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pk/nova-so
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filipi/asy
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30
.dockerignore
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30
.dockerignore
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@@ -0,0 +1,30 @@
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# flyctl launch added from .gitignore
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**/.vscode
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**/env
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**/__pycache__
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**/*~
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**/venv
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#*#
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# Distribution / packaging
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**/.Python
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**/build
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**/develop-eggs
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**/dist
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**/downloads
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**/eggs
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**/.eggs
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**/lib
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**/lib64
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**/parts
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**/sdist
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**/var
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**/wheels
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**/share/python-wheels
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**/*.egg-info
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**/.installed.cfg
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**/*.egg
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**/MANIFEST
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**/.DS_Store
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**/.env
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fly.toml
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8
.github/workflows/format.yaml
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8
.github/workflows/format.yaml
vendored
@@ -32,9 +32,7 @@ jobs:
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run: uv python install 3.12
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- name: Install development dependencies
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# `--all-extras` (matching the dev setup in README.md) so pyright can
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# resolve types from various optional dependencies.
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run: uv sync --group dev --all-extras --no-extra gstreamer --no-extra local
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run: uv sync --group dev
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- name: Ruff formatter
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id: ruff-format
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@@ -43,7 +41,3 @@ jobs:
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- name: Ruff linter (all rules)
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id: ruff-check
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run: uv run ruff check
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- name: Type check (pyright)
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id: pyright
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run: uv run pyright
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2
.github/workflows/python-compatibility.yaml
vendored
2
.github/workflows/python-compatibility.yaml
vendored
@@ -14,7 +14,7 @@ jobs:
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strategy:
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fail-fast: false
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matrix:
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python-version: ['3.11.15', '3.12.13', '3.13.12', '3.14.3']
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python-version: ['3.10.19', '3.11.14', '3.12.12', '3.13.12']
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name: Python ${{ matrix.python-version }}
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steps:
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1
.github/workflows/update-docs.yml
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1
.github/workflows/update-docs.yml
vendored
@@ -114,7 +114,6 @@ jobs:
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GH_TOKEN=$DOCS_SYNC_TOKEN gh pr create \
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--repo pipecat-ai/docs \
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--label auto-docs \
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--label pipecat \
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--title "docs: update for pipecat PR #${{ steps.pr.outputs.number }}" \
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--body "$(cat <<'BODY'
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Automated documentation update for [pipecat PR #${{ steps.pr.outputs.number }}](https://github.com/pipecat-ai/pipecat/pull/${{ steps.pr.outputs.number }}).
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@@ -11,7 +11,7 @@ build:
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jobs:
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post_install:
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- pip install uv
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- UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra mlx-whisper
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- UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
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sphinx:
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configuration: docs/api/conf.py
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1016
CHANGELOG.md
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CHANGELOG.md
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62
CHANGELOG.md.template
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62
CHANGELOG.md.template
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@@ -0,0 +1,62 @@
|
||||
# Changelog
|
||||
|
||||
All notable changes to the **<project name>** SDK 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).
|
||||
|
||||
Please make sure to add your changes to the appropriate categories:
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
### Added
|
||||
|
||||
<!-- for new functionality -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Changed
|
||||
|
||||
<!-- for changed functionality -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Deprecated
|
||||
|
||||
<!-- for soon-to-be removed functionality -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Removed
|
||||
|
||||
<!-- for removed functionality -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Fixed
|
||||
|
||||
<!-- for fixed bugs -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Performance
|
||||
|
||||
<!-- for performance-relevant changes -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Security
|
||||
|
||||
<!-- for security-relevant changes -->
|
||||
|
||||
- n/a
|
||||
|
||||
### Other
|
||||
|
||||
<!-- for everything else -->
|
||||
|
||||
- n/a
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||||
|
||||
## [0.1.0] - YYYY-MM-DD
|
||||
|
||||
Initial release.
|
||||
@@ -10,7 +10,7 @@ Pipecat is an open-source Python framework for building real-time voice and mult
|
||||
|
||||
```bash
|
||||
# Setup development environment
|
||||
uv sync --group dev --all-extras --no-extra gstreamer --no-extra local
|
||||
uv sync --group dev --all-extras --no-extra gstreamer
|
||||
|
||||
# Install pre-commit hooks
|
||||
uv run pre-commit install
|
||||
|
||||
42
README.md
42
README.md
@@ -28,10 +28,6 @@
|
||||
|
||||
## 🌐 Pipecat Ecosystem
|
||||
|
||||
### 🧩 Multi-agent systems
|
||||
|
||||
Need multiple AI agents working together? [Pipecat Subagents](https://github.com/pipecat-ai/pipecat-subagents) lets you build distributed multi-agent systems where each agent runs its own pipeline and communicates through a shared message bus. Hand off conversations between specialists, dispatch background tasks, and scale agents across processes or machines.
|
||||
|
||||
### 📱 Client SDKs
|
||||
|
||||
Building client applications? You can connect to Pipecat from any platform using our official SDKs:
|
||||
@@ -71,7 +67,7 @@ and install any of the available plugins.
|
||||
|
||||
### 🧩 Community Integrations
|
||||
|
||||
Build and share your own Pipecat service integrations! Browse existing [community integrations](https://docs.pipecat.ai/api-reference/server/services/community-integrations) or check out our [guide](COMMUNITY_INTEGRATIONS.md) to create your own.
|
||||
Build and share your own Pipecat service integrations! Browse existing [community integrations](https://docs.pipecat.ai/server/services/community-integrations) or check out our [guide](COMMUNITY_INTEGRATIONS.md) to create your own.
|
||||
|
||||
### 📺️ Pipecat TV Channel
|
||||
|
||||
@@ -83,28 +79,28 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/simple-chatbot/image.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/storytelling-chatbot/image.png" width="400" /></a>
|
||||
<br/>
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/daily-multi-translation"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/daily-multi-translation/image.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/translation-chatbot/image.png" width="400" /></a>
|
||||
<a href="https://github.com/pipecat-ai/pipecat/blob/main/examples/vision/vision-moondream.py"><img src="https://github.com/pipecat-ai/pipecat/blob/main/examples/assets/moondream.png" width="400" /></a>
|
||||
</p>
|
||||
|
||||
## 🧩 Available services
|
||||
|
||||
| Category | Services |
|
||||
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/api-reference/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/api-reference/server/services/stt/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/api-reference/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/api-reference/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/api-reference/server/services/stt/gladia), [Google](https://docs.pipecat.ai/api-reference/server/services/stt/google), [Gradium](https://docs.pipecat.ai/api-reference/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/api-reference/server/services/stt/groq), [Mistral](https://docs.pipecat.ai/api-reference/server/services/stt/mistral), [NVIDIA](https://docs.pipecat.ai/api-reference/server/services/stt/nvidia), [OpenAI (Whisper)](https://docs.pipecat.ai/api-reference/server/services/stt/openai), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/api-reference/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/api-reference/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/api-reference/server/services/stt/whisper), [xAI](https://docs.pipecat.ai/api-reference/server/services/stt/xai) |
|
||||
| LLMs | [Anthropic](https://docs.pipecat.ai/api-reference/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/api-reference/server/services/llm/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/api-reference/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/api-reference/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/api-reference/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/api-reference/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/api-reference/server/services/llm/grok), [Groq](https://docs.pipecat.ai/api-reference/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/api-reference/server/services/llm/mistral), [Nebius](https://docs.pipecat.ai/api-reference/server/services/llm/nebius), [Novita](https://docs.pipecat.ai/api-reference/server/services/llm/novita), [NVIDIA NIM](https://docs.pipecat.ai/api-reference/server/services/llm/nvidia), [Ollama](https://docs.pipecat.ai/api-reference/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/llm/openai), [OpenAI Responses](https://docs.pipecat.ai/api-reference/server/services/llm/openai-responses), [OpenRouter](https://docs.pipecat.ai/api-reference/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/api-reference/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/api-reference/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/api-reference/server/services/llm/sambanova), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/llm/sarvam), [Together AI](https://docs.pipecat.ai/api-reference/server/services/llm/together) |
