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Author SHA1 Message Date
Mark Backman
708ef71c96 Update python-compatibility workflow to include new user project check 2025-08-09 20:19:16 -04:00
355 changed files with 11162 additions and 22353 deletions

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@@ -25,7 +25,7 @@ jobs:
version: "latest"
- name: Set up Python
run: uv python install 3.12
run: uv python install 3.10
- name: Install system packages
run: |

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@@ -9,14 +9,14 @@ on:
paths: ['pyproject.toml']
jobs:
test-compatibility:
test-dev-environment:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ['3.10.18', '3.11.13', '3.12.11', '3.13.5']
name: Python ${{ matrix.python-version }}
name: Dev Environment - Python ${{ matrix.python-version }}
steps:
- name: Checkout code
uses: actions/checkout@v4
@@ -55,7 +55,69 @@ jobs:
--no-extra moondream \
--no-extra mlx-whisper
- name: Verify installation
- name: Verify dev installation
run: |
uv run python --version
uv run python -c "import pipecat; print('✅ Pipecat imports successfully')"
uv run python -c "import pipecat; print('✅ Dev environment - Pipecat imports successfully')"
test-user-experience:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ['3.10.18', '3.11.13', '3.12.11', '3.13.5']
name: User Experience - Python ${{ matrix.python-version }}
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Install system dependencies
run: |
sudo apt-get update
sudo apt-get install -y \
portaudio19-dev \
libcairo2-dev \
libgirepository1.0-dev \
pkg-config
- name: Install uv
uses: astral-sh/setup-uv@v4
with:
version: 'latest'
- name: Set up Python ${{ matrix.python-version }}
run: |
uv python install ${{ matrix.python-version }}
- name: Build local package
run: |
uv build
- name: Create test project
run: |
mkdir test-project
cd test-project
uv init --python ${{ matrix.python-version }}
- name: Test comprehensive extras with uv add (Python 3.10-3.12)
if: "!startsWith(matrix.python-version, '3.13.')"
run: |
cd test-project
# Use uv add with built wheel to leverage dependency management
uv add "../dist/pipecat_ai-"*".whl[anthropic,assemblyai,asyncai,aws,aws-nova-sonic,azure,cartesia,cerebras,deepseek,daily,deepgram,elevenlabs,fal,fireworks,fish,gladia,google,grok,groq,gstreamer,heygen,inworld,koala,langchain,livekit,lmnt,local,mcp,mem0,mlx-whisper,moondream,nim,neuphonic,noisereduce,openai,openpipe,openrouter,perplexity,playht,qwen,rime,riva,runner,sambanova,sentry,local-smart-turn,remote-smart-turn,silero,simli,soniox,soundfile,speechmatics,tavus,together,tracing,ultravox,webrtc,websocket,whisper]"
- name: Test Python 3.13 compatible extras with uv add
if: startsWith(matrix.python-version, '3.13.')
run: |
cd test-project
# Use uv add with built wheel and Python 3.13 compatible extras
uv add "../dist/pipecat_ai-"*".whl[anthropic,assemblyai,asyncai,aws,aws-nova-sonic,azure,cartesia,cerebras,deepseek,daily,deepgram,elevenlabs,fal,fireworks,fish,gladia,google,grok,groq,gstreamer,heygen,inworld,koala,langchain,livekit,lmnt,local,mcp,mem0,nim,neuphonic,noisereduce,openai,openpipe,openrouter,perplexity,playht,qwen,rime,riva,runner,sambanova,sentry,remote-smart-turn,silero,simli,soniox,soundfile,speechmatics,tavus,together,tracing,webrtc,websocket,whisper]"
- name: Verify user installation
run: |
cd test-project
uv run python --version
uv run python -c "import pipecat; print('✅ User experience - Pipecat imports successfully')"
# Test that basic functionality works
uv run python -c "from pipecat.pipeline.pipeline import Pipeline; print('✅ Pipeline import works')"

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@@ -23,12 +23,17 @@ jobs:
token: ${{ secrets.QUICKSTART_SYNC_TOKEN }}
path: quickstart-repo
- name: Sync files (excluding uv.lock and README.md)
- name: Sync files (excluding READMEs)
run: |
# Copy all files except uv.lock and README.md
# Copy code files only, skip READMEs
cp examples/quickstart/bot.py quickstart-repo/
cp examples/quickstart/requirements.txt quickstart-repo/
cp examples/quickstart/env.example quickstart-repo/
# Copy any other files that aren't README.md
find examples/quickstart -type f \
-not -name "README.md" \
-not -name "uv.lock" \
-not -name "*.md" \
-exec cp {} quickstart-repo/ \;
- name: Commit and push changes

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@@ -29,7 +29,7 @@ jobs:
version: "latest"
- name: Set up Python
run: uv python install 3.12
run: uv python install 3.10
- name: Install system packages
run: |

42
.github/workflows/update-lockfile.yaml vendored Normal file
View File

@@ -0,0 +1,42 @@
name: Update lockfile
on:
push:
paths:
- 'pyproject.toml'
branches:
- main
workflow_dispatch: # Allows manual triggering from GitHub UI
jobs:
update-lockfile:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
# This gives the workflow permission to push back to the repo
token: ${{ secrets.GITHUB_TOKEN }}
- name: Install uv
uses: astral-sh/setup-uv@v1
- name: Update lockfile
run: uv lock
- name: Check for changes
id: verify-changed-files
run: |
if [ -n "$(git status --porcelain)" ]; then
echo "changed=true" >> $GITHUB_OUTPUT
else
echo "changed=false" >> $GITHUB_OUTPUT
fi
- name: Commit lockfile
if: steps.verify-changed-files.outputs.changed == 'true'
run: |
git config --local user.email "action@github.com"
git config --local user.name "GitHub Action"
git add uv.lock
git commit -m "chore: update uv.lock after dependency changes"
git push

