Merge branch 'main' into vl_fixing_deepgram_language_bug_#868
This commit is contained in:
Vaibhav159
20
CHANGELOG.md
20
CHANGELOG.md
@@ -9,15 +9,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
|||||||
|
|
||||||
### Added
|
### Added
|
||||||
|
|
||||||
- Add support for more languages to ElevenLabs (Arabic, Croatian, Filipino,
|
- Pipecat now supports Python 3.13. We had a dependency on the `audioop` package
|
||||||
|
which was deprecated and now removed on Python 3.13. We are now using
|
||||||
|
`audioop-lts` (https://github.com/AbstractUmbra/audioop) to provide the same
|
||||||
|
functionality.
|
||||||
|
|
||||||
|
- Added support for more languages to ElevenLabs (Arabic, Croatian, Filipino,
|
||||||
Tamil) and PlayHT (Afrikans, Albanian, Amharic, Arabic, Bengali, Croatian,
|
Tamil) and PlayHT (Afrikans, Albanian, Amharic, Arabic, Bengali, Croatian,
|
||||||
Galician, Hebrew, Mandarin, Serbian, Tagalog, Urdu, Xhosa).
|
Galician, Hebrew, Mandarin, Serbian, Tagalog, Urdu, Xhosa).
|
||||||
|
|
||||||
### Changed
|
### Changed
|
||||||
|
|
||||||
- Changed: Room expiration (`exp`) in `DailyRoomProperties` is now optional
|
- Room expiration (`exp`) in `DailyRoomProperties` is now optional (`None`) by
|
||||||
(None) by default instead of automatically setting a 5-minute expiration
|
default instead of automatically setting a 5-minute expiration time. You must
|
||||||
time. You must explicitly set expiration time if desired.
|
explicitly set expiration time if desired.
|
||||||
|
|
||||||
### Deprecated
|
### Deprecated
|
||||||
|
|
||||||
@@ -33,6 +38,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
|
|||||||
only be pushed downstream after the audio generated from `TTSSpeakFrame` has
|
only be pushed downstream after the audio generated from `TTSSpeakFrame` has
|
||||||
been spoken.
|
been spoken.
|
||||||
|
|
||||||
|
## [0.0.51] - 2024-12-16
|
||||||
|
|
||||||
|
### Fixed
|
||||||
|
|
||||||
|
- Fixed an issue in websocket-based TTS services that was causing infinite
|
||||||
|
reconnections (Cartesia, ElevenLabs, PlayHT and LMNT).
|
||||||
|
|
||||||
## [0.0.50] - 2024-12-11
|
## [0.0.50] - 2024-12-11
|
||||||
|
|
||||||
### Added
|
### Added
|
||||||
|
|||||||
24
README.md
24
README.md
@@ -55,19 +55,19 @@ pip install "pipecat-ai[option,...]"
|
|||||||
|
|
||||||
Available options include:
|
Available options include:
|
||||||
|
|
||||||
| Category | Services | Install Command Example |
|
| Category | Services | Install Command Example |
|
||||||
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
|
| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
|
||||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/api-reference/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/api-reference/services/stt/azure), [Deepgram](https://docs.pipecat.ai/api-reference/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/api-reference/services/stt/gladia), [Whisper](https://docs.pipecat.ai/api-reference/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
||||||
| LLMs | [Anthropic](https://docs.pipecat.ai/api-reference/services/llm/anthropic), [Azure](https://docs.pipecat.ai/api-reference/services/llm/azure), [Fireworks AI](https://docs.pipecat.ai/api-reference/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/api-reference/services/llm/gemini), [Grok](https://docs.pipecat.ai/api-reference/services/llm/grok), [Groq](https://docs.pipecat.ai/api-reference/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/api-reference/services/llm/nim), [Ollama](https://docs.pipecat.ai/api-reference/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/api-reference/services/llm/openai), [Together AI](https://docs.pipecat.ai/api-reference/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
||||||
| Text-to-Speech | [AWS](https://docs.pipecat.ai/api-reference/services/tts/aws), [Azure](https://docs.pipecat.ai/api-reference/services/tts/azure), [Cartesia](https://docs.pipecat.ai/api-reference/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/api-reference/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/api-reference/services/tts/elevenlabs), [Google](https://docs.pipecat.ai/api-reference/services/tts/google), [LMNT](https://docs.pipecat.ai/api-reference/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/api-reference/services/tts/openai), [PlayHT](https://docs.pipecat.ai/api-reference/services/tts/playht), [Rime](https://docs.pipecat.ai/api-reference/services/tts/rime), [XTTS](https://docs.pipecat.ai/api-reference/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
||||||
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/api-reference/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
|
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
|
||||||
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/api-reference/services/transport/daily), WebSocket, Local | `pip install "pipecat-ai[daily]"` |
|
| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), WebSocket, Local | `pip install "pipecat-ai[daily]"` |
|
||||||
