Compare commits
267 Commits
v0.0.52
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hush/callT
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48
.github/workflows/android.yaml
vendored
Normal file
48
.github/workflows/android.yaml
vendored
Normal file
@@ -0,0 +1,48 @@
|
||||
name: android
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
paths:
|
||||
- "examples/simple-chatbot/client/android/**"
|
||||
pull_request:
|
||||
branches:
|
||||
- "**"
|
||||
paths:
|
||||
- "examples/simple-chatbot/client/android/**"
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
sdk_git_ref:
|
||||
type: string
|
||||
description: "Which git ref of the app to build"
|
||||
|
||||
concurrency:
|
||||
group: build-android-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
sdk:
|
||||
name: "Simple chatbot demo"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout repo
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
ref: ${{ github.event.inputs.sdk_git_ref || github.ref }}
|
||||
|
||||
- name: "Install Java"
|
||||
uses: actions/setup-java@v4
|
||||
with:
|
||||
distribution: 'temurin'
|
||||
java-version: '17'
|
||||
|
||||
- name: Build demo app
|
||||
working-directory: examples/simple-chatbot/client/android
|
||||
run: ./gradlew :simple-chatbot-client:assembleDebug
|
||||
|
||||
- name: Upload demo APK
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: Simple Chatbot Android Client
|
||||
path: examples/simple-chatbot/client/android/simple-chatbot-client/build/outputs/apk/debug/simple-chatbot-client-debug.apk
|
||||
4
.github/workflows/tests.yaml
vendored
4
.github/workflows/tests.yaml
vendored
@@ -1,4 +1,4 @@
|
||||
name: test
|
||||
name: tests
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
@@ -49,4 +49,4 @@ jobs:
|
||||
- name: Test with pytest
|
||||
run: |
|
||||
source .venv/bin/activate
|
||||
pytest --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
|
||||
pytest
|
||||
|
||||
7
.pre-commit-config.yaml
Normal file
7
.pre-commit-config.yaml
Normal file
@@ -0,0 +1,7 @@
|
||||
repos:
|
||||
- repo: local
|
||||
hooks:
|
||||
- id: ruff-format-hook
|
||||
name: Check ruff formatting
|
||||
entry: sh scripts/pre-commit.sh
|
||||
language: system
|
||||
153
CHANGELOG.md
153
CHANGELOG.md
@@ -5,6 +5,159 @@ All notable changes to **Pipecat** will be documented in this file.
|
||||
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
|
||||
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
### Added
|
||||
|
||||
- It is now possible to specify the period of the `PipelineTask` heartbeat
|
||||
frames with `heartbeats_period_secs`.
|
||||
|
||||
### Changed
|
||||
|
||||
- Modified `TranscriptProcessor` to use TTS text frames for more accurate assistant
|
||||
transcripts. Assistant messages are now aggregated based on bot speaking boundaries
|
||||
rather than LLM context, providing better handling of interruptions and partial
|
||||
utterances.
|
||||
|
||||
- Updated foundational examples `28a-transcription-processor-openai.py`,
|
||||
`28b-transcript-processor-anthropic.py`, and
|
||||
`28c-transcription-processor-gemini.py` to use the updated
|
||||
`TranscriptProcessor`.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed a type error when using `voice_settings` in `ElevenLabsHttpTTSService`.
|
||||
|
||||
- Fixed an issue where `OpenAIRealtimeBetaLLMService` function calling resulted
|
||||
in an error.
|
||||
|
||||
### Performance
|
||||
|
||||
- Replaced audio resampling library `resampy` with `soxr`. Resampling a 2:21s
|
||||
audio file from 24KHz to 16KHz took 1.41s with `resampy` and 0.031s with
|
||||
`soxr` with similar audio quality.
|
||||
|
||||
### Other
|
||||
|
||||
- Added initial unit test infrastructure.
|
||||
|
||||
## [0.0.53] - 2025-01-18
|
||||
|
||||
### Added
|
||||
|
||||
- Added `ElevenLabsHttpTTSService` which uses EleveLabs' HTTP API instead of the
|
||||
websocket one.
|
||||
|
||||
- Introduced pipeline frame observers. Observers can view all the frames that go
|
||||
through the pipeline without the need to inject processors in the
|
||||
pipeline. This can be useful, for example, to implement frame loggers or
|
||||
debuggers among other things. The example
|
||||
`examples/foundational/30-observer.py` shows how to add an observer to a
|
||||
pipeline for debugging.
