
||||
### Launch the fly project
|
||||
|
||||
`mv fly.example.toml fly.toml`
|
||||
|
||||
`fly launch` (using the included fly.toml)
|
||||
|
||||
### Setup your secrets on Fly
|
||||
|
||||
Set the necessary secrets (found in `env.example`)
|
||||
|
||||
`fly secrets set DAILY_API_KEY=... OPENAI_API_KEY=... ELEVENLABS_API_KEY=... ELEVENLABS_VOICE_ID=...`
|
||||
|
||||
If you're using Twilio as a number vendor:
|
||||
|
||||
`fly secrets set TWILIO_ACCOUNT_SID=... TWILIO_AUTH_TOKEN=...`
|
||||
|
||||
### Deploy!
|
||||
|
||||
`fly deploy`
|
||||
|
||||
## Need to do something more advanced?
|
||||
|
||||
This demo covers the basics of bot telephony. If you want to know more about working with PSTN / SIP, please ping us on [Discord](https://discord.gg/pipecat).
|
||||
104
examples/dialin-chatbot/bot_daily.py
Normal file
104
examples/dialin-chatbot/bot_daily.py
Normal file
@@ -0,0 +1,104 @@
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
import argparse
|
||||
|
||||
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.frames.frames import LLMMessagesFrame, EndFrame
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport, DailyDialinSettings
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
daily_api_key = os.getenv("DAILY_API_KEY", "")
|
||||
daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
|
||||
|
||||
|
||||
async def main(room_url: str, token: str, callId: str, callDomain: str):
|
||||
# diallin_settings are only needed if Daily's SIP URI is used
|
||||
# If you are handling this via Twilio, Telnyx, set this to None
|
||||
# and handle call-forwarding when on_dialin_ready fires.
|
||||
diallin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
token,
|
||||
"Chatbot",
|
||||
DailyParams(
|
||||
api_url=daily_api_url,
|
||||
api_key=daily_api_key,
|
||||
dialin_settings=diallin_settings,
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
camera_out_enabled=False,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
transcription_enabled=True,
|
||||
),
|
||||
)
|
||||
|
||||
tts = ElevenLabsTTSService(
|
||||
api_key=os.getenv("ELEVENLABS_API_KEY", ""),
|
||||
voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are Chatbot, a friendly, helpful robot. 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, but keep your responses brief. Start by saying 'Oh, hello! Who dares dial me at this hour?!'.",
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
|
||||
parser.add_argument("-u", type=str, help="Room URL")
|
||||
parser.add_argument("-t", type=str, help="Token")
|
||||
parser.add_argument("-i", type=str, help="Call ID")
|
||||
parser.add_argument("-d", type=str, help="Call Domain")
|
||||
config = parser.parse_args()
|
||||
|
||||
asyncio.run(main(config.u, config.t, config.i, config.d))
|
||||
@@ -7,14 +7,14 @@ provisioning a room and starting a Pipecat bot in response.
|
||||
Refer to README for more information.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import aiohttp
|
||||
import os
|
||||
import argparse
|
||||
import subprocess
|
||||
|
||||
from contextlib import asynccontextmanager
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from fastapi import FastAPI, HTTPException, Request
|
||||
from fastapi import FastAPI, Request, HTTPException
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import JSONResponse, PlainTextResponse
|
||||
from twilio.twiml.voice_response import VoiceResponse
|
||||
@@ -22,11 +22,13 @@ from twilio.twiml.voice_response import VoiceResponse
|
||||
from pipecat.transports.services.helpers.daily_rest import (
|
||||
DailyRESTHelper,
|
||||
DailyRoomObject,
|
||||
DailyRoomParams,
|
||||
DailyRoomProperties,
|
||||
DailyRoomSipParams,
|
||||
DailyRoomParams,
|
||||
)
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
|
||||
@@ -73,29 +75,24 @@ action using the Twilio Client library.