| Video | [Tavus](https://docs.pipecat.ai/api-reference/services/video/tavus), [Simli](https://docs.pipecat.ai/api-reference/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
|
| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
|
||||||
| Vision & Image | [Moondream](https://docs.pipecat.ai/api-reference/services/vision/moondream), [fal](https://docs.pipecat.ai/api-reference/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
||||||
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/api-reference/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/api-reference/utilities/audio/krisp-filter), [Noisereduce](https://docs.pipecat.ai/api-reference/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
||||||
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/api-reference/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/api-reference/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
||||||
|
|
||||||
📚 [View full services documentation →](https://docs.pipecat.ai/api-reference/services/supported-services)
|
📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
|
||||||
|
|
||||||
## Code examples
|
## Code examples
|
||||||
|
|
||||||
|
|||||||
@@ -1,8 +1,9 @@
|
|||||||
build~=1.2.1
|
build~=1.2.2
|
||||||
grpcio-tools~=1.65.4
|
grpcio-tools~=1.68.1
|
||||||
pip-tools~=7.4.1
|
pip-tools~=7.4.1
|
||||||
pyright~=1.1.376
|
pyright~=1.1.390
|
||||||
pytest~=8.3.2
|
pytest~=8.3.4
|
||||||
ruff~=0.6.7
|
ruff~=0.8.3
|
||||||
setuptools~=72.2.0
|
setuptools~=75.6.0
|
||||||
setuptools_scm~=8.1.0
|
setuptools_scm~=8.1.0
|
||||||
|
python-dotenv~=1.0.1
|
||||||
|
|||||||
@@ -65,7 +65,7 @@ async def main():
|
|||||||
)
|
)
|
||||||
|
|
||||||
llm = NimLLMService(
|
llm = NimLLMService(
|
||||||
api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.1-405b-instruct"
|
api_key=os.getenv("NVIDIA_API_KEY"), model="meta/llama-3.3-70b-instruct"
|
||||||
)
|
)
|
||||||
# Register a function_name of None to get all functions
|
# Register a function_name of None to get all functions
|
||||||
# sent to the same callback with an additional function_name parameter.
|
# sent to the same callback with an additional function_name parameter.
|
||||||
@@ -76,18 +76,18 @@ async def main():
|
|||||||
type="function",
|
type="function",
|
||||||
function={
|
function={
|
||||||
"name": "get_current_weather",
|
"name": "get_current_weather",
|
||||||
"description": "Get the current weather",
|
"description": "Returns the current weather at a location, if one is specified, and defaults to the user's location.",
|
||||||
"parameters": {
|
"parameters": {
|
||||||
"type": "object",
|
"type": "object",
|
||||||
"properties": {
|
"properties": {
|
||||||
"location": {
|
"location": {
|
||||||
"type": "string",
|
"type": "string",
|
||||||
"description": "The city and state, e.g. San Francisco, CA",
|
"description": "The location to find the weather of, or if not provided, it's the default location.",
|
||||||
},
|
},
|
||||||
"format": {
|
"format": {
|
||||||
"type": "string",
|
"type": "string",
|
||||||
"enum": ["celsius", "fahrenheit"],
|
"enum": ["celsius", "fahrenheit"],
|
||||||
"description": "The temperature unit to use. Infer this from the users location.",
|
"description": "Whether to use SI or USCS units (celsius or fahrenheit).",
|
||||||
},
|
},
|
||||||
},
|
},
|
||||||
"required": ["location", "format"],
|
"required": ["location", "format"],
|
||||||
|
|||||||
@@ -24,12 +24,12 @@ This repository demonstrates a simple AI chatbot with real-time audio/video inte
|
|||||||
|
|
||||||
2. **JavaScript**
|
2. **JavaScript**
|
||||||
|
|
||||||
- Basic implementation using [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/reference/js/introduction)
|
- Basic implementation using [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction)
|
||||||
- No framework dependencies
|
- No framework dependencies
|
||||||
- Good for learning the fundamentals
|
- Good for learning the fundamentals
|
||||||
|
|
||||||
3. **React**
|
3. **React**
|
||||||
- Basic impelmentation using [Pipecat React SDK](https://docs.pipecat.ai/client/reference/react/introduction)
|
- Basic impelmentation using [Pipecat React SDK](https://docs.pipecat.ai/client/react/introduction)
|
||||||
- Demonstrates the basic client principles with Pipecat React
|
- Demonstrates the basic client principles with Pipecat React
|
||||||
|
|
||||||
## Quick Start
|
## Quick Start
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
# JavaScript Implementation
|
# JavaScript Implementation
|
||||||
|
|
||||||
Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/reference/js/introduction).
|
Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
|
||||||
|
|
||||||
## Setup
|
## Setup
|
||||||
|
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
# React Implementation
|
# React Implementation
|
||||||
|
|
||||||
Basic implementation using the [Pipecat React SDK](https://docs.pipecat.ai/client/reference/react/introduction).
|
Basic implementation using the [Pipecat React SDK](https://docs.pipecat.ai/client/react/introduction).