|
||||
|
||||
- Introduced heartbeat frames. The pipeline task can now push periodic
|
||||
heartbeats down the pipeline when `enable_heartbeats=True`. Heartbeats are
|
||||
system frames that are supposed to make it all the way to the end of the
|
||||
pipeline. When a heartbeat frame is received the traversing time (i.e. the
|
||||
time it took to go through the whole pipeline) will be displayed (with TRACE
|
||||
logging) otherwise a warning will be shown. The example
|
||||
`examples/foundational/31-heartbeats.py` shows how to enable heartbeats and
|
||||
forces warnings to be displayed.
|
||||
|
||||
- Added `LLMTextFrame` and `TTSTextFrame` which should be pushed by LLM and TTS
|
||||
services respectively instead of `TextFrame`s.
|
||||
|
||||
- Added `OpenRouter` for OpenRouter integration with an OpenAI-compatible
|
||||
interface. Added foundational example `14m-function-calling-openrouter.py`.
|
||||
|
||||
- Added a new `WebsocketService` based class for TTS services, containing
|
||||
base functions and retry logic.
|
||||
|
||||
- Added `DeepSeekLLMService` for DeepSeek integration with an OpenAI-compatible
|
||||
interface. Added foundational example `14l-function-calling-deepseek.py`.
|
||||
|
||||
- Added `FunctionCallResultProperties` dataclass to provide a structured way to
|
||||
control function call behavior, including:
|
||||
|
||||
- `run_llm`: Controls whether to trigger LLM completion
|
||||
- `on_context_updated`: Optional callback triggered after context update
|
||||
|
||||
- Added a new foundational example `07e-interruptible-playht-http.py` for easy
|
||||
testing of `PlayHTHttpTTSService`.
|
||||
|
||||
- Added support for Google TTS Journey voices in `GoogleTTSService`.
|
||||
|
||||
- Added `29-livekit-audio-chat.py`, as a new foundational examples for
|
||||
`LiveKitTransportLayer`.
|
||||
|
||||
- Added `enable_prejoin_ui`, `max_participants` and `start_video_off` params
|
||||
to `DailyRoomProperties`.
|
||||
|
||||
- Added `session_timeout` to `FastAPIWebsocketTransport` and
|
||||
`WebsocketServerTransport` for configuring session timeouts (in
|
||||
seconds). Triggers `on_session_timeout` for custom timeout handling.
|
||||
See [examples/websocket-server/bot.py](https://github.com/pipecat-ai/pipecat/blob/main/examples/websocket-server/bot.py).
|
||||
|
||||
- Added the new modalities option and helper function to set Gemini output
|
||||
modalities.
|
||||
|
||||
- Added `examples/foundational/26d-gemini-multimodal-live-text.py` which is
|
||||
using Gemini as TEXT modality and using another TTS provider for TTS process.
|
||||
|
||||
### Changed
|
||||
|
||||
- Modified `UserIdleProcessor` to start monitoring only after first
|
||||
conversation activity (`UserStartedSpeakingFrame` or
|
||||
`BotStartedSpeakingFrame`) instead of immediately.
|
||||
|
||||
- Modified `OpenAIAssistantContextAggregator` to support controlled completions
|
||||
and to emit context update callbacks via `FunctionCallResultProperties`.
|
||||
|
||||
- Added `aws_session_token` to the `PollyTTSService`.
|
||||
|
||||
- Changed the default model for `PlayHTHttpTTSService` to `Play3.0-mini-http`.
|
||||
|
||||
- `api_key`, `aws_access_key_id` and `region` are no longer required parameters
|
||||
for the PollyTTSService (AWSTTSService)
|
||||
|
||||
- Added `session_timeout` example in `examples/websocket-server/bot.py` to
|
||||
handle session timeout event.
|
||||
|
||||
- Changed `InputParams` in
|
||||
`src/pipecat/services/gemini_multimodal_live/gemini.py` to support different
|
||||
modalities.
|
||||
|
||||
- Changed `DeepgramSTTService` to send `finalize` event whenever VAD detects
|
||||
`UserStoppedSpeakingFrame`. This helps in faster transcriptions and clearing
|
||||
the `Deepgram` audio buffer.
|
||||
|
||||
### Fixed
|
||||
|
||||
- Fixed an issue where `DeepgramSTTService` was not generating metrics using
|
||||
pipeline's VAD.
|
||||
|
||||
- Fixed `UserIdleProcessor` not properly propagating `EndFrame`s through the
|
||||
pipeline.
|
||||
|
||||
- Fixed an issue where websocket based TTS services could incorrectly terminate
|
||||
their connection due to a retry counter not resetting.
|
||||
|
||||
- Fixed a `PipelineTask` issue that would cause a dangling task after stopping
|
||||
the pipeline with an `EndFrame`.
|
||||
|
||||
- Fixed an import issue for `PlayHTHttpTTSService`.