|
||||
| Text-to-Speech | [Async](https://docs.pipecat.ai/api-reference/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/api-reference/server/services/tts/aws), [Azure](https://docs.pipecat.ai/api-reference/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/api-reference/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/api-reference/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/api-reference/server/services/tts/fish), [Google](https://docs.pipecat.ai/api-reference/server/services/tts/google), [Gradium](https://docs.pipecat.ai/api-reference/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/api-reference/server/services/tts/groq), [Hume](https://docs.pipecat.ai/api-reference/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/api-reference/server/services/tts/inworld), [Kokoro](https://docs.pipecat.ai/api-reference/server/services/tts/kokoro), [LMNT](https://docs.pipecat.ai/api-reference/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/api-reference/server/services/tts/minimax), [Mistral](https://docs.pipecat.ai/api-reference/server/services/tts/mistral), [Neuphonic](https://docs.pipecat.ai/api-reference/server/services/tts/neuphonic), [NVIDIA](https://docs.pipecat.ai/api-reference/server/services/tts/nvidia), [OpenAI](https://docs.pipecat.ai/api-reference/server/services/tts/openai), [Piper](https://docs.pipecat.ai/api-reference/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/api-reference/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/api-reference/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/api-reference/server/services/tts/sarvam), [Smallest](https://docs.pipecat.ai/api-reference/server/services/tts/smallest), [Soniox](https://docs.pipecat.ai/api-reference/server/services/tts/soniox), [Speechmatics](https://docs.pipecat.ai/api-reference/server/services/tts/speechmatics), [xAI](https://docs.pipecat.ai/api-reference/server/services/tts/xai), [XTTS](https://docs.pipecat.ai/api-reference/server/services/tts/xtts) |
|
||||
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/api-reference/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/api-reference/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/api-reference/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/api-reference/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/api-reference/server/services/s2s/ultravox), |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/api-reference/server/services/transport/fastapi-websocket), [LiveKit (WebRTC)](https://docs.pipecat.ai/api-reference/server/services/transport/livekit), [SmallWebRTCTransport](https://docs.pipecat.ai/api-reference/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/api-reference/server/services/transport/websocket-server), [WhatsApp](https://docs.pipecat.ai/api-reference/server/services/transport/whatsapp), Local |
|
||||
| Serializers | [Exotel](https://docs.pipecat.ai/api-reference/server/services/serializers/exotel), [Genesys](https://docs.pipecat.ai/api-reference/server/services/serializers/genesys), [Plivo](https://docs.pipecat.ai/api-reference/server/services/serializers/plivo), [Twilio](https://docs.pipecat.ai/api-reference/server/services/serializers/twilio), [Telnyx](https://docs.pipecat.ai/api-reference/server/services/serializers/telnyx), [Vonage](https://docs.pipecat.ai/api-reference/server/services/serializers/vonage) |
|
||||
| Video | [HeyGen](https://docs.pipecat.ai/api-reference/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/api-reference/server/services/transport/lemonslice), [Tavus](https://docs.pipecat.ai/api-reference/server/services/video/tavus), [Simli](https://docs.pipecat.ai/api-reference/server/services/video/simli) |
|
||||
| Memory | [mem0](https://docs.pipecat.ai/api-reference/server/services/memory/mem0) |
|
||||
| Vision & Image | [fal](https://docs.pipecat.ai/api-reference/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/api-reference/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/api-reference/server/services/vision/moondream) |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/api-reference/server/utilities/audio/silero-vad-analyzer), [Krisp Viva](https://docs.pipecat.ai/guides/features/krisp-viva), [Koala](https://docs.pipecat.ai/api-reference/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/api-reference/server/utilities/audio/aic-filter), [RNNoise](https://docs.pipecat.ai/api-reference/server/utilities/audio/rnnoise-filter) |
|
||||
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/api-reference/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/api-reference/server/services/analytics/sentry) |
|
||||
| Community | [Browse community integrations →](https://docs.pipecat.ai/api-reference/server/services/community-integrations) |
|
||||
| Category | Services |
|
||||
| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
|
||||
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [Nebius](https://docs.pipecat.ai/server/services/llm/nebius), [Novita](https://docs.pipecat.ai/server/services/llm/novita), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nvidia), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/llm/sarvam), [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
|
||||
| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [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), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [Kokoro](https://docs.pipecat.ai/server/services/tts/kokoro), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Smallest](https://docs.pipecat.ai/server/services/tts/smallest), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [xAI](https://docs.pipecat.ai/server/services/tts/xai), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
|
||||
| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), |
|
||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [LiveKit (WebRTC)](https://docs.pipecat.ai/server/services/transport/livekit), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), [WhatsApp](https://docs.pipecat.ai/server/services/transport/whatsapp), Local |
|
||||
| Serializers | [Exotel](https://docs.pipecat.ai/server/services/serializers/exotel), [Genesys](https://docs.pipecat.ai/server/services/serializers/genesys), [Plivo](https://docs.pipecat.ai/server/services/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/services/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/services/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/services/serializers/vonage) |
|
||||
| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/transport/lemonslice), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
|
||||
| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
|
||||
| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
|
||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp Viva](https://docs.pipecat.ai/guides/features/krisp-viva), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter), [RNNoise](https://docs.pipecat.ai/server/utilities/audio/rnnoise-filter) |
|
||||
| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
|
||||
| Community | [Browse community integrations →](https://docs.pipecat.ai/server/services/community-integrations) |
|
||||
|
||||
📚 [View full services documentation →](https://docs.pipecat.ai/api-reference/server/services/supported-services)
|
||||
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
|
||||
|
||||
## ⚡ Getting started
|
||||
|
||||
@@ -153,8 +149,8 @@ You can get started with Pipecat running on your local machine, then move your a
|
||||
|
||||
### Prerequisites
|
||||
|
||||
**Minimum Python Version:** 3.11
|
||||
**Recommended Python Version:** >= 3.12
|
||||
**Minimum Python Version:** 3.10
|
||||
**Recommended Python Version:** 3.12
|
||||
|
||||
### Setup Steps
|
||||
|
||||
|
||||
1
changelog/4141.added.md
Normal file
1
changelog/4141.added.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Added WebSocket-based `OpenAIResponsesLLMService` as the new default for the OpenAI Responses API. It maintains a persistent connection to `wss://api.openai.com/v1/responses` and automatically uses `previous_response_id` to send only incremental context, falling back to full context on reconnection or cache miss. The previous HTTP-based implementation is now available as `OpenAIResponsesHttpLLMService`.
|
||||
1
changelog/4191.removed.md
Normal file
1
changelog/4191.removed.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `OpenPipeLLMService` and the `openpipe` extra. OpenPipe was acquired by CoreWeave and the package is no longer maintained. If you were using `openpipe` as an LLM provider, switch to the underlying provider directly (e.g. `openai`). The OpenPipe interface can still be used with `OpenAILLMService` by specifying a `base_url`.
|
||||
1
changelog/4192.changed.md
Normal file
1
changelog/4192.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Updated `langchain` extra to require langchain 1.x (from 0.3.x), langchain-community 0.4.x (from 0.3.x), and langchain-openai 1.x (from 0.3.x). If you pin these packages in your project, update your pins accordingly.
|
||||
1
changelog/4202.fixed.md
Normal file
1
changelog/4202.fixed.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed `InworldHttpTTSService` streaming responses crashing with `UnicodeDecodeError` when multi-byte UTF-8 characters were split across chunk boundaries. This caused TTS audio to cut off mid-sentence intermittently.
|
||||
1
changelog/4203.fixed.md
Normal file
1
changelog/4203.fixed.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed a crash (`JSONDecodeError`) when a user interruption occurs while the LLM is streaming function call arguments. Previously, the incomplete JSON arguments were passed directly to `json.loads()`, causing an unhandled exception. Affected services: OpenAI, Google (OpenAI-compatible), and SambaNova.
|
||||
1
changelog/4204.removed.10.md
Normal file
1
changelog/4204.removed.10.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `observers` field from `PipelineParams`. Pass observers directly to `PipelineTask` constructor instead.
|
||||
1
changelog/4204.removed.11.md
Normal file
1
changelog/4204.removed.11.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `on_pipeline_ended`, `on_pipeline_cancelled`, and `on_pipeline_stopped` events from `PipelineTask`. Use `on_pipeline_finished` instead.
|
||||
1
changelog/4204.removed.12.md
Normal file
1
changelog/4204.removed.12.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `AudioBufferProcessor.user_continuous_stream` parameter. Use `user_audio_passthrough` instead.
|
||||
1
changelog/4204.removed.13.md
Normal file
1
changelog/4204.removed.13.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `camera_in_enabled`, `camera_in_is_live`, `camera_in_width`, `camera_in_height`, `camera_out_enabled`, `camera_out_is_live`, `camera_out_width`, `camera_out_height`, and `camera_out_color` transport params. Use the `video_in_*` and `video_out_*` equivalents instead.
|
||||
1
changelog/4204.removed.14.md
Normal file
1
changelog/4204.removed.14.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `RTVIObserver.errors_enabled` parameter.
|
||||
1
changelog/4204.removed.15.md
Normal file
1
changelog/4204.removed.15.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `vad_enabled` and `vad_audio_passthrough` transport params.
|
||||
1
changelog/4204.removed.16.md
Normal file
1
changelog/4204.removed.16.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `TTSService.say()`. Push a `TTSSpeakFrame` into the pipeline instead.
|
||||
1
changelog/4204.removed.17.md
Normal file
1
changelog/4204.removed.17.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `DailyRunner.configure_with_args()`. Use `PipelineRunner` with `RunnerArguments` instead.