|
||||||
|
|
||||||
## Setup
|
## Setup
|
||||||
|
|
||||||
|
|||||||
@@ -1,4 +1,4 @@
|
|||||||
DAILY_SAMPLE_ROOM_URL= # Follow instructions here and put your https://YOURDOMAIN.daily.co/YOURROOM (Instructions: https://docs.pipecat.ai/quickstart#preparing-your-environment)
|
DAILY_SAMPLE_ROOM_URL= # Follow instructions here and put your https://YOURDOMAIN.daily.co/YOURROOM (Instructions: https://docs.pipecat.ai/getting-started/installation)
|
||||||
DAILY_API_KEY= # Create here: https://dashboard.daily.co/developers
|
DAILY_API_KEY= # Create here: https://dashboard.daily.co/developers
|
||||||
OPENAI_API_KEY= # Create here: https://platform.openai.com/docs/overview
|
OPENAI_API_KEY= # Create here: https://platform.openai.com/docs/overview
|
||||||
CARTESIA_API_KEY= # Create here: https://play.cartesia.ai/console
|
CARTESIA_API_KEY= # Create here: https://play.cartesia.ai/console
|
||||||
|
|||||||
@@ -21,14 +21,17 @@ classifiers = [
|
|||||||
]
|
]
|
||||||
dependencies = [
|
dependencies = [
|
||||||
"aiohttp~=3.11.10",
|
"aiohttp~=3.11.10",
|
||||||
"loguru~=0.7.2",
|
"audioop-lts~=0.2.1; python_version>='3.13'",
|
||||||
|
"loguru~=0.7.3",
|
||||||
"Markdown~=3.7",
|
"Markdown~=3.7",
|
||||||
"numpy~=1.26.4",
|
"numpy~=2.1.3",
|
||||||
"Pillow~=10.4.0",
|
"numba~=0.61.0rc1",
|
||||||
|
"Pillow~=11.0.0",
|
||||||
"protobuf~=5.29.1",
|
"protobuf~=5.29.1",
|
||||||
"pydantic~=2.8.2",
|
"pydantic~=2.10.3",
|
||||||
"pyloudnorm~=0.1.1",
|
"pyloudnorm~=0.1.1",
|
||||||
"resampy~=0.4.3",
|
"resampy~=0.4.3",
|
||||||
|
"tenacity~=9.0.0"
|
||||||
]
|
]
|
||||||
|
|
||||||
[project.urls]
|
[project.urls]
|
||||||
@@ -45,7 +48,6 @@ cartesia = [ "cartesia~=1.0.13", "websockets~=13.1" ]
|
|||||||
daily = [ "daily-python~=0.13.0" ]
|
daily = [ "daily-python~=0.13.0" ]
|
||||||
deepgram = [ "deepgram-sdk~=3.7.7" ]
|
deepgram = [ "deepgram-sdk~=3.7.7" ]
|
||||||
elevenlabs = [ "websockets~=13.1" ]
|
elevenlabs = [ "websockets~=13.1" ]
|
||||||
examples = [ "python-dotenv~=1.0.1", "flask~=3.0.3", "flask_cors~=4.0.1" ]
|
|
||||||
fal = [ "fal-client~=0.4.1" ]
|
fal = [ "fal-client~=0.4.1" ]
|
||||||
gladia = [ "websockets~=13.1" ]
|
gladia = [ "websockets~=13.1" ]
|
||||||
google = [ "google-generativeai~=0.8.3", "google-cloud-texttospeech~=2.21.1" ]
|
google = [ "google-generativeai~=0.8.3", "google-cloud-texttospeech~=2.21.1" ]
|
||||||
@@ -55,15 +57,15 @@ gstreamer = [ "pygobject~=3.48.2" ]
|
|||||||
fireworks = [ "openai~=1.57.2" ]
|
fireworks = [ "openai~=1.57.2" ]
|
||||||
krisp = [ "pipecat-ai-krisp~=0.3.0" ]
|
krisp = [ "pipecat-ai-krisp~=0.3.0" ]
|
||||||
langchain = [ "langchain~=0.2.14", "langchain-community~=0.2.12", "langchain-openai~=0.1.20" ]
|
langchain = [ "langchain~=0.2.14", "langchain-community~=0.2.12", "langchain-openai~=0.1.20" ]
|
||||||
livekit = [ "livekit~=0.18.2", "livekit-api~=0.8.0", "tenacity~=8.5.0" ]
|
livekit = [ "livekit~=0.17.5", "livekit-api~=0.7.1" ]
|
||||||
lmnt = [ "lmnt~=1.1.4" ]
|
lmnt = [ "lmnt~=1.1.4" ]
|
||||||
local = [ "pyaudio~=0.2.14" ]
|
local = [ "pyaudio~=0.2.14" ]
|
||||||
moondream = [ "einops~=0.8.0", "timm~=1.0.8", "transformers~=4.44.0" ]
|
moondream = [ "einops~=0.8.0", "timm~=1.0.8", "transformers~=4.44.0" ]
|
||||||
nim = [ "openai~=1.57.2" ]
|
nim = [ "openai~=1.57.2" ]
|
||||||
noisereduce = [ "noisereduce~=3.0.3" ]
|
noisereduce = [ "noisereduce~=3.0.3" ]
|
||||||
openai = [ "openai~=1.57.2", "websockets~=13.1", "python-deepcompare~=1.0.1" ]
|
openai = [ "openai~=1.57.2", "websockets~=13.1", "python-deepcompare~=1.0.1" ]
|
||||||
openpipe = [ "openpipe~=4.38.0" ]
|
openpipe = [ "openpipe~=4.40.0" ]
|
||||||
playht = [ "pyht~=0.1.8", "websockets~=13.1" ]
|
playht = [ "pyht~=0.1.9", "websockets~=13.1" ]
|
||||||
riva = [ "nvidia-riva-client~=2.17.0" ]
|
riva = [ "nvidia-riva-client~=2.17.0" ]
|
||||||
silero = [ "onnxruntime~=1.20.1" ]
|
silero = [ "onnxruntime~=1.20.1" ]
|
||||||
simli = [ "simli-ai~=0.1.7"]
|
simli = [ "simli-ai~=0.1.7"]
|
||||||
|
|||||||
@@ -1,3 +1,9 @@
|
|||||||
|
#
|
||||||
|
# Copyright (c) 2024, Daily
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: BSD 2-Clause License
|
||||||
|
#
|
||||||
|
|
||||||
import time
|
import time
|
||||||
|
|
||||||
from pipecat.frames.frames import MetricsFrame
|
from pipecat.frames.frames import MetricsFrame
|
||||||
|
|||||||
@@ -1,3 +1,9 @@
|
|||||||
|
#
|
||||||
|
# Copyright (c) 2024, Daily
|
||||||
|
#
|
||||||
|
# SPDX-License-Identifier: BSD 2-Clause License
|
||||||
|
#
|
||||||
|
|
||||||
import time
|
import time
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
|
|
||||||
@@ -29,8 +35,9 @@ class SentryMetrics(FrameProcessorMetrics):
|
|||||||
description=f"TTFB for {self._processor_name()}",
|
description=f"TTFB for {self._processor_name()}",
|
||||||
start_timestamp=self._start_ttfb_time,
|
start_timestamp=self._start_ttfb_time,
|
||||||
)
|
)
|
||||||
logger.debug(f"Sentry Span ID: {self._ttfb_metrics_span.span_id} Description: {
|
logger.debug(
|
||||||
self._ttfb_metrics_span.description} started.")