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@@ -5,518 +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).
## [0.0.83] - 2025-09-03
### Added
- Added new frames `InputTransportMessageUrgentFrame` and
`DailyInputTransportMessageUrgentFrame` for transport messages received from
external sources.
- Added `UserSpeakingFrame`. This will be sent upstream and downstream while VAD
detects the user is speaking.
- Expanded support for universal `LLMContext` to more LLM services. Using the
universal `LLMContext` and associated `LLMContextAggregatorPair` is a
pre-requisite for using `LLMSwitcher` to switch between LLMs at runtime.
Here are the newly-supported services:
- Azure
- Cerebras
- Deepseek
- Fireworks AI
- Google Vertex AI
- Grok
- Groq
- Mistral
- NVIDIA NIM
- Ollama
- OpenPipe
- OpenRouter
- Perplexity
- Qwen
- SambaNova
- Together.ai
- Added support for WhatsApp User-initiated Calls.
- Added new audio filter `AICFilter`, speech enhancement for improving VAD/STT
performance, no ONNX dependency.
See https://ai-coustics.com/sdk/
- Added a timeout around cancel input tasks to prevent indefinite hangs when
cancellation is swallowed by third-party code.
- Added `pipecat.extensions.ivr` for automated IVR system navigation with
configurable goals and conversation handling. Supports DTMF input, verbal
responses, and intelligent menu traversal.
Basic usage:
```python
from pipecat.extensions.ivr.ivr_navigator import IVRNavigator
# Create IVR navigator with your goal
ivr_navigator = IVRNavigator(
llm=llm_service,
ivr_prompt="Navigate to billing department to dispute a charge"
)
# Handle different outcomes
@ivr_navigator.event_handler("on_conversation_detected")
async def on_conversation(processor, conversation_history):
# Switch to normal conversation mode
pass
@ivr_navigator.event_handler("on_ivr_status_changed")
async def on_ivr_status(processor, status):
if status == IVRStatus.COMPLETED:
# End pipeline, transfer call, or start bot conversation
elif status == IVRStatus.STUCK:
# Handle navigation failure
```
- `BaseOutputTransport` now implements `write_dtmf()` by loading DTMF audio and
sending it through the transport. This makes sending DTMF generic across all
output transports.
- Added new config parameters to `GladiaSTTService`.
- PreProcessingConfig > `audio_enhancer` to enhance audio quality.
- CustomVocabularyItem > `pronunciations` and `language` to specify special pronunciations and in which language it will be pronounced.
## Unreleased
### Changed
- `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` are also pushed
upstream.
- `ParallelPipeline` now waits for `CancelFrame` to finish in all branches
before pushing it downstream.
- Added `sip_codecs` to the `DailyRoomSipParams`.
- Updated the `configure()` function in `pipecat.runner.daily` to include new
args to create SIP-enabled rooms. Additionally, added new args to control the
room and token expiration durations.
- `pipecat.frames.frames.KeypadEntry` is deprecated and has been moved to
`pipecat.audio.dtmf.types.KeypadEntry`.
- Updated `RimeTTSService`'s flush_audio message to conform with Rime's official API.
- Updated the default model for `CerebrasLLMService` to GPT-OSS-120B.
### Removed
- Remove `StopInterruptionFrame`. This was a legacy frame that was not being
used really anywhere and it didn't provide any useful meaning. It was only
pushed after `UserStoppedSpeakingFrame`, so developers can just use
`UserStoppedSpeakingFrame`.
- `DailyTransport.write_dtmf()` has been removed in favor of the generic
`BaseOutputTransport.write_dtmf()`.
- Remove deprecated `DailyTransport.send_dtmf()`.
### Deprecated
- Transports have been re-organized.
```
pipecat.transports.network.small_webrtc -> pipecat.transports.smallwebrtc.transport
pipecat.transports.network.webrtc_connection -> pipecat.transports.smallwebrtc.connection
pipecat.transports.network.websocket_client -> pipecat.transports.websocket.client
pipecat.transports.network.websocket_server -> pipecat.transports.websocket.server
pipecat.transports.network.fastapi_websocket -> pipecat.transports.websocket.fastapi
pipecat.transports.services.daily -> pipecat.transports.daily.transport
pipecat.transports.services.helpers.daily_rest -> pipecat.transports.daily.utils
pipecat.transports.services.livekit -> pipecat.transports.livekit.transport
pipecat.transports.services.tavus -> pipecat.transports.tavus.transport
```
- `pipecat.frames.frames.KeypadEntry` is deprecated use
`pipecat.audio.dtmf.types.KeypadEntry` instead.
### Fixed
- Fixed an issue where messages received from the transport were always being resent.
- Fixed `SmallWebRTCTransport` to not use `mid` to decide if the transceiver should
be `sendrecv` or not.
- Fixed an issue where Deepgram swallowed `asyncio.CancelledError` during
disconnect, preventing tasks from being cancelled.
- Fixed an issue where `PipelineTask` was not cleaning up the observers.
### Performance
- Reduced latency and improved memory performance in `Mem0MemoryService`.
## [0.0.82] - 2025-08-28
### Added
- Added a new `LLMRunFrame` to trigger an LLM response:
```python
await task.queue_frames([LLMRunFrame()])
```
This replaces `OpenAILLMContextFrame`, which youd previously typically use
like this:
```python
await task.queue_frames([context_aggregator.user().get_context_frame()])
```
Use this way of kicking off your conversation when youve already initialized
your context and are simply instructing the bot when to go:
```python
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
# ...
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
# Kick off the conversation.
await task.queue_frames([LLMRunFrame()])
```
Note that if you want to add new messages when kicking off the conversation,
you could use `LLMMessagesAppendFrame` with `run_llm=True` instead:
```python
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
# Kick off the conversation.
await task.queue_frames([LLMMessagesAppendFrame(new_messages, run_llm=True)])
```
In the rare case you dont have a context aggregator in your pipeline, then
you may continue using a context frame.