|
||||
|
||||
- Fixed an issue where languages couldn't be used with the `PlayHTHttpTTSService`.
|
||||
|
||||
- Fixed an issue where `OpenAIRealtimeBetaLLMService` audio chunks were hitting
|
||||
an error when truncating audio content.
|
||||
|
||||
- Fixed an issue where setting the voice and model for `RimeHttpTTSService`
|
||||
wasn't working.
|
||||
|
||||
- Fixed an issue where `IdleFrameProcessor` and `UserIdleProcessor` were getting
|
||||
initialized before the start of the pipeline.
|
||||
|
||||
## [0.0.52] - 2024-12-24
|
||||
|
||||
### Added
|
||||
|
||||
2
LICENSE
2
LICENSE
@@ -1,6 +1,6 @@
|
||||
BSD 2-Clause License
|
||||
|
||||
Copyright (c) 2024, Daily
|
||||
Copyright (c) 2024–2025, Daily
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions are met:
|
||||
|
||||
39
README.md
39
README.md
@@ -2,7 +2,7 @@
|
||||
<img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
|
||||
</div></h1>
|
||||
|
||||
[](https://pypi.org/project/pipecat-ai) [](https://docs.pipecat.ai) [](https://discord.gg/pipecat) <a href="https://app.commanddash.io/agent/github_pipecat-ai_pipecat"><img src="https://img.shields.io/badge/AI-Code%20Agent-EB9FDA"></a>
|
||||
[](https://pypi.org/project/pipecat-ai)  [](https://docs.pipecat.ai) [](https://discord.gg/pipecat) <a href="https://app.commanddash.io/agent/github_pipecat-ai_pipecat"><img src="https://img.shields.io/badge/AI-Code%20Agent-EB9FDA"></a>
|
||||
|
||||
Pipecat is an open source Python framework for building voice and multimodal conversational agents. It handles the complex orchestration of AI services, network transport, audio processing, and multimodal interactions, letting you focus on creating engaging experiences.
|
||||
|
||||
@@ -55,17 +55,17 @@ pip install "pipecat-ai[option,...]"
|
||||
|
||||
Available options include:
|
||||
|
||||
| Category | Services | Install Command Example |
|
||||
| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
||||
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [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), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
||||
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
||||
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), WebSocket, Local | `pip install "pipecat-ai[daily]"` |
|
||||
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
|
||||
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
||||
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
||||
| Category | Services | Install Command Example |
|
||||
| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
||||
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
||||
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
||||
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
|
||||
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
|
||||
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
||||
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
||||
|
||||
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
|
||||
|
||||
@@ -160,15 +160,24 @@ From the root of this repo, run the following:
|
||||
|
||||
```shell
|
||||
pip install -r dev-requirements.txt
|
||||
python -m build
|
||||
```
|
||||
|
||||
This builds the package. To use the package locally (e.g. to run sample files), run
|
||||
This will install the necessary development dependencies. Also, make sure you install the git pre-commit hooks:
|
||||
|
||||
```shell
|
||||
pre-commit install
|
||||
```
|
||||
|
||||
The hooks will just save you time when you submit a PR by making sure your code follows the project rules.
|
||||
|
||||
To use the package locally (e.g. to run sample files), run:
|
||||
|
||||
```shell
|
||||
pip install --editable ".[option,...]"
|
||||
```
|
||||
|
||||
The `--editable` option makes sure you don't have to run `pip install` again and you can just edit the project files locally.
|
||||
|
||||
If you want to use this package from another directory, you can run:
|
||||
|
||||
```shell
|
||||
@@ -180,7 +189,7 @@ pip install "path_to_this_repo[option,...]"
|
||||
From the root directory, run:
|
||||
|
||||
```shell
|
||||
pytest --doctest-modules --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
|
||||
pytest
|
||||
```
|
||||
|
||||
## Setting up your editor
|
||||
|
||||
@@ -1,9 +1,11 @@
|
||||
build~=1.2.2
|
||||
grpcio-tools~=1.68.1
|
||||
grpcio-tools~=1.69.0
|
||||
pip-tools~=7.4.1
|
||||
pyright~=1.1.390
|
||||
pre-commit~=4.0.1
|
||||
pyright~=1.1.392
|
||||
pytest~=8.3.4
|
||||
ruff~=0.8.3
|
||||
setuptools~=75.6.0
|
||||
pytest-asyncio~=0.25.2
|
||||
ruff~=0.9.1
|
||||
setuptools~=75.8.0
|
||||
setuptools_scm~=8.1.0
|
||||
python-dotenv~=1.0.1
|
||||
|
||||
@@ -60,3 +60,27 @@ SIMLI_FACE_ID=...