|
f"Sentry Span ID: {self._ttfb_metrics_span.span_id} Description: {self._ttfb_metrics_span.description} started."
|
||||||
|
)
|
||||||
self._should_report_ttfb = not report_only_initial_ttfb
|
self._should_report_ttfb = not report_only_initial_ttfb
|
||||||
|
|
||||||
async def stop_ttfb_metrics(self):
|
async def stop_ttfb_metrics(self):
|
||||||
@@ -46,8 +53,9 @@ class SentryMetrics(FrameProcessorMetrics):
|
|||||||
description=f"Processing for {self._processor_name()}",
|
description=f"Processing for {self._processor_name()}",
|
||||||
start_timestamp=self._start_processing_time,
|
start_timestamp=self._start_processing_time,
|
||||||
)
|
)
|
||||||
logger.debug(f"Sentry Span ID: {self._processing_metrics_span.span_id} Description: {
|
logger.debug(
|
||||||
self._processing_metrics_span.description} started.")
|
f"Sentry Span ID: {self._processing_metrics_span.span_id} Description: {self._processing_metrics_span.description} started."
|
||||||
|
)
|
||||||
|
|
||||||
async def stop_processing_metrics(self):
|
async def stop_processing_metrics(self):
|
||||||
stop_time = time.time()
|
stop_time = time.time()
|
||||||
|
|||||||
@@ -12,6 +12,8 @@ from typing import AsyncGenerator, List, Optional, Union
|
|||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from pydantic import BaseModel
|
from pydantic import BaseModel
|
||||||
|
from tenacity import AsyncRetrying, RetryCallState, stop_after_attempt, wait_exponential
|
||||||
|
|
||||||
|
|
||||||
from pipecat.frames.frames import (
|
from pipecat.frames.frames import (
|
||||||
BotStoppedSpeakingFrame,
|
BotStoppedSpeakingFrame,
|
||||||
@@ -239,52 +241,64 @@ class CartesiaTTSService(WordTTSService):
|
|||||||
msg = self._build_msg(text="", continue_transcript=False)
|
msg = self._build_msg(text="", continue_transcript=False)
|
||||||
await self._websocket.send(msg)
|
await self._websocket.send(msg)
|
||||||
|
|
||||||
|
async def _receive_messages(self):
|
||||||
|
async for message in self._get_websocket():
|
||||||
|
msg = json.loads(message)
|
||||||
|
if not msg or msg["context_id"] != self._context_id:
|
||||||
|
continue
|
||||||
|
if msg["type"] == "done":
|
||||||
|
await self.stop_ttfb_metrics()