- Added support for switching between audio+text to text-only modes within the
same pipeline. This is done by pushing
`LLMConfigureOutputFrame(skip_tts=True)` to enter text-only mode, and
disabling it to return to audio+text. The LLM will still generate tokens and
add them to the context, but they will not be sent to TTS.
- Added `skip_tts` field to `TextFrame`. This lets a text frame bypass TTS while
still being included in the LLM context. Useful for cases like structured text
that isnt meant to be spoken but should still contribute to context.
- Added a `cancel_timeout_secs` argument to `PipelineTask` which defines how
long the pipeline has to complete cancellation. When `PipelineTask.cancel()`
is called, a `CancelFrame` is pushed through the pipeline and must reach the
end. If it does not reach the end within the specified time, a warning is
shown and the wait is aborted.
- Added a new "universal" (LLM-agnostic) `LLMContext` and accompanying
`LLMContextAggregatorPair`, which will eventually replace `OpenAILLMContext`
(and the other under-the-hood contexts) and the other context aggregators.
The new universal `LLMContext` machinery allows a single context to be shared
between different LLMs, enabling runtime LLM switching and scenarios like
failover.
From the developer's point of view, switching to using the new universal
context machinery will usually be a matter of going from this:
```python
context = OpenAILLMContext(messages, tools)
context_aggregator = llm.create_context_aggregator(context)
```
To this:
```python
context = LLMContext(messages, tools)
context_aggregator = LLMContextAggregatorPair(context)
```
To start, the universal `LLMContext` is supported with the following LLM
services:
- `OpenAILLMService`
- `GoogleLLMService`
- Added a new `LLMSwitcher` class to enable runtime LLM switching, built atop a
new generic `ServiceSwitcher`.
Switchers take a switching strategy. The first available strategy is
`ServiceSwitcherStrategyManual`.
To switch LLMs at runtime, the LLMs must be sharing one instance of the new
universal `LLMContext` (see above bullet).
```python
# Instantiate your LLM services
llm_openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
llm_google = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
# Instantiate a switcher
# (ServiceSwitcherStrategyManual defaults to OpenAI, as it's first in the list)
llm_switcher = LLMSwitcher(
llms=[llm_openai, llm_google], strategy_type=ServiceSwitcherStrategyManual
)
# Create your pipeline
pipeline = Pipeline(
[
transport.input(),
stt,
context_aggregator.user(),
llm_switcher,
tts,
transport.output(),
context_aggregator.assistant(),
]
)
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
# ...
# Whenever is appropriate, switch LLMs!
await task.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
```
- Added an `LLMService.run_inference()` method to LLM services to enable
direct, out-of-band (i.e. out-of-pipeline) inference.
### Changed
- Updated `daily-python` to 0.19.8.
- `PipelineTask` now waits for `StartFrame` to reach the end of the pipeline
before pushing any other frames.
- Updated `CartesiaTTSService` and `CartesiaHttpTTSService` to align with
Cartesia's changes for the `speed` parameter. It now takes only an enum of
`slow`, `normal`, or `fast`.
- Added support to `AWSBedrockLLMService` for setting authentication
credentials through environment variables.
- Updated `SarvamTTSService` to use WebSocket streaming for real-time audio
generation with multiple Indian languages, with HTTP support still available
via `SarvamHttpTTSService`.
### Fixed
- Fixed an RTVI issue that was causing frames to be pushed before pipeline was
properly initialized.
- Fixed some `get_messages_for_logging()` that were returning a JSON string
instead of a list.
- Fixed a `DailyTransport` issue that prevented DTMF tones from being sent.
- Fixed a missing import in `SentryMetrics`.
- Fixed `AWSPollyTTSService` to support AWS credential provider chain (IAM
roles, IRSA, instance profiles) instead of requiring explicit environment
variables.
- Fixed a `CartesiaTTSService` issue that was causing the application to hang
after Cartesia's 5 minutes timed out.
- Fixed an issue preventing `SpeechmaticsSTTService` from transcribing audio.
## [0.0.81] - 2025-08-25
### Added
- Added `pipecat.extensions.voicemail`, a module for detecting voicemail vs.
live conversation, primarily intended for use in outbound calling scenarios.
The voicemail module is optimized for text LLMs only.
- Added new frames to the `idle_timeout_frames` arg: `TranscriptionFrame`,
`InterimTranscriptionFrame`, `UserStartedSpeakingFrame`, and
`UserStoppedSpeakingFrame`. These additions serve as indicators of user
activity in the pipeline idle detection logic.
- Allow passing custom pipeline sink and source processors to a
`Pipeline`. Pipeline source and sink processors are used to know and control
what's coming in and out of a `Pipeline` processor.
- Added `FrameProcessor.pause_processing_system_frames()` and
`FrameProcessor.resume_processing_system_frames()`. These allow to pause and
resume the processing of system frame.
- Added new `on_process_frame()` observer method which makes it possible to know
when a frame is being processed.
- Added new `FrameProcessor.entry_processor()` method. This allows you to access
the first non-compound processor in a pipeline.
- Added `FrameProcessor` properties `processors`, `next` and `previous`.
- `ElevenLabsTTSService` now supports additional runtime changes to the `model`,
`language`, and `voice_settings` parameters.
- Added `apply_text_normalization` support to `ElevenLabsTTSService` and
`ElevenLabsHttpTTSService`.
- Added `MistralLLMService`, using Mistral's chat completion API.
- Added the ability to retry executing a chat completion after a timeout period
for `OpenAILLMService` and its subclasses, `AnthropicLLMService`, and
`AWSBedrockLLMService`. The LLM services accept new args:
`retry_timeout_secs` and `retry_on_timeout`. This feature is disabled by
default.
### Changed
- Updated `daily-python` to 0.19.7.