|
||||
|
||||
# Krisp
|
||||
KRISP_MODEL_PATH=...
|
||||
|
||||
# DeepSeek
|
||||
DEEPSEEK_API_KEY=...
|
||||
|
||||
# Groq
|
||||
GROQ_API_KEY=...
|
||||
|
||||
# Grok
|
||||
GROK_API_KEY=...
|
||||
|
||||
# Together.ai
|
||||
TOGETHER_API_KEY=...
|
||||
|
||||
# Cerebras
|
||||
CEREBRAS_API_KEY=...
|
||||
|
||||
# Fish Audio
|
||||
FISH_API_KEY=...
|
||||
|
||||
# Assembly AI
|
||||
ASSEMBLYAI_API_KEY=...
|
||||
|
||||
# OpenRouter
|
||||
OPENROUTER_API_KEY=...
|
||||
|
||||
@@ -42,7 +42,7 @@ Next, follow the steps in the README for each demo.
|
||||
| [Dialin Chatbot](dialin-chatbot) | A chatbot that connects to an incoming phone call from Daily or Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
|
||||
| [Twilio Chatbot](twilio-chatbot) | A chatbot that connects to an incoming phone call from Twilio. | Deepgram, ElevenLabs, OpenAI, Daily, Twilio |
|
||||
| [studypal](studypal) | A chatbot to have a conversation about any article on the web | |
|
||||
| [WebSocket Chatbot Server](websocket-server) | A real-time websocket server that handles audio streaming and bot interactions with speech-to-text and text-to-speech capabilities | `python-websockets`, `openai`, `deepgram`, `silero-tts`, `numpy` |
|
||||
| [WebSocket Chatbot Server](websocket-server) | A real-time websocket server that handles audio streaming and bot interactions with speech-to-text and text-to-speech capabilities. | Cartesia, Deepgram, OpenAI, Websockets |
|
||||
|
||||
> [!IMPORTANT]
|
||||
> These example projects use Daily as a WebRTC transport and can be joined using their hosted Prebuilt UI.
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -15,7 +15,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -97,7 +97,7 @@ async def main():
|
||||
call completion, CanonicalMetrics will send the audio buffer to Canonical for
|
||||
analysis. Visit https://voice.canonical.chat to learn more.
|
||||
"""
|
||||
audio_buffer_processor = AudioBufferProcessor()
|
||||
audio_buffer_processor = AudioBufferProcessor(num_channels=2)
|
||||
canonical = CanonicalMetricsService(
|
||||
audio_buffer_processor=audio_buffer_processor,
|
||||
aiohttp_session=session,
|
||||
@@ -105,6 +105,7 @@ async def main():
|
||||
call_id=str(uuid.uuid4()),
|
||||
assistant="pipecat-chatbot",
|
||||
assistant_speaks_first=True,
|
||||
context=context,
|
||||
)
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
@@ -124,7 +125,7 @@ async def main():
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -18,7 +18,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -134,7 +134,7 @@ async def main():
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -7,7 +7,7 @@ from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -75,7 +75,7 @@ async def main(room_url: str, token: str):
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -13,7 +13,7 @@ logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
async def main(room_url: str, token: str):
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -75,7 +75,7 @@ async def main(room_url: str, token: str):
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
python-dotenv==1.0.1
|
||||
modal==0.65.48
|
||||
pipecat-ai[daily,silero,cartesia,openai]==0.0.48
|
||||
fastapi==0.115.4
|
||||
aiohttp==3.11.9
|
||||
modal==0.71.3
|
||||
pipecat-ai[daily,silero,cartesia,openai]==0.0.52
|
||||
fastapi==0.115.6
|
||||
aiohttp==3.11.11
|
||||
|
||||
@@ -37,7 +37,16 @@ Run `bot_runner.py` to handle incoming HTTP requests:
|
||||
|
||||
Then target the following URL:
|
||||
|
||||
`POST /daily_start_bot`
|
||||
```bash
|
||||
curl -X POST 'http://localhost:7860/daily_start_bot' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-d '{
|
||||
"callId": "callId-from-call",
|
||||
"callDomain": "callDomain-from-call"
|
||||
}'
|
||||
```
|
||||
|
||||
Use [this guide](https://docs.pipecat.ai/guides/telephony/daily-webrtc) to connect a phone number purchased from Daily to the bot.
|
||||
|
||||
For more configuration options, please consult Daily's API documentation.
|
||||
|
||||
@@ -82,4 +91,4 @@ If you're using Twilio as a number vendor:
|
||||
|
||||
## Need to do something more advanced?
|
||||
|
||||
This demo covers the basics of bot telephony. If you want to know more about working with PSTN / SIP, please ping us on [Discord](https://discord.gg/pipecat).