|
||||
"""
|
||||
|
||||
|
||||
async def _create_daily_room(
|
||||
room_url, callId, callDomain=None, dialoutNumber=None, vendor="daily", detect_voicemail=False
|
||||
):
|
||||
async def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
|
||||
if not room_url:
|
||||
# Create base properties with SIP settings
|
||||
properties = DailyRoomProperties(
|
||||
sip=DailyRoomSipParams(
|
||||
display_name="dialin-user", video=False, sip_mode="dial-in", num_endpoints=1
|
||||
params = DailyRoomParams(
|
||||
properties=DailyRoomProperties(
|
||||
# Note: these are the default values, except for the display name
|
||||
sip=DailyRoomSipParams(
|
||||
display_name="dialin-user", video=False, sip_mode="dial-in", num_endpoints=1
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
# Only enable dialout if dialoutNumber is provided
|
||||
if dialoutNumber:
|
||||
properties.enable_dialout = True
|
||||
|
||||
params = DailyRoomParams(properties=properties)
|
||||
|
||||
print(f"Creating new room...")
|
||||
room: DailyRoomObject = await daily_helpers["rest"].create_room(params=params)
|
||||
|
||||
else:
|
||||
# Check passed room URL exist (we assume that it already has a sip set up!)
|
||||
try:
|
||||
print(f"Joining existing room: {room_url}")
|
||||
room: DailyRoomObject = await daily_helpers["rest"].get_room_from_url(room_url)
|
||||
except Exception:
|
||||
raise HTTPException(status_code=500, detail=f"Room not found: {room_url}")
|
||||
@@ -111,9 +108,7 @@ async def _create_daily_room(
|
||||
# Spawn a new agent, and join the user session
|
||||
# Note: this is mostly for demonstration purposes (refer to 'deployment' in docs)
|
||||
if vendor == "daily":
|
||||
bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {callId} -d {callDomain}{' -v' if detect_voicemail else ''}"
|
||||
if dialoutNumber:
|
||||
bot_proc += f" -o {dialoutNumber}"
|
||||
bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {callId} -d {callDomain}"
|
||||
else:
|
||||
bot_proc = f"python3 -m bot_twilio -u {room.url} -t {token} -i {callId} -s {room.config.sip_endpoint}"
|
||||
|
||||
@@ -184,18 +179,13 @@ async def daily_start_bot(request: Request) -> JSONResponse:
|
||||
if "test" in data:
|
||||
# Pass through any webhook checks
|
||||
return JSONResponse({"test": True})
|
||||
detect_voicemail = data.get("detectVoicemail", False)
|
||||
callId = data.get("callId", None)
|
||||
callDomain = data.get("callDomain", None)
|
||||
dialoutNumber = data.get("dialoutNumber", None)
|
||||
except Exception:
|
||||
raise HTTPException(
|
||||
status_code=500, detail="Missing properties 'callId', 'callDomain', or 'dialoutNumber'"
|
||||
)
|
||||
raise HTTPException(status_code=500, detail="Missing properties 'callId' or 'callDomain'")
|
||||
|
||||
room: DailyRoomObject = await _create_daily_room(
|
||||
room_url, callId, callDomain, dialoutNumber, "daily", detect_voicemail
|
||||
)
|
||||
print(f"CallId: {callId}, CallDomain: {callDomain}")
|
||||
room: DailyRoomObject = await _create_daily_room(room_url, callId, callDomain, "daily")
|
||||
|
||||
# Grab a token for the user to join with
|
||||
return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})
|
||||
@@ -1,21 +1,24 @@
|
||||
import argparse
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from twilio.rest import Client
|
||||
import argparse
|
||||
|
||||
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.frames.frames import LLMMessagesFrame, EndFrame
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from twilio.rest import Client
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -82,11 +85,11 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
@transport.event_handler("on_dialin_ready")
|
||||
async def on_dialin_ready(transport, cdata):
|
||||
|
Before Width: | Height: | Size: 19 KiB After Width: | Height: | Size: 19 KiB |
@@ -1,25 +1,27 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
|
||||
@@ -1,22 +1,25 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
|
||||
from pipecat.transports.base_transport import TransportParams
|
||||
from pipecat.transports.local.audio import LocalAudioTransport
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
@@ -25,7 +28,7 @@ logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def main():
|
||||
transport = LocalAudioTransport(LocalAudioTransportParams(audio_out_enabled=True))
|
||||
transport = LocalAudioTransport(TransportParams(audio_out_enabled=True))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
@@ -40,7 +43,7 @@ async def main():
|
||||
await asyncio.sleep(1)
|
||||
await task.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
|
||||
|
||||
runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
|
||||
runner = PipelineRunner()
|
||||
|
||||
await asyncio.gather(runner.run(task), say_something())
|
||||
|
||||
|
||||
@@ -4,9 +4,6 @@ import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from livekit import api
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.frames.frames import TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
@@ -15,6 +12,12 @@ from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.transports.services.livekit import LiveKitParams, LiveKitTransport
|
||||
|
||||
from livekit import api
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
|
||||
@@ -1,54 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.services.riva import FastPitchTTSService
|
||||
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, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
|
||||
)
|
||||
|
||||