### Deprecated
- `FrameProcessor.wait_for_task()` is deprecated. Use `await task` or
`await asyncio.wait_for(task, timeout)` instead.
### Removed
- Watchdog timers have been removed. They were introduced in 0.0.72 to help
diagnose pipeline freezes. Unfortunately, they proved ineffective since they
required developers to use Pipecat-specific queues, iterators, and events to
correctly reset the timer, which limited their usefulness and added friction.
- Removed unused `FrameProcessor.set_parent()` and
`FrameProcessor.get_parent()`.
### Fixed
- Fixed an issue that would cause `PipelineRunner` and `PipelineTask` to not
handle external asyncio task cancellation properly.
- Added `SpeechmaticsSTTService` exception handling on connection and sending.
- Replaced `asyncio.wait_for()` for `wait_for2.wait_for()` for Python <
3.12. because of issues regarding task cancellation (i.e. cancellation is
never propagated).
See https://bugs.python.org/issue42130
- Fixed an `AudioBufferProcessor` issues that would cause audio overlap when
setting a max buffer size.
- Fixed an issue where `AsyncAITTSService` had very high latency in responding
by adding `force=true` when sending the flush command.
### Performance
- Improve `PipelineTask` performance by using direct mode processors and by
removing unnecessary tasks.
- Improve `ParallelPipeline` performance by using direct mode, by not
creating a task for each frame and every sub-pipeline and also by removing
other unnecessary tasks.
- `Pipeline` performance improvements by using direct mode.
### Other
- Added `14w-function-calling-mistal.py` using `MistralLLMService`.
- Added `13j-azure-transcription.py` using `AzureSTTService`.
## [0.0.80] - 2025-08-13
### Added
- Added `GeminiTTSService` which uses Google Gemini to generate TTS output. The
Gemini model can be prompted to insert styled speech to control the TTS
output.
- Added Exotel support to Pipecat's development runner. You can now connect
using the runner with `uv run bot.py -t exotel` and an ngrok connection to
HTTP port 7860.
- Added `enable_direct_mode` argument to `FrameProcessor`. The direct mode is
for processors which require very little I/O or compute resources, that is
processors that can perform their task almost immediately. These type of
processors don't need any of the internal tasks and queues usually created by
frame processors which means overall application performance might be slightly
increased. Use with care.
- Added TTFB metrics for `HeyGenVideoService` and `TavusVideoService`.
- Added `endpoint_id` parameter to `AzureSTTService`. ([Custom EndpointId](https://docs.azure.cn/en-us/ai-services/speech-service/how-to-recognize-speech?pivots=programming-language-python#use-a-custom-endpoint))
### Changed
- `WatchdogPriorityQueue` now requires the items to be inserted to always be
tuples and the size of the tuple needs to be specified in the constructor when
creating the queue with the `tuple_size` argument.
- Updated Moondream to revision `2025-01-09`.
- Updated `PlayHTHttpTTSService` to no longer use the `pyht` client to remove
compatibility issues with other packages. Now you can use the PlayHT HTTP
service with other services, like GoogleLLMService.
- Updated `pyproject.toml` to once again pin `numba` to `>=0.61.2` in order to
resolve package versioning issues.
- Updated the `STTMuteFilter` to include `VADUserStartedSpeakingFrame` and
`VADUserStoppedSpeakingFrame` in the list of frames to filter when the
filtering is on.
### Performance
- Improving the latency of the `HeyGenVideoService`.
- Improved some frame processors performance by using the new frame processor
direct mode. In direct mode a frame processor will process frames right away
avoiding the need for internal queues and tasks. This is useful for some
simple processors. For example, in processors that wrap other processors
(e.g. `Pipeline`, `ParallelPipeline`), we add one processor before and one
after the wrapped processors (internally, you will see them as sources and
sinks). These sources and sinks don't do any special processing and they
basically forward frames. So, for these simple processors we now enable the
new direct mode which avoids creating any internal tasks (and queues) and
therefore improves performance.
### Fixed
- Fixed an issue with the `BaseWhisperSTTService` where the language was
specified as an enum and not a string.
- Fixed an issue where `SmallWebRTCTransport` ended before TTS finished.
- Fixed an issue in `OpenAIRealtimeBetaLLMService` where specifying a `text`
`modalities` didn't result in text being outputted from the model.
- Added SSML reserved character escaping to `AzureBaseTTSService` to properly
handle special characters in text sent to Azure TTS. This fixes an issue
where characters like `&`, `<`, `>`, `"`, and `'` in LLM-generated text would
cause TTS failures.
- Fixed a `WatchdogPriorityQueue` issue that could cause an exception when
compating watchdog cancel sentinel items with other items in the queue.
- Fixed an issue that would cause system frames to not be processed with higher
priority than other frames. This could cause slower interruption times.
- Fixed an issue where retrying a websocket connection error would result in an
error.
### Other
- Add foundation example `19b-openai-realtime-beta-text.py`, showing how to use
`OpenAIRealtimeBetaLLMService` to output text to a TTS service.
- Add vision support to release evals so we can run the foundational examples 12
series.
- Added foundational example `15a-switch-languages.py` to release evals. It is
able to detect if we switched the language properly.
- Updated foundational examples to show how to enclose complex logic
(e.g. `ParallelPipeline`) into a single processor so the main pipeline becomes
simpler.
- Added `07n-interruptible-gemini.py`, demonstrating how to use
`GeminiTTSService`.
- Updated `15-switch-voices.py` and `15a-switch-languages.py` examples to show
how to enclose complex logic (e.g. `ParallelPipeline`) into a single processor
so the main pipeline becomes simpler.
## [0.0.79] - 2025-08-07