|
||||
1
changelog/4204.removed.18.md
Normal file
1
changelog/4204.removed.18.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated RTVI models, frames, and processor methods including `RTVIConfig`, `RTVIServiceConfig`, `RTVIServiceOptionConfig`, various `RTVI*Data` models, `RTVIActionFrame`, and `RTVIProcessor.handle_function_call`/`handle_function_call_start`. Use the updated RTVI processor API instead.
|
||||
1
changelog/4204.removed.19.md
Normal file
1
changelog/4204.removed.19.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `FrameProcessor.wait_for_task()`. Use `create_task()` and manage tasks with the built-in `TaskManager` instead.
|
||||
1
changelog/4204.removed.2.md
Normal file
1
changelog/4204.removed.2.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `KrispFilter`. The `krisp` extra has been removed from `pyproject.toml`.
|
||||
1
changelog/4204.removed.20.md
Normal file
1
changelog/4204.removed.20.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `LLMService.request_image_frame()`. Push a `UserImageRequestFrame` instead.
|
||||
1
changelog/4204.removed.3.md
Normal file
1
changelog/4204.removed.3.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `create_default_resampler()` from `pipecat.audio.utils`.
|
||||
1
changelog/4204.removed.4.md
Normal file
1
changelog/4204.removed.4.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `FalSmartTurnAnalyzer` and `LocalSmartTurnAnalyzer`.
|
||||
1
changelog/4204.removed.5.md
Normal file
1
changelog/4204.removed.5.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated transport frames: `TransportMessageFrame`, `TransportMessageUrgentFrame`, `InputTransportMessageUrgentFrame`, `DailyTransportMessageFrame`, and `DailyTransportMessageUrgentFrame`. Use `OutputTransportMessageFrame`, `OutputTransportMessageUrgentFrame`, `InputTransportMessageFrame`, `DailyOutputTransportMessageFrame`, and `DailyOutputTransportMessageUrgentFrame` instead.
|
||||
1
changelog/4204.removed.6.md
Normal file
1
changelog/4204.removed.6.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `KeypadEntryFrame` alias.
|
||||
1
changelog/4204.removed.7.md
Normal file
1
changelog/4204.removed.7.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated interruption frames: `StartInterruptionFrame` and `BotInterruptionFrame`. Use `InterruptionFrame` and `InterruptionTaskFrame` instead.
|
||||
1
changelog/4204.removed.8.md
Normal file
1
changelog/4204.removed.8.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `LLMService.start_callback` parameter. Register an `on_llm_response_start` event handler instead.
|
||||
1
changelog/4204.removed.9.md
Normal file
1
changelog/4204.removed.9.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed single-argument function call support from `LLMService`. Functions must use named parameters instead of a single `arguments` parameter.
|
||||
1
changelog/4204.removed.md
Normal file
1
changelog/4204.removed.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `NoisereduceFilter`. Use system-level noise reduction or a service-based alternative instead.
|
||||
1
changelog/4208.removed.10.md
Normal file
1
changelog/4208.removed.10.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.riva` package. Use `pipecat.services.nvidia.stt` and `pipecat.services.nvidia.tts` instead (`RivaSTTService` → `NvidiaSTTService`, `RivaTTSService` → `NvidiaTTSService`).
|
||||
1
changelog/4208.removed.11.md
Normal file
1
changelog/4208.removed.11.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.nim` package. Use `pipecat.services.nvidia.llm` instead (`NimLLMService` → `NvidiaLLMService`).
|
||||
1
changelog/4208.removed.2.md
Normal file
1
changelog/4208.removed.2.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.gemini_multimodal_live` package. Use `pipecat.services.google.gemini_live` instead. Note that class names no longer include "Multimodal" (e.g. `GeminiMultimodalLiveLLMService` → `GeminiLiveLLMService`).
|
||||
1
changelog/4208.removed.3.md
Normal file
1
changelog/4208.removed.3.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.aws_nova_sonic` package. Use `pipecat.services.aws.nova_sonic` instead.
|
||||
1
changelog/4208.removed.4.md
Normal file
1
changelog/4208.removed.4.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.openai_realtime` package. Use `pipecat.services.openai.realtime` instead.
|
||||
1
changelog/4208.removed.5.md
Normal file
1
changelog/4208.removed.5.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `OpenAIRealtimeBetaLLMService` and `AzureRealtimeBetaLLMService`. Use `OpenAIRealtimeLLMService` and `AzureRealtimeLLMService` from `pipecat.services.openai.realtime` and `pipecat.services.azure.realtime` instead.
|
||||
1
changelog/4208.removed.6.md
Normal file
1
changelog/4208.removed.6.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.deepgram.stt_sagemaker` and `pipecat.services.deepgram.tts_sagemaker` modules. Use `pipecat.services.deepgram.sagemaker.stt` and `pipecat.services.deepgram.sagemaker.tts` instead.
|
||||
1
changelog/4208.removed.7.md
Normal file
1
changelog/4208.removed.7.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `GoogleLLMOpenAIBetaService` from `pipecat.services.google.openai`. Use `GoogleLLMService` from `pipecat.services.google.llm` instead.
|
||||
1
changelog/4208.removed.8.md
Normal file
1
changelog/4208.removed.8.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.google.llm_vertex` module. Use `pipecat.services.google.vertex.llm` instead.
|
||||
1
changelog/4208.removed.9.md
Normal file
1
changelog/4208.removed.9.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.google.gemini_live.llm_vertex` module. Use `pipecat.services.google.gemini_live.vertex.llm` instead.
|
||||
1
changelog/4208.removed.md
Normal file
1
changelog/4208.removed.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated `pipecat.services.ai_services` module. Import from `pipecat.services.ai_service`, `pipecat.services.llm_service`, `pipecat.services.stt_service`, `pipecat.services.tts_service`, etc. instead.
|
||||
1
changelog/4209.changed.md
Normal file
1
changelog/4209.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- Changed `GrokLLMService` default model from `grok-3-beta` to `grok-3`, now that the model is generally available.
|
||||
1
changelog/4213.changed.md
Normal file
1
changelog/4213.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- `GoogleImageGenService` now defaults to `imagen-4.0-generate-001` (previously `imagen-3.0-generate-002`).
|
||||
1
changelog/4215.changed.md
Normal file
1
changelog/4215.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ `BaseOpenAILLMService.get_chat_completions()` now accepts an `LLMContext` instead of `OpenAILLMInvocationParams`. If you override this method, update your signature accordingly.
|
||||
22
changelog/4215.removed.2.md
Normal file
22
changelog/4215.removed.2.md
Normal file
@@ -0,0 +1,22 @@
|
||||
- ⚠️ Removed deprecated service-specific context and aggregator machinery, which was superseded by the universal `LLMContext` system.
|
||||
|
||||
Service-specific classes removed: `AnthropicLLMContext`, `AnthropicContextAggregatorPair`, `AWSBedrockLLMContext`, `AWSBedrockContextAggregatorPair`, `OpenAIContextAggregatorPair`, and their user/assistant aggregators. Also removed `create_context_aggregator()` from `LLMService`, `OpenAILLMService`, `AnthropicLLMService`, and `AWSBedrockLLMService`.
|
||||
|
||||
Base aggregator classes removed (from `pipecat.processors.aggregators.llm_response`): `BaseLLMResponseAggregator`, `LLMContextResponseAggregator`, `LLMUserContextAggregator`, `LLMAssistantContextAggregator`, `LLMUserResponseAggregator`, `LLMAssistantResponseAggregator`.
|
||||
|
||||
From the developer's point of view, migrating will usually be a matter of going from this:
|
||||
|
||||
```python
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
```
|
||||
|
||||
To this:
|
||||
|
||||
```python
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
|
||||
|
||||
context = LLMContext(messages, tools)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
```
|
||||
1
changelog/4215.removed.3.md
Normal file
1
changelog/4215.removed.3.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated frame types `LLMMessagesFrame` and `OpenAILLMContextAssistantTimestampFrame` from `pipecat.frames.frames`. Instead of `LLMMessagesFrame`, use `LLMContextFrame` with the new messages, or `LLMMessagesUpdateFrame` with `run_llm=True`.
|
||||
1
changelog/4215.removed.4.md
Normal file
1
changelog/4215.removed.4.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `GatedOpenAILLMContextAggregator` (from `pipecat.processors.aggregators.gated_open_ai_llm_context`). Use `GatedLLMContextAggregator` (from `pipecat.processors.aggregators.gated_llm_context`) instead.
|
||||
1
changelog/4215.removed.5.md
Normal file
1
changelog/4215.removed.5.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed `VisionImageFrameAggregator` (from `pipecat.processors.aggregators.vision_image_frame`). Vision/image handling is now built into `LLMContext` (from `pipecat.processors.aggregators.llm_context`). See the `12*` examples for the recommended replacement pattern.