|
||||||
|
# Unset _context_id but not the _context_id_start_timestamp
|
||||||
|
# because we are likely still playing out audio and need the
|
||||||
|
# timestamp to set send context frames.
|
||||||
|
self._context_id = None
|
||||||
|
await self.add_word_timestamps(
|
||||||
|
[("TTSStoppedFrame", 0), ("LLMFullResponseEndFrame", 0), ("Reset", 0)]
|
||||||
|
)
|
||||||
|
elif msg["type"] == "timestamps":
|
||||||
|
await self.add_word_timestamps(
|
||||||
|
list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["start"]))
|
||||||
|
)
|
||||||
|
elif msg["type"] == "chunk":
|
||||||
|
await self.stop_ttfb_metrics()
|
||||||
|
self.start_word_timestamps()
|
||||||
|
frame = TTSAudioRawFrame(
|
||||||
|
audio=base64.b64decode(msg["data"]),
|
||||||
|
sample_rate=self._settings["output_format"]["sample_rate"],
|
||||||
|
num_channels=1,
|
||||||
|
)
|
||||||
|
await self.push_frame(frame)
|
||||||
|
elif msg["type"] == "error":
|
||||||
|
logger.error(f"{self} error: {msg}")
|
||||||
|
await self.push_frame(TTSStoppedFrame())
|
||||||
|
await self.stop_all_metrics()
|
||||||
|
await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
|
||||||
|
else:
|
||||||
|
logger.error(f"{self} error, unknown message type: {msg}")
|
||||||
|
|
||||||
|
async def _reconnect_websocket(self, retry_state: RetryCallState):
|
||||||
|
logger.warning(f"{self} reconnecting (attempt: {retry_state.attempt_number})")
|
||||||
|
await self._disconnect_websocket()
|
||||||
|
await self._connect_websocket()
|
||||||
|
|
||||||
async def _receive_task_handler(self):
|
async def _receive_task_handler(self):
|
||||||
while True:
|
while True:
|
||||||
try:
|
try:
|
||||||
async for message in self._get_websocket():
|
async for attempt in AsyncRetrying(
|
||||||
msg = json.loads(message)
|
stop=stop_after_attempt(3),
|
||||||
if not msg or msg["context_id"] != self._context_id:
|
wait=wait_exponential(multiplier=1, min=4, max=10),
|
||||||
continue
|
before_sleep=self._reconnect_websocket,
|
||||||
if msg["type"] == "done":
|
reraise=True,
|
||||||
await self.stop_ttfb_metrics()
|
):
|
||||||
# Unset _context_id but not the _context_id_start_timestamp
|
with attempt:
|
||||||
# because we are likely still playing out audio and need the
|
await self._receive_messages()
|
||||||
# timestamp to set send context frames.
|
|
||||||
self._context_id = None
|
|
||||||
await self.add_word_timestamps(
|
|
||||||
[("TTSStoppedFrame", 0), ("LLMFullResponseEndFrame", 0), ("Reset", 0)]
|
|
||||||
)
|
|
||||||
elif msg["type"] == "timestamps":
|
|
||||||
await self.add_word_timestamps(
|
|
||||||
list(
|
|
||||||
zip(
|
|
||||||
msg["word_timestamps"]["words"], msg["word_timestamps"]["start"]
|
|
||||||
)
|
|
||||||
)
|
|
||||||
)
|
|
||||||
elif msg["type"] == "chunk":
|
|
||||||
await self.stop_ttfb_metrics()
|
|
||||||
self.start_word_timestamps()
|
|
||||||
frame = TTSAudioRawFrame(
|
|
||||||
audio=base64.b64decode(msg["data"]),
|
|
||||||
sample_rate=self._settings["output_format"]["sample_rate"],
|
|
||||||
num_channels=1,
|
|
||||||
)
|
|
||||||
await self.push_frame(frame)
|
|
||||||
elif msg["type"] == "error":
|
|
||||||
logger.error(f"{self} error: {msg}")
|
|
||||||
await self.push_frame(TTSStoppedFrame())
|
|
||||||
await self.stop_all_metrics()
|
|
||||||
await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
|
|
||||||
else:
|
|
||||||
logger.error(f"{self} error, unknown message type: {msg}")
|
|
||||||
except asyncio.CancelledError:
|
except asyncio.CancelledError:
|
||||||
break
|
break
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"{self} exception: {e}")
|
message = f"{self} error receiving messages: {e}"
|
||||||
await self._disconnect_websocket()
|
logger.error(message)
|
||||||
await self._connect_websocket()
|
await self.push_error(ErrorFrame(message, fatal=True))
|
||||||
|
break
|
||||||
|
|
||||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||||
await super().process_frame(frame, direction)
|
await super().process_frame(frame, direction)
|
||||||
|
|||||||
@@ -11,11 +11,13 @@ from typing import Any, AsyncGenerator, Dict, List, Literal, Mapping, Optional,
|
|||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from pydantic import BaseModel, model_validator
|
from pydantic import BaseModel, model_validator
|
||||||
|
from tenacity import AsyncRetrying, RetryCallState, stop_after_attempt, wait_exponential
|
||||||
|
|
||||||
from pipecat.frames.frames import (
|
from pipecat.frames.frames import (
|
||||||
BotStoppedSpeakingFrame,
|
BotStoppedSpeakingFrame,
|
||||||
CancelFrame,
|
CancelFrame,
|
||||||
EndFrame,
|
EndFrame,
|
||||||
|
ErrorFrame,
|
||||||
Frame,
|
Frame,
|
||||||
LLMFullResponseEndFrame,
|
LLMFullResponseEndFrame,
|
||||||
StartFrame,
|
StartFrame,
|
||||||
@@ -352,28 +354,44 @@ class ElevenLabsTTSService(WordTTSService):