View File

@@ -31,23 +31,6 @@ git push origin your-branch-name
Our maintainers will review your PR, and once everything is good, your contributions will be merged!
## Dependency Management
This project uses [uv](https://docs.astral.sh/uv/) for dependency management. The `uv.lock` file is committed to ensure reproducible builds.
### Adding or Updating Dependencies
1. Edit `pyproject.toml` to add/update dependencies
2. Run `uv lock` to update the lockfile with new dependency resolution
3. Run `uv sync` to install the updated dependencies locally
4. Always commit both files together:
```bash
git add pyproject.toml uv.lock
git commit -m "feat: add new dependency for feature X"
```
**Important:** Never manually edit `uv.lock`. It's auto-generated by `uv lock`.
## Code Style and Documentation
### Python Code Style

View File

@@ -54,7 +54,7 @@ You can connect to Pipecat from any platform using our official SDKs:
| Category | Services |
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [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), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) |
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
@@ -62,7 +62,7 @@ You can connect to Pipecat from any platform using our official SDKs:
| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/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), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) |
| 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) |
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
@@ -114,8 +114,7 @@ You can get started with Pipecat running on your local machine, then move your a
### Prerequisites
**Minimum Python Version:** 3.10
**Recommended Python Version:** 3.12
**Python Version:** 3.10+
### Setup Steps

10
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@@ -0,0 +1,10 @@
# Pipecat Docs
## [Architecture Overview](architecture.md)
Learn about the thinking behind the framework's design.
## [A Frame's Progress](frame-progress.md)
See how a Frame is processed through a Transport, a Pipeline, and a series of Frame Processors.

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@@ -21,7 +21,6 @@ Quick Links
Adapters <api/pipecat.adapters>
Audio <api/pipecat.audio>
Clocks <api/pipecat.clocks>
Extensions <api/pipecat.extensions>
Frames <api/pipecat.frames>
Metrics <api/pipecat.metrics>
Observers <api/pipecat.observers>

17
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@@ -0,0 +1,17 @@
# Pipecat architecture guide
## Frames
Frames can represent discrete chunks of data, for instance a chunk of text, a chunk of audio, or an image. They can also be used to as control flow, for instance a frame that indicates that there is no more data available, or that a user started or stopped talking. They can also represent more complex data structures, such as a message array used for an LLM completion.
## FrameProcessors
Frame processors operate on frames. Every frame processor implements a `process_frame` method that consumes one frame and produces zero or more frames. Frame processors can do simple transforms, such as concatenating text fragments into sentences, or they can treat frames as input for an AI Service, and emit chat completions based on message arrays or transform text into audio or images.
## Pipelines
Pipelines are lists of frame processors linked together. Frame processors can push frames upstream or downstream to their peers. A very simple pipeline might chain an LLM frame processor to a text-to-speech frame processor, with a transport as an output.
## Transports
Transports provide input and output frame processors to receive or send frames respectively. For example, the `DailyTransport` does this with a WebRTC session joined to a Daily.co room.

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@@ -0,0 +1,46 @@
# A Frame's Progress
1. A user says “Hello, LLM” and the cloud transcription service delivers a transcription to the Transport.
![A transcript frame arrives](images/frame-progress-01.png)
2. The Transport places a Transcription frame in the Pipelines source queue.
![Frame in source queue](images/frame-progress-02.png)
3. The Pipeline passes the Transcription frame to the first Frame Processor in its list, the LLM User Message Aggregator.
![To UMA](images/frame-progress-03.png)
4. The LLM User Message Aggregator updates the LLM Context with a `{“user”: “Hello LLM”}` message.
![Update context](images/frame-progress-04.png)
5. The LLM User Message Aggregator yields an LLM Message Frame, containing the updated LLM Context. The Pipeline passes this frame to the LLM Frame Processor.
![Update context](images/frame-progress-05.png)
6. The LLM Frame Processor creates a streaming chat completion based on the LLM context and yields the first chunk of a response, Text Frame with the value “Hi, “. The Pipeline passes this frame to the TTS Frame Processor. The TTS Frame Processor aggregates this response but doesnt yield anything, yet, because its waiting for a full sentence.
![LLM yields Text](images/frame-progress-06.png)
7. The LLM Frame Processor yields another Text Frame with the value “there.”. The Pipeline passes this frame to the TTS Frame Processor.
![LLM yields more Text](images/frame-progress-07.png)
8. The TTS Frame Processor now has a full sentence, so it starts streaming audio based on “Hi, there.” It yields the first chunk of streaming audio as an Audio frame, which the Pipeline passes to the LLM Assistant Message Aggregator.
![TTS yields Audio](images/frame-progress-08.png)
9. The LLM Assistant Message Aggregator doesnt do anything with Audio frames, so it immediately yields the frame, unchanged. This is the convention for all Frame Processors: frames that the processor doesnt process should be immediately yielded.
![pass-through](images/frame-progress-09.png)
10. The Pipeline places the first Audio frame in its sink queue, which is being watched by the Transport. Since the frame is now in a queue, the Pipeline can continue processing other frames. Note that the source and sink queues form a sort of “boundary of concurrent processing” between a Pipeline and the outside world. In a Pipeline, Frames are processed sequentially; once a Frame is on a queue it can be processed in parallel with the frames being processed by the Pipeline. TODO: link to a more in-depth section about this.
![sink queue](images/frame-progress-10.png)
11. The TTS Frame Processor yields another Audio frame as the Transport transmits the first Audio frame.
![parallel audio](images/frame-progress-11.png)
12. As before, the LLM Assistant Message Aggregator immediately yields the Audio frame and the Pipeline places the Audio frame in the sink queue.
![sink queue 2](images/frame-progress-12.png)
13. The TTS Frame Processor has no more frames to yield. The LLM Frame Processor emits an LLM Response End Frame, which the Pipeline passes to the TTS Frame Processor.
![response end](images/frame-progress-13.png)
14. The TTS Frame Processor immediately yields the LLM Response End Frame, so the Pipeline passes it along to the LLM Assistant Message Aggregator. The LLM Assistant Message Aggregator updates the LLM Context with the full response from the LLM. TODO TODO: I realized I forgot that the TSS Frame Processor also yields the Text frames that the LLM emitted so that the LLM Assistant Message Aggregator could accumulate them, arrggh.
![response end](images/frame-progress-14.png)
15. The system is quiet, and waiting for the next message from the Transport.
![response end](images/frame-progress-15.png)