tts = FastPitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
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):
|
||||
participant_name = participant.get("info", {}).get("userName", "")
|
||||
await task.queue_frames([TTSSpeakFrame(f"Aloha, {participant_name}!"), EndFrame()])
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,18 +1,14 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
@@ -21,6 +17,12 @@ from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
|
||||
@@ -1,25 +1,27 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import TextFrame
|
||||
from pipecat.frames.frames import EndFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -53,7 +55,7 @@ async def main():
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
@@ -1,17 +1,15 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
import tkinter as tk
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
import tkinter as tk
|
||||
|
||||
from pipecat.frames.frames import TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
@@ -21,6 +19,10 @@ from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.transports.base_transport import TransportParams
|
||||
from pipecat.transports.local.tk import TkLocalTransport
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
|
||||
@@ -1,64 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import EndFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.services.google import GoogleImageGenService
|
||||
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, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
None,
|
||||
"Show a still frame image",
|
||||
DailyParams(camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024),
|
||||
)
|
||||
|
||||
imagegen = GoogleImageGenService(
|
||||
api_key=os.getenv("GOOGLE_API_KEY"),
|
||||
)
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
task = PipelineTask(
|
||||
Pipeline([imagegen, transport.output()]), PipelineParams(enable_metrics=True)
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await task.queue_frame(TextFrame("a cat in the style of picasso"))
|
||||
await task.queue_frame(TextFrame("a dog in the style of picasso"))
|
||||
await task.queue_frame(TextFrame("a fish in the style of picasso"))
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -8,24 +8,27 @@
|
||||
# This example broken on latest pipecat and needs updating.
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import EndPipeFrame, LLMMessagesFrame, TextFrame
|
||||
from pipecat.pipeline.merge_pipeline import SequentialMergePipeline
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
|
||||
from pipecat.frames.frames import EndPipeFrame, LLMMessagesFrame, TextFrame
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.services.azure import AzureLLMService, AzureTTSService
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.transport_services import TransportServiceOutput
|
||||
from pipecat.services.transports.daily_transport import DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -51,6 +54,7 @@ async def main():
|
||||
)
|
||||
|
||||
elevenlabs_tts = ElevenLabsTTSService(
|
||||
aiohttp_session=session,
|
||||
api_key=os.getenv("ELEVENLABS_API_KEY"),
|
||||
voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
|
||||
)
|
||||
|
||||
@@ -1,21 +1,18 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
from dataclasses import dataclass
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
DataFrame,
|
||||
AppFrame,
|
||||
Frame,
|
||||
LLMFullResponseStartFrame,
|
||||
LLMMessagesFrame,
|
||||
@@ -25,13 +22,19 @@ from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.processors.aggregators.sentence import SentenceAggregator
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.processors.aggregators.sentence import SentenceAggregator
|
||||
from pipecat.services.cartesia import CartesiaHttpTTSService
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -39,7 +42,7 @@ logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
@dataclass
|
||||
class MonthFrame(DataFrame):
|
||||
class MonthFrame(AppFrame):
|
||||
month: str
|
||||
|
||||
def __str__(self):
|
||||
|
||||
@@ -1,25 +1,23 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
import tkinter as tk
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
import tkinter as tk
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
Frame,
|
||||
LLMMessagesFrame,
|
||||
OutputAudioRawFrame,
|
||||
TextFrame,
|
||||
TTSAudioRawFrame,
|
||||
URLImageRawFrame,
|
||||
LLMMessagesFrame,
|
||||
TextFrame,
|
||||
)
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
@@ -28,11 +26,15 @@ from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.processors.aggregators.sentence import SentenceAggregator
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.services.cartesia import CartesiaHttpTTSService
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.transports.base_transport import TransportParams
|
||||
from pipecat.transports.local.tk import TkLocalTransport, TkOutputTransport
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import Frame, MetricsFrame
|
||||
from pipecat.frames.frames import Frame, LLMMessagesFrame, MetricsFrame
|
||||
from pipecat.metrics.metrics import (
|
||||
LLMUsageMetricsData,
|
||||
ProcessingMetricsData,
|
||||
@@ -38,8 +38,6 @@ logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
class MetricsLogger(FrameProcessor):
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, MetricsFrame):
|
||||
for d in frame.data:
|
||||
if isinstance(d, TTFBMetricsData):
|
||||
@@ -49,7 +47,9 @@ class MetricsLogger(FrameProcessor):