|
||||
This demo covers the basics of bot telephony. If you want to know more about working with PSTN / SIP, please ping us on [Discord](https://discord.gg/pipecat).
|
||||
|
||||
@@ -1,3 +1,8 @@
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import os
|
||||
@@ -5,13 +10,16 @@ import sys
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from openai.types.chat import ChatCompletionToolParam
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.ai_services import LLMService
|
||||
from pipecat.services.deepgram import DeepgramSTTService
|
||||
from pipecat.services.elevenlabs import ElevenLabsTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyDialinSettings, DailyParams, DailyTransport
|
||||
@@ -55,16 +63,62 @@ async def main(room_url: str, token: str, callId: str, callDomain: str):
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
|
||||
content = f"""
|
||||
You are a delivery service customer support specialist supporting customers with their orders.
|
||||
Begin with: "Hello, this is Hailey from customer support. What can I help you with today?"
|
||||
"""
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are Chatbot, a friendly, helpful robot. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by saying 'Oh, hello! Who dares dial me at this hour?!'.",
|
||||
"content": content,
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages)
|
||||
tools = [
|
||||
ChatCompletionToolParam(
|
||||
type="function",
|
||||
function={
|
||||
"name": "transfer_call",
|
||||
"description": "Transfer the call to a person. This function is used to connect the call to a real person. Examples of real people are: managers, supervisors, or other customer support specialists. Any person is okay as long as they are not a bot.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"call_id": {
|
||||
"type": "string",
|
||||
"description": "This is always {callId}.",
|
||||
},
|
||||
"summary": {
|
||||
"type": "string",
|
||||
"description": """
|
||||
Provide a concise summary in 3-5 sentences. Highlight any important details or unusual aspects of the conversation.
|
||||
""",
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
)
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
async def default_transfer_call(
|
||||
function_name, tool_call_id, args, llm: LLMService, context, result_callback
|
||||
):
|
||||
logger.debug(f"default_transfer_call: {function_name} {tool_call_id} {args}")
|
||||
await result_callback(
|
||||
{
|
||||
"transfer_call": False,
|
||||
"reason": "To transfer call calls, please dial in to the room using a phone or a SIP client.",
|
||||
}
|
||||
)
|
||||
|
||||
llm.register_function(
|
||||
function_name="transfer_call",
|
||||
callback=default_transfer_call,
|
||||
)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
@@ -81,12 +135,50 @@ async def main(room_url: str, token: str, callId: str, callDomain: str):
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
@transport.event_handler("on_dialin_ready")
|
||||
async def on_dialin_ready(_, sip_endpoint):
|
||||
logger.info(f"on_dialin_ready: {sip_endpoint}")
|
||||
|
||||
@transport.event_handler("on_dialin_connected")
|
||||
async def on_dialin_connected(transport, event):
|
||||
logger.info(f"on_dialin_connected: {event}")
|
||||
sip_session_id = event["sessionId"]
|
||||
|
||||
async def transfer_call(
|
||||
function_name, tool_call_id, args, llm: LLMService, context, result_callback
|
||||
):
|
||||
logger.debug(f"transfer_call: {function_name} {tool_call_id} {args}")
|
||||
|
||||
# sip_url = "sip:your_user_name@sip.linphone.org"
|
||||
|
||||
sip_url = (
|
||||
f"sip:your_username@dailyco.sip.twilio.com?x-daily_id={room_url.split('/')[-1]}"
|
||||
)
|
||||
|
||||
try:
|
||||
await transport.sip_refer(
|
||||
settings={
|
||||
"sessionId": sip_session_id,
|
||||
"toEndPoint": sip_url,
|
||||
}
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"An error occurred during SIP refer: {e}")
|
||||
await result_callback({"transfer_call": False})
|
||||
|
||||
await result_callback({"transfer_call": True})
|
||||
|
||||
llm.register_function(
|
||||
function_name="transfer_call",
|
||||
callback=transfer_call,
|
||||
)
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
@@ -8,7 +8,7 @@ from loguru import logger
|
||||
from twilio.rest import Client
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -83,7 +83,7 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import Frame, LLMMessagesFrame, MetricsFrame
|
||||
from pipecat.frames.frames import EndFrame, Frame, MetricsFrame
|
||||
from pipecat.metrics.metrics import (
|
||||
LLMUsageMetricsData,
|
||||
ProcessingMetricsData,
|
||||
@@ -47,9 +47,7 @@ class MetricsLogger(FrameProcessor):
|
||||
elif isinstance(d, LLMUsageMetricsData):
|
||||
tokens = d.value
|
||||
print(
|
||||
f"!!! MetricsFrame: {frame}, tokens: {
|
||||
tokens.prompt_tokens}, characters: {
|
||||
tokens.completion_tokens}"
|
||||
f"!!! MetricsFrame: {frame}, tokens: {tokens.prompt_tokens}, characters: {tokens.completion_tokens}"
|
||||
)
|
||||
elif isinstance(d, TTSUsageMetricsData):
|
||||
print(f"!!! MetricsFrame: {frame}, characters: {d.value}")
|
||||
@@ -113,7 +111,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -15,7 +15,7 @@ from PIL import Image