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@@ -0,0 +1,110 @@
# Understanding Different Frame Types in the Pipecat System
In the Pipecat system, frames are used to represent different types of data and control signals that flow through the pipeline. Understanding these frame types is crucial for working with the system effectively. This tutorial will cover the main categories of frames and their specific uses.
## 1. Base Frame Classes
### Frame
The `Frame` class is the base class for all frames. It includes:
- `id`: A unique identifier
- `name`: A descriptive name
- `pts`: Presentation timestamp (optional)
### DataFrame
`DataFrame` is a subclass of `Frame` and serves as a base for most data-carrying frames.
## 2. Audio Frames
### AudioRawFrame
Represents a chunk of audio with properties:
- `audio`: Raw audio data
- `sample_rate`: Audio sample rate
- `num_channels`: Number of audio channels
Subclasses include:
- `InputAudioRawFrame`: For audio from input sources
- `OutputAudioRawFrame`: For audio to be played by output devices
- `TTSAudioRawFrame`: For audio generated by Text-to-Speech services
## 3. Image Frames
### ImageRawFrame
Represents an image with properties:
- `image`: Raw image data
- `size`: Image dimensions
- `format`: Image format (e.g., JPEG, PNG)
Subclasses include:
- `InputImageRawFrame`: For images from input sources
- `OutputImageRawFrame`: For images to be displayed
- `UserImageRawFrame`: For images associated with a specific user
- `VisionImageRawFrame`: For images with associated text for description
- `URLImageRawFrame`: For images with an associated URL
### SpriteFrame
Represents an animated sprite, containing a list of `ImageRawFrame` objects.
## 4. Text and Transcription Frames
### TextFrame
Represents a chunk of text, used for various purposes in the pipeline.
### TranscriptionFrame
A specialized `TextFrame` for speech transcriptions, including:
- `user_id`: ID of the speaking user
- `timestamp`: When the transcription was generated
- `language`: Detected language of the speech
### InterimTranscriptionFrame
Similar to `TranscriptionFrame`, but for interim (not final) transcriptions.
## 5. LLM (Language Model) Frames
### LLMMessagesFrame
Contains a list of messages for an LLM service to process.
### LLMMessagesAppendFrame and LLMMessagesUpdateFrame
Used to modify the current context of LLM messages.
### LLMSetToolsFrame
Specifies tools (functions) available for the LLM to use.
### LLMEnablePromptCachingFrame
Controls prompt caching in certain LLMs.
## 6. System and Control Frames
### SystemFrame
Base class for system-level frames.
Important system frames include:
- `StartFrame`: Initiates a pipeline
- `CancelFrame`: Stops a pipeline immediately
- `ErrorFrame`: Notifies of errors (with `FatalErrorFrame` for unrecoverable errors)
- `EndTaskFrame` and `CancelTaskFrame`: Control pipeline tasks
- `StartInterruptionFrame` and `StopInterruptionFrame`: Indicate user speech for interruptions
### ControlFrame
Base class for control-flow frames.
Notable control frames:
- `EndFrame`: Signals the end of a pipeline
- `LLMFullResponseStartFrame` and `LLMFullResponseEndFrame`: Bracket LLM responses
- `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame`: Indicate user speech activity
- `BotStartedSpeakingFrame` and `BotStoppedSpeakingFrame`: Indicate bot speech activity
- `TTSStartedFrame` and `TTSStoppedFrame`: Bracket Text-to-Speech responses
## 7. Special Purpose Frames
### MetricsFrame
Contains performance metrics data.
### FunctionCallInProgressFrame and FunctionCallResultFrame
Used for handling LLM function (tool) calls.
### ServiceUpdateSettingsFrame
Base class for updating service settings, with specific subclasses for LLM, TTS, and STT services.
## Conclusion
Understanding these frame types is essential for working with the Pipecat system. Each frame type serves a specific purpose in the pipeline, whether it's carrying data (like audio or images), controlling the flow of the pipeline, or managing system-level operations. By using the appropriate frame types, you can effectively process and transmit various kinds of information through your pipeline.

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@@ -1,6 +1,3 @@
# AI-COUSTICS
AICOUSTICS_LICENSE_KEY=...
# Anthropic
ANTHROPIC_API_KEY=...
@@ -62,9 +59,6 @@ GOOGLE_VERTEX_TEST_CREDENTIALS=...
LMNT_API_KEY=...
LMNT_VOICE_ID=...
# Perplexity
PERPLEXITY_API_KEY=...
# PlayHT
PLAY_HT_USER_ID=...
PLAY_HT_API_KEY=...
@@ -146,12 +140,3 @@ SENTRY_DSN=...
# Heygen
HEYGEN_API_KEY=...
# Mistral
MISTRAL_API_KEY=...
# NVIDIA
NVIDIA_API_KEY=...
# Qwen
QWEN_API_KEY=...

View File

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.piper.tts import PiperTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.rime.tts import RimeHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -17,8 +17,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -17,7 +17,7 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.runner.livekit import configure
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
from pipecat.transports.services.livekit import LiveKitParams, LiveKitTransport
load_dotenv(override=True)

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@@ -17,8 +17,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.riva.tts import FastPitchTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -22,8 +22,8 @@ from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -18,7 +18,7 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.fal.image import FalImageGenService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -17,7 +17,7 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.image import GoogleImageGenService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -18,7 +18,6 @@ from loguru import logger
from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -27,8 +26,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection
from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import IceServer, SmallWebRTCConnection
load_dotenv(override=True)
@@ -104,7 +103,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -13,7 +13,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -21,7 +20,7 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.runner.daily import configure
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.daily.transport import DailyLogLevel, DailyParams, DailyTransport
from pipecat.transports.services.daily import DailyLogLevel, DailyParams, DailyTransport
load_dotenv(override=True)
@@ -87,7 +86,7 @@ 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([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_participant_left")
async def on_participant_left(transport, participant, reason):

View File

@@ -28,7 +28,7 @@ from pipecat.runner.livekit import configure
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
from pipecat.transports.services.livekit import LiveKitParams, LiveKitTransport
load_dotenv(override=True)