|
||||
1
changelog/4215.removed.6.md
Normal file
1
changelog/4215.removed.6.md
Normal file
@@ -0,0 +1 @@
|
||||
- ⚠️ Removed deprecated compatibility modules: `pipecat.services.openai_realtime_beta` (use `pipecat.services.openai.realtime`), `pipecat.services.openai_realtime.context`, `pipecat.services.openai_realtime.frames`, `pipecat.services.openai.realtime.context`, `pipecat.services.openai.realtime.frames`, `pipecat.services.gemini_multimodal_live` (use `pipecat.services.google.gemini_live`), `pipecat.services.aws_nova_sonic.context` (use `pipecat.services.aws.nova_sonic`), `pipecat.services.google.openai` and `pipecat.services.google.llm_openai` (use `pipecat.services.google.llm`).
|
||||
18
changelog/4215.removed.md
Normal file
18
changelog/4215.removed.md
Normal file
@@ -0,0 +1,18 @@
|
||||
- ⚠️ Removed `OpenAILLMContext`, `OpenAILLMContextFrame`, and `OpenAILLMContext.from_messages()`. Use `LLMContext` (from `pipecat.processors.aggregators.llm_context`) and `LLMContextFrame` (from `pipecat.frames.frames`) instead. All services now exclusively use the universal `LLMContext`.
|
||||
|
||||
From the developer's point of view, migrating will usually be a matter of going from this:
|
||||
|
||||
```python
|
||||
context = OpenAILLMContext(messages, tools)
|
||||
context_aggregator = llm.create_context_aggregator(context)
|
||||
```
|
||||
|
||||
To this:
|
||||
|
||||
```python
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
|
||||
|
||||
context = LLMContext(messages, tools)
|
||||
context_aggregator = LLMContextAggregatorPair(context)
|
||||
```
|
||||
1
changelog/4217.added.2.md
Normal file
1
changelog/4217.added.2.md
Normal file
@@ -0,0 +1 @@
|
||||
- Added `group_parallel_tools` parameter to `LLMService` (default `True`). When `True`, all function calls from the same LLM response batch share a group ID and the LLM is triggered exactly once after the last call completes. Set to `False` to trigger inference independently for each function call result as it arrives.
|
||||
1
changelog/4217.added.md
Normal file
1
changelog/4217.added.md
Normal file
@@ -0,0 +1 @@
|
||||
- Added `is_async=True` support to `register_function()` and `register_direct_function()`. When enabled, the LLM continues the conversation immediately without waiting for the function result. The result is injected back into the context as a `developer` message once available, triggering a new LLM inference at that point.
|
||||
1
changelog/4217.changed.md
Normal file
1
changelog/4217.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- When multiple function calls are returned in a single LLM response, the LLM is now triggered exactly once after the last call in the batch completes, rather than waiting for all function calls.
|
||||
1
changelog/4217.fixed.2.md
Normal file
1
changelog/4217.fixed.2.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed `BaseOutputTransport` discarding pending `UninterruptibleFrame` items (e.g. function-call context updates) when an interruption arrived. The audio task is now kept alive and only interruptible frames are drained when uninterruptible frames are present in the queue.
|
||||
1
changelog/4217.fixed.3.md
Normal file
1
changelog/4217.fixed.3.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed spurious LLM inference being triggered when a function call result arrived while the user was actively speaking. The context frame is now suppressed until the user stops speaking.
|
||||
1
changelog/4217.fixed.md
Normal file
1
changelog/4217.fixed.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed an issue where `UninterruptibleFrame` items queued in `FrameProcessor` could be incorrectly dropped on interruption. Previously only the frame currently being processed was checked; now the entire process queue is scanned so pending uninterruptible frames are always delivered.
|
||||
@@ -1 +0,0 @@
|
||||
- Added a `session_id` field to `RunnerArguments` so bots can log or trace a per-session identifier in local development the same way they can in Pipecat Cloud. The development runner now mints a UUID at every construction site, and paths that already returned a `sessionId` to the caller (Daily `/start`, dial-in webhook) share that same UUID with the runner args instead of generating two. The SmallWebRTC `/api/offer` endpoint also accepts an optional `session_id` query parameter so the `/sessions/{session_id}/...` proxy can thread it through.
|
||||
@@ -1 +0,0 @@
|
||||
- Updated the default `SonioxTTSService` model from `tts-rt-v1-preview` to the generally available `tts-rt-v1`.
|
||||
@@ -1 +0,0 @@
|
||||
- Added a `max_buffer_delay_ms` constructor argument to `CartesiaTTSService` for controlling Cartesia's server-side text buffering. When unset, Pipecat picks a sensible default based on `text_aggregation_mode`: `0` in `SENTENCE` mode (custom buffering — avoids stacking client-side aggregation on top of Cartesia's default 3000ms server buffer) and unset in `TOKEN` mode (Cartesia's managed buffering applies). Pass an explicit value (0–5000ms) to override.
|
||||
@@ -1 +0,0 @@
|
||||
- Default `cartesia_version` for `CartesiaTTSService` bumped from `2025-04-16` to `2026-03-01`, matching `CartesiaHttpTTSService` and unlocking the `use_normalized_timestamps` and `max_buffer_delay_ms` fields.
|
||||
@@ -1 +0,0 @@
|
||||
- ⚠️ `CartesiaTTSService` now sends `use_normalized_timestamps: true` instead of the deprecated `use_original_timestamps` field. Word timestamps now reflect what was actually spoken (post text-normalization and pronunciation-dictionary substitution), matching the convention Pipecat uses for ElevenLabs. This is a behavior change for `sonic-3` users, who were previously receiving timestamps tied to the input transcript.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed `CartesiaHttpTTSService` pushing two `ErrorFrame`s on a non-200 response — one with the API's error text and a second, less informative "Unknown error" frame from the outer exception handler. It now pushes a single frame that includes the HTTP status code and returns cleanly.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed Cartesia tag helpers (`SPELL`, `EMOTION_TAG`, `PAUSE_TAG`, `VOLUME_TAG`, `SPEED_TAG`) raising `TypeError` when called on an instance (e.g. `tts.SPELL("hi")`). They're now `@staticmethod` and callable from both the class and an instance.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed `CartesiaTTSService` surfacing `flush_done` messages from Cartesia as `ErrorFrame`s. The latest API emits a `flush_done` per transcript when server-side buffering is disabled; Pipecat now consumes them silently since each turn already has its own `context_id`.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed an issue where `LocalSmartTurnAnalyzerV3` was imported unconditionally for user turn stop strategies. It is now only imported when `default_user_turn_stop_strategies()` is called. This improves startup time and removes the `transformers` "PyTorch/TensorFlow/Flax not found" warning when the default stop strategies are not used.
|
||||
@@ -1 +0,0 @@
|
||||
- Broadened `tool_resources` to `app_resources` for easy access not just in tool handlers but in other places like custom `FrameProcessor`s. Three changes: a rename (`tool_resources` → `app_resources`), a new `app_resources` property on `PipelineTask`, and a new `pipeline_task` property on `FrameProcessor`. Tool handlers now read `params.app_resources`; custom processors read `self.pipeline_task.app_resources`. The previous `tool_resources` aliases (on `PipelineTask`, `FunctionCallParams`, and `FrameProcessorSetup`) keep working but are deprecated as of 1.2.0 and emit `DeprecationWarning`s.
|
||||
@@ -1 +0,0 @@
|
||||
- Added a `mip_opt_out` constructor argument to `DeepgramTTSService` and `DeepgramHttpTTSService` so callers can opt out of the Deepgram Model Improvement Program. When set, the value is forwarded to Deepgram as a query parameter on the speak request. Defaults to `None`, which preserves the existing behavior. See https://dpgr.am/deepgram-mip for pricing implications before enabling.
|
||||
@@ -1 +0,0 @@
|
||||
- Added support to `AWSNovaSonicLLMService` for the new "async tool call" mechanism activated by `cancel_on_interruption=False`, which includes delivering results asynchronously, delivering result streams, and cancelling running async tools. Support for the other major realtime services (`GeminiLiveLLMService`, `OpenAIRealtimeLLMService`) will be added in a follow-up PR.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed a regression in `AWSNovaSonicLLMService` where `cancel_on_interruption=False` (which previously worked under the old async-tool-call mechanism, by simply avoiding discarding tool calls on interruptions) stopped working after the introduction of the new "async tool call" mechanism.
|
||||
@@ -5,7 +5,7 @@
|
||||
|
||||
{% for text, values in sections[section][category].items() %}
|
||||
{{ text }}
|
||||
(PR {{ values|join(', ') }})
|
||||
(PR {{ values|join(', ') }})
|
||||
|
||||
{% endfor %}
|
||||
{% endfor %}
|
||||
|
||||
@@ -1,60 +1,108 @@
|
||||
# Pipecat API Documentation
|
||||
# Pipecat Documentation
|
||||
|
||||
This directory contains the source files for auto-generating Pipecat's API reference documentation.