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import Frame, OutputImageRawFrame, SystemFrame, TextFrame
|
||||
from pipecat.frames.frames import EndFrame, Frame, OutputImageRawFrame, SystemFrame, TextFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineTask
|
||||
@@ -126,6 +126,10 @@ async def main():
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
await task.queue_frames([TextFrame(f"Hi there {participant_name}!")])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -13,7 +13,7 @@ from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -90,7 +90,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -88,7 +88,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -78,13 +78,25 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -19,7 +19,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -101,7 +101,15 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
@@ -114,6 +122,10 @@ async def main():
|
||||
messages = [({"content": "Please briefly introduce yourself to the user."})]
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -16,7 +16,7 @@ from runner import configure
|
||||
|
||||
from pipecat.frames.frames import (
|
||||
BotInterruptionFrame,
|
||||
LLMMessagesFrame,
|
||||
EndFrame,
|
||||
StopInterruptionFrame,
|
||||
UserStartedSpeakingFrame,
|
||||
UserStoppedSpeakingFrame,
|
||||
@@ -80,7 +80,15 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@stt.event_handler("on_speech_started")
|
||||
async def on_speech_started(stt, *args, **kwargs):
|
||||
@@ -94,7 +102,11 @@ async def main():
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -73,13 +73,25 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -88,7 +88,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
105
examples/foundational/07e-interruptible-playht-http.py
Normal file
105
examples/foundational/07e-interruptible-playht-http.py
Normal file
@@ -0,0 +1,105 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.services.playht import PlayHTHttpTTSService
|
||||
from pipecat.transcriptions.language import Language
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, token) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
token,
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
transcription_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
)
|
||||
|
||||
tts = PlayHTHttpTTSService(
|
||||
user_id=os.getenv("PLAYHT_USER_ID"),
|
||||
api_key=os.getenv("PLAYHT_API_KEY"),
|
||||
voice_url="s3://voice-cloning-zero-shot/d9ff78ba-d016-47f6-b0ef-dd630f59414e/female-cs/manifest.json",
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -91,7 +91,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -82,14 +82,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -70,14 +70,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -15,7 +15,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -80,14 +80,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -74,14 +74,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import EndFrame, LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -79,14 +79,22 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
# Register an event handler to exit the application when the user leaves.
|
||||
@transport.event_handler("on_participant_left")
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -71,14 +71,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -90,7 +90,10 @@ async def main():
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@@ -98,7 +101,11 @@ async def main():
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -80,14 +80,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -22,6 +22,7 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.deepgram import DeepgramSTTService
|
||||
from pipecat.services.google import GoogleTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transcriptions.language import Language
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
@@ -50,8 +51,8 @@ async def main():
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = GoogleTTSService(
|
||||
voice_id="en-US-Neural2-J",
|
||||
params=GoogleTTSService.InputParams(language="en-US", rate="1.05"),
|
||||
voice_id="en-US-Journey-F",
|
||||
params=GoogleTTSService.InputParams(language=Language.EN_US),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
|
||||
@@ -78,14 +79,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -79,14 +79,26 @@ async def main():
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,14 +14,11 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.filters.krisp_filter import KrispFilter
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.llm_response import (
|
||||
LLMAssistantResponseAggregator,
|
||||
LLMUserResponseAggregator,
|
||||
)
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
@@ -63,28 +60,40 @@ async def main():
|
||||
},
|
||||
]
|
||||
|
||||
tma_in = LLMUserResponseAggregator(messages)
|
||||
tma_out = LLMAssistantResponseAggregator(messages)
|
||||
context = OpenAILLMContext(messages)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
stt, # STT
|
||||
tma_in, # User responses
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
transport.output(), # Transport bot output
|
||||
tma_out, # Assistant spoken responses
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -89,7 +89,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -81,7 +81,11 @@ async def main():