|
|||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"{self} error closing websocket: {e}")
|
logger.error(f"{self} error closing websocket: {e}")
|
||||||
|
|
||||||
|
async def _receive_messages(self):
|
||||||
|
async for message in self._websocket:
|
||||||
|
msg = json.loads(message)
|
||||||
|
if msg.get("audio"):
|
||||||
|
await self.stop_ttfb_metrics()
|
||||||
|
self.start_word_timestamps()
|
||||||
|
|
||||||
|
audio = base64.b64decode(msg["audio"])
|
||||||
|
frame = TTSAudioRawFrame(audio, self._settings["sample_rate"], 1)
|
||||||
|
await self.push_frame(frame)
|
||||||
|
if msg.get("alignment"):
|
||||||
|
word_times = calculate_word_times(msg["alignment"], self._cumulative_time)
|
||||||
|
await self.add_word_timestamps(word_times)
|
||||||
|
self._cumulative_time = word_times[-1][1]
|
||||||
|
|
||||||
|
async def _reconnect_websocket(self, retry_state: RetryCallState):
|
||||||
|
logger.warning(f"{self} reconnecting (attempt: {retry_state.attempt_number})")
|
||||||
|
await self._disconnect_websocket()
|
||||||
|
await self._connect_websocket()
|
||||||
|
|
||||||
async def _receive_task_handler(self):
|
async def _receive_task_handler(self):
|
||||||
while True:
|
while True:
|
||||||
try:
|
try:
|
||||||
async for message in self._websocket:
|
async for attempt in AsyncRetrying(
|
||||||
msg = json.loads(message)
|
stop=stop_after_attempt(3),
|
||||||
if msg.get("audio"):
|
wait=wait_exponential(multiplier=1, min=4, max=10),
|
||||||
await self.stop_ttfb_metrics()
|
before_sleep=self._reconnect_websocket,
|
||||||
self.start_word_timestamps()
|
reraise=True,
|
||||||
|
):
|
||||||
audio = base64.b64decode(msg["audio"])
|
with attempt:
|
||||||
frame = TTSAudioRawFrame(audio, self._settings["sample_rate"], 1)
|
await self._receive_messages()
|
||||||
await self.push_frame(frame)
|
|
||||||
if msg.get("alignment"):
|
|
||||||
word_times = calculate_word_times(msg["alignment"], self._cumulative_time)
|
|
||||||
await self.add_word_timestamps(word_times)
|
|
||||||
self._cumulative_time = word_times[-1][1]
|
|
||||||
except asyncio.CancelledError:
|
except asyncio.CancelledError:
|
||||||
break
|
break
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"{self} exception: {e}")
|
message = f"{self} error receiving messages: {e}"
|
||||||
await self._disconnect_websocket()
|
logger.error(message)
|
||||||
await self._connect_websocket()
|
await self.push_error(ErrorFrame(message, fatal=True))
|
||||||
|
break
|
||||||
|
|
||||||
async def _keepalive_task_handler(self):
|
async def _keepalive_task_handler(self):
|
||||||
while True:
|
while True:
|
||||||
|
|||||||
@@ -5,11 +5,102 @@
|
|||||||
#
|
#
|
||||||
|
|
||||||
|
|
||||||
|
import json
|
||||||
|
from dataclasses import dataclass
|
||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
|
|
||||||
from pipecat.metrics.metrics import LLMTokenUsage
|
from pipecat.metrics.metrics import LLMTokenUsage
|
||||||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
from pipecat.processors.aggregators.openai_llm_context import (
|
||||||
from pipecat.services.openai import OpenAILLMService
|
OpenAILLMContext,
|
||||||
|
OpenAILLMContextFrame,
|
||||||
|
)
|
||||||
|
from pipecat.services.openai import (
|
||||||
|
OpenAIAssistantContextAggregator,
|
||||||
|
OpenAILLMService,
|
||||||
|
OpenAIUserContextAggregator,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
class GrokAssistantContextAggregator(OpenAIAssistantContextAggregator):
|
||||||
|
"""Custom assistant context aggregator for Grok that handles empty content requirement."""
|
||||||
|
|
||||||
|
async def _push_aggregation(self):
|
||||||
|
if not (
|
||||||
|
self._aggregation or self._function_call_result or self._pending_image_frame_message
|
||||||
|
):
|
||||||
|
return
|
||||||
|
|
||||||
|
run_llm = False
|
||||||
|
|
||||||
|
aggregation = self._aggregation
|
||||||
|
self._reset()
|
||||||
|
|
||||||
|
try:
|
||||||
|
if self._function_call_result:
|
||||||
|
frame = self._function_call_result
|
||||||
|
self._function_call_result = None
|
||||||
|
if frame.result:
|
||||||
|
# Grok requires an empty content field for function calls
|
||||||
|
self._context.add_message(
|
||||||
|
{
|
||||||
|
"role": "assistant",
|
||||||
|
"content": "", # Required by Grok
|
||||||
|
"tool_calls": [
|
||||||
|
{
|
||||||
|
"id": frame.tool_call_id,
|
||||||
|
"function": {
|
||||||
|
"name": frame.function_name,
|
||||||
|
"arguments": json.dumps(frame.arguments),
|
||||||
|
},
|
||||||
|
"type": "function",
|
||||||
|
}
|
||||||
|
],
|
||||||
|
}
|
||||||
|
)
|
||||||
|
self._context.add_message(
|
||||||
|
{
|
||||||
|
"role": "tool",
|
||||||
|
"content": json.dumps(frame.result),
|
||||||
|
"tool_call_id": frame.tool_call_id,
|
||||||
|
}
|
||||||
|
)