|
||||
This directory contains the source files for auto-generating Pipecat's server API reference documentation.
|
||||
|
||||
## Setup
|
||||
|
||||
1. Install documentation dependencies:
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
2. Make the build scripts executable:
|
||||
|
||||
```bash
|
||||
chmod +x build-docs.sh rtd-test.py
|
||||
```
|
||||
|
||||
## Building Documentation
|
||||
|
||||
From this directory:
|
||||
From this directory, you can build the documentation in several ways:
|
||||
|
||||
### Local Build
|
||||
|
||||
```bash
|
||||
# Build docs (warnings shown but don't fail the build)
|
||||
cd docs/api && uv run ./build-docs.sh
|
||||
# Using the build script (automatically opens docs when done)
|
||||
./build-docs.sh
|
||||
|
||||
# Build with strict mode (warnings treated as errors)
|
||||
cd docs/api && uv run ./build-docs.sh --strict
|
||||
# Or directly with sphinx-build
|
||||
sphinx-build -b html . _build/html -W --keep-going
|
||||
```
|
||||
|
||||
The build script will:
|
||||
### ReadTheDocs Test Build
|
||||
|
||||
1. Install documentation dependencies via `uv sync --group docs`
|
||||
2. Clean previous build output
|
||||
3. Run `sphinx-build` to generate HTML documentation
|
||||
4. Open the result in your browser (macOS)
|
||||
To test the documentation build process exactly as it would run on ReadTheDocs:
|
||||
|
||||
```bash
|
||||
./rtd-test.py
|
||||
```
|
||||
|
||||
This script:
|
||||
|
||||
- Creates a fresh virtual environment
|
||||
- Installs all dependencies as specified in requirements files
|
||||
- Handles conflicting dependencies (like grpcio versions for Riva)
|
||||
- Builds the documentation in an isolated environment
|
||||
- Provides detailed logging of the build process
|
||||
|
||||
Use this script to verify your documentation will build correctly on ReadTheDocs before pushing changes.
|
||||
|
||||
## Viewing Documentation
|
||||
|
||||
The built documentation will be available at `_build/html/index.html`. To open:
|
||||
|
||||
```bash
|
||||
# On MacOS
|
||||
open _build/html/index.html
|
||||
|
||||
# On Linux
|
||||
xdg-open _build/html/index.html
|
||||
|
||||
# On Windows
|
||||
start _build/html/index.html
|
||||
```
|
||||
|
||||
## Directory Structure
|
||||
|
||||
```
|
||||
.
|
||||
├── api/ # Auto-generated API documentation (created during build)
|
||||
├── _build/ # Built documentation output
|
||||
├── conf.py # Sphinx configuration (mock imports, extensions, etc.)
|
||||
├── api/ # Auto-generated API documentation
|
||||
├── _build/ # Built documentation
|
||||
├── _static/ # Static files (images, css, etc.)
|
||||
├── conf.py # Sphinx configuration
|
||||
├── index.rst # Main documentation entry point
|
||||
├── requirements-base.txt # Base documentation dependencies
|
||||
├── requirements-riva.txt # Riva-specific dependencies
|
||||
├── build-docs.sh # Local build script
|
||||
└── rtd-test.sh # ReadTheDocs test build script (uses pip, not uv)
|
||||
└── rtd-test.py # ReadTheDocs test build script
|
||||
```
|
||||
|
||||
## How It Works
|
||||
## Notes
|
||||
|
||||
- `conf.py` runs `sphinx-apidoc` during Sphinx's `setup()` phase to generate `.rst` files from Python source
|
||||
- Sphinx autodoc imports each module to extract docstrings
|
||||
- Modules with unavailable dependencies are listed in `autodoc_mock_imports` in `conf.py`
|
||||
- Napoleon extension converts Google-style docstrings to reStructuredText
|
||||
- Documentation is auto-generated from Python docstrings
|
||||
- Service modules are automatically detected and included
|
||||
- The build process matches our ReadTheDocs configuration
|
||||
- Warnings are treated as errors (-W flag) to maintain consistency
|
||||
- The --keep-going flag ensures all errors are reported
|
||||
- Dependencies are split into multiple requirements files to handle version conflicts
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
**Module not appearing in docs:**
|
||||
If you encounter missing service modules:
|
||||
|
||||
1. Check the build output for `autodoc: failed to import` warnings
|
||||
2. If the module has an unresolvable import dependency, add it to `autodoc_mock_imports` in `conf.py`
|
||||
3. Verify the module is importable: `uv run python -c "import pipecat.module.name"`
|
||||
1. Verify the service is installed with its extras: `pip install pipecat-ai[service-name]`
|
||||
2. Check the build logs for import errors
|
||||
3. Ensure the service module is properly initialized in the package
|
||||
4. Run `./rtd-test.py` to test in an isolated environment matching ReadTheDocs
|
||||
|
||||
**Duplicate object warnings:**
|
||||
For dependency conflicts:
|
||||
|
||||
These come from re-export modules or Sphinx discovering the same class through multiple import paths. Usually cosmetic.
|
||||
1. Check the requirements files for version specifications
|
||||
2. Use `rtd-test.py` to verify dependency resolution
|
||||
3. Consider adding service-specific requirements files if needed
|
||||
|
||||
**Docstring formatting warnings:**
|
||||
For more information:
|
||||
|
||||
Docstrings use reStructuredText, not Markdown. Common issues:
|
||||
- Use `Example::` with indented code blocks, not `` ```python ``
|
||||
- Ensure blank lines between directive content and subsequent sections
|
||||
- Use `Parameters:` (not `Attributes:`) for dataclass field documentation to avoid duplicate entries
|
||||
- [ReadTheDocs Configuration](.readthedocs.yaml)
|
||||
- [Sphinx Documentation](https://www.sphinx-doc.org/)
|
||||
|
||||
@@ -1,16 +1,8 @@
|
||||
#!/bin/bash
|
||||
|
||||
# Usage: ./build-docs.sh [--strict]
|
||||
# --strict: Treat warnings as errors (default: warnings only)
|
||||
|
||||
SPHINX_OPTS=""
|
||||
if [ "$1" = "--strict" ]; then
|
||||
SPHINX_OPTS="-W --keep-going"
|
||||
fi
|
||||
|
||||
# Build docs using uv
|
||||
echo "Installing dependencies with uv..."
|
||||
uv sync --group docs --all-extras --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra mlx-whisper
|
||||
uv sync --group docs --all-extras --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
|
||||
|
||||
# Check if sphinx-build is available
|
||||
if ! uv run sphinx-build --version &> /dev/null; then
|
||||
@@ -22,7 +14,8 @@ fi
|
||||
rm -rf _build
|
||||
|
||||
echo "Building documentation..."
|
||||
uv run sphinx-build -b html -d _build/doctrees . _build/html $SPHINX_OPTS
|
||||
# Build docs matching ReadTheDocs configuration
|
||||
uv run sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
|
||||
|
||||
if [ $? -eq 0 ]; then
|
||||
echo "Documentation built successfully!"