|
||||
elif isinstance(d, LLMUsageMetricsData):
|
||||
tokens = d.value
|
||||
print(
|
||||
f"!!! MetricsFrame: {frame}, tokens: {tokens.prompt_tokens}, characters: {tokens.completion_tokens}"
|
||||
f"!!! MetricsFrame: {frame}, tokens: {
|
||||
tokens.prompt_tokens}, characters: {
|
||||
tokens.completion_tokens}"
|
||||
)
|
||||
elif isinstance(d, TTSUsageMetricsData):
|
||||
print(f"!!! MetricsFrame: {frame}, characters: {d.value}")
|
||||
@@ -113,11 +113,7 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,35 +1,33 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from PIL import Image
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import (
|
||||
BotStartedSpeakingFrame,
|
||||
BotStoppedSpeakingFrame,
|
||||
Frame,
|
||||
OutputImageRawFrame,
|
||||
TextFrame,
|
||||
)
|
||||
from pipecat.frames.frames import Frame, OutputImageRawFrame, SystemFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.cartesia import CartesiaHttpTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
from pipecat.transports.services.daily import DailyTransport
|
||||
|
||||
from pipecat.transports.services.daily import DailyParams
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
@@ -51,7 +49,7 @@ class ImageSyncAggregator(FrameProcessor):
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, BotStartedSpeakingFrame):
|
||||
if not isinstance(frame, SystemFrame) and direction == FrameDirection.DOWNSTREAM:
|
||||
await self.push_frame(
|
||||
OutputImageRawFrame(
|
||||
image=self._speaking_image_bytes,
|
||||
@@ -59,8 +57,7 @@ class ImageSyncAggregator(FrameProcessor):
|
||||
format=self._speaking_image_format,
|
||||
)
|
||||
)
|
||||
|
||||
elif isinstance(frame, BotStoppedSpeakingFrame):
|
||||
await self.push_frame(frame)
|
||||
await self.push_frame(
|
||||
OutputImageRawFrame(
|
||||
image=self._waiting_image_bytes,
|
||||
@@ -68,8 +65,8 @@ class ImageSyncAggregator(FrameProcessor):
|
||||
format=self._waiting_image_format,
|
||||
)
|
||||
)
|
||||
|
||||
await self.push_frame(frame)
|
||||
else:
|
||||
await self.push_frame(frame)
|
||||
|
||||
|
||||
async def main():
|
||||
@@ -91,7 +88,7 @@ async def main():
|
||||
),
|
||||
)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
tts = CartesiaHttpTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
|
||||
)
|
||||
@@ -116,24 +113,16 @@ async def main():
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
image_sync_aggregator,
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
image_sync_aggregator,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
@@ -141,10 +130,6 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([TextFrame(f"Hi there {participant_name}!")])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
@@ -1,27 +1,30 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.processors.audio.vad.silero import SileroVAD
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -89,11 +92,7 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,19 +1,16 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -22,6 +19,12 @@ from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -87,11 +90,7 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,6 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -77,25 +78,13 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
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()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -9,14 +9,6 @@ import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
|
||||
from langchain_community.chat_message_histories import ChatMessageHistory
|
||||
from langchain_core.chat_history import BaseChatMessageHistory
|
||||
from langchain_core.runnables.history import RunnableWithMessageHistory
|
||||
from langchain_openai import ChatOpenAI
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
@@ -31,6 +23,18 @@ from pipecat.processors.frameworks.langchain import LangchainProcessor
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
|
||||
from langchain_community.chat_message_histories import ChatMessageHistory
|
||||
from langchain_core.chat_history import BaseChatMessageHistory
|
||||
from langchain_core.runnables.history import RunnableWithMessageHistory
|
||||
from langchain_openai import ChatOpenAI
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from runner import configure
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
|
||||
@@ -101,15 +105,7 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
@@ -122,10 +118,6 @@ async def main():
|
||||
messages = [({"content": "Please briefly introduce yourself to the user."})]
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
@@ -1,116 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from deepgram import LiveOptions
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
BotInterruptionFrame,
|
||||
StopInterruptionFrame,
|
||||
UserStartedSpeakingFrame,
|
||||
UserStoppedSpeakingFrame,
|
||||
)
|
||||
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.deepgram import DeepgramSTTService, DeepgramTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
None,
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
),
|
||||
)
|
||||
|
||||
stt = DeepgramSTTService(
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
live_options=LiveOptions(vad_events=True, utterance_end_ms="1000"),
|
||||
)
|
||||
|
||||
tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
|
||||
|
||||
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, # STT
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@stt.event_handler("on_speech_started")