|
||||||
|
# Only run the LLM if there are no more function calls in progress.
|
||||||
|
run_llm = not bool(self._function_calls_in_progress)
|
||||||
|
else:
|
||||||
|
self._context.add_message({"role": "assistant", "content": aggregation})
|
||||||
|
|
||||||
|
if self._pending_image_frame_message:
|
||||||
|
frame = self._pending_image_frame_message
|
||||||
|
self._pending_image_frame_message = None
|
||||||
|
self._context.add_image_frame_message(
|
||||||
|
format=frame.user_image_raw_frame.format,
|
||||||
|
size=frame.user_image_raw_frame.size,
|
||||||
|
image=frame.user_image_raw_frame.image,
|
||||||
|
text=frame.text,
|
||||||
|
)
|
||||||
|
run_llm = True
|
||||||
|
|
||||||
|
if run_llm:
|
||||||
|
await self._user_context_aggregator.push_context_frame()
|
||||||
|
|
||||||
|
frame = OpenAILLMContextFrame(self._context)
|
||||||
|
await self.push_frame(frame)
|
||||||
|
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"Error processing frame: {e}")
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class GrokContextAggregatorPair:
|
||||||
|
_user: "OpenAIUserContextAggregator"
|
||||||
|
_assistant: "GrokAssistantContextAggregator"
|
||||||
|
|
||||||
|
def user(self) -> "OpenAIUserContextAggregator":
|
||||||
|
return self._user
|
||||||
|
|
||||||
|
def assistant(self) -> "GrokAssistantContextAggregator":
|
||||||
|
return self._assistant
|
||||||
|
|
||||||
|
|
||||||
class GrokLLMService(OpenAILLMService):
|
class GrokLLMService(OpenAILLMService):
|
||||||
@@ -101,3 +192,13 @@ class GrokLLMService(OpenAILLMService):
|
|||||||
# Update completion tokens count if it has increased
|
# Update completion tokens count if it has increased
|
||||||
if tokens.completion_tokens > self._completion_tokens:
|
if tokens.completion_tokens > self._completion_tokens:
|
||||||
self._completion_tokens = tokens.completion_tokens
|
self._completion_tokens = tokens.completion_tokens
|
||||||
|
|
||||||
|
@staticmethod
|
||||||
|
def create_context_aggregator(
|
||||||
|
context: OpenAILLMContext, *, assistant_expect_stripped_words: bool = True
|
||||||
|
) -> GrokContextAggregatorPair:
|
||||||
|
user = OpenAIUserContextAggregator(context)
|
||||||
|
assistant = GrokAssistantContextAggregator(
|
||||||
|
user, expect_stripped_words=assistant_expect_stripped_words
|
||||||
|
)
|
||||||
|
return GrokContextAggregatorPair(_user=user, _assistant=assistant)
|
||||||
|
|||||||
@@ -8,6 +8,7 @@ import asyncio
|
|||||||
from typing import AsyncGenerator
|
from typing import AsyncGenerator
|
||||||
|
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
|
from tenacity import AsyncRetrying, RetryCallState, stop_after_attempt, wait_exponential
|
||||||
|
|
||||||
from pipecat.frames.frames import (
|
from pipecat.frames.frames import (
|
||||||
CancelFrame,
|
CancelFrame,
|
||||||
@@ -159,31 +160,47 @@ class LmntTTSService(TTSService):
|
|||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"{self} error closing connection: {e}")
|
logger.error(f"{self} error closing connection: {e}")
|
||||||
|
|
||||||
|
async def _receive_messages(self):
|
||||||
|
async for msg in self._connection:
|
||||||
|
if "error" in msg:
|
||||||
|
logger.error(f'{self} error: {msg["error"]}')
|
||||||
|
await self.push_frame(TTSStoppedFrame())
|
||||||
|
await self.stop_all_metrics()
|
||||||
|
await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
|
||||||
|
elif "audio" in msg:
|
||||||
|
await self.stop_ttfb_metrics()
|
||||||
|
frame = TTSAudioRawFrame(
|
||||||
|
audio=msg["audio"],
|
||||||
|
sample_rate=self._settings["output_format"]["sample_rate"],
|
||||||
|
num_channels=1,
|
||||||
|
)
|
||||||
|
await self.push_frame(frame)
|
||||||
|
else:
|
||||||
|
logger.error(f"{self}: LMNT error, unknown message type: {msg}")
|
||||||
|
|
||||||
|
async def _reconnect_websocket(self, retry_state: RetryCallState):
|
||||||
|
logger.warning(f"{self} reconnecting (attempt: {retry_state.attempt_number})")
|
||||||
|
await self._disconnect_lmnt()
|
||||||
|
await self._connect_lmnt()
|
||||||
|
|
||||||
async def _receive_task_handler(self):
|
async def _receive_task_handler(self):
|
||||||
while True:
|
while True:
|
||||||
try:
|
try:
|
||||||
async for msg in self._connection:
|
async for attempt in AsyncRetrying(
|
||||||
if "error" in msg:
|
stop=stop_after_attempt(3),
|
||||||
logger.error(f'{self} error: {msg["error"]}')
|
wait=wait_exponential(multiplier=1, min=4, max=10),
|
||||||
await self.push_frame(TTSStoppedFrame())
|
before_sleep=self._reconnect_websocket,
|
||||||
await self.stop_all_metrics()
|
reraise=True,
|
||||||
await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
|
):
|
||||||
elif "audio" in msg:
|
with attempt:
|
||||||
await self.stop_ttfb_metrics()
|
await self._receive_messages()
|
||||||
frame = TTSAudioRawFrame(
|
|
||||||
audio=msg["audio"],
|
|
||||||
sample_rate=self._settings["output_format"]["sample_rate"],
|
|
||||||
num_channels=1,
|
|
||||||
)
|
|
||||||