|
||||
|
||||
@@ -4,19 +4,6 @@ import sys
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
# Fix Pydantic v2 + Sphinx autodoc incompatibility: ConfigDict(extra="allow") fails
|
||||
# during Sphinx's import because __pydantic_extra__ annotation on BaseModel resolves to
|
||||
# `Dict[str, Any] | None` whose get_origin() is Union, not dict. Patch the check to
|
||||
# accept Union-wrapped dict types (i.e., Optional[Dict[str, Any]]).
|
||||
import pydantic._internal._generate_schema as _pydantic_gs
|
||||
|
||||
_ORIG_DICT_TYPES = _pydantic_gs.DICT_TYPES
|
||||
# Expand the accepted types to include Union (Optional[Dict[str, Any]])
|
||||
import types
|
||||
import typing
|
||||
|
||||
_pydantic_gs.DICT_TYPES = [*_ORIG_DICT_TYPES, typing.Union, types.UnionType]
|
||||
|
||||
# Configure logging
|
||||
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
|
||||
logger = logging.getLogger("sphinx-build")
|
||||
@@ -89,6 +76,16 @@ autodoc_mock_imports = [
|
||||
"einops",
|
||||
"intel_extension_for_pytorch",
|
||||
"huggingface_hub",
|
||||
# riva dependencies
|
||||
"riva",
|
||||
"riva.client",
|
||||
"riva.client.Auth",
|
||||
"riva.client.ASRService",
|
||||
"riva.client.StreamingRecognitionConfig",
|
||||
"riva.client.RecognitionConfig",
|
||||
"riva.client.AudioEncoding",
|
||||
"riva.client.proto.riva_tts_pb2",
|
||||
"riva.client.SpeechSynthesisService",
|
||||
# MLX dependencies (Apple Silicon specific)
|
||||
"mlx",
|
||||
"mlx_whisper", # Note: might need underscore format too
|
||||
@@ -110,8 +107,6 @@ autodoc_mock_imports = [
|
||||
"fastapi.middleware",
|
||||
"fastapi.responses",
|
||||
"uvicorn",
|
||||
# Deepgram dependencies
|
||||
"deepgram",
|
||||
]
|
||||
|
||||
# HTML output settings
|
||||
@@ -138,8 +133,6 @@ def import_core_modules():
|
||||
"pipecat.runner",
|
||||
"pipecat.serializers",
|
||||
"pipecat.transcriptions",
|
||||
"pipecat.turns",
|
||||
"pipecat.extensions",
|
||||
"pipecat.utils",
|
||||
]
|
||||
|
||||
@@ -184,6 +177,7 @@ def setup(app):
|
||||
logger.info(f"Source directory: {source_dir}")
|
||||
|
||||
excludes = [
|
||||
str(project_root / "src/pipecat/pipeline/to_be_updated"),
|
||||
str(project_root / "src/pipecat/examples"),
|
||||
str(project_root / "src/pipecat/tests"),
|
||||
"**/test_*.py",
|
||||
|
||||
@@ -32,5 +32,4 @@ Quick Links
|
||||
Services <api/pipecat.services>
|
||||
Transcriptions <api/pipecat.transcriptions>
|
||||
Transports <api/pipecat.transports>
|
||||
Turns <api/pipecat.turns>
|
||||
Utils <api/pipecat.utils>
|
||||
|
||||
10
env.example
10
env.example
@@ -1,5 +1,5 @@
|
||||
# AI-COUSTICS
|
||||
AIC_LICENSE_KEY=...
|
||||
AICOUSTICS_LICENSE_KEY=...
|
||||
|
||||
# Anthropic
|
||||
ANTHROPIC_API_KEY=...
|
||||
@@ -214,10 +214,4 @@ WHATSAPP_PHONE_NUMBER_ID=...
|
||||
WHATSAPP_APP_SECRET=...
|
||||
|
||||
# xAI / Grok
|
||||
XAI_API_KEY=...
|
||||
|
||||
# PIPECAT_SCTP_MAX_CHUNK_SIZE controls the maximum SCTP DATA-chunk payload
|
||||
# size (bytes) used by aiortc's data channel. The default is 1100.
|
||||
# All the details here:
|
||||
# https://docs.pipecat.ai/api-reference/server/services/transport/small-webrtc#pipecat_sctp_max_chunk_size
|
||||
#PIPECAT_SCTP_MAX_CHUNK_SIZE=1100
|
||||
XAI_API_KEY=...
|
||||
@@ -34,7 +34,7 @@ from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
||||
load_dotenv(override=True)
|
||||
|
||||
OFFICE_SOUND_FILE = os.path.join(
|
||||
os.path.dirname(__file__), "../assets", "office-ambience-24000-mono.mp3"
|
||||
os.path.dirname(__file__), "assets", "office-ambience-24000-mono.mp3"
|
||||
)
|
||||
|
||||
# We use lambdas to defer transport parameter creation until the transport
|
||||
@@ -71,17 +71,17 @@ transport_params = {
|
||||
|
||||
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
|
||||
@@ -108,17 +108,17 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"], audio_passthrough=True)
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"), audio_passthrough=True)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121",
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
|
||||
@@ -102,17 +102,17 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
|
||||
@@ -89,10 +89,10 @@ async def get_current_weather(params: FunctionCallParams):
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info("Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
@@ -109,7 +109,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
|
||||
# Primary LLM for conversation (could be any provider)
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction=system_prompt,
|
||||
),
|
||||
@@ -117,7 +117,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
|
||||
# Dedicated cheap/fast LLM for summarization only
|
||||
summarization_llm = GoogleLLMService(
|
||||
api_key=os.environ["GOOGLE_API_KEY"],
|
||||
api_key=os.getenv("GOOGLE_API_KEY"),
|
||||
settings=GoogleLLMService.Settings(
|
||||
model="gemini-2.5-flash",
|
||||
),
|
||||
|
||||
@@ -36,7 +36,7 @@ from pipecat.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||||
from pipecat.services.google.llm import GoogleLLMService
|
||||
from pipecat.services.google import GoogleLLMService
|
||||
from pipecat.services.llm_service import FunctionCallParams
|
||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.daily.transport import DailyParams
|
||||
@@ -77,17 +77,17 @@ async def get_current_weather(params: FunctionCallParams):
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info("Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = GoogleLLMService(
|
||||
api_key=os.environ["GOOGLE_API_KEY"],
|
||||
api_key=os.getenv("GOOGLE_API_KEY"),
|
||||
settings=GoogleLLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You have access to tools to get the current weather - use them when relevant.",
|
||||
),
|
||||
|
||||
@@ -72,10 +72,10 @@ async def summarize_conversation(params: FunctionCallParams):
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info("Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
@@ -91,7 +91,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
"""
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction=system_prompt,
|
||||
),
|
||||
|
||||
@@ -77,17 +77,17 @@ async def get_current_weather(params: FunctionCallParams):
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info("Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You have access to tools to get the current weather - use them when relevant.",
|
||||
),
|
||||
|
||||
@@ -1,327 +0,0 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Example demonstrating ``PipelineTask(app_resources=...)``.
|
||||
|
||||
``app_resources`` is an application-defined bag of anything your
|
||||
application code may want to share across a session: database handles,
|
||||
HTTP clients, feature flags, per-user state, observability clients,
|
||||
in-memory caches — whatever fits your app. Pipecat passes it through
|
||||
untouched and exposes it as ``task.app_resources``, so any code with a
|
||||
handle on the task can read or mutate it.
|
||||
|
||||
Two of the convenience aliases exercised below:
|
||||
|
||||
- Tool handlers read it from ``FunctionCallParams.app_resources``.
|
||||
- Custom ``FrameProcessor`` subclasses read it from
|
||||
``self.pipeline_task.app_resources``.
|
||||
|
||||
This example uses two small loggers as stand-ins for that "shared thing":
|
||||
``ToolCallLogger`` (written from tool handlers) and
|
||||
``TranscriptionLogger`` (written from a custom ``FrameProcessor`` that
|
||||
sits in the pipeline). A real app might just as easily pass a Postgres
|
||||
pool, a Redis client, a Stripe SDK instance, or any combination thereof.
|
||||
The mechanics shown here — construct once, hand to the task, read it
|
||||
from each site, inspect it after the session — are the same regardless
|
||||
of what you put in.
|
||||
|
||||
We bundle resources in a typed ``AppResources`` dataclass and cast back
|
||||
to it at each read site. Pipecat doesn't care what type you pass (a
|
||||
plain dict works too), but a typed container gives you autocomplete and
|
||||
refactor safety instead of dict-by-string-key lookups.
|
||||
"""
|
||||
|
||||
import json
|
||||
import os
|
||||
from collections.abc import Mapping
|
||||
from dataclasses import dataclass
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any, cast
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.adapters.schemas.function_schema import FunctionSchema
|
||||
from pipecat.adapters.schemas.tools_schema import ToolsSchema
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import Frame, LLMRunFrame, TranscriptionFrame, TTSSpeakFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
||||
from pipecat.processors.aggregators.llm_response_universal import (
|
||||
LLMContextAggregatorPair,
|
||||
LLMUserAggregatorParams,
|
||||
)
|
||||
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
||||
from pipecat.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||||
from pipecat.services.llm_service import FunctionCallParams
|
||||
from pipecat.services.openai.responses.llm import OpenAIResponsesLLMService
|
||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
||||
from pipecat.transports.daily.transport import DailyParams
|
||||
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
||||
|
||||
load_dotenv(override=True)
|
||||
|
||||
|
||||
class ToolCallLogger:
|
||||
"""Stand-in shared resource — swap for whatever your app actually needs."""
|
||||
|
||||
def __init__(self):
|
||||
"""Initialize the logger with an empty list of recorded calls."""
|
||||
self._calls: list[dict[str, Any]] = []
|
||||
|
||||
def log_tool_call(self, function_name: str, arguments: Mapping[str, Any]) -> None:
|
||||
"""Record a tool call invocation.
|
||||
|
||||
Args:
|
||||
function_name: The name of the tool being invoked.
|
||||
arguments: The arguments passed to the tool.
|
||||
"""
|
||||
entry = {
|
||||
"timestamp": datetime.now(UTC).isoformat(),
|
||||
"function_name": function_name,
|
||||
"arguments": dict(arguments),
|
||||
}
|
||||
self._calls.append(entry)
|
||||
logger.info(f"[ToolCallLogger] {function_name} called with {dict(arguments)}")
|
||||
|
||||
def dump(self) -> str:
|
||||
"""Return all recorded tool calls as a JSON string."""