View File

@@ -33,7 +33,7 @@ from pipecat.services.cartesia.tts import CartesiaHttpTTSService
from pipecat.services.fal.image import FalImageGenService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

View File

@@ -10,7 +10,7 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import Frame, LLMRunFrame, MetricsFrame
from pipecat.frames.frames import Frame, MetricsFrame
from pipecat.metrics.metrics import (
LLMUsageMetricsData,
ProcessingMetricsData,
@@ -28,8 +28,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -127,7 +127,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -15,7 +15,6 @@ from pipecat.frames.frames import (
BotStartedSpeakingFrame,
BotStoppedSpeakingFrame,
Frame,
LLMRunFrame,
OutputImageRawFrame,
)
from pipecat.pipeline.pipeline import Pipeline
@@ -29,7 +28,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -66,7 +65,7 @@ class ImageSyncAggregator(FrameProcessor):
)
)
await self.push_frame(frame, direction)
await self.push_frame(frame)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -145,7 +144,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# Kick off the conversation.
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -10,7 +10,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -21,8 +20,8 @@ from pipecat.services.cartesia.tts import CartesiaHttpTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -97,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -10,7 +10,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -21,8 +20,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -96,7 +95,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -9,7 +9,6 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -25,8 +24,8 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.speechmatics.stt import SpeechmaticsSTTService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -155,7 +154,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Say a short hello to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -10,7 +10,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -26,8 +25,8 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.speechmatics.stt import SpeechmaticsSTTService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -138,7 +137,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Say a short hello to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.soniox.stt import SonioxSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -95,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.inworld.tts import InworldTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -110,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.asyncai.tts import AsyncAIHttpTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -102,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.asyncai.tts import AsyncAITTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -98,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -1,163 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import datetime
import os
import wave
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.filters.aic_filter import AICFilter
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
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.audio_buffer_processor import AudioBufferProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
load_dotenv(override=True)
# Create audio buffer processor so we can hear the audio fitler results.
audiobuffer = AudioBufferProcessor(
num_channels=2, # 1 for mono, 2 for stereo (user left, bot right)
enable_turn_audio=False, # Enable per-turn audio recording
user_continuous_stream=True, # User has continuous audio stream
)
def _create_aic_filter() -> AICFilter:
license_key = os.getenv("AICOUSTICS_LICENSE_KEY", "")
return AICFilter(
license_key=license_key,
enhancement_level=1.0,
)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=_create_aic_filter(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=_create_aic_filter(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
audio_in_filter=_create_aic_filter(),
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_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
audiobuffer, # write audio data to a file
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
await audiobuffer.start_recording()
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
@audiobuffer.event_handler("on_audio_data")
async def on_audio_data(buffer, audio, sample_rate, num_channels):
# Save or process the composite audio
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"./conversation_{timestamp}.wav"
# Create the WAV file
with wave.open(filename, "wb") as wf:
wf.setnchannels(num_channels)
wf.setsampwidth(2) # 16-bit audio
wf.setframerate(sample_rate)
wf.writeframes(audio)
logger.info(f"Saved recording to {filename}")
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()

View File

@@ -33,8 +33,8 @@ from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

View File

@@ -12,8 +12,8 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.frames.frames import (
LLMRunFrame,
StartInterruptionFrame,
BotInterruptionFrame,
StopInterruptionFrame,
UserStartedSpeakingFrame,
UserStoppedSpeakingFrame,
)
@@ -27,8 +27,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -97,18 +97,18 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
@stt.event_handler("on_speech_started")
async def on_speech_started(stt, *args, **kwargs):
await task.queue_frames([StartInterruptionFrame(), UserStartedSpeakingFrame()])
await task.queue_frames([BotInterruptionFrame(), UserStartedSpeakingFrame()])
@stt.event_handler("on_utterance_end")
async def on_utterance_end(stt, *args, **kwargs):
await task.queue_frames([UserStoppedSpeakingFrame()])
await task.queue_frames([StopInterruptionFrame(), UserStoppedSpeakingFrame()])
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -95,7 +94,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -102,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -98,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.playht.tts import PlayHTHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -98,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.playht.tts import PlayHTTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -100,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.azure.llm import AzureLLMService
from pipecat.services.azure.stt import AzureSTTService
from pipecat.services.azure.tts import AzureTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -104,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.openai.stt import OpenAISTTService
from pipecat.services.openai.tts import OpenAITTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -99,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openpipe.llm import OpenPipeLLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -103,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.xtts.tts import XTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -101,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -24,8 +23,8 @@ from pipecat.services.gladia.stt import GladiaSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -107,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.lmnt.tts import LmntTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -94,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.groq.llm import GroqLLMService
from pipecat.services.groq.stt import GroqSTTService
from pipecat.services.groq.tts import GroqTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -99,7 +98,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -9,7 +9,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -20,8 +19,8 @@ from pipecat.services.aws.llm import AWSBedrockLLMService
from pipecat.services.aws.stt import AWSTranscribeSTTService
from pipecat.services.aws.tts import AWSPollyTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -100,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "user", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -1,164 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""
A conversational AI bot using Gemini for both LLM and TTS.
This example demonstrates how to use Gemini's TTS capabilities with the new
GeminiTTSService, which uses Gemini's TTS-specific models instead of Google Cloud TTS.
Features showcased:
- Gemini LLM for conversation
- Gemini TTS with natural voice control
- Support for different voice personalities
- Style and tone control through natural language prompts
Run with:
python examples/foundational/gemini-tts.py
Make sure to set your environment variables:
export GOOGLE_API_KEY=your_api_key_here
"""
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
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.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.google.stt import GoogleSTTService
from pipecat.services.google.tts import GeminiTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot with Gemini TTS")
stt = GoogleSTTService(
params=GoogleSTTService.InputParams(languages=Language.EN_US),
credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
)
tts = GeminiTTSService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash-preview-tts", # TTS-specific model
voice_id="Charon",
params=GeminiTTSService.InputParams(language=Language.EN_US),
)
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
model="gemini-2.5-flash",
)
# System message that instructs the AI on how to speak
messages = [
{
"role": "system",
"content": """You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
IMPORTANT: Since you're using Gemini TTS which supports natural voice control, you can include speaking instructions in your responses. For example:
- "Say cheerfully: Welcome to our conversation!"
- "Read this in a calm, professional tone: Here are the details you requested."
- "Speak in an excited whisper: I have some great news to share!"
- "Say slowly and clearly: Let me explain this step by step."
Feel free to use natural language instructions to control your voice style, tone, pace, and emotion. The TTS system will interpret these instructions and adjust the speech accordingly.
Your output will be converted to audio, so avoid 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, # Gemini TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# Kick off the conversation with a styled introduction
messages.append(
{
"role": "system",
"content": "Say cheerfully and warmly: Hello! I'm your AI assistant powered by Gemini's new TTS technology. I can speak with different voices, tones, and styles. How can I help you today?",
}
)
await task.queue_frames([LLMRunFrame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.google.stt import GoogleSTTService
from pipecat.services.google.tts import GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -107,7 +106,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.assemblyai.stt import AssemblyAISTTService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -100,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from loguru import logger
from pipecat.audio.filters.krisp_filter import KrispFilter
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -98,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.rime.tts import RimeHttpTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -103,7 +102,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.rime.tts import RimeTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -97,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.nim.llm import NimLLMService
from pipecat.services.riva.stt import RivaSTTService
from pipecat.services.riva.tts import RivaTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -94,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -18,7 +18,6 @@ from pipecat.frames.frames import (
InputAudioRawFrame,
LLMFullResponseEndFrame,
LLMFullResponseStartFrame,
LLMRunFrame,
StartInterruptionFrame,
TextFrame,
TranscriptionFrame,
@@ -36,8 +35,8 @@ from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.google.tts import GoogleTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -275,7 +274,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.fish.tts import FishAudioTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -98,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -19,8 +19,8 @@ from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.ultravox.stt import UltravoxSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,8 +22,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -102,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.neuphonic.tts import NeuphonicTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -97,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -11,7 +11,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +21,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.fal.stt import FalSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -100,7 +99,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -79,7 +78,7 @@ async def main():
)
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
runner = PipelineRunner()