|
||||
async def on_speech_started(stt, *args, **kwargs):
|
||||
await task.queue_frames([BotInterruptionFrame(), UserStartedSpeakingFrame()])
|
||||
|
||||
@stt.event_handler("on_utterance_end")
|
||||
async def on_utterance_end(stt, *args, **kwargs):
|
||||
await task.queue_frames([StopInterruptionFrame(), UserStoppedSpeakingFrame()])
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([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())
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -9,12 +9,12 @@ import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from deepgram import LiveOptions
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -45,23 +45,7 @@ async def main():
|
||||
),
|
||||
)
|
||||
|
||||
# stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
stt = DeepgramSTTService(
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
# url=deepgram_url,
|
||||
live_options=LiveOptions(
|
||||
encoding="linear16",
|
||||
language="en-US",
|
||||
model="nova-3",
|
||||
channels=1,
|
||||
interim_results=True,
|
||||
# smart_format=smart_format,
|
||||
# endpointing=endpointing,
|
||||
vad_events=True,
|
||||
diarize=True,
|
||||
filler_words=True,
|
||||
),
|
||||
)
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
|
||||
|
||||
@@ -89,25 +73,13 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=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": "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()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -11,13 +11,14 @@ import sys
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
@@ -87,11 +88,7 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,103 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.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.openai import OpenAILLMService
|
||||
from pipecat.services.playht import PlayHTHttpTTSService
|
||||
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_out_enabled=True,
|
||||
transcription_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
)
|
||||
|
||||
tts = PlayHTHttpTTSService(
|
||||
user_id=os.getenv("PLAYHT_USER_ID"),
|
||||
api_key=os.getenv("PLAYHT_API_KEY"),
|
||||
voice_url="s3://voice-cloning-zero-shot/d9ff78ba-d016-47f6-b0ef-dd630f59414e/female-cs/manifest.json",
|
||||
)
|
||||
|
||||
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
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,6 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -90,11 +91,7 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,19 +1,16 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -21,6 +18,13 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.azure import AzureLLMService, AzureSTTService, AzureTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -81,26 +85,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -11,15 +11,15 @@ import sys
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.fish import FishAudioTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.openai import OpenAILLMService, OpenAITTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
@@ -38,16 +38,14 @@ async def main():
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
audio_out_sample_rate=24000,
|
||||
transcription_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
)
|
||||
|
||||
tts = FishAudioTTSService(
|
||||
api_key=os.getenv("FISH_API_KEY"),
|
||||
model="4ce7e917cedd4bc2bb2e6ff3a46acaa1", # Barack Obama
|
||||
)
|
||||
tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
|
||||
@@ -72,26 +70,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
@@ -1,109 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.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.openai import OpenAILLMService, OpenAISTTService, OpenAITTSService
|
||||
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_out_enabled=True,
|
||||
audio_out_sample_rate=24000,
|
||||
transcription_enabled=False,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
vad_audio_passthrough=True,
|
||||
),
|
||||
)
|
||||
|
||||
# You can use the OpenAI compatible API like Groq.
|
||||
# stt = OpenAISTTService(
|
||||
# base_url="https://api.groq.com/openai/v1",
|
||||
# api_key="gsk_***",
|
||||
# model="whisper-large-v3",
|
||||
# )
|
||||
stt = OpenAISTTService(api_key=os.getenv("OPENAI_API_KEY"), model="whisper-1")
|
||||
|
||||
tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
|
||||
|
||||
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, # STT
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,20 +1,16 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -23,6 +19,13 @@ from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.openpipe import OpenPipeLLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
import time
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -79,26 +82,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,19 +1,16 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import aiohttp
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -22,6 +19,12 @@ from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.xtts import XTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -47,6 +50,7 @@ async def main():
|
||||
tts = XTTSService(
|
||||
aiohttp_session=session,
|
||||
voice_id="Claribel Dervla",
|
||||
language="en",
|
||||
base_url="http://localhost:8000",
|
||||
)
|
||||
|
||||
@@ -73,26 +77,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,6 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -78,27 +79,19 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