|
||||
return json.dumps(self._calls, indent=2)
|
||||
|
||||
|
||||
class TranscriptionLogger:
|
||||
"""Records final user transcriptions — written from a custom FrameProcessor."""
|
||||
|
||||
def __init__(self):
|
||||
"""Initialize the logger with an empty list of recorded transcriptions."""
|
||||
self._entries: list[dict[str, Any]] = []
|
||||
|
||||
def log_transcription(self, text: str) -> None:
|
||||
"""Record a transcription.
|
||||
|
||||
Args:
|
||||
text: The transcribed user utterance.
|
||||
"""
|
||||
entry = {
|
||||
"timestamp": datetime.now(UTC).isoformat(),
|
||||
"text": text,
|
||||
}
|
||||
self._entries.append(entry)
|
||||
logger.info(f"[TranscriptionLogger] {text!r}")
|
||||
|
||||
def dump(self) -> str:
|
||||
"""Return all recorded transcriptions as a JSON string."""
|
||||
return json.dumps(self._entries, indent=2)
|
||||
|
||||
|
||||
@dataclass
|
||||
class AppResources:
|
||||
"""Typed container for everything the app shares across this session.
|
||||
|
||||
Add fields here as the app grows (e.g. ``db: AsyncConnection``,
|
||||
``http: httpx.AsyncClient``). Read sites ``cast()`` to this type to
|
||||
get autocomplete and refactor safety:
|
||||
|
||||
- In tools: ``cast(AppResources, params.app_resources)``.
|
||||
- In custom processors: ``cast(AppResources, self.pipeline_task.app_resources)``.
|
||||
"""
|
||||
|
||||
tool_call_logger: ToolCallLogger
|
||||
transcription_logger: TranscriptionLogger
|
||||
|
||||
|
||||
async def fetch_weather_from_api(params: FunctionCallParams):
|
||||
resources = cast(AppResources, params.app_resources)
|
||||
resources.tool_call_logger.log_tool_call(params.function_name, params.arguments)
|
||||
await params.result_callback({"conditions": "nice", "temperature": "75"})
|
||||
|
||||
|
||||
async def fetch_restaurant_recommendation(params: FunctionCallParams):
|
||||
resources = cast(AppResources, params.app_resources)
|
||||
resources.tool_call_logger.log_tool_call(params.function_name, params.arguments)
|
||||
await params.result_callback({"name": "The Golden Dragon"})
|
||||
|
||||
|
||||
class TranscriptionLoggingProcessor(FrameProcessor):
|
||||
"""Logs each final user transcription into the shared app resources.
|
||||
|
||||
Demonstrates the second read site for ``app_resources``: any custom
|
||||
``FrameProcessor`` can reach the same bag every tool handler sees by
|
||||
going through ``self.pipeline_task.app_resources``. ``pipeline_task``
|
||||
is ``None`` until the task sets the processor up, so we guard against
|
||||
that case.
|
||||
"""
|
||||
|
||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||
"""Forward all frames; log final user transcriptions on the way through."""
|
||||
await super().process_frame(frame, direction)
|
||||
|
||||
if isinstance(frame, TranscriptionFrame) and self.pipeline_task is not None:
|
||||
resources = cast(AppResources, self.pipeline_task.app_resources)
|
||||
resources.transcription_logger.log_transcription(frame.text)
|
||||
|
||||
await self.push_frame(frame, direction)
|
||||
|
||||
|
||||
# We use lambdas to defer transport parameter creation until the transport
|
||||
# type is selected at runtime.
|
||||
transport_params = {
|
||||
"daily": lambda: DailyParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
),
|
||||
"twilio": lambda: FastAPIWebsocketParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
),
|
||||
"webrtc": lambda: TransportParams(
|
||||
audio_in_enabled=True,
|
||||
audio_out_enabled=True,
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAIResponsesLLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
settings=OpenAIResponsesLLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
)
|
||||
|
||||
# You can also register a function_name of None to get all functions
|
||||
# sent to the same callback with an additional function_name parameter.
|
||||
llm.register_function("get_current_weather", fetch_weather_from_api)
|
||||
llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
|
||||
|
||||
@llm.event_handler("on_connection_error")
|
||||
async def on_connection_error(service, error):
|
||||
logger.error(f"LLM connection error: {error}")
|
||||
|
||||
@llm.event_handler("on_function_calls_started")
|
||||
async def on_function_calls_started(service, function_calls):
|
||||
# Avoid appending this filler message to the LLM context — it would
|
||||
# alter the conversation history and prevent
|
||||
# OpenAIResponsesLLMService's previous_response_id optimization from
|
||||
# matching, forcing a full context resend.
|
||||
await tts.queue_frame(TTSSpeakFrame("Let me check on that.", append_to_context=False))
|
||||
|
||||
weather_function = FunctionSchema(
|
||||
name="get_current_weather",
|
||||
description="Get the current weather",
|
||||
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 user's location.",
|
||||
},
|
||||
},
|
||||
required=["location", "format"],
|
||||
)
|
||||
restaurant_function = FunctionSchema(
|
||||
name="get_restaurant_recommendation",
|
||||
description="Get a restaurant recommendation",
|
||||
properties={
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
},
|
||||
required=["location"],
|
||||
)
|
||||
tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
|
||||
|
||||
context = LLMContext(tools=tools)
|
||||
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
|
||||
context,
|
||||
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
|
||||
)
|
||||
|
||||
pipeline = Pipeline(
|
||||
[
|
||||
transport.input(),
|
||||
stt,
|
||||
TranscriptionLoggingProcessor(),
|
||||
user_aggregator,
|
||||
llm,
|
||||
tts,
|
||||
transport.output(),
|
||||
assistant_aggregator,
|
||||
]
|
||||
)
|
||||
|
||||
# Keep local handles so we can read collected state after the session
|
||||
# ends; Pipecat never copies or clears the object.
|
||||
tool_call_logger = ToolCallLogger()
|
||||
transcription_logger = TranscriptionLogger()
|
||||
resources = AppResources(
|
||||
tool_call_logger=tool_call_logger,
|
||||
transcription_logger=transcription_logger,
|
||||
)
|
||||
|
||||
task = PipelineTask(
|
||||
pipeline,
|
||||
params=PipelineParams(
|
||||
enable_metrics=True,
|
||||
enable_usage_metrics=True,
|
||||
),
|
||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
||||
app_resources=resources,
|
||||
)
|
||||
|
||||
@transport.event_handler("on_client_connected")
|
||||
async def on_client_connected(transport, client):
|
||||
logger.info(f"Client connected")
|
||||
# Kick off the conversation.
|
||||
context.add_message(
|
||||
{"role": "developer", "content": "Please introduce yourself to the user."}
|
||||
)
|
||||
await task.queue_frames([LLMRunFrame()])
|
||||
|
||||
@transport.event_handler("on_client_disconnected")
|
||||
async def on_client_disconnected(transport, client):
|
||||
logger.info(f"Client disconnected")
|
||||
await task.cancel()
|
||||
|
||||
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
|
||||
|
||||
await runner.run(task)
|
||||
|
||||
# The session has ended; read whatever state the handlers built up.
|
||||
logger.info(f"Tool calls logged during session:\n{tool_call_logger.dump()}")
|
||||
logger.info(f"Transcriptions logged during session:\n{transcription_logger.dump()}")
|
||||
|
||||
|
||||
async def bot(runner_args: RunnerArguments):
|
||||
"""Main bot entry point compatible with Pipecat Cloud."""