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
# Kick off the conversation.
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -17,6 +17,7 @@ from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import (
|
||||
EndFrame,
|
||||
Frame,
|
||||
InputAudioRawFrame,
|
||||
LLMFullResponseEndFrame,
|
||||
@@ -268,6 +269,10 @@ async def main():
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -88,7 +88,11 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
148
examples/foundational/14l-function-calling-deepseek.py
Normal file
148
examples/foundational/14l-function-calling-deepseek.py
Normal file
@@ -0,0 +1,148 @@
|
||||
#
|
||||
# Copyright (c) 2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from openai.types.chat import ChatCompletionToolParam
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.deepseek import DeepSeekLLMService
|
||||
from pipecat.services.openai import OpenAILLMContext
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def start_fetch_weather(function_name, llm, context):
|
||||
# note: we can't push a frame to the LLM here. the bot
|
||||
# can interrupt itself and/or cause audio overlapping glitches.
|
||||
# possible question for Aleix and Chad about what the right way
|
||||
# to trigger speech is, now, with the new queues/async/sync refactors.
|
||||
# await llm.push_frame(TextFrame("Let me check on that."))
|
||||
logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
|
||||
|
||||
|
||||
async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
|
||||
await result_callback({"conditions": "nice", "temperature": "75"})
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, token) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
token,
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
transcription_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
|
||||
)
|
||||
|
||||
llm = DeepSeekLLMService(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
|
||||
# Register a function_name of None to get all functions
|
||||
# sent to the same callback with an additional function_name parameter.
|
||||
llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
|
||||
|
||||
tools = [
|
||||
ChatCompletionToolParam(
|
||||
type="function",
|
||||
function={
|
||||
"name": "get_current_weather",
|
||||
"description": "Get the current weather for a specific location. You MUST use this function whenever asked about weather.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"format": {
|
||||
"type": "string",
|
||||
"enum": ["celsius", "fahrenheit"],
|
||||
"description": "The temperature unit to use. Use fahrenheit for US locations, celsius for others.",
|
||||
},
|
||||
},
|
||||
"required": ["location", "format"],
|
||||
},
|
||||
},
|
||||
)
|
||||
]
|
||||
messages = [
|
||||
{
|
||||
"role": "system",
|
||||
"content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
|
||||
|
||||
You have one functions available:
|
||||
|
||||
1. get_current_weather is used to get current weather information.
|
||||
|
||||
Infer whether to use Fahrenheit or Celsius automatically based on the location, unless the user specifies a preference.
|
||||
|
||||
Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast.
|
||||
|
||||
Respond to what the user said in a creative and helpful way.""",
|
||||
},
|
||||
]
|
||||
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
142
examples/foundational/14m-function-calling-openrouter.py
Normal file
142
examples/foundational/14m-function-calling-openrouter.py
Normal file
@@ -0,0 +1,142 @@
|
||||
#
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import sys
|
||||
|
||||
import aiohttp
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
from openai.types.chat import ChatCompletionToolParam
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.azure import AzureTTSService
|
||||
from pipecat.services.openrouter import OpenRouterLLMService
|
||||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
logger.remove(0)
|
||||
logger.add(sys.stderr, level="DEBUG")
|
||||
|
||||
|
||||
async def start_fetch_weather(function_name, llm, context):
|
||||
# note: we can't push a frame to the LLM here. the bot
|
||||
# can interrupt itself and/or cause audio overlapping glitches.
|
||||
# possible question for Aleix and Chad about what the right way
|
||||
# to trigger speech is, now, with the new queues/async/sync refactors.
|
||||
# await llm.push_frame(TextFrame("Let me check on that."))
|
||||
logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
|
||||
|
||||
|
||||
async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
|
||||
await result_callback({"conditions": "nice", "temperature": "75"})
|
||||
|
||||
|
||||
async def main():
|
||||
async with aiohttp.ClientSession() as session:
|
||||
(room_url, token) = await configure(session)
|
||||
|
||||
transport = DailyTransport(
|
||||
room_url,
|
||||
token,
|
||||
"Respond bot",
|
||||
DailyParams(
|
||||
audio_out_enabled=True,
|
||||
transcription_enabled=True,
|
||||
vad_enabled=True,
|
||||
vad_analyzer=SileroVADAnalyzer(),
|
||||
),
|
||||
)
|
||||
|
||||
tts = AzureTTSService(
|
||||
api_key=os.getenv("AZURE_API_KEY"),
|
||||
region="eastus",
|
||||
voice="en-US-JennyNeural",
|
||||
params=AzureTTSService.InputParams(language="en-US", rate="1.1", style="cheerful"),
|
||||
)
|
||||
|
||||
llm = OpenRouterLLMService(
|
||||
api_key=os.getenv("OPENROUTER_API_KEY"), model="openai/gpt-4o-2024-11-20"
|
||||
)