# Register an event handler to exit the application when the user leaves.
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,19 +1,16 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -22,6 +19,12 @@ from pipecat.services.lmnt import LmntTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -38,6 +41,7 @@ async def main():
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
audio_out_sample_rate=24000,
|
||||
transcription_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
@@ -69,26 +73,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,6 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -89,10 +90,7 @@ async def main():
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
|
||||
),
|
||||
)
|
||||
|
||||
@@ -100,11 +98,7 @@ async def main():
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
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()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,11 +14,12 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.aws import PollyTTSService
|
||||
from pipecat.services.aws import AWSTTSService
|
||||
from pipecat.services.deepgram import DeepgramSTTService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
@@ -47,12 +48,12 @@ async def main():
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = PollyTTSService(
|
||||
tts = AWSTTSService(
|
||||
api_key=os.getenv("AWS_SECRET_ACCESS_KEY"),
|
||||
aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
|
||||
region=os.getenv("AWS_REGION"),
|
||||
voice_id="Amy",
|
||||
params=PollyTTSService.InputParams(engine="neural", language="en-GB", rate="1.05"),
|
||||
params=AWSTTSService.InputParams(engine="neural", language="en-GB", rate="1.05"),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
@@ -79,26 +80,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,12 +14,14 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.google import GoogleLLMService, GoogleSTTService, GoogleTTSService
|
||||
from pipecat.transcriptions.language import Language
|
||||
from pipecat.services.deepgram import DeepgramSTTService
|
||||
from pipecat.services.google import GoogleTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
@@ -38,22 +40,21 @@ async def main():
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
audio_out_sample_rate=24000,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
vad_audio_passthrough=True,
|
||||
),
|
||||
)
|
||||
|
||||
stt = GoogleSTTService(
|
||||
params=GoogleSTTService.InputParams(languages=Language.EN_US),
|
||||
)
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = GoogleTTSService(
|
||||
voice_id="en-US-Journey-F",
|
||||
params=GoogleTTSService.InputParams(language=Language.EN_US),
|
||||
voice_id="en-US-Neural2-J",
|
||||
params=GoogleTTSService.InputParams(language="en-US", rate="1.05"),
|
||||
)
|
||||
|
||||
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
|
||||
messages = [
|
||||
{
|
||||
@@ -77,26 +78,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,6 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -78,26 +79,14 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,40 +1,41 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
from dataclasses import dataclass
|
||||
|
||||
import aiohttp
|
||||
import google.ai.generativelanguage as glm
|
||||
|
||||
from dataclasses import dataclass
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
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 import CartesiaTTSService
|
||||
from pipecat.services.google import GoogleLLMService
|
||||
from pipecat.processors.frame_processor import FrameProcessor
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
from pipecat.frames.frames import (
|
||||
Frame,
|
||||
InputAudioRawFrame,
|
||||
LLMFullResponseEndFrame,
|
||||
LLMFullResponseStartFrame,
|
||||
LLMFullResponseEndFrame,
|
||||
InputAudioRawFrame,
|
||||
Frame,
|
||||
StartInterruptionFrame,
|
||||
TextFrame,
|
||||
TranscriptionFrame,
|
||||
UserStartedSpeakingFrame,
|
||||
UserStoppedSpeakingFrame,
|
||||
)
|
||||
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.frame_processor import FrameProcessor
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.google import GoogleLLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
@@ -216,7 +217,7 @@ async def main():
|
||||
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
|
||||
)
|
||||
|
||||
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
|
||||
llm = GoogleLLMService(model="gemini-1.5-flash-latest", api_key=os.getenv("GOOGLE_API_KEY"))
|
||||
|
||||
messages = [
|
||||
{
|
||||
@@ -264,10 +265,6 @@ async def main():