|
||||
transport = await create_transport(runner_args, transport_params)
|
||||
await run_bot(transport, runner_args)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from pipecat.runner.run import main
|
||||
|
||||
main()
|
||||
@@ -63,17 +63,17 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
|
||||
@@ -58,24 +58,24 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
openai_llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
)
|
||||
|
||||
groq_llm = GroqLLMService(
|
||||
api_key=os.environ["GROQ_API_KEY"],
|
||||
api_key=os.getenv("GROQ_API_KEY"),
|
||||
settings=GroqLLMService.Settings(
|
||||
system_instruction="You are a very helpful assistant. Your goal is to demonstrate your capabilities in detail in a creative and helpful way.",
|
||||
),
|
||||
|
||||
@@ -63,10 +63,10 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info("Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
@@ -74,7 +74,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
|
||||
# Main LLM — drives the conversation. Its RTVI events reach the client.
|
||||
main_llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
@@ -83,7 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
# Evaluator LLM — silently grades the user's message in the background.
|
||||
# Its RTVI events will be suppressed so the client is unaware of this branch.
|
||||
evaluator_llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
name="EvaluatorLLM",
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a silent quality evaluator. When given a user message, respond with a single JSON object: {'score': <1-5>, 'reason': '<brief reason>'}. Do not respond conversationally.",
|
||||
|
||||
@@ -91,17 +91,17 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
|
||||
@@ -56,10 +56,10 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = DeepgramTTSService(
|
||||
api_key=os.environ["DEEPGRAM_API_KEY"],
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
settings=DeepgramTTSService.Settings(
|
||||
voice="aura-asteria-en",
|
||||
),
|
||||
@@ -68,7 +68,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
|
||||
llm = OpenAILLMService(
|
||||
# To use OpenAI
|
||||
# api_key=os.environ["OPENAI_API_KEY"],
|
||||
# api_key=os.getenv("OPENAI_API_KEY"),
|
||||
# Or, to use a local vLLM (or similar) api server
|
||||
settings=OpenAILLMService.Settings(
|
||||
model="meta-llama/Meta-Llama-3-8B-Instruct",
|
||||
|
||||
@@ -55,17 +55,17 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.",
|
||||
),
|
||||
|
||||
@@ -45,7 +45,7 @@ from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||||
from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
|
||||
from pipecat.frames.frames import LLMRunFrame
|
||||
from pipecat.pipeline.pipeline import Pipeline
|
||||
from pipecat.pipeline.runner import PipelineRunner
|
||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||||
@@ -54,7 +54,6 @@ from pipecat.processors.aggregators.llm_response_universal import (
|
||||
LLMContextAggregatorPair,
|
||||
LLMUserAggregatorParams,
|
||||
)
|
||||
from pipecat.processors.aggregators.llm_text_processor import LLMTextProcessor
|
||||
from pipecat.runner.types import RunnerArguments
|
||||
from pipecat.runner.utils import create_transport
|
||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||||
@@ -101,43 +100,39 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
# Create pattern pair aggregator for voice switching
|
||||
llm_text_aggregator = PatternPairAggregator()
|
||||
pattern_aggregator = PatternPairAggregator()
|
||||
|
||||
# Add pattern for voice switching
|
||||
llm_text_aggregator.add_pattern(
|
||||
pattern_aggregator.add_pattern(
|
||||
type="voice",
|
||||
start_pattern="<voice>",
|
||||
end_pattern="</voice>",
|
||||
action=MatchAction.AGGREGATE,
|
||||
action=MatchAction.REMOVE, # Remove tags from final text
|
||||
)
|
||||
|
||||
# Register handler for voice switching
|
||||
async def on_voice_tag(match: PatternMatch):
|
||||
voice_name = match.text.strip().lower()
|
||||
if voice_name in VOICE_IDS:
|
||||
await llm_text_processor.push_frame(
|
||||
TTSUpdateSettingsFrame(
|
||||
delta=CartesiaTTSService.Settings(voice=VOICE_IDS[voice_name])
|
||||
)
|
||||
)
|
||||
# First flush any existing audio to finish the current context
|
||||
await tts.flush_audio()
|
||||
# Then set the new voice
|
||||
await tts.set_voice(VOICE_IDS[voice_name])
|
||||
logger.info(f"Switched to {voice_name} voice")
|
||||
else:
|
||||
logger.warning(f"Unknown voice: {voice_name}")
|
||||
|
||||
llm_text_aggregator.on_pattern_match("voice", on_voice_tag)
|
||||
pattern_aggregator.on_pattern_match("voice", on_voice_tag)
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
|
||||
# Process LLM text through the pattern aggregator before TTS
|
||||
llm_text_processor = LLMTextProcessor(text_aggregator=llm_text_aggregator)
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
# Initialize TTS with narrator voice as default
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice=VOICE_IDS["narrator"],
|
||||
),
|
||||
skip_aggregator_types=["voice"], # Skip voice tags in TTS speech
|
||||
text_aggregator=pattern_aggregator,
|
||||
)
|
||||
|
||||
# System prompt for storytelling with voice switching
|
||||
@@ -190,7 +185,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue.""
|
||||
|
||||
# Initialize LLM
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction=system_prompt,
|
||||
),
|
||||
@@ -209,8 +204,7 @@ Remember: Use narrator voice for EVERYTHING except the actual quoted dialogue.""
|
||||
stt,
|
||||
user_aggregator,
|
||||
llm,
|
||||
llm_text_processor,
|
||||
tts,
|
||||
tts, # TTS with pattern aggregator
|
||||
transport.output(),
|
||||
assistant_aggregator,
|
||||
]
|
||||
|
||||
@@ -94,19 +94,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
required=["location", "format"],
|
||||
)
|
||||
|
||||
stt_cartesia = CartesiaSTTService(api_key=os.environ["CARTESIA_API_KEY"])
|
||||
stt_deepgram = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt_cartesia = CartesiaSTTService(api_key=os.getenv("CARTESIA_API_KEY"))
|
||||
stt_deepgram = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
# Uses ServiceSwitcherStrategyManual by default
|
||||
stt_switcher = ServiceSwitcher(services=[stt_cartesia, stt_deepgram])
|
||||
|
||||
tts_cartesia = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
tts_deepgram = DeepgramTTSService(
|
||||
api_key=os.environ["DEEPGRAM_API_KEY"],
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
settings=DeepgramTTSService.Settings(
|
||||
voice="aura-2-helena-en",
|
||||
),
|
||||
@@ -117,11 +117,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
system_prompt = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way."
|
||||
|
||||
llm_openai = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(system_instruction=system_prompt),
|
||||
)
|
||||
llm_google = GoogleLLMService(
|
||||
api_key=os.environ["GOOGLE_API_KEY"],
|
||||
api_key=os.getenv("GOOGLE_API_KEY"),
|
||||
settings=GoogleLLMService.Settings(system_instruction=system_prompt),
|
||||
)
|
||||
# Uses ServiceSwitcherStrategyManual by default
|
||||
|
||||
@@ -42,14 +42,14 @@ class SwitchLanguage(ParallelPipeline):
|
||||
self._current_language = "English"
|
||||
|
||||
english_tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
spanish_tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady
|
||||
),
|
||||
@@ -101,7 +101,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(
|
||||
api_key=os.environ["DEEPGRAM_API_KEY"],
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
settings=DeepgramSTTService.Settings(
|
||||
language="multi",
|
||||
),
|
||||
@@ -110,7 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
tts = SwitchLanguage()
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. You can speak the following languages: 'English' and 'Spanish'.",
|
||||
),
|
||||
|
||||
@@ -42,21 +42,21 @@ class SwitchVoices(ParallelPipeline):
|
||||
self._current_voice = "News Lady"
|
||||
|
||||
news_lady = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="bf991597-6c13-47e4-8411-91ec2de5c466", # Newslady
|
||||
),
|
||||
)
|
||||
|
||||
british_lady = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
barbershop_man = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="a0e99841-438c-4a64-b679-ae501e7d6091", # Barbershop Man
|
||||
),
|
||||
@@ -114,12 +114,12 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = SwitchVoices()
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative and helpful way. You can do the following voices: 'News Lady', 'British Lady' and 'Barbershop Man'.",
|
||||
),
|
||||
|
||||
@@ -60,13 +60,13 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
# Cartesia offers a `<spell></spell>` tags that we can use to ask the user
|
||||
# to confirm the emails.
|
||||
# (see https://docs.cartesia.ai/build-with-sonic/formatting-text-for-sonic/spelling-out-input-text)
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
@@ -84,7 +84,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
# )
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You need to gather a valid email or emails from the user. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. If the user provides one or more email addresses confirm them with the user. Enclose all emails with <spell> tags, for example <spell>a@a.com</spell>.",
|
||||
),
|
||||
|
||||
@@ -52,22 +52,22 @@ transport_params = {
|
||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
)
|
||||
classifier_llm = OpenAILLMService(api_key=os.environ["OPENAI_API_KEY"])
|
||||
classifier_llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||||
|
||||
voicemail = VoicemailDetector(llm=classifier_llm)
|
||||
|
||||
|
||||
@@ -57,21 +57,21 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
||||
logger.info(f"Starting bot")
|
||||
|
||||
stt = DeepgramSTTService(
|
||||
api_key=os.environ["DEEPGRAM_API_KEY"],
|
||||
api_key=os.getenv("DEEPGRAM_API_KEY"),
|
||||
settings=DeepgramSTTService.Settings(
|
||||
keyterm=["pipecat"],
|
||||
),
|
||||
)
|
||||
|
||||
tts = CartesiaTTSService(
|
||||
api_key=os.environ["CARTESIA_API_KEY"],
|
||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||||
settings=CartesiaTTSService.Settings(
|
||||
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||||
),
|
||||
)
|
||||
|
||||
llm = OpenAILLMService(
|
||||
api_key=os.environ["OPENAI_API_KEY"],
|
||||
api_key=os.getenv("OPENAI_API_KEY"),
|
||||
settings=OpenAILLMService.Settings(
|
||||
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
|
||||
),
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user