|
||||
# Register a function_name of None to get all functions
|
||||
# sent to the same callback with an additional function_name parameter.
|
||||
llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
|
||||
|
||||
tools = [
|
||||
ChatCompletionToolParam(
|
||||
type="function",
|
||||
function={
|
||||
"name": "get_current_weather",
|
||||
"description": "Get the current weather",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"format": {
|
||||
"type": "string",
|
||||
"enum": ["celsius", "fahrenheit"],
|
||||
"description": "The temperature unit to use. Infer this from the users location.",
|
||||
},
|
||||
},
|
||||
"required": ["location", "format"],
|
||||
},
|
||||
},
|
||||
)
|
||||
]
|
||||
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, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
context_aggregator.user(),
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
context_aggregator.assistant(),
|
||||
]
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
PipelineParams(
|
||||
allow_interruptions=True,
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
report_only_initial_ttfb=True,
|
||||
),
|
||||
)
|
||||
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
await transport.capture_participant_transcription(participant["id"])
|
||||
# Kick off the conversation.
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -15,7 +15,6 @@ from openai.types.chat import ChatCompletionToolParam
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
@@ -146,7 +145,7 @@ async def main():
|
||||
"content": f"Please introduce yourself to the user and let them know the voices you can do. Your initial responses should be as if you were a {current_voice}.",
|
||||
}
|
||||
)
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -16,7 +16,6 @@ from openai.types.chat import ChatCompletionToolParam
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
@@ -139,7 +138,7 @@ async def main():
|
||||
"content": f"Please introduce yourself to the user and let them know the languages you speak. Your initial responses should be in {current_language}.",
|
||||
}
|
||||
)
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,6 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -98,7 +97,7 @@ async def main():
|
||||
@transport.event_handler("on_first_participant_joined")
|
||||
async def on_first_participant_joined(transport, participant):
|
||||
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
# Handle "latency-ping" messages. The client will send app messages that look like
|
||||
# this:
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -100,7 +100,7 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,14 +14,11 @@ from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame
|
||||
from pipecat.frames.frames import EndFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.llm_response import (
|
||||
LLMAssistantResponseAggregator,
|
||||
LLMUserResponseAggregator,
|
||||
)
|
||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||||
from pipecat.services.cartesia import CartesiaTTSService
|
||||
from pipecat.services.deepgram import DeepgramSTTService
|
||||
from pipecat.services.openai import OpenAILLMService
|
||||
@@ -39,7 +36,6 @@ async def main():
|
||||
tavus = TavusVideoService(
|
||||
api_key=os.getenv("TAVUS_API_KEY"),
|
||||
replica_id=os.getenv("TAVUS_REPLICA_ID"),
|
||||
persona_id=os.getenv("TAVUS_PERSONA_ID", "pipecat0"),
|
||||
session=session,
|
||||
)
|
||||
|
||||
@@ -74,19 +70,19 @@ async def main():
|
||||
},
|
||||
]
|
||||
|
||||
tma_in = LLMUserResponseAggregator(messages)
|
||||
tma_out = LLMAssistantResponseAggregator(messages)
|
||||
context = OpenAILLMContext(messages)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(), # Transport user input
|
||||
stt, # STT
|
||||
tma_in, # User responses
|
||||
context_aggregator.user(), # User responses
|
||||
llm, # LLM
|
||||
tts, # TTS
|
||||
tavus, # Tavus output layer
|
||||
transport.output(), # Transport bot output
|
||||
tma_out, # Assistant spoken responses
|
||||
context_aggregator.assistant(), # Assistant spoken responses
|
||||
]
|
||||
)
|
||||
|
||||
@@ -120,7 +116,11 @@ async def main():
|
||||
messages.append(
|
||||
{"role": "system", "content": "Please introduce yourself to the user."}
|
||||
)
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_participant_left")
|
||||
async def on_participant_left(transport, participant, reason):
|
||||
await task.queue_frame(EndFrame())
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -14,7 +14,7 @@ from loguru import logger
|
||||
from runner import configure
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMMessagesFrame, TextFrame
|
||||
from pipecat.frames.frames import TextFrame
|
||||
from pipecat.pipeline.parallel_pipeline import ParallelPipeline
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
@@ -155,7 +155,7 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
runner = PipelineRunner()
|
||||
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -311,7 +311,7 @@ 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([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_app_message")
|
||||
async def on_app_message(transport, message, sender):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
@@ -525,7 +525,7 @@ async def main():
|
||||
"content": "Start by just saying \"Hello I'm ready.\" Don't say anything else.",
|
||||
}
|
||||
)
|
||||
await task.queue_frames([LLMMessagesFrame(messages)])
|
||||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||||
|
||||
@transport.event_handler("on_app_message")
|
||||
async def on_app_message(transport, message, sender):
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright (c) 2024, Daily
|
||||
# Copyright (c) 2024–2025, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user