|
||||
# Kick off the conversation.
|
||||
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)
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -13,15 +13,19 @@ from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.filters.krisp_filter import KrispFilter
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.processors.aggregators.llm_response import (
|
||||
LLMAssistantResponseAggregator,
|
||||
LLMUserResponseAggregator,
|
||||
)
|
||||
from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
from pipecat.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.audio.filters.krisp_filter import KrispFilter
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
@@ -59,40 +63,28 @@ async def main():
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
tma_in = LLMUserResponseAggregator(messages)
|
||||
tma_out = LLMAssistantResponseAggregator(messages)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
stt, # STT
|
||||
context_aggregator.user(), # User responses
|
||||
tma_in, # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
tma_out, # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=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": "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()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,12 +14,13 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.rime import RimeTTSService
|
||||
from pipecat.services.rime import RimeHttpTTSService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
@@ -44,9 +45,10 @@ async def main():
|
||||
),
|
||||
)
|
||||
|
||||
tts = RimeTTSService(
|
||||
tts = RimeHttpTTSService(
|
||||
api_key=os.getenv("RIME_API_KEY", ""),
|
||||
voice_id="rex",
|
||||
params=RimeHttpTTSService.InputParams(reduce_latency=True),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
@@ -87,11 +89,7 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.cancel()
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,95 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.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.nim import NimLLMService
|
||||
from pipecat.services.riva import FastPitchTTSService, ParakeetSTTService
|
||||
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, _) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
None,
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
vad_audio_passthrough=True,
|
||||
),
|
||||
)
|
||||
|
||||
stt = ParakeetSTTService(api_key=os.getenv("NVIDIA_API_KEY"))
|
||||
|
||||
llm = NimLLMService(
|
||||
api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct"
|
||||
)
|
||||
|
||||
tts = FastPitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
|
||||
|
||||
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
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=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": "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())
|
||||
@@ -1,19 +1,20 @@
|
||||
from typing import Tuple
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import logging
|
||||
import os
|
||||
from typing import Tuple
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.processors.aggregators import SentenceAggregator
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
|
||||
from pipecat.transports.services.daily import DailyTransport
|
||||
from pipecat.services.azure import AzureLLMService, AzureTTSService
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.fal import FalImageGenService
|
||||
from pipecat.transports.services.daily import DailyTransport
|
||||
from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesFrame, TextFrame
|
||||
|
||||
from runner import configure
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
@@ -48,6 +49,7 @@ async def main():
|
||||
region=os.getenv("AZURE_SPEECH_REGION"),
|
||||
)
|
||||
tts2 = ElevenLabsTTSService(
|
||||
aiohttp_session=session,
|
||||
api_key=os.getenv("ELEVENLABS_API_KEY"),
|
||||
voice_id="jBpfuIE2acCO8z3wKNLl",
|
||||
)
|
||||
|
||||
@@ -1,17 +1,13 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
Frame,
|
||||
InputAudioRawFrame,
|
||||
@@ -21,9 +17,15 @@ from pipecat.frames.frames import (
|
||||
)
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
from pipecat.transports.services.daily import DailyTransport, DailyParams
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
@@ -61,6 +63,7 @@ async def main():
|
||||
"Test",
|
||||
DailyParams(
|
||||
audio_in_enabled=True,
|
||||
audio_in_sample_rate=24000,
|
||||
audio_out_enabled=True,
|
||||
camera_out_enabled=True,
|
||||
camera_out_is_live=True,
|
||||
@@ -77,9 +80,7 @@ async def main():
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
|
||||
)
|
||||
task = PipelineTask(pipeline)
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
@@ -1,17 +1,14 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
# Copyright (c) 2024, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import aiohttp
|
||||
import asyncio
|
||||
import sys
|
||||
import tkinter as tk
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
import tkinter as tk
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
Frame,
|
||||
@@ -22,12 +19,18 @@ from pipecat.frames.frames import (
|
||||
)
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.transports.base_transport import TransportParams
|
||||
from pipecat.transports.local.tk import TkLocalTransport
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
from runner import configure
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
@@ -62,7 +65,7 @@ async def main():
|
||||
tk_root.title("Local Mirror")
|
||||
|
||||
daily_transport = DailyTransport(
|
||||
room_url, token, "Test", DailyParams(audio_in_enabled=True)
|
||||
room_url, token, "Test", DailyParams(audio_in_enabled=True, audio_in_sample_rate=24000)
|
||||
)
|
||||
|
||||
tk_transport = TkLocalTransport(
|
||||
@@ -82,9 +85,7 @@ async def main():
|
||||
|
||||
pipeline = Pipeline([daily_transport.input(), MirrorProcessor(), tk_transport.output()])
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
|
||||
)
|
||||
task = PipelineTask(pipeline)
|
||||
|
||||
async def run_tk():
|
||||
while not task.has_finished():
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user