View File

@@ -12,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -24,8 +23,8 @@ from pipecat.services.minimax.tts import MiniMaxHttpTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -104,7 +103,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
await task.queue_frames([context_aggregator.user().get_context_frame()])
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):

View File

@@ -1,126 +0,0 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import os
import aiohttp
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.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.sarvam.tts import SarvamHttpTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"twilio": lambda: FastAPIWebsocketParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
"webrtc": lambda: TransportParams(
audio_in_enabled=True,
audio_out_enabled=True,
vad_analyzer=SileroVADAnalyzer(),
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
# Create an HTTP session
async with aiohttp.ClientSession() as session:
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = SarvamHttpTTSService(
api_key=os.getenv("SARVAM_API_KEY"),
aiohttp_session=session,
params=SarvamHttpTTSService.InputParams(language=Language.EN),
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_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,
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# 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_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()

View File

@@ -5,7 +5,6 @@
#
import asyncio
import os
import aiohttp
@@ -13,7 +12,6 @@ from dotenv import load_dotenv
from loguru import logger
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -23,9 +21,10 @@ from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.sarvam.tts import SarvamTTSService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
@@ -55,64 +54,64 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
# Create an HTTP session
async with aiohttp.ClientSession() as session:
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
tts = SarvamTTSService(
api_key=os.getenv("SARVAM_API_KEY"),
model="bulbul:v2",
voice_id="manisha",
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
tts = SarvamTTSService(
api_key=os.getenv("SARVAM_API_KEY"),
aiohttp_session=session,
params=SarvamTTSService.InputParams(language=Language.EN),
)
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.",
},
]
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
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.",
},
]
)
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
)
context = OpenAILLMContext(messages)
context_aggregator = llm.create_context_aggregator(context)
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
pipeline = Pipeline(
[
transport.input(), # Transport user input
stt,
context_aggregator.user(), # User responses
llm, # LLM
tts, # TTS
transport.output(), # Transport bot output
context_aggregator.assistant(), # Assistant spoken responses
]
)
# Optionally, you can wait for 30 seconds and then change the voice.
# await asyncio.sleep(30)
# await task.queue_frame(TTSUpdateSettingsFrame(settings={"voice": "anushka"}))
task = PipelineTask(
pipeline,
params=PipelineParams(
enable_metrics=True,
enable_usage_metrics=True,
),
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
# 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()])
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
@transport.event_handler("on_client_disconnected")
async def on_client_disconnected(transport, client):
logger.info(f"Client disconnected")
await task.cancel()
await runner.run(task)
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):

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@@ -17,7 +17,7 @@ from pipecat.runner.daily import configure
from pipecat.services.azure import AzureLLMService, AzureTTSService
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.services.fal import FalImageGenService
from pipecat.transports.daily.transport import DailyTransport
from pipecat.transports.services.daily import DailyTransport
load_dotenv(override=True)

View File

@@ -22,7 +22,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

View File

@@ -24,8 +24,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport, maybe_capture_participant_camera
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -22,8 +22,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -32,8 +32,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -28,7 +28,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.moondream.vision import MoondreamService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -28,7 +28,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -28,7 +28,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -28,7 +28,7 @@ from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.whisper.stt import WhisperSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.deepgram.stt import DeepgramSTTService, Language, LiveOptions
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.gladia import GladiaSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -25,8 +25,8 @@ from pipecat.services.gladia.config import (
from pipecat.services.gladia.stt import GladiaSTTService
from pipecat.transcriptions.language import Language
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

View File

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.assemblyai.stt import AssemblyAISTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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@@ -20,8 +20,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.whisper.stt import MLXModel, WhisperSTTServiceMLX
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

View File

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.stt import CartesiaSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)

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