await self.push_frame(frame)
|
|
||||||
else:
|
|
||||||
logger.error(f"{self}: LMNT error, unknown message type: {msg}")
|
|
||||||
except asyncio.CancelledError:
|
except asyncio.CancelledError:
|
||||||
break
|
break
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"{self} exception: {e}")
|
message = f"{self} error receiving messages: {e}"
|
||||||
await self._disconnect_lmnt()
|
logger.error(message)
|
||||||
await self._connect_lmnt()
|
await self.push_error(ErrorFrame(message, fatal=True))
|
||||||
|
break
|
||||||
|
|
||||||
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
|
||||||
logger.debug(f"Generating TTS: [{text}]")
|
logger.debug(f"Generating TTS: [{text}]")
|
||||||
|
|||||||
@@ -559,7 +559,6 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
|
|||||||
self._context.add_message(
|
self._context.add_message(
|
||||||
{
|
{
|
||||||
"role": "assistant",
|
"role": "assistant",
|
||||||
"content": "", # content field required for Grok function calling
|
|
||||||
"tool_calls": [
|
"tool_calls": [
|
||||||
{
|
{
|
||||||
"id": frame.tool_call_id,
|
"id": frame.tool_call_id,
|
||||||
|
|||||||
@@ -15,6 +15,7 @@ import aiohttp
|
|||||||
import websockets
|
import websockets
|
||||||
from loguru import logger
|
from loguru import logger
|
||||||
from pydantic import BaseModel
|
from pydantic import BaseModel
|
||||||
|
from tenacity import AsyncRetrying, RetryCallState, stop_after_attempt, wait_exponential
|
||||||
|
|
||||||
from pipecat.frames.frames import (
|
from pipecat.frames.frames import (
|
||||||
BotStoppedSpeakingFrame,
|
BotStoppedSpeakingFrame,
|
||||||
@@ -234,35 +235,51 @@ class PlayHTTTSService(TTSService):
|
|||||||
await self.stop_all_metrics()
|
await self.stop_all_metrics()
|
||||||
self._request_id = None
|
self._request_id = None
|
||||||
|
|
||||||
|
async def _receive_messages(self):
|
||||||
|
async for message in self._get_websocket():
|
||||||
|
if isinstance(message, bytes):
|
||||||
|
# Skip the WAV header message
|
||||||
|
if message.startswith(b"RIFF"):
|
||||||
|
continue
|
||||||
|
await self.stop_ttfb_metrics()
|
||||||
|
frame = TTSAudioRawFrame(message, self._settings["sample_rate"], 1)
|
||||||
|
await self.push_frame(frame)
|
||||||
|
else:
|
||||||
|
logger.debug(f"Received text message: {message}")
|
||||||
|
try:
|
||||||
|
msg = json.loads(message)
|
||||||
|
if "request_id" in msg and msg["request_id"] == self._request_id:
|
||||||
|
await self.push_frame(TTSStoppedFrame())
|
||||||
|
self._request_id = None
|
||||||
|
elif "error" in msg:
|
||||||
|
logger.error(f"{self} error: {msg}")
|
||||||
|
await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
|
||||||
|
except json.JSONDecodeError:
|
||||||
|
logger.error(f"Invalid JSON message: {message}")
|
||||||
|
|
||||||
|
async def _reconnect_websocket(self, retry_state: RetryCallState):
|
||||||
|
logger.warning(f"{self} reconnecting (attempt: {retry_state.attempt_number})")
|
||||||
|
await self._disconnect_websocket()
|
||||||
|
await self._connect_websocket()
|
||||||
|
|
||||||
async def _receive_task_handler(self):
|
async def _receive_task_handler(self):
|
||||||
while True:
|
while True:
|
||||||
try:
|
try:
|
||||||
async for message in self._get_websocket():
|
async for attempt in AsyncRetrying(
|
||||||
if isinstance(message, bytes):
|
stop=stop_after_attempt(3),
|
||||||
# Skip the WAV header message
|
wait=wait_exponential(multiplier=1, min=4, max=10),
|
||||||
if message.startswith(b"RIFF"):
|
before_sleep=self._reconnect_websocket,
|
||||||
continue
|
reraise=True,
|
||||||
await self.stop_ttfb_metrics()
|
):
|
||||||
frame = TTSAudioRawFrame(message, self._settings["sample_rate"], 1)
|
with attempt:
|
||||||
await self.push_frame(frame)
|
await self._receive_messages()
|
||||||
else:
|
|
||||||
logger.debug(f"Received text message: {message}")
|
|
||||||
try:
|
|
||||||
msg = json.loads(message)
|
|
||||||
if "request_id" in msg and msg["request_id"] == self._request_id:
|
|
||||||
await self.push_frame(TTSStoppedFrame())
|
|
||||||
self._request_id = None
|
|
||||||
elif "error" in msg:
|
|
||||||
logger.error(f"{self} error: {msg}")
|
|
||||||
await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
|
|
||||||
except json.JSONDecodeError:
|
|
||||||
logger.error(f"Invalid JSON message: {message}")
|
|
||||||
except asyncio.CancelledError:
|
except asyncio.CancelledError:
|
||||||
break
|
break
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"{self} exception in receive task: {e}")
|
message = f"{self} error receiving messages: {e}"
|
||||||
await self._disconnect_websocket()
|
logger.error(message)
|
||||||
await self._connect_websocket()
|
await self.push_error(ErrorFrame(message, fatal=True))
|
||||||
|
break
|
||||||
|
|
||||||
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
||||||
await super().process_frame(frame, direction)
|
await super().process_frame(frame, direction)
|
||||||
|
|||||||
Reference in New Issue
Block a user